基于灰色预测模型的无刷直流电机控制与故障诊断

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中图分类号：TP273 文献标识码：A DOI： 10.7535/hbgykj.2025yx06010

Control and fault diagnosis of brushless DC motor based on grey prediction model

WAN Jun，WANG Qiuyong，GUO Lulu，GAO Shuyuan （School of Mechanical Enginering and Rail Transit，Changzhou University，Changzhou，Jiangsu ，China）

Abstract：To enhance the robustness of the sped controlsystem for brushlessDC motors （BLDC）and mitigate the adverse efects induced by inverter transistoropen-circuit faults，acontroland fault diagnosis strategy basedon thediscrete grey predition model（DGM（1，1））was proposed.Initially，therotational spedand three-phase currnt values of the BLDC motor were predictedusing DGM（1，1）.Subsequently，thepredictedandactual speed values were fed back into the proportional integral（PI） speed control loop to continuously adjust the proportional coefficient KP and integral coefficient Ki ， therebyachieving precise sped regulation.Furthermore，open-circuitfaultdetectionandlocalizationof invertertransistors were performed bycomparing the expected threephase current values derived from the dq-axis transformation with the predicted current values obtained via DGM（1，1）.Finall，asimulationmodel wasconstructedonthe MATLAB platform for experimentalvalidation.Theresults demonstrate thatDGM（1，1）achievesefective speedregulationcontrolforthe BLDC motor，witha stabilizationtimeofO.O02 sfrom theonsetof reaching therated spee.Aditionally，the strategy exhibits a rapid fault response time of 0.036s upon fault occurrence，indicating superior fault diagnosis performance. The proposed strategy significantly improves the responsivenessandstabilityof BLDC speedcontrol，whileenabling fastandaccurate diagnosis of inverter transistor open-circuit faults.

Keywords： brushless DC motor； discrete grey prediction model;adaptive PI； fault diagnosis

无刷直流电机（brushlessDCmotor，BLDC）具有结构简单、维护方便、调速性能好、运行效率高等众多优点，广泛用于农业、工业、航空航天等领域[1-4]。（剩余13282字）