Modeling, control, and design optimization of a fuel cell hybrid vehicle

Among the alternatives for future vehicle technologies to address growing environmental concerns and increasing demand for fossil fuels, fuel cell hybrid vehicles (FCHVs) are regarded as a promising solution, because they can achieve virtually zero emissions with high efficiency. However, since FCHVs are in the early stage of development, the procedure for optimal controller design and component sizing to explore their full potential is not yet established. This dissertation presents a comprehensive procedure for modeling, control, and design optimization of FCHVs. It provides a powerful tool for vehicle designers to make critical choices such as supervisory controller design and powertrain component sizing that affect fuel economy and performance of FCHVs.; We first develop a dynamic simulation model of a fuel cell hybrid vehicle. The subsystems are modeled based on carefully designed test data, and then the vehicle model is constructed and validated by prototype vehicle test results. The strength of the high-fidelity simulation model is that it is based on the experimental data of a prototype fuel cell vehicle and a test bench setup.; A supervisory controller for FCHVs is then developed using the stochastic dynamic programming methodology to optimize fuel economy while ensuring drivability. Two aspects are improved in the original formulation presented here: we use the concept of equivalent fuel consumption to penalize the energy draw from the battery, and consider the vehicle speed as storable energy in kinetic form.; Component sizing as well as the control strategy affects the fuel economy of FCHVs. We present a systematic framework that makes it possible to simultaneously optimize the control strategy and the component sizing for the future design of FCHVs. We suggest a parameterized controller to reduce the computational requirement of the optimization process, and present subsystem-scaling laws that can predict the effect of sizing parameters on the system efficiency characteristics. This procedure provides a combined optimal design and control of the FCHV, which is of ultimate importance during the evaluation of the FCHV.