【摘要】 电动汽车驱动电机多采用永磁同步电机，针对永磁同步电机因复杂工况易受负载扰动而导致系统产生超调和震荡的问题，提出了一种自适应PI参数整定方法。首先，基于传统麻雀搜索算法引入Levy飞行策略，以增强算法的全局搜索能力。其次，结合自适应步长机制，提高参数收敛效率。最后，将改进算法应用于矢量控制系统，实现PI参数的实时整定。仿真实验结果表明，改进麻雀搜索算法优化的PI控制器在突加负载工况下超调量低至1.265%，且稳态误差、响应时间、调节时间等评价指标均优于传统PI控制器和传统麻雀搜索算法优化的PI控制器。硬件在环实验进一步验证了算法的有效性，控制系统超调量得到改善，系统鲁棒性得到提升。更多还原

【Abstract】 A self-adaptive PI parameter tuning method is proposed to address the issues of overshoot and oscillation in electric vehicle drive motors,which predominantly use permanent magnet synchronous motors and are susceptible to load disturbances under complex operating conditions. First,building upon the traditional sparrow search algorithm,a Levy flight strategy is introduced to enhance its global search capability. Second,by incorporating an adaptive step size mechanism,the parameter convergence efficiency is improved. Finally,the improved algorithm is applied to the vector control system to achieve real-time tuning of PI parameters. Simulation experimental results show that the improved Sparrow Search algorithm-optimized PI controller achieves an overshoot as low as 1.265% under sudden load conditions,and its evaluation metrics such as steady-state error,response time,and settling time are superior to those of traditional PI controllers and traditional Sparrow Search algorithm-optimized PI controllers. Hardware-in-the-loop experiments further verify the effectiveness of the algorithm,with improved control system overshoot and enhanced system robustness.更多还原