Chu Liang, Li Jinwei, Guo Zhiqi, Jiang Zewei, Li Shibo, Du Weiming, Wang Yilin, Guo Chong
State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China.
Sensors (Basel). 2024 May 12;24(10):3076. 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.
在电动汽车制动过程中，再生制动系统（RBS）和防抱死制动系统（ABS）都会对液压制动力进行调节，从而导致控制冲突，影响协同控制的有效性和实时性。为提高电动液压复合制动系统中RBS和ABS的协同控制效果，本文提出一种基于显式模型预测控制（eMPC-CCS）的协同控制策略。首先，建立一个综合制动控制框架，结合离线自适应控制律生成、在线优化控制律应用和状态补偿，通过电动液压系统有效协调制动力。在离线处理过程中，eMPC基于实际微观行程段生成面向实时的状态反馈控制律，提高制动策略在不同驾驶条件下的适应性。在在线实现过程中，调用针对当前驾驶条件开发的三维eMPC控制律，从而增强实时制动策略实施的可能性。此外，将状态误差补偿器集成到eMPC-CCS中，得到一个状态增益矩阵，优化车辆制动状态，并确保在各种制动条件下的鲁棒性。最后，仿真评估和硬件在环（HIL）测试表明，所提出的eMPC-CCS有效地协调了再生制动系统和液压制动系统，在制动能量回收和实时性方面优于其他协同控制系统。
