Research on Longitudinal–Vertical Coordinated Recovery Drive Control for Corner-Modular Distributed Drive Vehicles

This article addresses the issue of rapid recovery for corner-modular electric vehicles on low-traction surfaces such as ice, snow, and sand. A drive anti-slip controller based on observing wheel dynamic load variations is proposed, integrating model predictive control (MPC) and sliding mode control (SMC). This approach achieves “synchronized” control between the drive system and active suspension for rapid vehicle recovery. In this study, an extended Kalman filter (EKF)-based observer is developed to monitor the vertical dynamic load between the wheel and the ground. Concurrently, a synchronous phase pre-compensation calculator (SPPC) is designed to address control signal delays. Building upon this, a fusion controller semi-implicit Euler method for model prediction and conditional integration for switching SMC laws (SIMP-CISMC)—which utilizes the SIMP and CISMC—is proposed. This controller enables coordinated control between the drivetrain and the active suspension system, enhancing effective driving force during recovery. The results indicate that the proposed method shows significant advantages in joint simulations with CarSim and Simulink, improving tire longitudinal driving force by 6.99%, 5.09%, and 4.13% compared to traditional SMC, MPC, and sliding mode predictive control (SMPC), respectively.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Transportation Electrification
Published
2025-01-27
DOI
https://doi.org/10.1109/tte.2025.3534568
Citations
6
Primary Topic
Industrial Technology and Control Systems
Type
article
Field-Weighted Citation Impact
7.29

Funders

Controls
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article

Research on Longitudinal–Vertical Coordinated Recovery Drive Control for Corner-Modular Distributed Drive Vehicles

Yongjun Yan, Shifei Tao, Pengyu Xue, J.T. Wang et al.
6 citations
IEEE Transactions on Transportation Electrification
Industrial Technology and Control Systems
7.29
article

Research on Longitudinal–Vertical Coordinated Recovery Drive Control for Corner-Modular Distributed Drive Vehicles

Yongjun Yan, Shifei Tao, Pengyu Xue, J.T. Wang, Weihua Wang, Dawei Pi, Pak Kin Wong, Jing Zhao, Hongliang Wang, Yibo Hu
article en
6 citations

Abstract

This article addresses the issue of rapid recovery for corner-modular electric vehicles on low-traction surfaces such as ice, snow, and sand. A drive anti-slip controller based on observing wheel dynamic load variations is proposed, integrating model predictive control (MPC) and sliding mode control (SMC). This approach achieves “synchronized” control between the drive system and active suspension for rapid vehicle recovery. In this study, an extended Kalman filter (EKF)-based observer is developed to monitor the vertical dynamic load between the wheel and the ground. Concurrently, a synchronous phase pre-compensation calculator (SPPC) is designed to address control signal delays. Building upon this, a fusion controller semi-implicit Euler method for model prediction and conditional integration for switching SMC laws (SIMP-CISMC)—which utilizes the SIMP and CISMC—is proposed. This controller enables coordinated control between the drivetrain and the active suspension system, enhancing effective driving force during recovery. The results indicate that the proposed method shows significant advantages in joint simulations with CarSim and Simulink, improving tire longitudinal driving force by 6.99%, 5.09%, and 4.13% compared to traditional SMC, MPC, and sliding mode predictive control (SMPC), respectively.

IEEE Transactions on Transportation ElectrificationVol. 11(3)
University of Macau (MO), Nanjing University of Science and Technology (CN), Southeast University (BD), Southeast University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 3%
Industrial Technology and Control Systems
7.29
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