Motion Posture Control of Corner Module Architecture Intelligent Electric Vehicle on Deep-Potholed Roads
To address the passability issues of a corner module architecture intelligent electric vehicle (CAV) on deep-potholed roads during emergency rescue operations, the motion posture control of the CAV is investigated. First, the posture coordinated control flow was designed, and the stability mechanism of the vehicle supported by three wheels is formulated. Second, a model for three-wheel supported vehicle (TWSV) is established, including the transition process between TWSV and four-wheel supported vehicle. Third, a novel corner module was designed, integrating in-wheel motor drive system, wheel-side steer-by-wire system, brake by-wire system, and active suspension system (ASS) into one unit. A coordinated control method based on feedforward and feedback is proposed. The feedforward value is calculated based on the vertical load of the TWSV, and the feedback controller is designed based on Takagi–Sugeno robust sliding mode control. Finally, the correctness of the ASS model with ball screw is verified through experiments. The validity of the new dynamics is confirmed through comparison with CarSim, and the effectiveness of the coordinated control strategy is validated through hardware-in-the-loop testing. This provides a theoretical foundation for the passability control of CAV on deep-potholed roads.
Authors
- Jiantao Wang
- Lipeng Zhang (ORCID: https://orcid.org/0000-0001-5204-8610)
- Junda Zhang (ORCID: https://orcid.org/0000-0001-5763-7123)
- Yifan Liu (ORCID: https://orcid.org/0009-0000-6143-904X)
- Shuaishuai Liu (ORCID: https://orcid.org/0000-0002-3787-5738)
- Chao Yang (ORCID: https://orcid.org/0009-0008-5880-5086)
Institutions
- Yanshan University (CN)
Publication Details
- Journal
- IEEE/ASME Transactions on Mechatronics
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1109/tmech.2024.3377904
- Citations
- 12
- Primary Topic
- Simulation and Modeling Applications
- Type
- article
- Field-Weighted Citation Impact
- 3.94
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Hebei Province