在矿山作业环境中，运输电车于高载荷条件下存在电能供给不足及电力消耗过度的问题。针对这一挑战，提出了一种基于转矩分配的四轮独立驱动矿山运输电车电控优化系统。利用直流无刷电动机三相绕组结构特性，构建了四轮独立驱动矿山运输电车模型，并明确了相应的目标函数以指导优化过程。采用粒子群优化算法对该模型进行智能化求解，以获得最优的转矩分配方案。仿真试验结果显示，转矩分配控制策略使电车在速度达到 50 km/h 时的制动时间缩短至8.4 s，完全满足矿山矿石运输作业的实际需求。在粒子群算法的控制下，电车电池用电量维持在30.2 %～30.6 %，相较于模拟退火算法控制下的电池状态，展现出了更高的稳定性。研究结果证明，转矩分配方法对于四轮独立驱动矿山运输电车的适用性不仅满足了运输作业中的制动性能要求，还确保了车辆运行的安全性。  

In mining operations, electric transport vehicles often face issues of insufficient power supply and excessive energy consumption under high-load conditions. To address this challenge, a control optimization system based on torque distribution for independently driven four-wheel electric mine transport vehiclesis proposed. Utilizing the structural characteristics of three-phase windings in brushless DC motors, a model of the independently driven four-wheel electricmine transport vehicles was constructed, and the corresponding objective function was defined to guide the optimization process. A particle swarm optimization (PSO) algorithm was employed to intelligently solve the mathematical model and obtain the optimal torque distribution scheme. Simulation results show that the torque distribution control strategyshortens the braking time to 8.4 s at a speed of 50 km/h, fully meeting the practical demands of ore transport in mines. Under PSO control, the state of charge of the vehicle battery was maintained within 30.2 %-30.6 %, demonstrating higher stability compared to control with the simulated annealing algorithm. The results verify that the proposed torque distri-bution method is suitable for independently driven four-wheel electric mine transport vehicles, as it not only satisfies the braking performance requirements but also ensures safe vehicle operation.