基于分层多传感器感知融合的智能主动悬挂控制方法
Chen Huang1, Yang Liu1, Xiaoqiang Sun1
1Institute of Automotive Engineering, Jiangsu University, Zhenjiang 212013, China.
Sensors (Basel, Switzerland)
|August 14, 2025
概括
这项研究引入了用于主动悬架控制的新型传感器融合框架,显著提高了车辆的稳定性和舒适性. 该系统有效地减少了各种道路条件下的垂直,斜坡和滚动加速.
科学领域:
- 汽车工程 汽车工程
- 控制系统 控制系统
- 机器人和智能系统 机器人和智能系统
背景情况:
- 智能悬架系统对于车辆动态,驾驶舒适度和安全至关重要.
- 由于传感器数据有限,当前的系统经常面临精确控制方面的挑战.
- 传感器融合提供了一条整合各种数据以提高性能的途径.
研究的目的:
- 开发和验证一个层次化的多传感器融合框架,用于主动悬挂控制.
- 提高控制精度和适应不同道路条件的适应性.
- 为了提高车辆的动态稳定性,驾驶舒适性和乘客安全性.
主要方法:
- 使用双眼视觉系统检测道路特征 (车道曲率,阻塞) 和测量距离.
- 综合全球定位系统 (GPS) 和惯性测量单元 (IMU) 数据用于预测道路高度配置文件.
- 实施了BP-PID控制策略,包括模式切换规则和使用群优化优化悬挂参数.
- 使用一个硬件在循环 (HIL) 模拟平台验证了框架.
主要成果:
- 在垂直加速 (5.37%),俯冲加速 (9.63%) 和滚动加速 (11.58%) 中显著降低.
- 拟议的框架有效地适应了平坦,曲和有障碍的道路条件.
- 硬件在循环中的模拟证实了系统的有效性和稳定性.
结论:
- 层次化的多传感器融合框架为主动悬挂控制提供了强大而有效的解决方案.
- 这种方法通过精确的自适应控制来提高车辆动态稳定性,驾驶舒适性和安全性.
- 视觉,GPS和IMU数据的整合代表了智能汽车系统的重大进步.
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