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Simplifying CAN Automotive Applications with Highly Integrated 8-bit MCUs

Tuesday, April 10th, 2018

Why 8-bit MCUs and CAN form an effective team

Designed for the automotive industry in the mid-1980’s, the controller area network (CAN) protocol addressed and continues to address the need to reduce the wiring complexity (weight, amount and cost) for data transmission in increasingly interconnected applications.

The advantages of CAN have also been embraced and adopted in other markets including factory automation and medical applications, so extensively that well over 1 billion CAN nodes are shipped worldwide each year. Similarly, over 1 billion 8-bit microcontroller units (MCUs) are shipped annually. While today there is some overlap in these statistics, that should increase considerably in the future.

…these 8-bit MCUs provide an alternative to 16-bit MCUs that are more expensive and more difficult to program.

CAN Continues to Meet Carmaker’s Needs
Traditional CAN communications are event-based, allowing microcontrollers and application specific integrated circuits (ASICS) to directly communicate with each other in applications without a host computer. The integration by semiconductor companies has greatly added to CAN’s cost-effectiveness and compatibility with many automotive systems. Since the early 2000’s, 8-bit MCUs have also included the CAN protocol. More recently an 8-bit MCU design approach, initially introduced in 2015, uses Core Independent Peripherals (CIPs) to allow a new family of 8-bit MCUs to address many system aspects in CAN applications.

In addition to its cost-effectiveness, CAN’s success can be attributed to its:

  • Robustness
  • Reliable data transmission
  • Rather simple implementation

Not surprisingly, 8-bit MCUs also have these same attributes in addition to their cost-effectiveness. So, 8-bit MCUs with CAN are a natural combination to address many automotive networking requirements.

Over the years, CAN has proven to be capable of meeting a variety of control system requirements. As automotive networks increased to require different attributes including time-triggered, fault-tolerant and single-wire implementations, as well as CAN with flexible data rate (CAN FD), CAN specifications expanded. Table 1 shows many of the CAN variations that have occurred since its initial introduction over 30 years ago.

Table 1: CAN adaptations can meet a variety of automotive needs.

For networking sensors and actuators to comfort systems, automotive engineers have used the local area network (LIN) protocol to reduce costs. However, LIN, a single-wire, master-slave network, requires both hardware and software changes from CAN. Some of the newest automotive applications for CAN include access control, battery charging/battery management, and diagnostic equipment. These and other vehicle requirements, especially those that require access to data from another CAN control system, are driving the use of 8-bit MCUs/CAN. Figure 1 shows the easy addition of an 8-bit MCU/CAN node to an existing CAN bus.

Figure 1: Different CAN implementations can coexist and add to the flexibility of the CAN bus.

Solving Low-Cost Networking Requirements Using an 8-Bit MCU with CAN
While connecting to the CAN bus is the minimum capability that system designers need, added peripherals that specifically address other system requirements simplify the designer’s task. Those system tasks could include sensing a parameter or two for control purposes, moving a motor, activating a solenoid, or providing some other functions.

The CIP approach can reduce software complexity and deliver faster response times at lower clock speeds while using less power. Broad system categories for CIPs in Microchip’s PIC18 K83 family include:

  • Intelligent analog (including sensor interface)
  • Waveform control
  • Timing and measurements
  • Logic and math
  • Safety and monitoring
  • Communications
  • Low power and system flexibility

Within these categories, specific peripherals include:

  • Cyclic Redundancy Check (CRC) with memory scan to ensure the integrity of non-volatile memory
  • Direct Memory Access (DMA) to enable data transfers between memory and peripherals without CPU involvement
  • Windowed Watchdog Timer (WWDT) for triggering system resets
  • A 12-bit Analog-to-Digital Converter with Computation (ADC2) for automating analog signal analysis for real-time system response
  • Complementary Waveform Generator (CWG) for enabling high-efficiency synchronous switching for motor control

In addition to working with CAN 2.0B, the integrated CAN controller is fully backwards compatible with previous CAN modules (CAN 1.2 and CAN 2.0A). The products’ capabilities include the Memory Access Partition (MAP) to support designers in data protection and bootloader applications. Device Information Area (DIA) provides a dedicated memory space for factory-programmed device ID and peripheral calibration values.

Since communications are a primary goal for CAN nodes, the 8-bit MCUs have improved serial communications, including UART with support for Asynchronous and LIN protocols as well as higher-speed, standalone I2C and SPI serial communication interfaces. Table 2 shows the 15 CIPs and how they address specific system requirements.

Table 2: Core Independent Peripherals in PIC18 K83 family address several system requirements.

Thanks to these on-chip structures that were not thought of or implemented in 8-bit MCUs in the past, today’s 8-bit MCUs can perform quite differently than many designers have come to expect and deliver much more than MCUs designed over a decade ago.

Programming an 8-bit MCU is simple and easy and with the CAN plus CIPs, it is even easier. When they provide sufficient processing power, especially for remote nodes, these 8-bit MCUs provide an alternative to 16-bit MCUs that are more expensive and more difficult to program. With CIPs, even more processing power is available, enabling more 8-bit MCU options.

The highly configurable on-chip hardware modules handle repetitive embedded tasksmore efficiently and deterministically. Thanks to the deterministic nature of CAN, if an MCU gets caught in a loop, one with CIPs can still continue operations outside of the core.

With the newest 8-bit MCUs/CAN+CIPs, as well as LIN, network designers now have more flexibility and options for implementing CAN and LIN communications. In fact, some typical 8-bit MCU LIN applications are now potential CAN applications. For example, if the module needs to be aware of other data on the network, such as vehicle speed, CAN may be a better choice or at least an option to LIN. This can be useful for windshield wipers that can change their speed based on the vehicle’s speed to avoid a CAN to LIN gateway. In addition, the system-level CIPs may avoid the need for an additional ASIC or two, as shown in Figure 2.

The same PWM and complementary waveform generator CIPs have been used for years to do fairly complex, multi-color LED mood lighting in vehicles. Those drivers were connected to a LIN bus because the MCUs did not have CAN. The combination of that functionality in a cost-effective 8-bit MCU with CAN could provide flexibility and a simplified alternate approach to the design.

While most 8-bit MCUs on the market rely heavily on the core for processing its peripheral’s functions, other system design possibilities that can be performed by CIPs without significantly taxing the CPU include: precision interface to various sensors, high-power LED driver and/or a reasonably complex level of motor control.

To determine which of these and other possibilities are appropriate for a specific network, a variety of development tools are available. For example, the MPLAB® Code Configurator (MCC) is a free software plug-in that provides a graphical interface to configure peripherals and functions specific to the application. With this tool, system design engineers can easily configure the hardware-based peripherals—rather than writing and validating an entire software routine—to accomplish a specific task.

Developing a CAN-Do Attitude
For automotive and industrial applications, system designers certainly have several choices for bus architectures. As a widely accepted bus, and certainly when additional sensing and/or control are required for an existing network, an MCU with additional functions to address different system requirements makes CAN an excellent option. With its Core Independent Peripherals, the 8-bit MCU/CAN family allows CAN expansion into more cost-sensitive nodes on the network.

The new 8-bit MCU/CAN+CIPs address emerging automotive network applications that require flexible, cost-effective, simple, and reliable robust data transmission. Present too are the increased performance and system support that access control, battery charging/battery management, and diagnostic equipment demand.

References

  1. PIC18 K83 Product Family: http://www.microchip.com/promo/pic18f-k83
  2. MPLAB Code Configurator (MCC): http://www.microchip.com/mplab/mplab-code-configurator

Edwin Romero began working in the semiconductor industry in 2006. Prior to joining Microchip Technology in 2012, he worked in various roles at ON Semiconductor, including application engineer, and in technical sales and marketing. As a product marketing manager within Microchip’s MCU8 Division, Romero is currently responsible for product definition and promotion of Microchip’s 8-bit PIC® microcontrollers. He has a Bachelor of Science degree in Electrical Engineering (BSEE) degree from Arizona State University.

 

Engineering Automated Driving Systems for Safety

Friday, March 9th, 2018

Modern autonomous vehicle designs benefit from safety-critical electronics built on proven, trusted military and aerospace systems engineering standards and practices.

Autonomous vehicles (AVs) of all types—including self-driving cars on city streets, trucks on military bases and the open road, and various unmanned platforms on land, at sea, and in air—are poised to transform transportation. The automotive market is on the cusp of significant change, enabled by innovative automated driving system (ADS) technologies; yet, widespread deployment hinges almost entirely on safety.

A single ADS mishap can have far-reaching implications, adversely affecting the acceptance and adoption of autonomous vehicles worldwide. Destruction of property and loss of life caused by any manner of ADS failure will not be tolerated, by the public, regulatory bodies, transportation officials, or lawmakers—all of whom seek assurances from automotive manufacturers that the vehicles, including all essential systems, can be trusted to perform reliably no matter what they might encounter on the road.

Figure 1: Automated Driving System technologies must work in environments from highways to city streets to the roughest back roads in all kinds of weather, a strong argument for relying on computer and electronics systems developed and designed for ruggedness.

Predictable, repeatable performance over time is integral to safety, which in turn builds trust. A single unfortunate event could slow, set back, or even bring an abrupt end to the advancement, adoption, and acceptance of autonomous driving systems and threaten the entire global autonomous vehicle industry. Automated driving system failures are not an option and must be avoided, through the use of systems specifically designed to be durable, offer high availability, and perform reliably in various operational environments throughout their life cycles.

Best Practices and Guidance
Transportation safety experts are encouraging autonomous vehicle and automated driving system manufacturers to benefit from lessons learned in the military and aerospace market. Best practices include the adoption of industry standards and systems engineering practices successfully employed for decades in aerospace and defense programs, according to the latest guidance from both the U.S. Department of Transportation (DoT) and the National Highway Traffic Safety Administration (NHTSA).

DoT officials issued Automated Driving Systems 2.0: A Vision for Safety, voluntary guidance that encourages best practices and prioritizes safety to help pave the way for the safe deployment of advanced driver assistance technologies. In it, officials encourage technology companies working on ADS to adopt guidance, best practices, design principles, and standards from industries such as aviation, space, and the military.

Military and aerospace vehicles and vehicle-based electronics are renowned the world over for being built to work reliably, without fail, over a long operational life in even the most challenging applications, rough terrains, and extreme environments. For example, the military continues to rely upon the Boeing B-52 Bomber military aircraft, currently in its sixth decade of service and expected to serve through 2045, while NASA’s Voyager 1 spacecraft is still receiving commands and communicating data, more than 40 years into its mission, from the harsh, radiation-rich environment of space.

Operational Environment
Transportation safety specialists also stress the importance of designing and validating ADS specifically for the entire operational design domain, defined as the specific environments in which the automated system is designed to operate, including roadway types, speed range, and environmental conditions, such as weather.

Military and aerospace organizations, including the Department of Defense (DoD) and NASA, learned decades ago that traditional computer and electronics systems would soon become ineffective, work only sporadically, or completely fail to function in the field. Consumer- and enterprise-level systems are largely designed to operate in climate-controlled, protected office environments and, when deployed in the field, typically cannot withstand and will succumb to various environmental elements, such as: shock and vibration, drops, hot and cold temperature extremes, dust and dirt, water and humidity, and snow and ice.

These and other environmental factors threaten computer and electronics reliability, which is inextricably linked to safety. Mission- and safety-critical projects, therefore, require computer and electronics systems to be protected from the elements. The most effective, efficient, and economical way to ensure high reliability, particularly for ADS expected to function daily on everything from highways to city streets to the roughest back roads in all kinds of weather, arguably is: to use computer and electronics systems that are built rugged from design and development, through meticulous manufacturing and testing, to deployment in modern autonomous vehicles of all types in various locales.

Autonomous Innovations
Today’s savvy automotive and automated driving system manufacturers recognize the value that long-time, trusted military and aerospace suppliers bring to the AV market, including: field-tested and proven technologies, standards and requirements compliance, experience, and expertise. Many are, therefore, proactively seeking out and partnering with technology companies that have extensive experience delivering rugged computer and electronics systems designed to meet strict industry standards and operational requirements and built to last in a variety of demanding applications and challenging environments.

Technology leader Intel Corporation partnered with Iowa-based Crystal Group Inc.—designer/manufacturer of rugged computer hardware, member of the Intel Internet of Things (IoT) Solutions Alliance, and award-winning Intel Technology Platinum Provider—to design, develop, manufacture, and test a robust, rugged, and reliable high-performance computer crafted specifically to speed time to market of autonomous vehicles and automated driving systems. Crystal Group’s technical staff applied decades of experience engineering systems to meet strict military small size, weight, and power (SWaP) requirements to pack the processing power and data storage capacity of a high-end server in a 3U high-performance embedded computer (HPEC) while reducing power consumption and limiting system temperature rise.

That award-winning AV computer designed in close collaboration with Intel formed the basis of the new Crystal Group Rugged Autonomous Computer Equipment (RACE™) line that is helping to accelerate AV and ADS development, testing, and deployment to bring innovations to market faster. The Crystal Group RACE0161 Rugged Server provides automaker OEMs with compute power, data-handling and Internet of Things (IoT) capabilities, and data storage capacity in a compact, rugged solution capable of withstanding harsh environmental conditions, including potholes, washboard roads, temperature extremes, and collisions that are likely to cause traditional systems to fail.

Specifically designed for unmanned and autonomous driving vehicles, the Crystal Group RACE0161 provides the horsepower AV and ADS projects need with dual Intel® Xeon® Scalable Processors (Skylake) to deliver a unique, turnkey AV/ADS computer with industry-leading compute and IoT capabilities. The rugged server combines robust I/O, multiple GPU capacity, dual Intel Xeon CPUs, sophisticated thermal management, and other high-quality components stabilized in a rugged, aluminum enclosure measuring just 6.5 x 14.1 x 15.6 inches and weighing 30 to 40 pounds. Providing superior performance per watt, the high-performance server can operate off a 12-volt (12V) car battery without the need for AC/DC power conversion and does not require costly and time-consuming power modifications to convert 12V power systems to existing 24V power systems.

Crystal Group’s RACE product line, including the RACE0161 and vehicle-specific development kits, is designed to deliver speed, agility, and quality in a single, turnkey package, helping AV and ADS manufacturers take advantage of the latest technology advances while speeding the pace of development. Crystal Group’s RACE0161 is garnering global industry attention for its potential to put AV and ADS projects on the fast track by speeding time to market, ahead of competitors, with the added confidence that comes with a military-grade, rugged, reliable solution.

High Reliability for Safety
“From reducing crash-related deaths and injuries, to improving access to transportation, to reducing traffic congestion and vehicle emissions, automated vehicles hold significant potential to increase productivity and improve the quality of life for millions of people,” A Vision for Safety 2.0 explains. Motor vehicle-related crashes on U.S. highways claimed 37,461 lives in 2016, DoT research indicates, noting that 94 percent of serious crashes are due to dangerous choices or errors people make behind the wheel.

“Technology can save lives,” transportation safety officials affirm, with the help of highly reliable, fail-safe automated driving systems tailored to fit the application and the environment. “Thanks to a convergence of technological advances,” A Vision for Safety 2.0 reads, “the promise of safer automated driving systems is closer to becoming a reality.”

Self-driving cars bring the promise of greater energy conservation, lower emissions, added convenience, and roads that are both safer and less congested. To fully realize this vision, automotive manufacturers and autonomous vehicle makers are opting to benefit from established standards and lessons learned in mission- and safety-critical military and aerospace programs. Through collaboration with experienced, trusted industry partners with proven, field-tested, military-grade products, services, and technologies manufacturers of autonomous vehicles and automated driving systems can bring their innovations to market faster. And with the added confidence that comes with rugged, reliable systems built to last in even the most extreme environments.


Chip Thurston is Chief Architect & Technical Director Crystal Group Inc. Thurston joined Crystal Group in late 2000, holding various leadership roles in engineering. Thurston pioneered advanced rugged technology for many major computing systems that are currently being used by NASA, Intel®, U.S. Armed Forces, and major automotive manufacturers. A native of Cedar Falls, Iowa, Thurston holds an AA in MIS/CIS and a BA in Business Management.

 

Automotive Ethernet: The Future of Autonomous Vehicles

Tuesday, February 27th, 2018

Understanding how the new Automotive PHYs differ from other BASE-T PHYs matters. Here’s why:

Introduction
From a broad market perspective, Automotive Ethernet is a joint effort of the Automotive and Networking industries to modernize, simplify, and expand the capabilities of vehicles by improving data communications inside vehicles. The key factors that led the Automotive industry to start this effort are the need for higher bandwidth, shifting of architectures to a centralized backbone, and guaranteed latency. Reducing the complexity of today’s vehicle network infrastructure, which commonly has up to eight different networks, is also a key driver. The complexity of handling so many different networks has a huge impact on the cost of today’s vehicles. Not only does the need for specialized skill sets for each networking type add expense, so does the difficulty of managing legacy software/firmware, with resulting incompatibility and inability to reuse parts. Because these improvements required a dedicated physical layer network, the industry widely recognized the strength of Ethernet as an ultra-compatible and flexible network that could handle the requirements of the Automotive industry. In 2014, the IEEE and the Automotive industry began efforts to make Automotive Ethernet a reality.

What Makes it ‘Automotive’?
‘Ethernet’ is one of the most ubiquitous LAN communication technologies in the world, but how an Ethernet network is implemented and physically represented can vary depending on the application. The IEEE 802.3 Ethernet standard has more than 100 clauses, each defining different protocols or physical layers (PHY) designed to cater to the many industries that have embraced Ethernet for the last 40+ years. When asked to describe ‘Ethernet,’ most people probably associate the plug on the back of their desktop PC and the Cat 5e network cable that connects to it. This form of Ethernet is one of several BASE-T PHYs that have been installed in office buildings for the better part of 30 years. These technologies all use the RJ-45 form factor (computer plug), designed to operate on Category cabling up to 100 meters, and can transfer data up to 10Gbps (but most installations are 1Gbps or slower). There are also the high-speed Ethernet implementations used in server farms that can transfer up to 100Gbps but have a reach of less than 10 meters over twinaxial based copper cable and implement different connectors. However, all Ethernet system models share the same media access control (MAC) definition (only the physical layer and transmission medium differ). So, all upper layer functionality is agnostic to the specific application being implemented. Another way to say this is that all Ethernet regardless of the physical medium use the same frame format. This is one of the key benefits of Ethernet.

‘Automotive Ethernet’ typically refers to one of two IEEE PHY definitions. Either IEEE 802.3bw, the 100Mbps PHY, or 802.3bp, the 1Gbps PHY, specified in Clause 96 and Clause 97 respectively. While these PHY types are commonly referred to as 100Mbps and 1Gbps Automotive Ethernet, their official IEEE PHY name is 100BASE-T1 and 1000BASE-T1. ‘BASE-T’ meaning a baseband technology that operates over a copper twisted pair medium, and ‘1’ specifying the number of differential pairs needed within the copper link segment. Both were developed within the IEEE at nearly the same time, and the use case for each is quite similar so they share several design features. These include a 15meter reach, full duplex operation over a point-to-point single unshielded twisted pair (UTP) architecture, and threelevel pulse amplitude modulation (PAM3) line coding

But why not just reuse the existing Ethernet definitions? Each protocol and PHY defined in the IEEE 802.3 standard is developed such that its implementation can be flexible to avoid limiting the technology to a specific application space. That being said, there also needs to be a starting point with use cases proving broad market potential, a distinct identity, and technical feasibility. The Automotive industry determined that existing Ethernet technologies didn’t meet all its needs as a costcompetitive option. First, cars are not 100 meters long, so the traditional BASE-T PHYs that are built into our laptops were over-designed in terms of reach for this specific PHY. Second, the environmentally conscientious climate of the world demands fuelefficient vehicles, and one of the simplest ways to improve fuel economy is to reduce a vehicle’s weight. Much to the IEEE community’s surprise, the third heaviest component in a car is the cable harness (heaviest is the engine, and second heaviest is the chassis). The Cat 5e cable used with BASE-T PHYs have four twisted pairs (eight wires), so one of the requests was to define the Ethernet network over a single twisted pair, leading to a weight (and therefore cost) reduction compared to Cat 5e cabling (Figure 1). Lastly, the environment inside a vehicle is drastically different than the office or home. Not only do the electronics and cabling need to withstand dirt, oil, grease, freezing temperatures, and blistering heat, but there are also electromagnetic interference (EMI) concerns so that the other circuitry in the vehicle isn’t compromised from radio frequency (RF) radiation of the Ethernet network. This is very different than the typical office and data-center environment considered by earlier Ethernet standards.

Figure 1: Example of automotive wiring system inside a car. (Image credit: Chris DiMinico, MC Communications)

Conformance Testing for Automotive Ethernet PHYs
As if the differences between the Automotive market and other Ethernet markets isn’t apparent by now, there’s also literally no room for error. In the office, it’s a slight annoyance if a data packet is received in error; in a self-driving car it could mean the difference between stopping at a traffic light or running a red light into oncoming traffic. With self-driving fully autonomous vehicles all but a reality, Automotive OEMs have countless safety regulations they need to prove can be maintained while a person is not under direct control of the vehicle. So, conformance test specifications have been defined for every aspect of the vehicle’s performance, including the Ethernet components that are installed.

There are three functions in the IEEE BASE-T1 PHY architecture (Figure 2) that have distinct capabilities and encompass all of the mandatory conformance requirements: physical medium attachment (PMA), physical coding sublayer (PCS), and PHY Control (function within the PMA).

Figure 2: 100BASE-T1 PHY Architecture (Image Credit: IEEE 802.3bw-2015 Standard)

Physical Medium Attachment Conformance Testing
The PMA is the PHY sublayer that drives the actual data signal onto the UTP cabling, directly manipulating the transmitted voltage. For this reason, most of the conformance requirements specified in the PMA test specification are related to voltage amplitude, transmit jitter, return loss, etc. The most difficult test to accurately set up is the Transmitter Distortion test. This test metric first appeared in the original Gigabit Ethernet (IEEE 802.3 Clause 40) standard as a time domain approach to quantify the linearity of an Ethernet transmitter. Since the PHY architecture is point-to-point full duplex operation, both 100BASE-T1 nodes that are linked together are transmitting and receiving on the same wires simultaneously. Therefore, it is important that each transmit output amplifier is operating in a linear state and can suppress any non-linear by-products of the two signals being summed on the copper UTP. To measure this, the test method described in Clause 96 defines a sine wave of specific amplitude and frequency to be injected into the transmit path of the device under test (DUT). The DUT is simultaneously transmitting a pseudorandom test pattern. The test pattern and the sine wave are summed and measured on an oscilloscope by probing the transmit path. The actual transmitter distortion value to determine conformance is a product of an IEEE-defined Matlab script that downloads the oscilloscope capture and analyzes the measured waveform.

The test equipment needed for the transmitter distortion test setup (Figure 3) consists of a real-time oscilloscope, differential probe, and waveform generator. All of these are common in test houses and used for most time domain test cases. However, the injected sine wave needs to be synchronized with both the oscilloscope sampling clock and DUT transmit clock to guarantee that the clock domains aren’t misaligned. Not doing so will unintentionally add distortion into the system and result in inaccurate distortion values. There are two commonly used methods to properly frequency lock all the clocks within the test setup: (1) synchronize the test equipment to the DUT’s 66.67 MHz transmit clock (TX_TCLK), or (2) provide the DUT an external reference clock that is generated from the test equipment. In either scenario the tester will need access to the TX_TCLK and the ability to probe it, or the option to provide an external clock source to the silicon. So, this requires the silicon vendor to provide such hardware features to properly characterize a PHYs transmitter distortion. This isn’t always the case. The IEEE standard does not define a test method for this scenario. To resolve this, recently some T&M vendors have implemented clock and data recovery (CDR) functionality into their oscilloscopes, which removes the need to have direct access to the DUT’s TX_TCLK.

Figure 3: 100BASE-T1 PMA Transmitter Distortion Test Setup

Physical Coding Sublayer and PHY Control Conformance Testing
The PCS and PHY Control test specifications are less straightforward. These sublayers are the digital logic within the PHY and are typically governed by transmitter and receiver state machines that define specific state behavior and timing requirements for each operation. Rather than calling for oscilloscope measurement of standardized test patterns transmitted by the PHY, these test cases require that the DUT successfully achieve a link with a test station that behaves as if it is a PHY. Meeting this requirement means that the test station must be able to encode a specific test sequence into the PAM3 signalling. What’s more, the test station must also decode the PAM3 signal the DUT transmits. To achieve these goals, the University of New Hampshire InterOperability Laboratory (UNH-IOL) created an FPGA-based test tool (Figure 4) that performs the necessary conversion to PAM3 signalling as well as bit-level error injection to fully stress the DUT’s receiver logic.

Figure 4: UNH-IOL 100BASE-T1 PCS and PHY Control Conformance Test Tool

Ethernet PHY receiver definitions specify many requirements, but how the functionality is implemented is left to the designer. So, test sequences necessary to test conformance can vary among silicon companies. One of the least consistent PHY parameters is the time necessary to achieve a link. Typically, the number of received idle symbols needed for the DUT to reliably recover the clock of the remote PHY governs the time needed to achieve a link—making test tool flexibility to accommodate any DUT crucial. Additionally, many test cases within these conformance test specifications perform negative test conditions, meaning intentionally injecting errors within the data stream to observe how the PHY behaves. Because of this, some test cases require bit errors, erroneous PAM3 symbols, or Ethernet packets with incorrect CRC values. The test setup used by UNH-IOL (Figure 5) uses a PC with custom software to dynamically control the test sequences used to accommodate any silicon design.

Figure 5: 100BASE-T1 PCS and PHY Control Test Setup

Conclusion
While the IEEE 802.3bw and IEEE 802.3bp PHY definitions may seem similar to other BASE-T PHYs, many environmental considerations and specific use-case data was used to create these unique Ethernet technologies within the IEEE standard. Test specifications were created specifically for these new Automotive PHYs, which require specialized test tools and attention to test setup details not considered in previous Ethernet conformance testing.


Curtis Donahue is the Senior Manager of Ethernet Technologies and manages the Automotive Ethernet Test Group at the University of New Hampshire InterOperability Laboratory (UNH-IOL). His main focus has been the development of test setups for physical layer conformance testing, and their respective test procedures, for High Speed Ethernet and Automotive Ethernet applications.

Donahue holds a Bachelor of Science in Electrical Engineering from the University of New Hampshire (UNH), Durham and is currently pursuing his Masters in Electrical Engineering at UNH.

 

WYSIWYG for the Automotive AR Era: Q&A with Mike Firth Texas Instruments

Wednesday, January 3rd, 2018

Why HUD system imagery and drivers stand to gain

Lynnette Reese, Embedded Systems Engineering

Editor’s Note: Automotive Head-Up Displays (HUDs) enable drivers to see critical information in front of their eyes so they no longer need to glance down. Augmented Reality (AR) is coming to automotive HUDs using technology that’s faced challenges in the harsh environment of the automobile. Thermal management has been an especially big challenge, since electronics are expected to start up and function properly from the instant the car is started. Texas Instruments (TI) has made improvements in HUD technology that overcome thermal management issues, double the Field of View (FOV), and provide drivers with image depth and vitality where AR can flourish.

TI marketing manager for automotive DLP Products Mike Firth took a moment to answer some questions for Embedded Systems Engineering on what makes a much-improved HUD experience possible.

Lynnette Reese, Embedded Systems Engineering (LR): Can you tell us a bit about the technology that Texas Instruments provides?

Mike Firth, Texas Instruments

Mike Firth, Texas Instruments: The technology powering these HUD interior automotive projection systems is the same basic technology that you find in corporate and educational projectors as well as digital cinema theatres but with a bit more to withstand the automotive venue. The DLP3030-Q1 has more than 400,000 individual micromirrors that switch on and off at extremely high rates. This fast switching is what enables the clear and bright imagery, high color saturation, and faithful color representation. Fundamentally, there are some unique features that enable the DLP3030-Q1 HUD chipset to address augmented reality (AR) in the automotive market, and they are the quality of the image that the chipset can produce, image brightness, and the ability of the chipset to withstand the thermal challenges that heavy solar loads—such as those found in a harsh automotive setting—pose. The digital micromirror device (DMD) automotive operating temperature range is from -40 ºC to +105 ºC, and the DLP technology performance does not deteriorate. In short, the DLP3030-Q1 chipset supports AR with amazing imagery, color, and very bright displays.

 

Figure 1:  Firth ponts out that the Texas Instruments DLP 3030-Q1 chipset is designed and optimized for a real-time augmented reality experience.

Digital imagery (Figure 1) is positioned in the driver’s field of view (FOV). You can see that it is not just a display. Instead, we are interacting with the driver’s FOV, the environment, and the objects in the environment, marking the distance between the driver and the next car. The red barrier on the right indicates potential danger. The system overlays digital information onto the windshield, interacting real-time with the world as the driver sees it.

What makes this next generation DLP 3030-Q1 chipset special is the solar load performance, accurate color reproduction, and brightness. And not to be overlooked is the decreased package size that enables smaller HUDs while increasing the overall performance. A new ceramic pin grid array package (CPGA) has reduced the overall footprint by 65 percent versus the previous generation.

LR: Are you saying that there’s no compromise in display quality in an automotive environment at all? What if the driver puts on polarized sunglasses? Won’t that make the HUD disappear?

Mike Firth, Texas Instruments: You see the same color, brightness, and contrast across that whole temperature range, enabling clear imagery in all types of conditions—images are visible regardless of temperature and polarization. And yes, in a typical HUD when the driver puts polarized sunglasses on, the image disappears because creating the image demands polarized light. With the DLP system images remain visible even when the driver wears polarized sunglasses.

LR: What makes an AR HUD any better than any other automotive HUD?

Mike Firth, Texas Instruments: To this point, an HUD has been primarily a display. It has not necessarily had the means to float far out over the road in the driver’s field of view, and both colors and information remain basic.

However, as we transition to AR HUDs, as seen in Figure 2, digital information is overlaid completely within the driver’s field of view, at varied distances away from the driver. The distance separation and the red warning bars are quite far out.

 

Figure 2: Moving to Augumented Reality Head-Up Displays

The virtual image distance, which is the measurement of how far from the driver’s eyes the images appear to be floating or resting, is typically somewhere in the two- to twenty-meter range. Today it is probably in the two- to two-and-a half meter range and essentially acts just as a secondary display. As the move to augmented reality takes place you’ll start seeing 7.5-, 10-, 15-, 20-meter virtual image distances, allowing those images to be projected farther.

So, in this case colors, brightness, and the field of view increase. While it’s great to have a wider FOV, you need more brightness to power a larger FOV. You need a technology that is very bright and very efficient at providing the light and accurate colors to enable that larger FOV. Part of the answer lies in the true augmented reality functionality that the DLP employs.


Figure 3: As virtual image distance grows, it opens up that canvas in which you can project images and interact with the driver’s field of view.

LR: Can you explain what you mean by “true augmented reality functionality”?

Mike Firth, Texas Instruments: Sure. It indicates how interactions occur and where that digital imagery can be projected (Figure 3). If you start with a 2.5-meter virtual image distance and, say, a five-degree field of view, which is the red, as Figure 3 shows you see that the image floats just over the hood of the car. You don’t have much field of view, so the images are not very large. You can’t interact with a whole lot of the driver’s environment, but as you start to increase the virtual image distance and increase the field of view with this technology, you can see that now you can start to interact with the cars ahead, sides of the street, turn indications, and so forth.

 

Figure 4: HUD optics magnify solar load.

LR: No pun intended, but have there been any significant road blocks in designing AR for automotive?

Mike Firth, Texas Instruments: One of the primary challenges in designing HUDs is related to the solar load (Figure 4), which is magnified by the HUD’s optics. That effect puts a whole lot of thermal energy on a very small area, causing considerable challenges to thermal load management. If not managed properly the amount of energy projected onto a very small area will cause significant damage to the imager.

LR: It sounds like part of the challenge includes optics. Could you tell us why, and go into more detail on why thermal management is a problem?

Mike Firth, Texas Instruments: Already thermal load management is challenging for today’s HUDs. And that’s with virtual image distances of just 2-2.5 meters. When you move to augmented reality, and you start getting to 7.5 meters, the challenge increases, because you have to increase the magnification to support that longer virtualized distance, which moves the imaging plane. So, whatever is making the image, it moves it closer to the focal point of the optical system, which results in a higher concentration of energy. In an augmented reality HUD, that imaging plane—the diffuser panel in the case of the DLP system—moves further back, resulting in a higher concentration of energy, not necessarily more energy coming in. Although with an AR HUD, because you have a wider field of view, you do let in more sunlight at the beginning than a traditional HUD out there today.

Table 1: The DLP technology diffuser maximum operating temp is 125 ºC.

LR: I can imagine that the DLP is what makes the difference. Can you connect the dots for us as to how the DLP technology creates an advantage over other HUD imaging solutions for harsh environments like automotive?

Mike Firth, Texas Instruments: DLP is a projection-based system that projects the image onto a diffuser, which receives the focused sunlight. The main advantage in DLP technology architecture is that the absorption of the sunlight is minimal, which eases the solar load problem; therefore, heat does not reach the level that other competing technologies introduce and then must deal with.

LR: What impact do you expect to see AR have in the automotive sector?

Mike Firth, Texas Instruments:  Trends are driving towards enabling AR displays, that is, trends are moving towards making it easier to implement augmented reality displays in the automobile. The trend in augmented reality itself is to increase that virtual image distance to at least 7.5 meters if not greater, and in a field of view of at least 10 degrees, as compared to the current six to eight degrees in FOV. The longer the virtual image distance and the wider the FOV, the better experience the driver is going to have.

LR: Does Texas Instruments see any other trends in automotive?

Mike Firth, Texas Instruments:  Three trends are gaining momentum, and they are Advanced Driver Assistance Systems (ADAS), electric cars, and autonomous cars. In 2024, lane departure and distance collision warning are forecast to be in over 50 percent of the automobiles produced worldwide[1].

The shift to electric cars is very strong, with several studies out there now that show that in Europe, up to 30 percent of the cars produced in 2025 could be electric—either plug-in hybrids or fully electric. Worldwide, it’s forecast that 14 percent of automobiles will be electric cars in 2025. And in an electric car, you no longer have a firewall separating occupants from a combustible engine compartment, so you have more space to install an augmented reality HUD. Electric cars can be designed from the ground up with AR in mind.

There is also a lot of interest in how AR can play a role in keeping drivers properly engaged in vehicles that are at less than Level 5 on the self-driving scale—especially at that transition point where the self-driving car is leaving fully autonomous mode, handing off control to the driver.

LR: Do you have any development tools for those interested in evaluating or developing an AR for a harsh environment like the automotive space?

Mike Firth, Texas Instruments:  There’s the DLP3030-Q1 EVM evaluation module for the electronics side of things, as well as the DLP3030PGUQ1EVM for evaluating a picture generation unit. A third EVM, DLP3030CHUDQ1EVM, is a table top demonstrator combiner HUD. It shows the image on a piece of glass and is a portable way to evaluate DLP technology and the performance. It’s a complete HUD system that you can drive with different test patterns and different video while assessing the overall performance of a DLP-based system and what it can offer.


Lynnette Reese is Editor-in-Chief, Embedded Intel Solutions and Embedded Systems Engineering, and has been working in various roles as an electrical engineer for over two decades. She is interested in open source software and hardware, the maker movement, and in increasing the number of women working in STEM so she has a greater chance of talking about something other than football at the water cooler.

 


[1] Strategy Analytics’ Aug 2017 Report (Advanced Driver Assistance Systems Demand Forecast 2015 – 2024)

Custom Cars for Everyone with 3D Printing?

Monday, August 21st, 2017

Why mass-scale personalization of cars is not right around the corner

Ultimately, as humans, we are all individuals and how we demonstrate this, through our appearance and behavior, is what characterizes our personality. This often extends to our immediate environment in terms of our possessions and how we decorate our homes and office workspaces. Fashion also plays its part, and how readily and how extravagantly we follow its ever-changing trends further indicates whether our sense of style is outrageous or more conservative.

Figure 1: 3D printing holds the possibility that, starting from a stock vehicle chassis and body, consumers can add features tied to their individual preferences. (Courtesy Mouser Electronics)

Figure 1: 3D printing holds the possibility that, starting from a stock vehicle chassis and body, consumers can add features tied to their individual preferences. (Courtesy Mouser Electronics)

Alongside personal styling, the gadgets we surround ourselves with and how we present our homes, one thing that probably says a lot about most of us is our car. Of course, for many, this is a very practical choice, influenced by considerations such as its capacity to carry people, pets and other loads, and running costs. For others, performance and style are key, which in the extreme, are often little more than an ostentatious display of wealth.

However, even the majority of “sensible and practical” car owners like to reflect some of their personality in their choice of vehicle, even if that is limited to the basics of make, model and color. This is not surprising when you consider that a 2016 report from the AAA Foundation for Traffic Safety found American drivers spend an average of more than 17,600 minutes behind the wheel each year. Unlike the early days of the automobile, when choices were limited and Henry Ford famously said words to the effect, “You can have any color as long as it is black,” the range of model, trim and styling choices from manufacturers today is almost bewildering. Even so, while the permutations possible may make it unlikely that you’ll see another car on the road that is exactly like yours, the level of personalization possible doesn’t amount to true customization.

This is not to say that everyone wants to own what we commonly refer to as a “custom car,” which usually evokes ideas of souped-up performance, extravagant styling and flamboyant color schemes. Rather, we might like the opportunity to impart something that’s a little original in the design or appearance of our car, something no one else will have. Wishful thinking or not? With the advent of 3D printers, this is entirely possible.

The Bounds of Possibility

From a theoretical standpoint, producing an entire car using 3D printing technology should be possible. However, the scenario of a customer visiting a dealership, specifying what they want and having that vehicle built to order to drive away is perhaps a little fanciful, at least in the immediately foreseeable future.

Nevertheless, all the elements are there, certainly for producing most of the parts using 3D printers. Today’s cars comprise some 20,000 components of all shapes and sizes, made from a variety of different materials. Printing these simultaneously with a single machine to produce a car in one go is simply not possible, even ignoring the complexities of some of the electronic components that require very specialized manufacturing processes.

Figure 2: Will 3D printing prove the means for vehicles to reflect their owners’ personalities? (courtesy Mouser Electronics)

Figure 2: Will 3D printing prove the means for vehicles to reflect their owners’ personalities? (courtesy Mouser Electronics)

Then there are the economies of scale to consider. Present day automotive assembly lines represent the evolution from having cars built one-at-a-time by teams of people to a situation where vehicles are built up step-by-step as they progress through the factory, with perhaps a hundred being worked on simultaneously, and then mostly by robotic machines dedicated to efficiently implementing a single function. Even allowing for the benefits of automation and robotics, reversing this manufacturing strategy would most likely also negate the cost benefits of current mass-production processes.

This is not to say that 3D-printed cars are just a pipe dream. Indeed, companies like Mouser’s partner, Local Motors, are demonstrating what is possible, particularly with a focus on autonomous vehicles. Despite such potential, the view of most industry experts is that the mass-scale personalization of cars is unlikely within even the next 100 years. Not only no infrastructure in place to support this, but also a host of design constraints would need to be addressed, not least meeting mandatory safety regulations. Instead, we have to look elsewhere for the benefits 3D printing can offer this industry.

Overnight Change? Not So Much

Automotive design and the large-scale manufacture of affordable cars using the production line approach has been refined not just over decades but now for more than a century. Consequently, we shouldn’t expect 3D printing to change things overnight, even allowing for the rapid evolution of that technology. So, while today it is possible to print a bare-bones mechanical car, it is important to understand the design requirements and the implications of material choices.

Regardless of how the material is formed to make a particular component, what is more important is how that component is designed to meet the required function. This is where the common expert refrain is that “design should be left to designers” because of the risk that, regardless of whether they know what they want, the majority of customers are incapable of designing something that will function correctly, let alone safely.

Mechanical elements need to perform in some different ways. They need to provide strength and rigidity while at the same time being lightweight and durable. The effects these components have on a vehicle’s handling, or its aerodynamic performance is not something even the maker generation of designer is equipped to deal with. Then there are the highly important considerations of safety and reliability, with many aspects of safety being highly regulated and often subject to rigorous testing. And of course, affordability is also essential.

Currently, the materials 3D printers do best are plastic and metals. Even so, the cost of producing something like a plastic bumper or a steel body panel would not only require a large printer but is unlikely to be cost-effective compared to the respective processes of using injection molding equipment or sheet metal presses. By contrast, 3D printers may provide the means to take advantage of a material like aluminum, which is difficult to work with using current production technologies but is attractive for making lightweight aluminum frames.

Squaring the Circle

Returning to the economics of custom versus mass production, one of the problems created by the extensive choice of options offered by vehicle manufacturers today is that of inventory. While producing in bulk typically reduces cost, to avoid the impact of lengthy component lead-times adding to the long waits customers already face when ordering a car that’s not a stock model, it is inevitably necessary to build ahead and hold inventory based on expected demand for these options.

And the wider the choice, the worse this problem becomes, which is where 3D printing may rebalance the cost equation in this consumer choice dilemma. Holding inventory entails a cost that is multiplied by the array of options available. For example, let’s consider just a few items of body detailing, such as a radiator grille, door trim, mirror cover and trunk sill protector. If each of these is offered in black, chrome and perhaps 2 or 3 other finishes to complement the vehicle’s body color, that already amounts to some 20 component variants. Under these circumstances, on demand printing may prove more cost effective.

Then we come to more creative options, which might potentially include customized body panels. There is an argument that vehicle manufacturers should start with a stock vehicle chassis and body to which customers can add features and styling details, with CAD software to ensure everything functions correctly—even through to running virtual wind tunnel and performance testing.

Whether this is where the future of the automobile industry lies remains to be seen. Undoubtedly manufacturers will embrace 3D printing technology where it offers obvious benefits, in much the same way as the aerospace industry has when it comes to designing parts that are lighter weight or achieve some key performance breakthrough. 3D printing could become economically viable with regard to addressing vehicle option proliferation, but its adoption for further enhanced customization will be another matter, which in part will reflect competitive pressures within the industry but equally could remain the preserve of after-market or specialist suppliers.


Photo-RobertHuntleyRobert Huntley is an HND-qualified engineer and technical writing specialist. Drawing on his background in telecommunications, navigation systems, and embedded applications engineering, he writes on a variety of technical and practical topics on behalf of Mouser Electronics.

Improving Autonomous Driving Communication and Safety with Private Blockchains

Thursday, June 22nd, 2017

Here’s why Blockchain, a powerhouse database in finance and digital identification, has what it takes to become the backbone of automotive data communication—beginning with the autonomous car.


Blockchain technology isn’t just for Bitcoin: It’s driving into several other industries at a breath-taking velocity. It’s now well established for financial markets and digital identification, with other major industries such as healthcare and insurance companies in fast pursuit. Emerging areas for Blockchain are also diverse, covering areas such as energy, where micro-grid producers see Blockchain as a method to keep track of the energy generated. Blockchain itself is evolving as well, with Blockchain 2.0 promising even more functionally for broader groups by introducing new applications.

Figure 1: Yes, the use of Blockchain technology for V2V and V2i communication could be even closer than it appears.

Figure 1: Yes, the use of Blockchain technology for V2V and V2i communication could be even closer than it appears.

Blockchain can also be used throughout the automotive industry. Automotive applications range from revolutionizing the supply chain to authenticating ride sharing for a passenger and the vehicle owner. However, the clearest overall group of opportunities for automotive targets the critical functions autonomous vehicles perform when under their own control.

Communication Opportunities
One of the opportunities for Blockchain in the autonomous car deals with communication. That is Vehicle-to-Vehicle (V2V) communication as well as Vehicle-to-Infrastructure (V2i). Along with other vehicle based communications they are commonly grouped with, V2V and V2i can also be referred to as Vehicle-to Everything (V2X). Regardless if it’s V2V, V2i, or just V2X, all require fast and secure transmission of data as well as undisputable records—of the data, the transmission itself, and the recipient(s).

In V2V, vehicles inform other vehicles within their communication community about myriad details in the surrounding environment. One example would be real-time information regarding the roads traveled, including themes such as traffic flow, construction zones, workers on the road, etc. This type of detailed information can empower other vehicles in the communication community. Cars and trucks can optimize their performance and take the shortest time or distance route, based on real-time data. V2V can also lend itself to more core vehicle functions such as gear optimization on a given incline, allowing trucks to minimize fuel consumption. In V2V, autonomous communication to other similar vehicles (peer-to-peer) employing a fast and secure method is critical to the intelligent car’s core functionality.

Meet the Automotive Information Broker

In V2i, a car can produce thousands of independent information packets every minute and push them to what could be hundreds of infrastructure receivers from traffic lights to data aggregators. It’s an automotive information broker. The packets of information themselves hold little value independently, but when assembled with other vehicles, it then has substantial value in determining everything from dynamic traffic control to component wear patterns for a given class of car in a given geography. In V2i, fast and undisputable records are the key to success.

By using Blockchain for V2X, an OEM gains additional speed and frequency of secure transmissions not available with the majority of today’s OTA solutions. That is, the OTA solutions available are specifically designed to perform file transfers for either a full binary update or partial update for major systems such as infotainment, telematics, and (in some cases) the vehicles’ ECUs as well.

While these updates are highly secure, they are designed for the specific purpose of software updates. In V2X, the data transfer to or from the vehicle is typically small packets of data intended to either inform the vehicle or take an immediate action. A history or log is also advantageous for proof of action should an accident occur. Given the unique design of Blockchain, any record of any transmission can be validated for accuracy, thereby giving the OEM or any vehicle owner undisputable records of truth. This unique validation method is not available to the automotive market today. Blockchain also addresses the V2X security issues (many senders, many receivers) without leaving the vehicles vulnerable to hacking, making it an ideal data record for small packets of information.

As Blockchain comprises data records—a database—using it will not necessarily be a design consideration for the communication transport system itself. Underlying transmission standards such as the Wireless Access for Vehicular Environments (WAVE) for the U.S., which is based on the lower level IEEE 802.11p standard, and ETSI ITS-G5 for Europe, a standard also based on IEEE 802.11P, have focused on the transport system definition use. And the Car-to-Car communication consortium, a nonprofit industry driven organization also in Europe, has focused on standards for V2V and V2i. Blockchain use, rather than having an impact on these standards, would instead operate within the standards defined.


Greg-Bohl-6-17-16_WEBGreg Bohl is Vice President of the U.S. Analytics Services organization for HARMAN Connected Services. His work with analytics was launched over 20 years ago while at the Sabre Group and has continued through several companies including multiple start-ups. Greg has worked globally with OEMs defining a path of how machine learning and artificial intelligence can be used in the connected car. Publications range from numerical studies in clean technology through patents for predictive systems and methods used in the automotive industry. Greg has earned a BS-IS and MBA from the University of Texas, Arlington.

Heterogeneous: Performance and Power Consumption Benefits

Wednesday, May 10th, 2017

Why multi-threaded, heterogeneous, and coherent CPU clusters are earning their place in the systems powering ADAS and autonomous vehicles, networking, drones, industrial automation, security, video analytics, and machine learning.

High-performance processors typically employ techniques such as deep, multi-issue pipelines, branch prediction, and out-of-order processing to maximize performance, but these do come at a cost; specifically, they impact power efficiency.

If some of these tasks can be parallelized, this impact could be mitigated by partitioning them across a number of efficient CPUs to deliver a high-performance, power-efficient solution. To accomplish this, CPU vendors have provided multicore and multi-cluster solutions, and operating system and application developers have designed their software to exploit these capabilities.

Similarly, application performance requirements can vary over time, so transferring the task to a more efficient CPU when possible improves power efficiency. For specialist computation tasks, dedicated accelerators offer excellent energy efficiency but can only be used for part of the time.

So, what should you be looking for when it comes to heterogeneous processors that deliver significant benefits in terms of performance and low power consumption? Let’s look at a few important considerations.

Multi-threading
Even with out-of-order execution, with typical workloads, CPUs aren’t fully utilized every CPU cycle; they spend most their time waiting for access to the memory system. However, when one portion of the program (known as a thread) is blocked, the hardware resources could potentially be used for another thread of execution. Multi-threading offers the benefit of being able to switch to a second thread when the first thread is blocked, leading to an increase in overall system throughput. Filling up all the CPU cycles with useful work that otherwise would be un-used leads to a performance boost; depending on the application, the addition of a second thread to a CPU typically adds 40 percent to the overall performance, for an additional silicon area cost of around 10 percent. Hardware multi-threading is a feature that in CPU IP is bespoke to Imagination’s MIPS CPUs.

A Common View
To move a task from one processor to another requires each processor to share the same instruction set and the same view of system memory. This is accomplished through shared virtual memory (SVM). Any pointer in the program must continue to point to the same code or data and any dirty cache line in the initial processor’s cache must be visible to the subsequent processor.

Figure 1: Memory moves when transferring between clusters.

Figure 1: Memory moves when transferring between clusters.

Figure 2: Smaller, faster memory movement when transferring within a cluster.

Figure 2: Smaller, faster memory movement when transferring within a cluster.

Cache Coherency
Cache coherency can be managed through software. This requires that the initial processor (CPU A) flush its cache to main memory before transferring to the subsequent processor (CPU B). CPU B then has to fetch the data and instructions back from main memory. This process can generate many memory accesses and is therefore time consuming and power hungry; this impact is magnified as the energy to access main memory is typically significantly higher than fetching from cache. To combat this, hardware cache coherency is vital, minimizing these power and performance costs. Hardware cache coherency tracks the location of these cache lines and ensures that the correct data is accessed by snooping the caches where necessary.

In many heterogeneous systems, the high-performance processors reside in one cluster, while the smaller, high-efficiency processors reside in another. Transferring a task between these different types of processors means that both the level 1 and level 2 caches of the new processor are cold. Warming them takes time and requires the previous cache hierarchy to remain active during the transition phase.

However, there is an alternative – the MIPS I6500 CPU. The I6500 supports a heterogeneous mix of external accelerators through an I/O Coherence Unit (IOCU) as well as different processor types within a cluster, allowing for a mix of high-performance, multi-threaded and power-optimized processors in the same cluster. Transferring a task from one type of processor to another is now much more efficient, as only the level 1 cache is cold, and the cost of snooping into the previous level 1 cache is much lower, so the transition time is much shorter.

Combining CPUs with Dedicated Accelerators
CPUs are general purpose machines. Their flexibility enables them to tackle almost any task but at the price of efficiency. Thanks to its optimizations, the PowerVR GPU can process larger, highly parallel computational tasks with very high performance and good power efficiency, in exchange for some reduction in flexibility compared to CPUs, and bolstered by a well-supported software development eco-system with APIs such as OpenCL or Open VX.

The specialization provided by dedicated hardware accelerators offers a combination of performance with power efficiency that is significantly better than a CPU, but with far less flexibility.

However, using accelerators for operations that occur frequently are ideal to maximize the potential performance and power efficiency gains. Specialized computational elements such as those for audio and video processing, as well as neural network processors used in machine learning, use similar mathematical operations.

Hardware acceleration can be coupled to the CPU by adding Single Instruction Multiple Data (SIMD) capabilities with floating point Arithmetic Logic Units (ALUs). However, while processing data through the SIMD unit, the CPU behaves as a Direct Memory Access (DMA) controller to move the data, and CPUs make very inefficient DMA controllers.

Conversely, a heterogeneous system essentially provides the best of both worlds. It contains some dedicated hardware accelerators that, coupled with a number of CPUs, offer the benefits of greater energy efficiency from dedicated hardware, while retaining much of the flexibility provided by CPUs.

These energy savings and performance boost depend on the proportion of time that the accelerator is doing useful work. Work packages appropriate for the accelerator are present in a wide range of sizes—you might expect a small number of large tasks, but many smaller tasks.

There is a cost in transferring the processing between a CPU and the accelerator, and this limits the size of the task that will save power or boost performance. For smaller tasks, the energy consumed and time taken to transfer the task exceeds the energy or time saved by using the accelerator.

Data Transfer Cost
To reduce time and energy costs, a Shared Virtual Memory with hardware cache coherency—as found in the I6500 CPU—is ideal as it addresses much of the cost of transferring the task. This is because it eliminates the copying of data and the flushing of caches. There are other available techniques to achieve even greater reductions.

The HSA Foundation has developed an environment to support the integration of heterogeneous processing elements in a system that extends beyond CPUs and GPUs. The HSA system’s intermediate language, HSAIL, provides a common compilation path to heterogeneous Instruction Set Architectures (ISAs) that greatly simplifies the system software development but also defines User Mode Queues.

These queues enable tasks to be scheduled and signals to trigger tasks on other processing elements, allowing sequences of tasks to execute with very little overhead between them.

Beyond Limitations
Heterogeneous systems offer the opportunity to significantly increase system performance and reduce system power consumption, enabling systems to continue to scale beyond the limitations imposed by ever shrinking process geometries.

Multi-threaded, heterogeneous and coherent CPU clusters such as the MIPS I6500 have the ideal characteristics to sit at the heart of these systems. As such they are well placed to efficiently power the next generation of devices.


Tim-Mace-2Tim Mace is Senior Manager, Business Development, MIPS Processors, Imagination Technologies.

Auto Makers See Opportunity with Embedded Handwriting

Monday, April 10th, 2017

Why handwriting technology in the automotive cockpit will continue to see dramatic growth.

Many people who don’t yet use handwriting technology on phones or tablets as computing input mechanisms may nonetheless already be familiar with digital handwriting technology. There’s a good chance they’ve been introduced to it in what might seem an unlikely place: Their cars.

Figure_1

Figure 1: In the new automotive ecosystem, embedded sensors and display units can communicate with mobile devices inside the car and gather all sorts of external information via the web.

Last year, higher-end auto manufacturers like Audi, Mercedes and Tesla began shipping cars with embedded handwriting technology for controlling GPS systems, entertainment systems and other dashboard controls. Watch a 10-second video showing handwriting at work in an Acura here and learn a bit more about the overall concept here.

But all of this is just the beginning. According to Frost & Sullivan, the market for handwriting recognition (HWR) technology in cars will grow at a rate of more than 30 percent each year through 2020. “The industry is now moving towards controlling the entire infotainment with help from HWR,” the firm adds.

Embedded systems are tough to design: By nature, they’re constrained not only by limited storage space, but also limited memory space and typically, lower performance CPUs compared to computational devices. But even bound by these limitations, today’s digital handwriting technology has delivered remarkable accuracy and consistent benefits to the automotive industry. The most recent technology includes the ability to superimpose characters, cursive words or portions of words on top of each other on the touchpad and still accurately recognize input. A keyboard option incorporating smooth typing enables a true multimodal solution. Here are some reasons why handwriting technology in the automotive cockpit will continue to see dramatic growth:

  • Low driver distraction interfaces have evolved to require handwriting. One reason that handwriting provides a more effective option for controlling GPS or entertainment systems compared to voice are because cars are often noisy, making it difficult to reliably give instructions. Another reason is that voice command systems are very difficult to edit, which makes it more challenging to either revise input or correct recognition errors. Finally, handwriting allows drivers to keep their attention safely focused on the road: Today’s tech is designed for use when the driver isn’t looking at what he’s writing on the touchpad.
  • Multimodal systems are easy for the user to manipulate. Car manufacturers care about customer satisfaction, and drivers today demand a consistent user experience when inputting information—whether they’re doing it by hand, keyboard or voice. Drivers want multiple methods to input that information, depending on what’s most convenient and more importantly, safe. Consistency is key: System responses to keyboard input need to be consistent with responses to handwritten input. No one wants to get a different dictionary response to a query if they’re writing by hand rather than  keyboarding, for instance. A single multimodal system pre-emptively solves that potential problem.
  • Multimodal is great for the integrator. What’s great about multimodal design for systems integrators is that they only need to integrate with a single technology provider that handles multiple forms of input instead of integrating several different functional libraries and debugging any adverse interactions. This shortens the development time required for integration and lessens demands on memory resources and storage. Ultimately, integrating a multimodal interface means developing products that are often lower-cost, quicker time-to-market, and easier to test and validate. A big win all around.

Handwriting also wins points for safety and accuracy. The American Automobile Association (AAA) ranked voice-based command systems, such as the iPhone’s Siri, and found that it significantly distracted car drivers. In a worst-case situation, drivers even at the low speed of 25 mph were distracted for up to 27 seconds, during which they travelled more than three football fields in length.

Handwriting adapts well to multiple situations—e.g., character input when driving, and word input when stopped. Drivers can reach down and direct their cars’ GPS or entertainment systems in dozens of languages (as selected by the OEM), via either cursive or block characters that are easily recognizable, and that can even be written at a tilt—up to over 30 degrees off a level line—and still be recognized. The ability to recognize letters even written at a significant tilt allows for a great deal of human error, which in turn enables increased safety.

Figure 2: Embedded handwriting technology, complemented with voice and other multimodal input options, offers today’s drivers an effective way to enjoy more applications with complex features even as states increase regulation

Figure 2: Embedded handwriting technology, complemented with voice and other multimodal input options, offers today’s drivers an effective way to enjoy more applications with complex features even as states increase regulation.

Handwriting, in sum, is a natural fit for inclusion in the auto market because it offers an intuitive method to control the automotive cockpit, assures minimum driver distraction, and provides a natural input method and low learning curve. Drivers of all ages can use it, and it offers high recognition accuracy of letters, numbers and gestures.

And the handwriting technology in cars can blossom into a full note-taking application for drivers to use when they’re stopped. This is ideal for road warrior executives who must constantly attend meetings, travel and share their notes.

Handwritten input, or ‘digital ink,’ is now as fully capable to be interpreted to text as input from the keyboard and mouse. Furthermore, diagrams such as mind maps, organizational charts, and flow diagrams are capable of being fully converted to digital form in a manner that allows for changes and editing. Today’s technology allows you to create content, edit and format that content, create diagrams, input complex math equations, and easily incorporate the interpreted handwriting results into your digital document workflow.

A booming professional services market has emerged to support developers of embedded handwriting technology, too. Handwriting technology vendors are offering in-depth professional engineering services for use cases based upon the SDK packages offered, all the way to complete turnkey subsystem design services.

Handwriting technology is already embedded in millions of cars today. But the most tremendous growth for this market lies ahead in a wide range of embedded applications and IoT devices. For ISVs and OEMs, the ultimate benefit is a massively improved user experience which enhances customer satisfaction and ultimately sales and profits.


Gary-Headshot_hi_resGary Baum is the Vice President of Marketing at MyScript, the source of the most advanced award winning technology for handwriting recognition and digital ink management. At the Car HMI Concepts and Systems conference, MyScript technology was recognized in the ‘Most Innovative Car HMI Technology’ category.

Read more about the MyScript SDK and other tools for the automotive industry.

Control, Drive, Sense: High-Power Density SiC and GaN Power Conversion Applications

Thursday, March 2nd, 2017

New power switch technologies are key to success with the next generation of motor control, solar inverters, energy storage and electric vehicles. Just as important—the ability to drive these technologies safely and sense them more accurately.

Sensing current within these systems while operating at these higher switching rates is becoming more challenging.

Electricity consumption and its generation, which adds to our carbon footprint and affects climate change, is one of the key problems the world faces. The largest global consumption of electricity is from electric motors and the systems they drive. These systems consume more than twice as much electricity as the next largest consumer, lighting. A 2011 International Energy Agency report estimates that electric motor systems account for between 43 and 46 percent of the world’s electricity consumption.

Farther on Less

The need to further shrink our carbon footprint by reducing the CO2 emissions from transportation is a key driver for the electrification of vehicles. With the electrification of vehicles comes the need for them to be able to travel greater distances with less energy consumed. At the same time, we must ensure that the electricity generated for charging these vehicles comes from clean sources. As important as reducing electricity consumption is improving electricity generation methods. Generating energy through renewable resources like the sun requires efficient solar farms that are becoming mainstream in implementations worldwide.

We’ve seen the emergence of Wide Bandgap semiconductor technologies like Silicon Carbide (SiC) and Gallium Nitride (GaN) and the use of power MOSFETS in applications such as solar inverters, motor drives, and electric vehicles. Along with these technologies comes the need for gate drivers that have the capability of driving them efficiently and safely at higher data rates with less dead time in the system. Sensing current within these systems while operating at these higher switching rates is becoming more challenging.

Moving to these new technologies makes electric motors and driving electronics smaller and lighter. Increasing the range of the electric vehicle and decreasing its charging time becomes possible. Higher switching frequencies in solar inverters, as specified in IEC62109-1, will improve the overall efficiency of the systems as well as reducing the size of the line filters. Industrial automation applications where motors are commonly used, as specified in the variable frequency motor drive standard IEC61800-5, will become less bulky and more efficient, reducing the overall energy footprint.

Greater Robustness, Reliability

Isolation is mandated for safety and operation. Implementing the isolation barriers within these applications without compromising on performance is critical. These systems often have long lifetimes and could be implemented in harsh environments, so high levels of component robustness and reliability are a must.

“Sensing current within these systems while operating at these higher switching rates is becoming more challenging.”

One example of a solution for driving new Power switch technologies is Analog Devices iCoupler® digital isolation integrated with gate drivers like the ADuM4121 (Figure 1). It has the capability of driving these new Power switch technologies because of its low industry leading propagation delay of 38ns typical, allowing faster switching and the ability to withstand high Common Mode Transients up to 150kV/µs during fast turn on and turn off events.

Integrating Analog Devices iCoupler digital isolation with industry leading sigma delta analog to digital converters, such as the AD7403, makes it possible to accurately sense the current in high-voltage applications across a smaller shunt resistor, improving system efficiency. This enables the use of higher accuracy shunt-based current measurement architecture rather than Hall Effect systems. Selecting smaller resistors reduces the overall size of the solution.

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Figure 1: ADuM4121 Driving GaN MOSFET GS66508B

To demonstrate system performance benefits, Analog Devices has developed a new Half Bridge GaN evaluation platform in collaboration with GaN Systems, as shown in Figure 2. On this platform we have the ADuM4121 isolated gate driver driving the GS66508B GaN MOSFET from GaN Systems that is rated to 650V at 30A. The gate charge requirement of the GS66508B is very low, making it much easier to drive at higher frequencies with a much lower supply voltage on VDD2 of 6V. The ADuM4121 also includes an internal Miller clamp that activates at 2V on the falling edge of the gate drive output, supplying the driven gate with a lower impedance path to reduce the chance of Miller capacitance induced turn on.

Making use of three of these half bridge evaluation boards combined with the Analog Devices Motor Control evaluation platform, a demonstration system showcasing a three-phase inverter driving a three-phase motor was built (Figure 3). Within the three-phase inverter, large currents are being switched at high frequencies that can cause radiated and conducted emissions. To reduce the conducted and radiated emissions in the system while operating efficiently, it is critical to slew the edges of the switching waveforms sufficiently by selecting an appropriate gate resistance. This series resistance can further help with dampening the output ringing by matching the source to the load.

Figure 2: Replacing an IGBT inverter with a GaN Inverter

Figure 2: Replacing an IGBT inverter with a GaN Inverter

In this demonstration platform, the ADSP-CM409 generates the PWM signals required to drive the power switches, while the integrated SINC filters allow for direct connection of the Isolated Sigma delta ADC used for accurately sensing the current. The reinforced isolation provided by the isolated gate drivers can withstand up to 5kVrms as well as working voltages as high as 849Vpeak according to VDE0884-10. The isolation AD7403 offers can achieve 5kVrms withstand with a working voltage 1250Vpeak, also according to VDE0884-10.

Figure 3: Three Phase Inverter Motor Control Platform

Figure 3: Three Phase Inverter Motor Control Platform

Implementing a three-phase inverter using GaN suits systems operating up to 650V. SiC, having much higher breakdown voltages, more closely matches systems going up as high as 1200V and 1700V because it will have more margin within three-phase systems with 690Vrms line voltages.


ProfilePicture_webHein Marais is a System Application Engineer at Analog Devices, Inc.

Can Autonomous Vehicles Absolve Human Responsibility?

Monday, January 23rd, 2017

In our rush to embrace the latest technology and take advantage of whatever benefits it offers—greater convenience, higher efficiency, improved reliability, lower cost, etc.—we must not neglect human safety.

Transportation has been a major driver of technological innovation (Figure 1) since the inventions of James Watt, the Wright Brothers and automotive pioneers Daimler and Maybach. Over the years, concerns for occupant safety have led to the development of seat belts and air bags in cars, while such things as improvements in vehicle body materials and profiles, and the deployment of reversing alarms on trucks and buses have reduced the risks of accident and injury to pedestrians, cyclists, and other road users.

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Figure 1: Mankind’s need to get from one spot to another has inspired innovators from James Watt to Elon Musk [Left image: By James Eckford Lauder (1811 - 1869) (Scottish) Details of artist on Google Art Project [Public domain], via Wikimedia Commons; Right image: [By jurvetson (Steve Jurvetson) [CC BY 2.0 (http://creativecommons.org/licenses/by/2.0)], via Wikimedia Commons]

Figure 1: Mankind’s need to get from one spot to another has inspired innovators from James Watt to Elon Musk (Top image: By James Eckford Lauder (1811 - 1869) (Scottish) Details of artist on Google Art Project (Public domain), via Wikimedia Commons; Bottom image: By jurvetson (Steve Jurvetson) - CC BY 2.0 (http://creativecommons.org/licenses/by/2.0), via Wikimedia Commons

In more recent times, the technology of artificial intelligence (AI) has started to pervade the various electronic control systems that are an integral part of modern automotive design and today’s driving experience. However, as we move from advanced driver assistance systems (ADAS) to fully autonomous self-driving vehicles we need to recognize the point at which responsibility for safe operation passes from human to machine. The ethics of the autonomous functionality offered by AI in vehicles has parallels with the “three laws of robotics” science-fiction writer Isaac Asimov postulated in 1942, which mostly aimed to protect humans from harm due to the actions of any robots. In similar fashion, implementing AI in vehicles needs ethical decision-making rules to define behavior that eliminates or reduces harm to humans.

From Fighter Pilots to Car Drivers

A fighter jet represents the pinnacle of aircraft evolution in terms of its performance and complexity of operation. Consequently, fighter pilots are assisted in flying them. A comprehensive suite of artificial intelligence algorithms can control almost every aspect of their operation, enhancing the pilot’s capability while still allowing him to take control when the situation demands it. In the same way, equally powerful, game-changing AI technology in automotive applications must account for the ability to return control of the vehicle to the driver.

Within the auto industry today, many electronic technology companies are focusing on the technical needs of ADAS, developing both adaptive and predictive systems and components that will allow for better and safer driving. ADAS assists the driver or any other agent in charge of the vehicle in a number of ways: It may warn the driver or take actions to reduce risk. It may also improve safety and performance by automating some portion of the control task of operating the vehicle.

In its current state ADAS mainly functions in cooperation with the driver, i.e. by providing a human-to-machine interface, which is part of the control system of the vehicle with the human still maintaining overall responsibility for the vehicle. Over time, it is expected that developments in technology will be successful in wielding ever-greater control of the vehicle, so assistance becomes the norm and driver intervention is reduced. ADAS are ultimately expected to develop further into the kind of autonomous system that will offer the ability to respond more quickly and with greater benefits than when a human agent is in control of the vehicle.

ADAS Demands Component Solutions

The development of electronic components for ADAS, and ultimately for truly autonomous vehicles, is being undertaken by leading component manufacturers worldwide. These companies are typically already experienced in meeting the demanding performance, quality and reliability standards expected by the automotive industry. For example, ON Semiconductor provides robust, AEC-qualified, production part approval process (PPAP) capable products for automotive applications, including the NCV78763 Power Ballast and Dual LED Driver for ADAS front headlights. Freescale Semiconductor is helping to drive the world’s most innovative ADAS solutions with its automotive, MCU, analog and sensors, and digital networking portfolio expertise. The development of its latest FXTH8715 Tire Pressure Monitoring Sensors (TPMS), which integrate an 8-bit microcontroller (MCU), pressure sensor, XZ-axis or Z-axis accelerometer and RF transmitter, was driven by a market requirement for improved safety. AVX, a technology leader in the manufacture of passive electronic components, developed the VCAS & VGAS Series TransGuard® Automotive Multi-Layer Varistors (MLVs) to provide protection against automotive-related transients in ADAS applications. Delphi Connection Systems supports challenging automotive applications that demand robust design and reliability with its high-performance APEX® Series Wire Connectors.

The Dream of Vehicle Autonomy

The electronics industry has long been characterized by continual improvements in performance that come at an ever-decreasing cost. This electronics industry has allowed technology that was once the preserve of racing cars and the luxury automobile market to percolate down through mid-range vehicles to everyday family vehicles. Many people, both inside and outside the industry, now dream of a future where completely autonomous vehicles will come to dominate the world’s roads. They visualize benefits in safety, travel efficiency, comfort, and convenience in vehicles that are programmed to avoid accidents, optimize journey times and costs and maximize the functional utility of the vehicle. Clearly, amongst these, preventing injury to passengers and others as well as damage to the vehicle and property is the highest priority.

Autonomous Vehicles Require Ethical Rules

Current laws regulating road use place the responsibility for safety squarely with the human driver. He or she must ensure that other people, both inside and outside the vehicle, are protected from harm arising from his/her operation of the vehicle. While a car may be viewed as a means of getting people from point A to point B as efficiently as possible, its use at excessive speed or in a dangerous manner resulting in an accident that injures or kills a pedestrian would likely be considered a criminal offense. Indeed, the deliberate use of a vehicle to run down and kill someone would, in most cases, constitute murder.

However, these judgments are rarely black or white, and there may be mitigating circumstances, depending on the situation and people involved. Moreover, while we would not expect an autonomous vehicle to exceed speed limits or undertake dangerous maneuvers in a typical situation, there may be occasions when, like a human operator, it needs to make decisions where the outcome may be questionable. These decisions are where we need to understand the ethics involved to apply appropriate rules. This can be appreciated by considering a few hypothetical scenarios:

1. When traveling at speed in traffic, a human driver might react to an animal jumping out into the road by swerving to avoid it and, in doing so, hitting another car. As the driver, you may have saved that animal but what if the result was an accident in which other people were hurt?

2. What if, instead of an animal in the above example, it was a pedestrian who had stepped into the road and hitting them was likely to be fatal. Then the action would have saved a human life at the cost of potential injuries to the occupants of the other vehicle.”

3. An autonomously driven vehicle confronted with the same situation of a pedestrian stepping into the road might decide it cannot run over that person but may also decide it cannot swerve into another vehicle. Instead, it swerves off the road hitting a wall resulting in serious injuries to the human ‘driver’ of the car and potentially any passengers too.

In the latter situation, the human ‘driver’ is not to blame, but equally, there is an ethical dilemma as to whether any fault lies with the autonomous vehicle. Undoubtedly, as we become more reliant on technologies such as ADAS and ultimately on Autonomous Technology Systems (ATS) the responsibility for operating a vehicle becomes less dependent on the individual driver and shifts to the vehicle itself and therefore to the car manufacturer. Not surprisingly, the automotive industry will not want to accept liability for such risks unless the market recognizes this requirement and establishes an appropriate business model that makes economic sense for the manufacturers and doesn’t result in endless litigation.

Conclusion

Technological solutions are now starting to outpace the real-world situations into which they are being introduced. The deployment of artificial intelligence is challenging the status quo and forcing us to consider ethical questions about how machines should operate and who has control and is, therefore, responsible for their behavior.

This moral issue is certainly true of autonomous vehicles where ceding control to the vehicle requires AI that follows agreed ethical rules to protect human life. If we are to benefit from improved transportation systems with greater freedom, flexibility, efficiency, and safety, then it is society as a whole rather than design engineers and vehicle manufacturers that have to face up to this challenge and take on this responsibility.


Photo-RudyRamos_webRudy Ramos is the Project Manager for the Technical Content Marketing team at Mouser Electronics, accountable for the timely delivery of the Application and Technology sites from concept to completion. He has 30 years of experience working with electromechanical systems, manufacturing processes, military hardware, and managing domestic and international technical projects. He holds an MBA from Keller Graduate School of Management with a concentration in Project Management. Prior to Mouser, he worked for National Semiconductor and Texas Instruments. Ramos may be reached at rudy.ramos@mouser.com

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