Predictive Energy Management for Fuel Cell Hybrid Electric Vehicles

Fuel cells are gradually becoming the competitive alternative to conventional internal combustion engines due to their high system efficiency and zero-local emission property. Nevertheless, the high manufacturing cost and the limited lifetime of fuel cell systems still remain the major barrier toward the massive promotion of fuel cell electric vehicles. To reduce the vehicle’s operating cost, reliable energy management strategies should be devised to coordinate the outputs of multiple energy sources in hybrid powertrain. This chapter intends to present the development of predictive energy management strategy for fuel cell hybrid electric vehicles, especially focusing on the possibility of combining the driving predictive information with the real-time optimization framework. To this end, two driving prediction techniques are proposed, namely, a vehicle speed forecasting approach and a driving pattern recognition method. Thereafter, model predictive control is adopted for real-time decision-making with the assistance of the predicted information. Validation results indicate that the proposed control strategy outperforms the benchmark control strategies in terms of fuel economy and fuel cell durability, thereby verifying the control performance improvement imposed by driving prediction integration.