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

被引：0

作者：

Shangguan J. ^{[1
]}

Gao J. ^{[2
]}

Guo H. ^{[1
]}

Sun Q. ^{[1
]}

机构：

[1] School of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng, Shandong

[2] Technology Department, Liaocheng Zhongtong Light Passenger Car Co., Ltd., Liaocheng, Shandong

来源：

International Journal of Vehicle Autonomous Systems | 2019年 / 14卷 / 04期

关键词：

Adaptive power distribution control; Back propagation neural network; Dual-motor coupling system; Dynamic programming; Electric vehicle; PID; Road gradient; Rulebased power distribution strategy; Shift schedule; Sub-optimal SOC predictive model;

D O I：

10.1504/IJVAS.2019.102447

中图分类号：

学科分类号：

摘要：

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. Copyright © 2019 Inderscience Enterprises Ltd.

引用

页码：367 / 388

页数：21

共 24 条

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