RBS and ABS Coordinated Control Strategy Based on Explicit Model Predictive Control

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 10; p. 3076
• Main Authors: Chu, Liang, Li, Jinwei, Guo, Zhiqi, Jiang, Zewei, Li, Shibo, Du, Weiming, Wang, Yilin, Guo, Chong
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 12.05.2024
• Subjects: Adaptability; Analysis; Automobiles, Electric; Braking systems; Controllers; coordinated control strategy (CCS); Electric vehicles; electro-hydraulic composite braking system; error compensator; explicit model predictive control (eMPC); four-wheel hub drive electric vehicle; Hydraulics; Industrial equipment; Laws, regulations and rules; Methods; Optimization; Variables; coordinated control strategy (CCS); four-wheel hub drive electric vehicle; error compensator; electro-hydraulic composite braking system; explicit model predictive control (eMPC)
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24103076

During the braking process of electric vehicles, both the regenerative braking system (RBS) and anti-lock braking system (ABS) modulate the hydraulic braking force, leading to control conflict that impacts the effectiveness and real-time capability of coordinated control. Aiming to enhance the coordinated control effectiveness of RBS and ABS within the electro-hydraulic composite braking system, this paper proposes a coordinated control strategy based on explicit model predictive control (eMPC-CCS). Initially, a comprehensive braking control framework is established, combining offline adaptive control law generation, online optimized control law application, and state compensation to effectively coordinate braking force through the electro-hydraulic system. During offline processing, eMPC generates a real-time-oriented state feedback control law based on real-world micro trip segments, improving the adaptiveness of the braking strategy across different driving conditions. In the online implementation, the developed three-dimensional eMPC control laws, corresponding to current driving conditions, are invoked, thereby enhancing the potential for real-time braking strategy implementation. Moreover, the state error compensator is integrated into eMPC-CCS, yielding a state gain matrix that optimizes the vehicle braking status and ensures robustness across diverse braking conditions. Lastly, simulation evaluation and hardware-in-the-loop (HIL) testing manifest that the proposed eMPC-CCS effectively coordinates the regenerative and hydraulic braking systems, outperforming other CCSs in terms of braking energy recovery and real-time capability.