A yaw stability-guaranteed hierarchical coordination control strategy for four-wheel drive electric vehicles using an unscented Kalman filter |
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| Institution: | 1. School of Mechanical and Precision Instrument Engineering, Xi''an University of Technology, Xi''an 710048, China;2. School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China;1. College of Information Engineering, Shenyang University of Chemical Technology, Shenyang, 110142, China;2. State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110169, China;3. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, 110169, China;4. University of Chinese Academy of Sciences, Beijing, 100049, China;5. The College of Automation, Shenyang Aerospace University, Shenyang, 110136, China;1. School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China;2. School of Mathematics, Southeast University, Nanjing 210096, China;1. Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Fars, Iran;2. Department of Power and Control Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Fars, Iran;1. Federal University of Minas Gerais, Graduate Program in Electrical Engineering, Av. Antonio Carlos, 6627, Belo Horizonte, MG 31270-901, Brazil;2. Federal University of Minas Gerais, Department of Electronics Engineering, Av. Antonio Carlos, 6627, Belo Horizonte, MG 31270-901, Brazil;3. Federal University of São João del-Rei, Department of Electrical Engineering, Praça Frei Orlando, 170, São João del-Rei, MG, Brazil |
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| Abstract: | A novel hierarchical coordination control strategy (HCCS) is offered to guarantee the stability of four-wheel drive electric vehicles (4WD-EVs) combining the Unscented Kalman filter (UKF). First, a dynamics model of the 4WD-EVs is established, and the UKF-based estimator of sideslip angle and yaw rate is constructed concurrently. Second, the equivalent cornering stiffness coefficients are jointly estimated to consider the impact of vehicle uncertainty parameters on the estimator design. Afterwards, a HCCS with two-level controller is presented. The sideslip angle and yaw rate are controlled by an adaptive backstepping-based yaw moment controller, and the computational burden is relieved by an improved adaptive neural dynamic surface control technology in the upper-level controller. Simultaneously, the optimal torque distribution controller of hub motors is developed to optimize the adhesion utilization ratio of tire in the lower-level controller. Finally, the proposed HCCS has shown effective improvement in the trajectory tracking capability and yaw stability of the 4WD-EVs under various maneuver conditions compared with the traditional Luenberger observer-based and the federal-cubature Kalman filter-based hierarchical controller. |
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