For compound braking systems integrating electro-mechanical brakes (EMBs) and regenerative braking, conventional torque optimization strategies may not fully account for the stage-dependent dynamic characteristics of EMBs during braking. This limitation can lead to suboptimal synchronization between torque allocation and EMB operational dynamics, leading to compromised braking stability and reduced energy recovery efficiency. To address these considerations, this study proposes an optimized torque allocation control framework for distributed-drive electric vehicles (EVs) equipped with EMBs. The framework consists of two core stages, aiming to balance braking performance and energy recovery efficiency. In the primary stage, an interval type-2 fuzzy controller is employed. By adjusting the uncertainty intervals between upper and lower boundaries. This enhancement enables effective adaptation to parameter disturbances under various operating conditions, while improving braking energy recovery efficiency. In the secondary stage, the four-stage torque output characteristics of EMBs are incorporated to dynamically correct the residual braking torque of regenerative braking system in real time. This correction compensates for deviations between the actual EMB braking torque and the target braking torque, ensuring braking stability while maintaining high energy recuperation rates. Simulation results show that under low-velocity/low-intensity and high-velocity/high-intensity braking scenarios, the root mean square error of longitudinal acceleration is reduced by 68.5% and 61.4%, respectively, compared with the strategy without torque optimization. Additionally, under the urban dynamometer driving schedule (UDDS) and worldwide harmonized light vehicle test cycle (WLTC), the average energy recuperation rate is improved by 39.2% and 46.8%, respectively.
Wáng et al. (Fri,) studied this question.
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