摘要
为更好地进行泊车运动过程的研究,建立适合泊车过程的专用泊车运动学模型,通过对实际泊车运动过程的分析,提出了一种基于模糊卡尔曼滤波车速估算的泊车运动学模型。泊车的运动过程是低速高精度的控制过程,尤其在较小泊车位中进行超低速自动泊车时,对车速的测量会由于起步惯性和轮胎磨损引起速度测量误差,这就需要对实际车速进行精确估算。通过车轮转动速度与车身加速度积分所得车速进行模糊卡尔曼滤波融合,得到泊车不同阶段的车速估算值。输入估算的车速与前轴中心转角建立泊车运动学模型,得到泊车车辆的位置信息与姿态航向角。经Matlab/Simulink仿真和泊车实验的数据对比分析,结果表明:建立的基于模糊卡尔曼滤波车速估算的泊车运动学模型与原泊车运动学模型精度整体上提高15%,与实际泊车情况偏差3%。因此,提出的泊车运动学模型符合泊车过程车辆运动学模型的要求,降低了泊车整个过程的位移和航向角计算误差,对于进一步研究泊车路径规划与控制具有重要意义。
In order to better study the parking motion process,a special parking kinematics model suitable for the parking process is established.Through the analysis of the actual parking motion process,a parking kinematics model based on Fuzzy Kalman filter speed estimation is proposed.The movement process of parking is a low-speed and high-precision control process,especially when ultra-low-speed automatic parking is carried out in small parking spaces,the measurement error of speed will be caused by starting inertia and tire wear,so it is necessary to accurately estimate the actual speed.The vehicle speed obtained from the integration of wheel rotation speed and body acceleration is fused by fuzzy Kalman filter to obtain the estimated vehicle speed in different stages of parking.Input the estimated vehicle speed and front axle center angle to establish the parking kinematics model,and obtain the position information and attitude heading angle of the parking vehicle.Through the comparative analysis of the data of Matlab/Simulink simulation and parking experiment,the results show that the accuracy of the parking kinematics model based on Fuzzy Kalman filter speed estimation is improved by 15%compared with the original parking kinematics model,and the deviation from the actual parking situation is 3%.Therefore,the proposed parking kinematics model meets the requirements of vehicle kinematics model in the parking process,reduces the calculation errors of displacement and heading angle in the whole parking process,and is of great significance for further research on parking path planning and control.
作者
王龙
李红娟
WANG Long;LI Hongjuan(School of Vehicle Engineering,Xi’an Institute of Aeronautics,Xi’an 710077,China;Automobile Testing Engineering Technology Center,Xi’an Institute of Aeronautics,Xi’an 710077,China)
出处
《重庆理工大学学报（自然科学）》
CAS
北大核心
2021年第10期63-70,共8页
Journal of Chongqing University of Technology：Natural Science
基金
国家自然科学基金项目(U1564201)。
关键词
模糊算法
卡尔曼滤波
车速估算
泊车运动学模型
fuzzy algorithm
Kalman filtering
vehicle speed estimation
parking kinematics model
