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This article presents a methodology to apply Model-Based Design to develop and automatically optimize vehicle stability control systems. Such systems are employed to improve the dynamic rollover stability of Sport Utility Vehicles (SUVs). A non-linear vehicle model, representative of a midsize SUV, was built in CarSim®. This vehicle model is used in Simulink® to design a control system that reduces the risk of rollover. Optimization methods are then used to automatically adjust controller parameters to meet the system specifications that ensure the stability of the vehicle. Cosimulation between the two software packages enables rapid design and verification of control algorithms in a virtual environment. The results of the simulation experiments can be visualized through a 3-D animation of vehicle motion. The control system is adapted for the specific vehicle model, enabling it to remain stable under standard test conditions.

This paper addresses a common issue in producing desktop simulations for production environments in which the most current version of the algorithm is available only in the form of the production code. The part of the system we are interested in is often called performance software (for example, slip control systems, transmission control, and engine control). From a control algorithm design perspective the ideal environment is a reference model in a high level language, which supports code generation. The complete environment would support templatized code generation so that the fixed-point code for the embedded controller can be generated directly. Many organizations have a significant investment in legacy C code, and the cost of remodeling the entire system may be unacceptably high (at least in the short term). In such an environment simulation tools are often underused because of the impression that the entire system must be remodeled.