控制理论(社会学)
开关磁阻电动机
联轴节(管道)
汽车工程
计算机科学
控制(管理)
振动
多目标优化
工程类
电动机驱动
控制工程
转子(电动)
机器学习
物理
机械工程
人工智能
量子力学
作者
Chao Xing,Yueying Zhu,Hao Wu
出处
期刊:IEEE-ASME Transactions on Mechatronics
[Institute of Electrical and Electronics Engineers]
日期:2022-07-20
卷期号:27 (6): 5701-5711
被引量:27
标识
DOI:10.1109/tmech.2022.3188342
摘要
To improve the comprehensive performance of the electromechanical coupling braking system (CBS) and suppress vertical vibration caused by the unbalanced radial forces of in-wheel motors, a CBS control strategy based on multiobjective optimization on the control parameters of switched reluctance motor (SRM) drive system is proposed in this article. First, the electromagnetic coupling and eccentricity characteristics of SRM are analyzed, and a multiobjective optimization strategy (MOOS) for the SRM-drive system is proposed to comprehensively improve the endurance mileage, battery life, and braking comfort. Then, switch angles and required regenerative braking force are optimized by the combination of MOOS and genetic algorithm, and the corresponding optimized controllers are established. Furthermore, the braking performance of optimized CBS is analyzed and compared to the other three single-objective optimization strategies (SOOSs), and the results indicate that the control strategy with MOOS can improve vehicle comprehensive performance, although the strategies with SOOSs have a great improvement for corresponding objectives. Meanwhile, based on the strategies, comprehensive switchable control logic is proposed to improve the overall performance of vehicles under different braking modes. Finally, the results from the simulation and processor in loop test are analyzed and compared, which validates the real-time performance and effectiveness of the control strategy.
科研通智能强力驱动
Strongly Powered by AbleSci AI