基于模型预测策略的永磁同步电机最大转矩电流比控制优化
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Optimization of Permanent Magnet Synchronous Motor MTPA Control Cased on Model Prediction Strategy
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    摘要:

    针对当前采用最大转矩电流比控制策略的永磁同步电机双闭环矢量控制系统中,因外在负载或电机转矩突变,造成电流调节器因积分饱和而导致电机实际定子交-直轴电流无法快速跟踪给定的MTPA电流问题。提出一种基于模型预测控制原理的两矢量模型预测控制策略,来取代传统双闭环电机控制系统中的电流内环调节器。在分析永磁同步电机MTPA控制原理、电流内环调节器饱和原因的基础上,利用模型预测控制的非线性约束处理能力在每个采样周期内通过两电压矢量模型预测控制策略,获得更加准确的电压矢量。实现系统实时动态跟踪永磁同步电机MTPA轨迹的目标。仿真和实验结果表明,该控制策略在电机给定转矩或外在负载转矩突变情况下可实时跟踪MTPA给定电流的变化,电机定子电流未出现较大波动。

    Abstract:

    In the current permanent magnet synchronous motor (PMSM) double closed loop vector control system which adopts the maximum torque current ratio control strategy, due to the external load of the motor or the sudden change of the motor torque, the current regulator is saturated with integral points, which leads to the problem that the actual stator ac-dc current of the motor cannot track the given MTPA current quickly. A two-vector model predictive control strategy based on model predictive control principle is proposed to replace the current loop regulator in traditional double closed loop motor control system. Based on the analysis of the control principle of permanent magnet synchronous motor MTPA and the causes for the saturation of current inner ring regulator, by use of the nonlinear constraint handling capacity of model predictive control, more accurate voltage vector can be obtained in each sampling cycle through two voltage vector model predictive control strategy, so as to realize the real-time dynamic tracking of the target of permanent magnet synchronous motor MTPA trajectory. The simulation and experimental results show that this control strategy can track the change of the given MTPA current in real time when the motor torque is given or the external load torque suddenly changes, and the current of motor stator shows no major fluctuation.

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吕常智,马西贺,张亚童. 基于模型预测策略的永磁同步电机最大转矩电流比控制优化[J]. 科学技术与工程, 2020, 20(8): 3062-3067.
Lü Changzhi, Ma Xihe, Zhang Yatong. Optimization of Permanent Magnet Synchronous Motor MTPA Control Cased on Model Prediction Strategy[J]. Science Technology and Engineering,2020,20(8):3062-3067.

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历史
  • 收稿日期:2019-06-19
  • 最后修改日期:2019-12-02
  • 录用日期:2019-10-09
  • 在线发布日期: 2020-04-29
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