Compensation Method for Current Measurement Errors in the Synchronous Reference Frame of a Small-Sized Surface Vehicle Propulsion Motor

This paper proposes a new method for compensating current measurement errors in shipboard permanent magnet propulsion motors. The method utilizes cascade decoupling second-order generalized integrators (SOGIs) and adaptive linear neurons (ADALINEs) as the current harmonic extractor and the compensator, respectively. It can compensate for the dq-axes offset and scaling errors simultaneously, improving phase current distortion while reducing the ripples of motor speed and torque. Compared to the traditional motor model-based compensation strategies, the proposed method is robust against the changes in motor parameters with the online adaptive capability of the ADALINE algorithm. Furthermore, due to the good real-time performance of SOGIs and ADALINEs, the proposed compensation strategy can effectively operate in both the steady state and transient state of the motor. Finally, the effectiveness of the proposed method is verified through the physical and hardware-in-the-loop (HIL) experiments. After compensating for the current measurement errors of a 1 kW test motor with the propeller-characteristics load, the torque ripple and speed ripple are reduced by more than 65% and 80%, respectively. At the same time, the DC component and the second-order and third-order harmonics in the phase currents are also significantly reduced. Similar test results can be also obtained on the HIL platform with a 100 kW permanent magnet motor.