An adaptive power distribution control strategy for an electric vehicle with dual-motor coupling in consideration of road gradient

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.