考虑侧向运动的整车质量与道路坡度估计
Joint estimation of vehicle mass and road slope considering lateral motion
郭洪艳 1王连冰 1赵旭 2戴启坤1
作者信息
- 1. 吉林大学 通信工程学院,长春 130022;吉林大学 汽车仿真与控制国家重点实验室,长春 130022
- 2. 吉林大学 通信工程学院,长春 130022;吉林化工学院 航空工程学院,吉林省 吉林市 132022
- 折叠
摘要
为减小侧向运动对整车质量与道路坡度估计精度的影响,提出了一种考虑侧向运动的估计算法,利用加速度修正车辆动力学模型,采用遗忘因子提高新数据适应车辆系统时变特性的最小二乘算法估计整车质量,并将质量估计结果实时输入道路坡度估计中;建立车辆运动学和动力学两个坡度估计模型,并在模型中添加加速度修正项,设计强跟踪滤波算法分别针对2种模型进行道路坡度估计,时变交互多模型融合算法根据两个坡度估计模型的权重系数和模型间的转移概率得到道路坡道估计值.本文算法在中国第一汽车股份有限公司技术中心农安汽车试验场进行了实车试验和评估,与未考虑侧向的融合估计算法相比,提高了车辆横向运动时的道路坡度估计精度.
Abstract
To reduce the influence of the lateral motion on the vehicle mass and the estimation accuracy of the road gradient,an estimation algorithm considering the lateral motion is proposed,the vehicle dynamics model is corrected by the acceleration,and the forgetting factor is used to enhance the new data to adapt to the minimum value of the time-varying characteristics of the vehicle system.The vehicle mass is estimated by the quadratic algorithm,and the mass estimation result is input into the road gradient estimation in real time;in addition,two gradient estimation models of vehicle kinematics and dynamics are established,and the acceleration correction term is added to the model,and the strong tracking filtering algorithm is designed respectively.A time-varying interactive multi-model fusion algorithm is proposed to estimate the road slope for the two models.The estimated road slope is obtained according to the weight coefficients of the two slope estimation models and the transition probability between the models.The proposed algorithm was tested and evaluated on a real vehicle in the Nong'an Automobile Proving Ground of the Technology Center of China FAW Co.,Ltd.Compared with the fusion estimation algorithm that did not consider the lateral direction,it improves the estimation accuracy of road slope when the vehicle moves laterally.
关键词
车辆工程/质量与坡度估计/时变交互多模型/融合/侧向运动/实车试验Key words
vehicle engineering/mass and road slope estimation/time-varying interacting multiple model/fusion/lateral movement/real vehicle test引用本文复制引用
基金项目
国家自然科学基金(U19A2069)
吉林省科技发展计划重点研发项目(20200401088GX)
上海汽车工业科技发展基金会开放基金(1909)
出版年
2024
NETL
NSTL
万方数据