Model-based Design And Analysis Of Automotive Systems Using Time-triggered Controller Area Networks
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As the numbers of electrical and electronics (E/E) components vastly increases in modern motor vehicles, vehicle safety risks and recalls due to E/E problems have become issues for both auto manufactures and customers. This thesis describes methods to assist designers to analyze legacy designs incorporating the Time-Triggered Controller Area Network (TTCAN) bus in a post-design phase. We present a case study for the UT-Arlington Formula SAE all-electric race car, which has 18 controller area network (CAN) PIC microcontroller nodes using the TTCAN protocol. The contributions include the general approach to re-using legacy software in MBD processes, the automotive case study and analysis thereof with SLSF simulation, and resulted in identifying and correcting two bugs in the legacy software for the car.