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A robust Vehicle Model Architecture (VMA) has been developed to support model-based Vehicle System Control (VSC) design work and, in general, model-based vehicle system engineering activities. It is based on a logical breakdown of the vehicle into key subsystems with supporting bus infrastructure for distribution of signals between subsystems. Primary physical interfaces between the top level subsystems have been defined. Subsystem models that comply with these interfaces can be easily plugged into the architecture for complete simulation of vehicle systems. The VMA encourages model re-use and sharing between project teams and, furthermore, removes key obstacles to sharing of models with suppliers.

The desire for improved vehicle fuel economy, driven by high gas prices and concerns over energy independence, have sparked interest and demand for hybrid electric vehicles. Hybrid electric vehicle propulsion systems exhibit complex interactions which need to be understood in order to maximize fuel economy over the range of operating modes. Model-based development processes which use vehicle system models capable of representing the functional behaviors with embedded controls are needed for fast, efficient design of vehicle control systems which manage overall energy usage. Model-based vehicle system development processes have been employed for a Dual Drive HEV system. The process for creating these vehicle system models is described along with an approach for using these models to develop HEV systems. Details of key subsystem models and the process for integration of full vehicle implementation level controls are discussed.

As the complexity of automotive chassis control systems increases with the introduction of technologies such as yaw and roll stability systems, processes for model-based development of chassis control systems becomes an essential part of ensuring overall vehicle safety, quality, and reliability. To facilitate such a model-based development process, a vehicle modeling framework intended for chassis control development has been created. This paper presents a design methodology centered on this modeling framework which has been applied to real world driving events and has demonstrated its capability to capture vehicle dynamic behavior for chassis control development applications.