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Embedded systems continue to become more complex. As a result, more companies are utilizing model-based design (MBD) development methods and tools. The use of MBD methods and tools is helpful in increasing time to market and having instant feedback on the system design. One area that continues to mature is the testing and verification of the MBD systems. This paper introduces a hybrid approach to functional tests. The test system is composed of simulation software and real-time hardware. It is not always necessary to test a system in a real-time environment, but it is recommended if the goal is to deploy the system to a situation that requires real-time response. Vehicle drive cycles and powertrain control are utilized in this research as the example test case for this paper. In order to test the algorithms on a real-time system, it is necessary to understand the target controller's computing limitations and adjust the algorithms to meet these limitations.

A 24 degree-of-freedom full vehicle-driving simulator is proposed in this paper. The simulator provides a full immersive graphical virtual scenery and force/motion feedback cues for the driver. The simulator has been developed to provide an open architecture in a local network environment. Using Matlab/Simulink one can interface with the vehicle model through this environment, designing and testing vehicle sub models while evaluating the ride performance of the vehicle. The development and implementation of a rollover detection and warning system is discussed, to illustrate the application of the driving simulator.

The Intelligent Ground Vehicle Competition (IGVC) is a multidisciplinary exercise in product realization for college engineering students. They design, build, and compete with autonomous vehicles in events ranging from lane following, obstacle avoidance, platooning, to Global Positioning System (GPS) navigation. Technologies involved include electronic controls, computer-based vision systems, object detection, rangefinding, and global positioning. The real world applications are in intelligent transportation systems, the military, and manufacturing automation. Students have been creative and have learned a great deal. Industry recruiters have been highly supportive.

The Wavelet Transform (WT) has been developed two decades ago, and has since then been put to use in an increasingly wide array of applications. The WT provides a time-scale analysis of a signal. Compared to the widely-popular Fourier Transform (FT), originally developed two hundred years ago, the WT provides the time-evolution of the signal at different scales. The Discrete Wavelet Transform (DWT) is a computationally efficient implementation of the WT, in which the time-scale analysis is performed on a dyadic scale. The DWT is very suitable for knock detection systems, since it can provide the history of the knock signal at discrete scales within a crank angle window. It allows for the extraction of a multitude of features from the time-scale plane. Moreover, the DWT is suitable for real-time knock detection implementations on engine control units.