一种基于轮胎模型参数自适应的车辆状态估计方法
一种基于轮胎模型参数自适应的车辆状态估计方法
本发明涉及一种基于轮胎模型参数自适应的车辆状态估计方法，包括：采集实车数据；基于车辆载荷转移模型与车轮中心速度计算，建立轮胎经验模型；建立基于无迹卡尔曼滤波的车辆状态估计方案；筛选典型工况下满足持续激励条件的数据片段并记忆；采用粒子群优化进行轮胎模型参数识别，根据不同车速段下的最优轮胎模型参数拟合得到轮胎模型参数随着车速变化的关系；将轮胎模型参数随着车速变化的关系，代入到基于无迹卡尔曼滤波的车辆状态估计方案中，得到车辆状态实时估计。本发明提供的轮胎模型与参数识别算法，充分考虑车辆的非线性与横纵向动力学耦合关系，通过优化算法自适应调整轮胎模型参数，能够实现更可靠、精确的车辆动力学参数识别。
The invention relates to a vehicle state estimation method based on tire model parameter self-adaption. The method comprises the following steps: collecting real vehicle data; based on the vehicle load transfer model and wheel center speed calculation, establishing a tire empirical model; establishing a vehicle state estimation scheme based on unscented Kalman filtering; screening and memorizing data fragments meeting continuous excitation conditions under typical working conditions; carrying out tire model parameter identification by adopting particle swarm optimization, and fitting according to the optimal tire model parameters under different vehicle speed sections to obtain the relationship of the tire model parameters changing along with the vehicle speed; and substituting the relationship of the tire model parameters along with the change of the vehicle speed into a vehicle state estimation scheme based on unscented Kalman filtering to obtain real-time estimation of the vehicle state. According to the tire model and parameter identification algorithm provided by the invention, the nonlinear and transverse and longitudinal dynamics coupling relationship of the vehicle is fully considered, and the tire model parameters are adaptively adjusted through the optimization algorithm, so that more reliable and accurate vehicle dynamics parameter identification can be realized.
Dokumentinformationen
一种基于轮胎模型参数自适应的车辆状态估计方法
2024-06-28
Patent
Elektronische Ressource
Chinesisch