Abstract
For the driving state estimation problem of four-wheel independent drive and steering electric vehicles, the algorithm based on cubature Kalman filter was studied. The driving state estimation model was established for the four-wheel independent drive and steering electric vehicle. Take advantage of that the four-wheel drive torque can be measured easily to calculate the longitudinal force and the Dugoff tyre model was used to compute lateral force. The low cost sensor signals are used. According to the four-wheel independent drive and steering electric vehicle’s dynamic control characteristics and the advantages of multiple information sources, the longitudinal velocity, lateral velocity and sideslip angle of the electric vehicle were estimated accurately through the application of dynamic theory and cubature Kalman filter theory. The algorithm was verified by CarSim and Matlab/Simulink co-simulation. The results show that the vehicle driving state of the four-wheel independent drive and steering electric vehicle can be estimated accurately using the vehicle driving state estimation algorithm based on cubature Kalman filter theory.
This work is supported by National Science Foundation of China (51675257, 51305190), and Project of Liaoning Province major science and technology platform (JP2016003, 2017001), Project of Liaoning Province Innovative Talents (LR2016054).
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Gang, L., Dongsheng, F., Ye, W. (2021). Study on Vehicle Driving State Estimation for Four-Wheel Independent Drive and Steering Electric Vehicle. In: Proceedings of China SAE Congress 2019: Selected Papers. Lecture Notes in Electrical Engineering, vol 646. Springer, Singapore. https://doi.org/10.1007/978-981-15-7945-5_24
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DOI: https://doi.org/10.1007/978-981-15-7945-5_24
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