Sliding mode control method of pump-controlled direct-drive brake-by-wire unit based on radial basis function neural network
Aiming at the requirements of high integration, high precision, and strong robustness of the braking system put forward by the development of distributed braking technology, a pump-controlled direct-drive brake-by-wire unit is proposed. The hydraulic pump is directly driven by the motor to realize the pressure building and regulating of the brake wheel cylinder. Compactness and efficiency of the system is enhanced by direct drive technology. A sliding mode control method based on radial basis function (RBF) neural network is designed. The total disturbances caused by uncertainties such as parameter changes, friction, and external disturbances are included in the dynamic equation. A sliding mode controller based on the second-order reaching law is designed to improve the response speed of the system. The recursive loop of the RBF neural network controller is designed to enhance the dynamic learning ability of the controller network, and then estimate and compensate for the total disturbances. The results show that the pump-controlled direct-drive brake-by-wire unit can quickly build and regulate the pressure. It also provides a new technical solution for distributed braking. The proposed control method can effectively improve the response speed, control accuracy and robustness of the system.
Authors
- Cao Tan (ORCID: https://orcid.org/0000-0002-0863-0010)
- Qingkun Wei (ORCID: https://orcid.org/0009-0006-1691-0553)
- Jiayu Lu (ORCID: https://orcid.org/0000-0002-5490-7797)
- Lixun Chen
- Zhaoyue Sun
Institutions
- Shandong University of Technology (CN)
Publication Details
- Journal
- Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
- Published
- 2025-05-30
- DOI
- https://doi.org/10.1177/09544070251334172
- Primary Topic
- Hydraulic and Pneumatic Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Shandong Province