在极端条件下,通过使用非政策安全的强化学习来进行FWID-EV的合作控制
Zhijiang Gao1, Pak Kin Wong1, Fuqiu Zhou1
1Department of Electromechanical Engineering, University of Macau, Taipa, 999078, Macao.
ISA transactions
|January 11, 2026
概括
本研究介绍了一种基于学习的非政策安全强化合作控制器,用于管理电动汽车的轮胎力量. 它通过协调直接曲面控制和主动悬架系统,在极端条件下提高了车辆的操控稳定性.
科学领域:
- 车辆动力学和控制系统.
- 机器人和智能控制.
- 汽车工程. 汽车工程.
背景情况:
- 由于横向负载转移造成的不平衡轮胎的正常力威胁到车辆的稳定性,尤其是在极端条件下.
- 悬架系统的功能限制了缓解这些力失衡的可能性.
- 四轮独立驱动电动汽车 (FWID-EVs) 需要先进的控制来保持驾驶稳定性.
研究的目的:
- 为优化轮胎正常力分布,提出一种新型控制器,协调直向偏航控制 (DYC) 和主动悬挂系统 (ASS).
- 为了提高FWID-EV在极端驾驶条件下的驾驶稳定性.
- 制定合作控制战略,以提高车辆的安全性和性能.
主要方法:
- 开发一个DYC-ASS合作架构,以优化轮胎的正常力分布.
- 关于联合轮胎滑动角度和相形图 (CTP) 方法的建议,以确定横向稳定区域 (LSR) 和轮胎力和.
- 采用双人游戏框架实现一种非政策安全的基于强化学习的合作控制器 (OSRC).
主要成果:
- OSRC控制器有效地协调DYC和ASS,以优化轮胎的正常力分布.
- 该CTP方法准确地描述了轮胎力和和LSR之间的关系.
- 快速控制原型测试验证了拟议的OSRC控制器在提高FWID-EV处理稳定性方面的有效性.
结论:
- 拟议的OSRC控制器成功地提高了FWID-EV在极端条件下的处理稳定性.
- DYC和ASS之间的合作控制对于管理轮胎的正常力和确保车辆安全至关重要.
- OSRC控制器为先进的车辆稳定性控制系统提供了一个有前途的方法.
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