TY - JOUR
T1 - Numerical Achieved Extended Kalman Filter State Observer Design Based on a Vehicle Model Containing UniTire Model
AU - Pan, Zhao
AU - Zong, Changfu
AU - Hu, Dan
AU - Zheng, Hongyu
AU - Wu, Kan
PY - 2008/6/23
Y1 - 2008/6/23
N2 - It is difficult to obtain state variables accurately or economically while vehicle is moving, however these state variables are significant for chassis control. Although many researches have been done, a complex model always leads to a control system with poor real-time performance, while simple model cannot show the real characteristics. So, in order to estimate the value of yaw rate and side slip angle accurately and sententiously, an Extended Kalman Filter (EKF) observer is proposed, which is based on an ameliorated 2-DOF “bicycle model”. The EKF algorithm is achieved numerically and verified by the results from the real field test.
AB - It is difficult to obtain state variables accurately or economically while vehicle is moving, however these state variables are significant for chassis control. Although many researches have been done, a complex model always leads to a control system with poor real-time performance, while simple model cannot show the real characteristics. So, in order to estimate the value of yaw rate and side slip angle accurately and sententiously, an Extended Kalman Filter (EKF) observer is proposed, which is based on an ameliorated 2-DOF “bicycle model”. The EKF algorithm is achieved numerically and verified by the results from the real field test.
U2 - 10.4271/2008-01-1783
DO - 10.4271/2008-01-1783
M3 - Article
SN - 0148-7191
SN - 2688-3627
JO - SAE Technical Papers
JF - SAE Technical Papers
ER -