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To address the growing need for detailed chemistry in engine simulations, new software tools and validated data sets are being developed under an industry-funded consortium involving members from the automotive and fuels industry. The results described here include systematic comparison and validation of detailed chemistry models using a wide range of fundamental experimental data, and the development of software tools that support the use of detailed mechanisms in engineering simulations. Such tools include the automated reduction of reaction mechanisms for targeted simulation conditions. Selected results are presented and discussed.

This paper proposes a new development method for highly reliable real-time embedded control systems using a CPU model-based hardware/software co-simulation. We take an approach that allows the full simulation of the virtual mechanical control system including CPU and object code level software. In this paper, Renesas SH-2A microcontroller model was developed on CoMET™ platform from VaST Systems Technology. A ETC (Electronic Throttle Control) system and engine control system were chosen to prove this concept. The ETB (Electronic Throttle Body) model on Saber® simulator from Synopsys® or engine model on MATLAB®/Simulink® simulator from MathWorks can be simulated with the SH-2A model. To help the system design, debug and evaluation, we developed an integrated behavior analyzer, which can display CPU behavior graphically during the simulation without affecting the simulation result, such as task level CPU load, interrupt statistics, software variable transition chart, and so on.

Software is becoming more prevalent on cars as the number of embedded processors per vehicle increases. Software Engineering used to be considered a “black art” and really was handled that way. It has now been elevated to Engineering status. Software Engineering follows the same principles as any other Engineering practice.

Microprocessors and microcontrollers are now widely used in automobiles. Microprocessor systems contain sources of interrupt and interrupt service routines, which are software components executed in response to the assertion of an interrupt in hardware. A major problem in designing the software of microprocessor systems is the analytical treatment of interrupt latency. Because multiple interrupt service routines are executed on the same CPU, they compete for the CPU and interfere with each other's latency requirements. Here, interrupt latency is defined as the delay between the assertion of the interrupt in hardware and the start of execution of the associated interrupt service routine. It is estimated that 80% of intermittent bugs in small microprocessor software loads are due to improper treatment of interrupts. Until this work, there is no analytic method for analyzing a particular system to determine if it may violate interrupt latency requirements.

With the recent advancement in sensing and controller technologies architecture design of an autonomous driving system becomes an important issue. Researchers have been developing different sensors and data processing technologies to solve the issues associated with fast processing, diverse weather, reliability, long distance recognition performance, etc. Necessary considerations of diverse traffic situations and safety factors of autonomous driving have also increased the complexity of embedded software as well as architecture of autonomous driving. In these circumstances, there are almost countless numbers of possible architecture designs. However, these design considerations have significant impacts on cost, controllability, and system reliability. Thus, it is crucial for the designers to make a challenging and critical design decision under several uncertainties during the conceptual design phase.

Automotive vehicles today consist of very complex network of electronic control units (ECU) connected with each other using different network implementations such as Controller Area Network (CAN), FlexRay, etc. There are several ECUs inside a vehicle targeting specific applications such as engine, transmission, body, steering, brakes, infotainment/navigation, etc. comprising on an average more than 50 ECUs executing more than 50 million lines of software code. It is expected to increase exponentially in the next few years. Such complex electric/electronic (E/E) architecture and software calls for a comprehensive, flexible and systematic development and validation environment especially for a system level or vehicle level development. To achieve this goal, we have built a virtual multi-ECU high fidelity cyber-physical multi-rate cosimulation that closely resembles a realistic hardware based automotive embedded system.

With the increasing complexity of automotive systems and the related increasing use of software in them, new approaches are needed to ensure safety. In these new types of automotive systems, safety and reliability are different and require different engineering approaches. Accidents are increasingly due to design errors and to dysfunctional interactions among components rather than component failure. In addition, safety must be engineered and built into the design from the beginning; it is not possible to effectively and affordably add safety devices onto a finished design. This paper describes the need for new approaches to automotive safety and describes an alternative to the traditional reliability-based approaches to safety engineering. The new approach is based on systems theory and views accidents in terms of lack of control or enforcement of the behavioral constraints required to ensure safety.

We have developed a full virtual engine system prototyping platform with 4-cylinder engine plant model, SH-2A CPU hardware model, and object code level software including OSEK OS. The virtual engine system prototyping platform can run simulation of an engine control system and digital knock detection system including 64-pt FFT computations that provide required high-resolution DSP capability for detection and control. To help the system design, debugging, and evaluation, the virtual system prototyping consists of behavior analyzer which can provide the visualization of useful CPU internal information for control algorithm tuning, RTOS optimization, and CPU architecture development. Thus the co-simulation enables time and cost saving at validation stage as validation can be performed at the design stage before production of actual components.