Hierarchical MPC for Velocity Tracking in Four in-Wheel Motor Actuated Vehicles

This paper proposes a hierarchical model predictive control (MPC) strategy for four in-wheel motor actuated electric vehicles (4-IWM EVs). Current studies on 4-IWM EVs mainly focus on a single objective. We propose a novel vehicle modeling method and a hierarchical MPC to address comprehensive problems of 4-IWM EVs in improving the vehicle’s efficiency and comfort while achieving accurate velocity tracking. The upper MPC aims to accurately track the desired velocity trajectory and the lower torque distribution controller aims to allocate the torque of each in-wheel motors to improve driving efficiency and comfort. The simulation results indicate that our method significantly enhances the tracking accuracy while improving driving efficiency and ride comfort compared to the widely used benchmark controller.

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Publication Details

Journal
Unmanned Systems
Published
2024-12-31
DOI
https://doi.org/10.1142/s2301385025430046
Primary Topic
Control Systems in Engineering
Type
article
Field-Weighted Citation Impact
0.00
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article

Hierarchical MPC for Velocity Tracking in Four in-Wheel Motor Actuated Vehicles

Zhiwei Hou, Keyou You, Tianxun Li, Xingchen Li
Unmanned Systems
Control Systems in Engineering
article

Hierarchical MPC for Velocity Tracking in Four in-Wheel Motor Actuated Vehicles

Zhiwei Hou, Keyou You, Tianxun Li, Xingchen Li
article en

Abstract

This paper proposes a hierarchical model predictive control (MPC) strategy for four in-wheel motor actuated electric vehicles (4-IWM EVs). Current studies on 4-IWM EVs mainly focus on a single objective. We propose a novel vehicle modeling method and a hierarchical MPC to address comprehensive problems of 4-IWM EVs in improving the vehicle’s efficiency and comfort while achieving accurate velocity tracking. The upper MPC aims to accurately track the desired velocity trajectory and the lower torque distribution controller aims to allocate the torque of each in-wheel motors to improve driving efficiency and comfort. The simulation results indicate that our method significantly enhances the tracking accuracy while improving driving efficiency and ride comfort compared to the widely used benchmark controller.

Unmanned SystemsVol. 13(06)
Tsinghua University (CN)
Affordable and clean energy
Openalex Percentile: Top 74%
Control Systems in Engineering
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