基于SABO算法的PMSM弱磁和MTPA控制方法

PMSM Weak Magnetic and MTPA Control Method Based on SABO Algorithm

永磁同步电机因其结构紧凑、噪声较少、功耗较少、运行速度快、操作稳定,已被普遍采用。针对永磁同步电机弱磁控制过程中,转速环参数选取采用传统PI(proportional-integral)控制方法,依靠经验整定参数,外界抗干扰能力较差、难以保证在各运行区间具有优良性能等问题,提出了一种基于减法平均优化算法的永磁同步电机的弱磁和MTPA(maximum torque per ampere)控制的宽运行范围方法。将智能寻优算法、MTPA控制、弱磁控制三者相结合,利用减法平均优化算法优化PI控制器的参数,提高了系统的响应性能和抗干扰能力;工作电压未超过电压极限圆使用MTPA控制策略运行;工作电压超过电压极限圆利用电压闭环反馈,进行弱磁控制。使用MATLAB/Simulink构建的永磁同步电机弱磁控制仿真模拟,通过PI控制器和减法平均优化算法优化后的PI控制器性能对比,从仿真结果得到控制器方法的有效性。实验有效证明了该控制方法能够解决各种运行工况下控制器参数的优化整定问题,提高电机控制精度。

Permanent magnet synchronous motor has been commonly adopted because of its compact structure,less noise,less power consumption,fast running speed and stable operation.Aiming at the weak magnetic control process of permanent magnet synchronous motor,the selection of speed ring parameters adopts the traditional PI(proportional-integral)control method,relying on the experience of parameter adjustment,the external anti-interference ability is poor,and it is difficult to ensure the excellent performance in each operation interval,etc.,a method of weak magnetic and MTPA(maximum torque per ampere)control of permanent magnet synchronous motor based on subtractive averaging optimization algorithm was proposed to provide a wide operation range method.Combining the intelligent optimization algorithm,MTPA control and weak magnetism control,the parameters of the PI(proportional-Integral)controller were optimized using the subtractive averaging optimization algorithm,which improves the system s response performance and anti-jamming ability.The operating voltage does not exceed the voltage limit circle using the MTPA control strategy.The operating voltage exceeds the voltage limit circle using the closed-loop feedback of the voltage,and the weak magnetism control was carried out.Using MATLAB/Simulink constructed permanent magnet synchronous motor weak magnetism control simulation simulation,through the PI controller and subtractive averaging optimization algorithm optimized PI controller performance comparison,from the simulation results to get the effectiveness of the controller method.The experiment effectively proves that the control method can solve the problem of optimized tuning of controller parameters under various operating conditions and improve the motor control accuracy.