A Rule-Based Energy Management Strategy for a Light-Duty Commercial P2 Hybrid Electric Vehicle Optimized by Dynamic Programming

An appropriate energy management strategy can further reduce the fuel consumption of P2 hybrid electric vehicles (HEV) with simple hybrid configuration and low cost. The rule-based real-time energy management strategy dominates the energy management strategies utilized in commercial HEVs, due to its robustness and low computational loads. However, its performance is sensitive to the setting of parameters and control actions. To further improve the fuel economy of a P2 HEV, the energy management strategy of the HEV has been re-designed based on the globally optimal control theory. An optimization strategy model based on the longitudinal dynamics of the vehicle and Bellman’s dynamic programming algorithm was established in this research and an optimal power split in the dual power sources including an internal combustion engine (ICE) and an electric machine at a given driving cycle was used as a benchmark for the development of the rule-based energy management strategy. Then, a novel rule-based real-time energy management strategy was proposed on the basis of the nonlinear relation between the output torque of the ICE and the torque demanded by the HEV, and then was used in a commercial P2 HEV. The experimental results show that the equivalent energy consumption of the HEV can be reduced around 6.1% in the world- harmonized light-duty vehicle test cycle (WLTC) when the energy management strategy is altered from the original strategy to the optimization strategy.