Research on Longitudinal Control of Electric Vehicle Platoons Based on Robust UKF–MPC

Jiading Bao, Zishan Lin, Hui Jing (), Huanqin Feng, Xiaoyuan Zhang and Ziqiang Luo
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Jiading Bao: Faculty of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, China
Zishan Lin: Faculty of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, China
Hui Jing: Faculty of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, China
Huanqin Feng: Faculty of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, China
Xiaoyuan Zhang: Faculty of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, China
Ziqiang Luo: Faculty of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 541004, China

Sustainability, 2024, vol. 16, issue 19, 1-14

Abstract: In a V2V communication environment, the control of electric vehicle platoons faces issues such as random communication delays, packet loss, and external disturbances, which affect sustainable transportation systems. In order to solve these problems and promote the development of sustainable transportation, a longitudinal control algorithm for the platoon based on robust Unscented Kalman Filter (UKF) and Model Predictive Control (MPC) is designed. First, a longitudinal kinematic model of the vehicle platoon is constructed, and discrete state–space equations are established. The robust UKF algorithm is derived by enhancing the UKF algorithm with Huber-M estimation. This enhanced algorithm is then used to estimate the state information of the leading vehicle. Based on the vehicle state information obtained from the robust UKF estimation, feedback correction and compensation are added to the MPC algorithm to design the robust UKF–MPC longitudinal controller. Finally, the effectiveness of the proposed controller is verified through CarSim/Simulink joint simulation. The simulation results show that in the presence of communication delay and data loss, the robust UKF–MPC controller outperforms the MPC and UKF–MPC controllers in terms of MSE and IAE metrics for vehicle spacing error and acceleration tracking error and exhibits stronger robustness and stability.

Keywords: electric vehicle; sustainable transportation; platoon longitudinal control; model predictive control; unscented Kalman filter (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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