基于明确模型预测控制的RBS和ABS协调控制策略
Liang Chu1, Jinwei Li1, Zhiqi Guo1
1State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China.
Sensors (Basel, Switzerland)
|May 25, 2024
概括
本研究介绍了电动汽车制动系统的明确模型预测控制策略. 新方法提高了再生制动和液压制动之间的协调,以获得更好的能量回收和实时性能.
科学领域:
- 汽车工程 汽车工程
- 控制系统 控制系统
- 电动汽车技术 电动汽车技术
背景情况:
- 电动汽车使用再生制动系统 (RBS) 和反锁制动系统 (ABS).
- RBS和ABS之间的协调可能导致控制冲突,影响制动效率和实时控制.
- 现有的方法很难优化电动液压联合制动系统.
研究的目的:
- 为电液复合制动系统提出和评估一种新的协调控制策略 (eMPC-CCS).
- 提高RBS和ABS之间的协调控制的有效性和实时能力.
- 为了提高制动能量回收和车辆整体制动性能.
主要方法:
- 开发一个全面的制动控制框架,整合线下自适应控制法生成和线上优化控制法应用.
- 使用显式模型预测控制 (eMPC) 来生成基于真实世界的驾驶数据的实时面向状态反控制规律.
- 整合状态错误补偿器以优化车辆制动状态并确保强度.
主要成果:
- 拟议的eMPC-CCS有效地协调了再生和液压制动力.
- 离线生成的控制规则可以提高适应不同驾驶条件的适应性.
- 在线实施预先计算的控制规则可以提高实时性能.
- 与其他控制策略相比,模拟和HIL测试证实了优越的制动能量回收和实时能力.
结论:
- 电动汽车制动系统 (eMPC-CCS) 提供了一种有效的解决方案,用于对电动汽车的再生制动和液压制动系统进行协调控制.
- 该策略显著改善了制动能量回收和实时控制性能.
- 拟议的方法在各种制动条件下提供了增强的稳定性.
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