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An online fault detection and isolation (FDI) method for several common sensor faults and even demagnetization of PMSM is proposed by combining model-based and signal analysis technology. To begin with, the field reconstruction method (FRM) of PMSM is employed to obtain the flux residuals which are used as the criterion of fault detection. Then, the flux residuals are transformed by multi sequence harmonic synchronous rotating transformation and inputted into low pass filters (LPFs) in order to obtain the DC components. Last, offset and gain faults of the two phase current sensors, offset fault of the rotor angle sensor and permanent magnet (PM) demagnetization can be isolated by comparing the DC components and preset thresholds. The detection and isolation strategy of PMSM is validated by motor controller hardware in motor bench tests.

Description of PMSM torque in high accuracy is critical and previous work for its further research. However, the traditional linear torque model fails to describe its non-ideal characteristics of practical working. This paper presents a generalized torque model of PMSM based on flux linkage reconstruction. In synchronous rotating space coordinates, flux linkage were reconstructed through Fourier series expansion and bivariate polynomial. Based on this model, a precise PMSM torque ripple description and corresponding suppression method were developed. Current feed-forward compensation and the rotor field oriented control were applied in torque ripple suppression. Simulation and experimental results both show that the model not only accurately describes the nonlinear variation of PMSM torque in different working conditions, but also can be used to suppress PMSM torque ripple effectively.