Rule-Based Control Strategy for a Novel Dual-Motor PHEV Improved by Dynamic Programming

Appropriate energy management strategy can further improve the fuel economy of plug-in hybrid electric vehicles (PHEV). Rule-based control strategies are dominant in actual vehicles because of their fast calculation and easy implementation. However, incorrect parameter settings and suboptimal control strategies may lead to substantial performance variations, preventing optimal fuel efficiency and emissions reduction. In this paper, the dynamic programming algorithm is implemented to design the control strategy for a dual-motor PHEV. The MATLAB/Simulink environment is used to construct models of the key components and powertrain controller, and simulation platforms for both rule-based and optimization-based strategies are established. Through the calculation results of dynamic programming (DP) algorithm, the rule of working mode switching and torque distribution is analyzed to improve the performance of rule-based control strategy. WLTC driving cycle simulation results show that the improved rule control effectively improves the economy of PHEV, and its comprehensive consumption per 100 km decreases by 2.853%.