分布式驱动电动汽车处理稳定性协调控制框架基于自适应模型预测控制
Jianhua Guo1, Zhiyuan Dai1, Ming Liu2
1National Key Laboratory of Automotive Chassis Integration and Bionics, Changchun 130022, China.
Sensors (Basel, Switzerland)
|August 10, 2024
概括
本研究介绍了电动汽车的自适应模型预测控制 (AMPC) 框架. 新的AMPC战略提高了车辆的机动性和稳定性,特别是在极端条件下.
科学领域:
- 汽车工程 汽车工程
- 控制系统 控制系统
- 机器人技术 机器人技术 机器人技术
背景情况:
- 分布式驱动电动汽车通过独立的电机控制提供了更好的转向和稳定性.
- 协调这些车辆的驾驶稳定性对于性能和安全至关重要.
研究的目的:
- 引入一种新的自适应模型预测控制 (AMPC) 框架,以提高分布式驱动电动汽车的驾驶稳定性.
- 开发一个多层控制策略,动态调整以优化机动性和稳定性.
主要方法:
- 一个三层的控制框架:动态监督,在线优化和低级控制.
- 动态监督层建立稳定性边界并设计可变的重量因子.
- 在线优化层实现重量适应AMPC策略,用于实时控制调整.
- 低级控制层使用扭矩分配误差和轮胎利用率作为精确的力和时刻分配的成本函数.
主要成果:
- 拟议的AMPC战略与传统的MPC相比,表现优越.
- 在正常驾驶条件下观察到增强的机动性.
- 在极端条件下实现了显著改善的横向稳定性控制.
结论:
- 开发的AMPC框架有效地协调分布式驱动电动汽车的处理稳定性.
- 适应性,多层次的方法为标准和具有挑战性的驾驶场景提供了强大的控制.
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