基于UKF算法的车辆质心侧偏角估计  

Estimation of Vehicle Side-slip Angle Based on Unscented Kalman Filter Algorithm

作　　者：丁红[1] 赵林峰[1] 周延明 刘晟昱 姚常瓦 

机构地区：[1]合肥工业大学机械与汽车工程学院,安徽合肥230009 [2]株洲易力达机电有限公司,湖南株洲412002

出　　处：《湖北汽车工业学院学报》2012年第4期5-9,共5页Journal of Hubei University Of Automotive Technology

基　　金：中航工业产学研合作创新工程专项(CXY2010HFGD27;CXY2010HFGD26);校博士专项科研资助(2010HGBZ0614);中央高校基本科研业务费专项资金(2011HGQC1010)

摘　　要：将无味卡尔曼滤波(UKF)算法运用到车辆质心侧偏角的估计之中,基于纵滑—侧偏联合工况下的统一指数(Uni-tire)轮胎模型建立非线性车辆动力学模型,采用最小偏度单形采样的UKF算法估计车辆的几个关键状态参量,并由此得到质心侧偏角估计。最后采用奇瑞A3两厢型汽车的车辆参数,使用车辆动力学实时仿真软件DYNAware/veDYNA对观测器进行了实时验证。仿真结果表明,UKF非线性估计方法精度高,估计结果能够满足实际应用要求。Unscented Kalman filter （UKF） algorithm was applied to vehicle side-slip angle estimation. And the nonlinear vehicle dynamics model was set up based on Uni-tire mode/. The estimates of the side-slip angle were determined based on several vehicle key state parameters which were estimated using UKF with the smallest skewness simplex sampling strategy. The observer was validated using the real-time vehicle dynamic simulation software DYNAware/veDYNA with the parameters of hatchback version of Chery A3. The simulation results show that the nonlinear UKF estimation method has high estimation precision, and the results satisfy the actual application requirements.

关 键 词：质心侧偏角 unscented卡尔曼滤波(UKF) 统一指数轮胎模型 仿真试验 

分 类 号：U461.6[机械工程—车辆工程]