智能辅助驾驶系统中横摆角速度信号估计方法的研究  

Research on Yaw Rate Estimation Method in Intelligent Assistant Driving System

作　　者：刘芬 曲延羽 廖尉华 覃高峰 林智桂 Liu Fen;Qu Yanyu;Liao Weihua;Qin Gaofeng;Lin Zhigui(SAIC GM Wuling Automobile Co.,Ltd.,Liuzhou 545007,China)

机构地区：[1]上汽通用五菱汽车股份有限公司,柳州545007

出　　处：《汽车与驾驶维修》2021年第10期29-31,共3页Auto Driving & Service

摘　　要：本文提出一种基于卡尔曼滤波的多信源融合的横摆角速度估计方法。首先,建立二自由度车辆动力学模型,基于该模型计算横摆角速度;其次,基于车辆运动学模型估计横摆角速度;最后,将2种结果与车身底盘输出的横摆角速度进行融合,得到最终的横摆角速度。实验数据表明,最终的横摆角速度在稳定性、精确性等方面有明显的提升。This paper proposes a multi-source fusion method to estimate yaw rate based on Kalman filter.Firstly,a vehicle model with three degrees of freedom was established and yaw rate was predicted based on the model.Secondly,the yaw rate was estimated based on Ackerman model.Finally,the two results are fused with the yaw rate output from can signal.Experimental data show that the stability and accuracy of yaw velocity are improved obviously after processing.

关 键 词：横摆角速度 卡尔曼滤波 信息融合 

分 类 号：U462[机械工程—车辆工程]