The Tradeoff Power Distribution Strategy Based on the Genetic -Pareto Algorithm for a Dual-Motor Coupling-Propulsion Electric Vehicle

Abstract

Abstract The dual-motor coupling-propulsion electric vehicle (DMCP-EV) has the merit of favorable energy efficiency due to its multiple operation modes. In the driving process, the performance of the DMCP-EV depends greatly on the power distribution to meet various driving requests. A power distribution coefficient is optimized by using the genetic-Pareto algorithm (GA-Pareto) algorithm. In addition to this effort, a power distribution strategy based on tradeoff optimization with comprehensive consideration of energy efficiency and ride comfort is proposed. Then, the sensitive analysis of optimized performance is conducted to obtain the three appropriate GA-Pareto algorithm parameters. The benchmark strategies are conducted to validate the proposed tradeoff power distribution strategy and the comparisons of three preference strategies with the hardware-in-loop (HIL) validation are performed. Results of the simulation and HIL experiments demonstrate that the proposed control strategies can address the tradeoff between energy-efficient and ride comfort for DMCP-EV.