An adaptive power distribution control strategy for an electric vehicle with dual-motor coupling in consideration of road gradient. (24th September 2019)

• Record Type: Journal Article
• Authors: Shangguan, Jinyong; Gao, Jianlu; Guo, Hongqiang; Sun, Qun
• Is Part Of: International journal of vehicle autonomous systems. Volume 14:Number 4(2019)
• Page Start: 367
• Page End: 388
• Publication Date: 2019-09-24
• Subjects: electric vehicle -- dual-motor coupling system -- sub-optimal SOC predictive model -- adaptive power distribution control -- shift schedule -- back propagation neural network -- dynamic programming -- road gradient -- PID -- rule-based power distribution strategy; Autonomous vehicles -- Periodicals; Motor vehicles -- Technological innovations -- Periodicals; Motor vehicles -- Electronic equipment -- Periodicals; Robots -- Control systems -- Periodicals; Intelligent transportation systems -- Periodicals; 629.20285
• Languages: English
• ISSNs: 1471-0226

Abstract

An optimal power distribution control strategy is proposed in consideration of road gradient. Two original contributions are made to distinguish our work from current research. First, a sub-optimal State of Charge (SOC) predictive model is proposed based on Back Propagation (BP) neural network. The sampling set of the BP is obtained from the optimal results from Dynamic Programming (DP), based on a series of driving cycles in real-world and the corresponding road gradient. Second, an adaptive control method based on PID is proposed with the designed sub-optimal SOC predictive model. Specifically, the optimal shift schedule of the coupler is designed offline based on DP and is implemented into the controller in a prior fashion, to decouple the relationship between the coupler and the motors. Simulation results demonstrate that the proposed adaptive control strategy can realise optimally real-time power distribution control and is better than rule-based power distribution strategy.