基于自适应调参滤波的路面坡度估计算法  

Road Slope Estimation Algorithm Based on Adaptive Parameter Tuning Filtering

作　　者：管信 李怡杰 裴作帷 侯亚飞 黄敏琦 Guan Xin;Li Yijie;Pei Zuowei;Hou Yafei;Huang Minqi(Hozon New Energy Automobile Co.,Ltd.,Shanghai 201100)

机构地区：[1]合众新能源汽车股份有限公司,上海201100

出　　处：《汽车技术》2024年第8期47-52,共6页Automobile Technology

基　　金：面向车能路云的一体化电子电气架构研究浙江省技术厅基金项目(2024C01011)。

摘　　要：为解决低配电动车型缺少直接的道路坡度信息问题,提出基于现有控制器局域网(CAN)总线信号的路面坡度估计算法。首先,对总线输入的车速和纵向加速度信号进行预处理,并根据坡度与车速、纵向加速度间的关系构建卡尔曼滤波方程,估算道路坡度;然后,分析卡尔曼滤波过程中噪声方差参数对坡度估算结果的影响,设计自适应调参的卡尔曼滤波器,对坡度估计结果进行优化;最后,通过实车测试验证了坡度估计算法的实时性与有效性。At present,low-end electric vehicle do not have direct slope signal information.To address this issue,this article proposed a road slope estimation algorithm based on the existing CAN bus signals.Firstly,vehicle speed signal and longitudinal acceleration signal values input from CAN were preprocessed,and a Kalman filtering equation was constructed based on the relationship between slope,vehicle speed and longitudinal acceleration,to estimate the road slope.Then,the impact of noise variance parameters on the slop estimation results was analyzed,and an adaptive tuning Kalman filter was designed to optimize the slope estimation results.Finally,the vehicle test was conducted,verifying the accuracy and realtime performance of the ramp estimation algorithm.

关 键 词：路面坡度估计 CAN总线信号 卡尔曼滤波 自适应调参 

分 类 号：U461.1[机械工程—车辆工程]