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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References
Zhuoping Y, Yuan F, Xiong L (2013) Review on vehicle dynamics control of distributed drive electric vehicle. J Mech Eng 49(8):105–114
Murata S (2012) Innovation by in-wheel-motor drive unit. Veh Syst Dyn 50(6):807–830
Rauh J, Ammon D (2011) System dynamics of electrified vehicles: some facts, thoughts, and challenges. Veh Syst Dyn 49(7):1005–1020
Zhuoping Y, Xiaojie G (2009) Review of vehicle state estimation problem under driving situation. J Mech Eng 05:20–33
Zhenpo W, Xue X, Yachao W (2018) State parameter estimation of distributed drive electric vehicle based on adaptive unscented Kalman filter. J Beijing Inst Technol 38(07):698–702
Gang L, Ruichun X, Shaoyuan W, Hailan H (2014) Vehicle driving state estimation based on adaptive Kalman filter. Soc Autom Eng China 7:479–485
Yanru S (2011) Vehicle longitudinal and lateral velocity estimation based on unscented Kalman filter. Master’ degree, Jilin University, Jilin
Shaoyuan W, Ruichun X, Gang L (2015) Estimation of vehicle’s driving state based on cubature Kalman filter. Mach Des Manuf 01:69–73
Gang L, Ruichun X, Shaoyuan W, Changfu Z (2015) Estimation of vehicle state and road adhesion coefficient based on dual-capacity Kalman filter. Sci China Tech Sci 04:403–414
Ning L, Gang L, Ruichun X, Hang Y (2015) Study on vehicle driving state estimation based on multiple information fusion. Comput Simul 12:113–118
Arasaratnam I, Haykin S, Hurd TR (2010) Cubature Kalman filter for continuous-discrete systems: theory and simulations. IEEE Trans Sig Process 58(10):4977–4993
Xiqing W, Shenmin S (2013) Cubature Kalman filter-based satellite attitude estimation. J Astronaut 02:193–200
Qiuzhao Z, Shubi Z, Zhiping L, Hefang B (2014) Robust cubature Kalman filter based on SVD and its application to integrated navigation. Control Decis 02:341–346
Qiuzhao Z, Shubi Z, Nanshan Z, Jian W (2014) Multiple fade-out robust volumetric Kalman filter for GPS/INS combined system. J China University Min Technol 01:162–168
Xiaofei C, Youzhu L, Mengyuan C (2017) Mobile robot localization algorithm based on gaussian mixture consider Kalman filter in WSNs environment. Chinese J Sens Actuators 30(01):133–138
Yu Z (2009) Vehicle Theory. 5th edn. China Machine Press, Beijing, pp 144–146
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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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