In order to solve the problems of difficulty in obtaining real-time vehicle driving sta-tus and low estimation accuracy of distributed driving electric vehicles,this paper proposes a distributed vehicle driving state estimation method based on the square root cubature Kalman fil-ter(SCKF)with singular value decomposition(SVD).The SCKF optimizes the error covari-ance matrix by singular value decomposition to improve the problem of reduced accuracy or even divergence of the CKF in strongly nonlinear vehicle systems or non-positive timing state estima-tion of the covariance matrix.The parameter information obtained from the 7-degree of freedom vehicle dynamics model and the Dugoff tire model is used to accurately estimate the vehicle driv-ing state.Experimental validation is carried out on a Matlab/Simulink simulation platform,and a comparison analysis with virtual values based on CarSim data is performed.The results show that the estimation results based on this algorithm are closer to the real values and have fast re-sponse and strong real-time performance.
vehicle state estimationsingular value decompositiondistributed driving vehicles
维普
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