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This is an overview of the development of a portable, real-time acoustic beamformer based on FPGA (Field Programmable Gate Arrays) and digital microphones for noise source identification. Microphone arrays can be a useful tool in identifying noise sources and give designers an image of noise distribution. The beamforming algorithm is a classic and efficient algorithm for signal processing of microphone arrays and is the core of many microphone array systems. High-speed real-time beamforming has not been implemented much in a portable instrument because it requires large computational resources. Utilizing a beamforming algorithm running on a Field Programmable Gate Array (FPGA), this camera is able to detect and locate both stationary and moving noise sources. A high-resolution optical camera located in the middle of the device records images at a rate of 25 frames per second. The use of the FPGA technology and digital microphones provides increased performance, reduced cost and weight.

To cope with the increasing number of advanced features (e.g., smart-phone integration and side-blind zone alert.) being deployed in vehicles, automotive manufacturers are designing flexible hardware architectures which can accommodate increasing feature content with as fewer as possible hardware changes so as to keep future costs down. In this paper, we propose a formal and quantitative definition of flexibility, a related methodology and a tool flow aimed at maximizing the flexibility of an automotive hardware architecture with respect to the features that are of greater importance to the designer. We define flexibility as the ability of an architecture to accommodate future changes in features with no changes in hardware (no addition/replacement of processors, buses, or memories). We utilize an optimization framework based on mixed integer linear programming (MILP) which computes the flexibility of the architecture while guaranteeing performance and safety requirements.

Automotive HW/SW architectures are becoming increasingly complex to support the deployment of new safety, comfort, and energy-efficiency features. Such architectures include several software tasks (100+), messages (1000+), computational and communication resources (70+ CPUs, 10+ buses), and (smart) sensors and actuators (20+). To cope with the increasing system complexity at lowest development and product costs, highest safety, and fastest time to market, model-based rapid-prototyping development processes are essential. The processes, coupled with optimization steps aimed at reducing the number of software and hardware resources while satisfying the safety requirements, enable reduction of the system complexity and ease downstream testing/validation efforts. This paper describes a novel model-based design exploration and optimization process for the deployment of a set of software tasks on a dual-processor control module implementing a fail-safe strategy.

Hardware-in-the-loop (HIL) simulation has become standard practice in the verification process of electronic control units (ECUs). However, new system control concepts continue to drive and expand the requirements for HIL systems. In this maturing application space, there is a natural trend towards the use of commercial-off-the-shelf (COTS) tools and open, multivendor hardware architectures. This open architecture is critical in helping HIL testers meet these requirements in an increasingly cost effective and higher performance manner. Multicore processors today offer performance and flexibility on a scalable computing platform, which furthers this COTS trend. Computer platforms like desktop PCs, CompactPCI and PXI [ 1 ] (CompactPCI eXtensions for Instrumentation) deliver high-performance systems that allow for the leveraging of multicore processor capabilities in achieving highly realistic plant simulations for controller testing.

LIN is a low-cost, low-speed vehicle communication sub-bus becoming increasingly pervasive in automotive subsystems. It is a simple, UART-based master-slave protocol designed as a low-speed supplement to a CAN or FlexRay bus. Its primary application is cabin comfort and human interface hardware such as dashboard controls, power seat harnesses, and power door/window systems. As automotive network designers attempt to reduce wiring complexity and lower system cost, modular, inexpensive sub-buses like LIN become an attractive option. This paper presents an overview of the LIN standard and its applications, and then proposes an architecture for rapid development of LIN networks via hardware simulations of LIN nodes. Using inexpensive, off-the-shelf hardware, LIN sensor and actuator applications can be tested in-place without microcode development, speeding overall network development time.

ECU designers are seeking more flexibility from HIL test systems. Often their needs are met by the development of custom hardware, either internally or by HIL test system vendors. Many systems also rely heavily on the use of multiple expensive microprocessors to achieve the required timing and synchronization performance. This paper discusses an alternative based on PC technology and reconfigurable I/O hardware. The HIL test system designer uses a graphical programming interface to reconfigure not only the real-time software portion of the system, but also the FPGA-based I/O hardware. This increases flexibility and lowers cost by providing capabilities such as generating simulated outputs synchronized to crank angle and implementing multiple serial communication protocols.

With the abundance of electronic devices and sensors in automotive technology, it has become increasingly important to establish efficient, cost-effective device validation methods for CAN, J1939, and GMLAN. An easy method of validation is simultaneous sampling of multiple measurements for comparison. For instance, if you have an ECU that receives inputs using CAN, and controls analog outputs, you can measure both CAN and analog data to verify that the ECU algorithm is behaving properly. This paper will discuss techniques for sharing timing and triggering signals between CAN, analog, and digital hardware to prevent clock drift and start latencies and reduce operating system jitter. We will cover techniques to use a common clock to drive multiple boards and specify events to trigger multiple board acquisitions. Timing and triggering signals can be shared in a PC through timing and triggering cables or in PXI through the PXI Trigger bus in the backplane.

The increasing number of features and complexity of today's automotive software architectures bring new challenges to the product development cycle. As a product is being developed, there is a need for information created during the early phases to flow seamlessly into subsequent phases. For example, information defined for an ECU during the design phase should be re-used when that ECU is tested during manufacture. Challenges often arise from the fact that one vendor's tools may be appropriate for design, but a different vendor's tools are best suited for manufacturing test. This paper discusses business and technical issues surrounding the transfer of information between such tools. Two case studies are used for discussion. One deals with databases describing signals transferred over an in-vehicle network and the other discusses simulation models as both transition from early designs through various test phases.

Empowering the end-user is the primary focus of most software developers, whether in the general computing industry or in automotive instrumentation applications. End-users' expectations for both ease of use and flexibility in software products are high. Products in the general computing industry, such as Microsoft Word and Excel, have set standards for what a user expects from a software product. Because of the complex nature of most analytical instrumentation applications, it is difficult to deliver a software product for these applications that is both easy to use and flexible for many applications. And, if the product does exist, it usually comes with a relatively high price tag. There are, however, some lower cost software development tools available for instrumentation applications that combine a good mix of flexibility and ease of use. These tools require some development on the part of the end-user, but they do not require a computer science background.