优化BP神经网络PID的半活跃悬浮控制基于子搜索算法
Mei Li1, Jie Xu1, Zelong Wang1
1Mechanical and Electrical Engineering College, Hainan University, Haikou 570100, China.
Sensors (Basel, Switzerland)
|March 28, 2024
概括
这项研究开发了一种优化的半活性悬挂,用于带有枢纽电机的电动汽车. 新系统通过减轻来自集成电机的振动,显著提高了驾驶舒适度和控制性能.
科学领域:
- 汽车工程 汽车工程
- 控制系统 控制系统
- 振动分析 振动分析
背景情况:
- 电动汽车中的枢纽电机增加了无弹性质量,导致振动加剧.
- 发动机激发和车路合效应降低了电动汽车的性能.
研究的目的:
- 为了研究一个合动力学模型,用于半活跃悬挂在枢纽电机电动汽车.
- 开发一个优化的控制策略,以减轻多源振动.
主要方法:
- 开发了一种考虑到道路和电机激发的联动动力学模型.
- 提出了一种BP神经网络PID控制器,该控制器通过子搜索算法进行优化.
- 使用车身加速,悬挂偏移和动态轮胎负载来评估性能.
主要成果:
- 优化的半活性悬架显著提高了驾驶舒适度.
- 与标准PID和PSO-BPNN-PID相比,拟议的控制器表现出更高的性能.
- 在各种驾驶条件下实现了有效的控制性能.
结论:
- 用子搜索算法优化的BP神经网络PID控制器提高了枢纽电机电动汽车的半活性悬挂性能.
- 这种方法有效地解决了由不弹性质量增加和电机引起的振动所带来的挑战.
- 这些发现有助于提高电动汽车的行驶质量和运行稳定性.
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