Predictive Motion Control Considering Body Attitude Constraints for Four in-Wheel Motor Vehicles

In-wheel motor distributed-drive electric vehicles have the unique characteristic of being able to control the torque of each wheel independently and accurately. However, when connected to a suspension system with anti-pitch geometry, the resulting output torque of the in-wheel motor can cause significant vertical forces, leading to body attitude oscillations during driving or braking. To address this issue, this study proposes an innovative predictive motion controller that combines learning model predictive control (MPC) and body attitude control. This controller determines the total driving torque, desired roll moment, pitch moment, and vertical force, taking into consideration the constraints of body attitude, and a transfer matrix is then utilized to calculate the required torque for each wheel. The effectiveness of the proposed controller is validated through a Simulink/Modelon co-simulation test. The results demonstrate the significant superiority of the proposed predictive motion controller over the default controller. Specifically, it enhances speed and trajectory tracking accuracy by 2.3% and 34.2%, respectively, when compared with the nonlinear MPC controller.

Authors

Institutions

Publication Details

Journal
Unmanned Systems
Published
2024-12-27
DOI
https://doi.org/10.1142/s2301385025430034
Primary Topic
Vehicle Dynamics and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive Motion Control Considering Body Attitude Constraints for Four in-Wheel Motor Vehicles

Hongqing Chu, Bingzhao Gao, Zongxuan Li, Hong Chen et al.
Unmanned Systems
Vehicle Dynamics and Control Systems
article

Predictive Motion Control Considering Body Attitude Constraints for Four in-Wheel Motor Vehicles

Hongqing Chu, Bingzhao Gao, Zongxuan Li, Hong Chen, Xiaoyan Liu, Qiao Kang
article en

Abstract

In-wheel motor distributed-drive electric vehicles have the unique characteristic of being able to control the torque of each wheel independently and accurately. However, when connected to a suspension system with anti-pitch geometry, the resulting output torque of the in-wheel motor can cause significant vertical forces, leading to body attitude oscillations during driving or braking. To address this issue, this study proposes an innovative predictive motion controller that combines learning model predictive control (MPC) and body attitude control. This controller determines the total driving torque, desired roll moment, pitch moment, and vertical force, taking into consideration the constraints of body attitude, and a transfer matrix is then utilized to calculate the required torque for each wheel. The effectiveness of the proposed controller is validated through a Simulink/Modelon co-simulation test. The results demonstrate the significant superiority of the proposed predictive motion controller over the default controller. Specifically, it enhances speed and trajectory tracking accuracy by 2.3% and 34.2%, respectively, when compared with the nonlinear MPC controller.

Unmanned SystemsVol. 13(06)
Tongji University (CN), Dongfeng Motor (China) (CN)
Openalex Percentile: Top 73%
Vehicle Dynamics and Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.