首页> 外文会议>IEEE Intelligent Vehicles Symposium >Tire force estimation for a passenger vehicle with the Unscented Kalman Filter
【24h】

Tire force estimation for a passenger vehicle with the Unscented Kalman Filter

机译:使用Unscented Kalman滤波器估算乘用车的轮胎力

获取原文

摘要

A robust method to estimate tire forces for a passenger vehicle with the Unscented Kalman Filter (UKF) is provided. Only standard vehicle sensors were used and no a priori knowledge of tire and road properties was required. The estimator uses the bicycle model and a random walk tire force model. The tire force estimates were compared to a CarSim reference model for combined slip maneuvers. The results showed a good overall tracking performance of the estimator. In addition, the UKF-estimator demonstrated a high convergence rate and good stability properties. The performed robustness studies showed that the estimator performs well even in the presence of disturbances such as changes in tire-road friction. This method enables a cost-effective and robust implementation for future real time vehicle applications.
机译:提供了一种鲁棒的方法,可利用无味卡尔曼滤波器(UKF)估算乘用车的轮胎力。仅使用标准的车辆传感器,不需要轮胎和道路特性的先验知识。估算器使用自行车模型和随机行走轮胎力模型。将轮胎推力估算值与CarSim参考模型进行了比较,以进行综合打滑操作。结果表明该估计器具有良好的整体跟踪性能。此外,UKF估计器显示出高收敛速度和良好的稳定性。进行的鲁棒性研究表明,即使在存在干扰(例如轮胎与路面摩擦的变化)的情况下,估算器也能保持良好的性能。这种方法可以为未来的实时车辆应用提供经济高效且可靠的实施方案。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号