نبذة مختصرة : Abstract Given the issues of low accuracy and slow calculation speed in traditional PMSM current segmented control methods, this study proposes an improved model predictive current control method based on duty cycle modulation. This method designs a current segmented control model by dynamically optimizing duty cycle allocation, introducing parameter adaptive adjustment mechanism, and combining second-order error differential observer and harmonic compensation. Matlab/Simulink simulation shows that the torque-ripple value of the improved algorithm is 4.2%, which is significantly lower than that of the traditional model predictive current control method based on duty cycle modulation and the variable vector model predictive control method. The system efficiency was 96.3%, significantly higher than the other two methods, proving that this method can effectively reduce the energy loss of the system. At different speeds, the step response of the improved algorithm was 0.28 ms, 0.52 ms, 0.45 ms, and the tracking error was 0.08 A, 0.12 A, 0.15 A, which was lower than the comparison method, indicating that its response to current changes was faster. The improved algorithm had a steady-state error of 0.24 A and a harmonic distortion rate of 4.6% when the stator resistance changed, both of which were superior to other methods, proving that it could ensure the steady-state performance of the system. The proposed model predictive current control method based on duty cycle modulation effectively improves the control accuracy, energy efficiency, and real-time performance of PMSM systems under high dynamics, parameter changes, and complex disturbances. It provides technical support for the application of permanent magnet synchronous motors in extreme environments and complex working conditions, and has important engineering value for promoting energy efficiency upgrades in industrial transmission systems.
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