针对纯电汽车制动能量回收的控制问题，提出一种电机制动力控制策略。该策略合理分配前轴机械制动力与电机制动力，通过自适应模糊神经网络(ANFIS)控制器实现前轴电机制动力比例的动态优化，并引入剪枝算法以降低计算复杂度，从而兼顾制动稳定性与能量回收效率。通过联合仿真验证控制算法，结果表明：该策略在不同制动强度下稳定性保持很好；在NEDC工况下，对比ANFIS控制策略和AVL Cruise控制策略，改进ANFIS控制策略下电池SOC要高出0.46%和1.81%，同时电机扭矩波动得到有效抑制。硬件在环（HiL）测试结果表明，改进ANFIS控制策略在有效性和实时性方面表现优异。

For the problem of braking energy recovery control in pure electric vehicles, a motor drive force control strategy was proposed. This strategy reasonably distributed the mechanical braking force of front axle and the electric braking force, which realized the dynamic optimization for the proportion of electric braking force on the front axle through the ANFIS controller and balanced the braking stability and energy recovery efficiency by introducing the pruning algorithm to reduce the computational complexity. The control algorithm was verified through joint simulation. The results show that the strategy maintains good stability under different braking intensities. Under the NEDC driving condition, the strategy achieves a SOC increase by 0.46% compared with the ANFIS control strategy and 1.81% compared with the AVL Cruise control. Meanwhile, the motor torque fluctuation is effectively suppressed. Hardware-in-the-loop (HIL) testing results demonstrate that the improved ANFIS control strategy performs excellently in terms of effectiveness and real-time performance.