Zhimeng Rao

In traditional one-dimensional signal-based fault diagnosis methods, there are difficulties in signal feature extraction and complexities in adjusting model hyperparameters. Therefore, a demagnetization fault diagnosis method for permanent magnet synchronous motor (PMSM) using custom phase space reconstruction (CPSR) image is proposed, which can be generalized to condition recognition. First, a CPSR method is proposed to reconstruct the magnetic leakage signal into a two-dimensional data image. Second, to overcome the problem of poor diagnosability of high-dimensional shallow features in existing local feature extraction methods, an image feature coding method is proposed, which can improve diagnostic performance through deep feature extraction and coding. Third, the improved autonomous learning multi-model constructs different fault data clouds with coded information, and realizes fault diagnosis according to the fuzzy rules of data cloud. Four kinds of demagnetized fault motors were manufactured for experimental verification. The extensive experimental results demonstrate that the proposed method is effective.

In this study, a robust predictive power control (R-PPC) method for an N*3-phase permanent magnet synchronous motor (PMSM) is developed in the field of flywheel energy storage systems application, which can effectively improve robustness against inductance parameter mismatch and compensate for the one-beat delay. Firstly, the mathematical model of the N*3-phase PMSM is illustrated, and the topological structure of the N*3-phase PMSM is established. The R-PPC method of the N*3-phase PMSM is then proposed by using the d–q axis current robust predictive control theory. Robustness factors are adopted to modify the current response values in the proposed robust predictive power controller, which can obtain excellent current control performance under the inductance parameter mismatch. Moreover, the next current predicted value is used to replace the current sampled value in the proposed R-PPC method to eliminate the one-beat delay. Finally, comparative simulation and experimental results verify that the proposed R-PPC method can achieve excellent current track performance and smaller torque ripple under both the charge state and discharge state.

In this study, a novel modular three-phase permanent magnet synchronous motor (PMSM) is proposed for low-voltage high power applications. The proposed modular three-phase PMSM has an independent segregated three-phase winding configuration, facilitating the implementation of the control algorithm. Firstly, on the basis of the electromagnetic properties, the mathematical model of the modular three-phase PMSM is established, considering the asymmetrical mutual inductances investigated by finite element analysis (FEA). Then, the predictive torque control (PTC) method combining the inductance characteristics of modular three-phase PMSM is developed, and excellent performance is obtained by adjusting the stator flux and torque. Finally, simulation and experiment are performed, and the results show that the proposed novel modular three-phase PMSM with the PTC method exhibits excellent control performance, and small stator current total harmonic distortion (THD).

High power density energy storage permanent magnet (PM) motor is an important energy storage module in flywheel energy storage system for urban rail transit. To expand the application of the PM motor in the field of urban rail transit, a predictive power control (PPC) strategy for the N*3-phase PM energy storage motor is proposed in this paper. Firstly, the output characteristics of the N*3-phase PM energy storage motor are analyzed by using the finite element method, and the mathematical model of the N*3-phase PM energy storage motor is established. Then, the topological structure and operation principle of N*3-phase PM energy storage motor system is illustrated. Furthermore, the N*3-phase PM energy storage motor system driven by six parallel voltage source inverters (VSIs) is proposed to generate the required power. Finally, a novel predictive direct power control method is developed for the N*3-phase PM energy storage motor. The feasibility and effectively of the proposed PPC method are verified by experiment and simulation. Comprehensive simulation and experimental results both show that the proposed PPC method can obtain the lower torque/stator flux ripple, smaller values of THD of stator winding currents, and zero error tracking of stator winding flux.

The permanent magnet synchronous generator (PMSG) is widely used in high voltage DC transmission technology of wind power systems due to its high-power density, high reliability and simple maintenance. To meet the increasing rated power of the generator (≥10 MW), the multi-converter parallel connection is usually used, which significantly increases the complexity and cost of the system. Therefore, a new modular N* three-phase PMSG is proposed in this paper. Based on the structure and working principle of the generator, the finite element model is established, and the electromagnetic properties are obtained by finite element analysis. Aiming at the unique winding structure and characteristics of modular N* three-phase PMSG, a generator side current converter harmonic control algorithm, combining a resonant controller with the proportional-integral regulator, is proposed. The suppression of stator current harmonics at different speeds could be achieved by the proposed algorithm, and the efficiency of the wind power generation system can be improved. Finally, the feasibility of the novel generator and the effectiveness of the proposed algorithm are verified by simulation and experiment.