volume | PIER Journals

Abstract

To enable accurate online observation of permanent-magnet (PM) flux linkage in permanent-magnet synchronous motors (PMSMs), this paper proposes an improved adaptive higher-order square-root cubature kalman filter (IAHSRCKF) flux-linkage observer. Firstly, a nonlinear PMSM model is established to capture complex operating conditions. Secondly, fifth-order cubature integration and an adaptive estimator are embedded into a square-root cubature Kalman framework, yielding an adaptive fifth-order SRCKF observer that tracks PM flux-linkage variations under parameter drift and disturbances. Then, experimental scenarios are created by perturbing key electromagnetic and mechanical parameters and injecting external time-varying disturbances. Finally, simulation and hardware tests benchmark the proposed IAHSRCKF against UKF, CKF, and SRCKF. Results demonstrate that IAHSRCKF achieves the highest flux-estimation accuracy, exhibits low sensitivity to parameter uncertainties, and maintains strong robustness across complex operating conditions, thereby enabling reliable online monitoring of PM flux linkage.

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Professor Junqin Liu

Dr. Zhentong Wang

Dr. Tianle Li

Dr. Feng Deng

Dr. Lin Liu

Professor Kaihui Zhao

Dr. Xiangfei Li