A predictive energy management for hybrid vehicles based on optimal control theory

In this paper we propose a predictive energy management for a hybrid electric vehicle with compound power-split powertrain configuration. The strategy relies on information on the future driving trip provided by modern navigation systems. Based on this information a simplified optimal control problem is solved via an indirect variation of extremals algorithm to determine a feasible start value of the adjungated variable. The powertrain controls are then determined from offline calculated maps using the value of the adjungated variables, the current vehicle speed and the requested wheel-torque. The strategy is implemented into a model-based simulation environment and has shown fuel savings on real world driving cycles. It has proven to be real-time applicable and very robust against low accuracy of the predicted driving trip.