Wenjuan Zhang

Cogging torque, an inherent pulsating torque in permanent magnet machines, can induce position and speed fluctuations during startup, potentially leading to inaccuracies in position estimation for sensorless control. Improving estimation precision and minimizing speed fluctuations during startup necessitate the mitigation of cogging torque in sensorless control. To address this challenge, this article proposes a new signal injection strategy. The key of the proposed method is to inject a high-frequency signal into the d-axis for accurate position estimation, and a low-frequency signal into the q-axis to counteract the cogging torque. Through experimental validation, the proposed method has exhibited significant improvements in position estimation accuracy and promoted smoother torque characteristics.

The encoderless deadbeat predictive current control (DBPCC) has been widely applied in surface-mounted permanent magnet synchronous motor (SPMSM). However, the DBPCC suffers from poor performance against motor parameters mismatches. An improved encoderless DBPCC method with online parameter identification is proposed to enhance the parameter robustness in this article. Firstly, a modified rotor position estimator is directly designed in the discrete-time domain. No observer is required to estimate back electromotive force (EMF). Hence, the proposed EMF estimator features simple structure and easy implementation. Then, the parameter sensitivity of the encoderless DBPCC method is analyzed. A simple demodulation method is proposed to identify motor parameters based on the injected high frequency current signals in the d -axis. The proposed online parameter identification algorithm would not introduce the extra torque harmonics in SPMSM. Meanwhile, theoretical analysis shows that the proposed parameter identification method presents high precision even with the severe initial motor parameters mismatches. Therefore, the mismatched parameters used in the encoderless DBPCC method can be replaced by the identified motor parameters to precisely correct the rotor position estimation errors. Finally, the experiments were tested in a two-level inverter-fed SPMSM drives to validate the effectiveness of the proposed encoderless DBPCC algorithm with online parameter identification.

Interior permanent magnet synchronous machines (IPMSMs) are extensively used in electric drives due to their high-power density and wide-speed operation capability. In order to improve the performance of the drive application, low torque ripple of the IPMSM is valuable and necessary. However, as far as the existing analytical models are concerned, it is difficult to establish a direct relationship between the structural parameters and the torque ripple law of IPMSMs due to the complexity of their flux circuits, and therefore, it is not easy to achieve a directional suppression of the torque ripple by means of design. With this in mind, this article establishes a general analytical model for electromagnetic torque and its ripples (including synchronous torque, reluctance torque, and cogging torque) based on the harmonic interaction effects. Thereby, a novel and simple design method to reduce torque ripple is proposed, and its principle is to change the rotor surface shape to artificially construct the specific number of reluctance harmonics. As a result, it is verified by finite element method and experiments that the proposed method can precisely eliminate the specific torque ripple and reduce the overall torque ripple.

An improved high-frequency pulsed sinusoidal voltage signal injection (HFPS-VSI) sensorless control strategy applied to interior permanent magnet synchronous motor (IPMSM) is proposed in this paper. In the high-frequency (HF) current signal demodulation process, this paper proposes a demodulation approach that can demodulate a four times injection frequency component. Hence, a low-pass filter (LPF) with higher cut-off frequency can be selected to suppress the HF component. The proposed demodulation method can improve the bandwidth of the position estimation loop and increase the signal-to-noise ratio (SNR) of position angle errors fed to the rotor position observer. To enhance the current loop bandwidth, this paper utilizes the current observer (CO) to extract the fundamental current. Theoretical analysis shows that the proposed fundamental current extraction method has no amplitude attenuation and time delay, and is robust against motor parameter mismatches at the fundamental frequency. Therefore, it can eliminate the LPF used in the fundamental current extraction to improve the dynamic response of the current loop. Meanwhile, a design method of CO is proposed, which makes CO keep a constant and high bandwidth in the low-speed region, suited for low-speed sensorless operation. Finally, the effectiveness of the improved HFPS-VSI algorithm is verified by experimental tests.

The maximum torque per ampere (MTPA) control is significant for improving the efficiency of the interior permanent magnet synchronous motor (IPMSM). However, for the high saturation IPMSM, the change of the permanent magnet (PM) flux linkage is more complicated, which can cause the MTPA control to deviate from the optimal solution. Therefore, an improved MTPA control method for the high saturation IPMSM is proposed in this paper. Compared with other methods, the proposed method improves the conventional models of flux linkage and torque by analyzing the nonlinear variation of the PM flux linkage with the dq-axis currents. Subsequently, an expression suitable for the MTPA control of high saturated IPMSM is derived based on the improved models. The proposed parameter fitting models are then fitted using data from 11 operating points and incorporated into the MTPA optimization algorithm to obtain the MTPA curve. Finally, the effectiveness of the proposed method in enhancing the control accuracy of the MTPA angle is verified through simulations and experiments.

Efficiency optimization is an important goal in the design of permanent magnet generators. However, traditional design optimization methods only focus on improving the rated efficiency without considering the annual cycle for overall efficiency improvement. To overcome this drawback, this paper presents a design optimization method for improving annual energy production (AEP) of wind direct-drive permanent magnet generators. Unlike the conventional efficiency optimization method that only improves the rated point efficiency, the proposed method improves the overall efficiency of the generator during the operating cycle by matching the maximum power point trajectory of the wind turbine. The periodic loss model of the permanent magnet generator is established and further constituted as the objective function to perform the optimization search using a genetic algorithm. Through simulation and experimental verification, the proposed method can obtain a higher AEP compared with the conventional design optimization method, and the proposed method can be extended to other variable speed power generation fields.

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).

Zhang, W. and Zhang, Z., 2020. Deck electrical system support technology of port tanker. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 392–396. Coconut Creek (Florida), ISSN 0749-0208.Port tanker is an important part of the development of port industry. The guarantee of deck electrical system of tanker is an important prerequisite to ensure the normal operation of tanker. When the traditional electrical system support technology detects the electrical system in the process of support, there is a high data packet loss rate, and the service life of the electrical system of the tanker after the application of the traditional support technology is short. In view of the above problems, the deck electrical system support technology of the port tanker will be studied. Firstly, the evaluation system of electrical system safety early warning index is established, and the operation state detection information of electrical system is counted. According to the detection information, combined with the electrical system safety early warning index system, the electrical system abnormal state part of the fault detection. According to the test results, the maintenance and repair of deck electrical system and the research on the support technology of deck electrical system of port tanker are completed. The experimental results show that the study of the electrical system support technology in the use process, has a lower packet loss rate, and the application of research support technology after the electrical system service life is longer.

This paper presents a novel multi-interval efficiency optimization strategy to improve the overall driving-cycle efficiency of permanent magnet synchronous generators for hybrid electric special vehicles. At first, the driving cycle rule of the hybrid electric special vehicles is investigated by mathematical statistics to fit the actual driving conditions. In addition, the multi-interval efficiency analytical model of permanent magnet generator is established for the most significant operating power intervals i.e. 0-25%, 25%-50%, 50%-75%, and 75%-100%. Then, the driving-cycle efficiency is iteratively involved in the improved genetic algorithm program to obtain the optimized solution, which is also compared with the solution by traditional rated efficiency optimization method to demonstrate the advantages of the proposed optimization method. At last, the proposed optimal design is validated on a laboratory prototype of a 500-kW generation system under different load conditions.