Shuai Zhou¹, Dazhi Wang^1,*, Yongliang Ni², Keling Song², Yanming Li²

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2187-2207, 2024, DOI:10.32604/cmc.2024.048859 - 15 May 2024

Abstract In the process of identifying parameters for a permanent magnet synchronous motor, the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration, resulting in low parameter accuracy. This work proposes a fuzzy particle swarm optimization approach based on the transformation function and the filled function. This approach addresses the topic of particle swarm optimization in parameter identification from two perspectives. Firstly, the algorithm uses a transformation function to change the form of the fitness function without changing the position of the extreme point of the fitness… More >

Youming Guo, Qinmu Wu^*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1489-1514, 2023, DOI:10.32604/cmc.2023.042313 - 29 November 2023

Abstract Permanent magnet synchronous motor (PMSM) is widely used in various production processes because of its high efficiency, fast reaction time, and high power density. With the continuous promotion of new energy vehicles, timely detection of PMSM faults can significantly reduce the accident rate of new energy vehicles, further enhance consumers’ trust in their safety, and thus promote their popularity. Existing fault diagnosis methods based on deep learning can only distinguish different PMSM faults and cannot interpret and analyze them. Convolutional neural networks (CNN) show remarkable accuracy in image data analysis. However, due to the “black… More >

S. Dinesh Kumar^1,*, A. Jagadeeshwaran²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2201-2215, 2023, DOI:10.32604/iasc.2023.027467 - 05 January 2023

Abstract Recent advancements in power electronics technology evolves inverter fed electric motors. Speed signals and rotor position are essential for controlling an electric motor accurately. In this paper, the sensorless speed control of surface-mounted permanent magnet synchronous motor (SPMSM) has been attempted. SPMSM wants a digital inverter for its precise working. Hence, this study incorporates fifteen level inverter to the SPMSM. A sliding mode observer (SMO) based sensorless speed control scheme is projected to determine rotor spot and speed of the multilevel inverter (MLI) fed SPMSM. MLI has been operated using a multi carrier pulse width More >

Smarajit Ghosh^*

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2391-2404, 2023, DOI:10.32604/csse.2023.028931 - 21 December 2022

Abstract In the field of fault tolerance estimation, the increasing attention in electrical motors is the fault detection and diagnosis. The tasks performed by these machines are progressively complex and the enhancements are likewise looked for in the field of fault diagnosis. It has now turned out to be essential to diagnose faults at their very inception; as unscheduled machine downtime can upset deadlines and cause heavy financial burden. In this paper, fault diagnosis and speed control of permanent magnet synchronous motor (PMSM) is proposed. Elman Neural Network (ENN) is used to diagnose the fault of… More >

Xiangfei Li, Yang Yin, Yang Zhou, Wenchang Liu, Kaihui Zhao^*

Energy Engineering, Vol.120, No.2, pp. 277-297, 2023, DOI:10.32604/ee.2023.022461 - 29 November 2022

Abstract This paper presents a novel non-singular fast terminal sliding mode control (NFTSMC) based on the deep flux weakening switching point tracking method in order to improve the control performance of permanent interior magnet synchronous motor (IPMSM) drive systems. The mathematical model of flux weakening (FW) control is established, and the deep flux weakening switching point is calculated accurately by analyzing the relationship between the torque curve and voltage decline curve. Next, a second-order NFTSMC is designed for the speed loop controller to ensure that the system converges to the equilibrium state in finite time. Then, More > Graphic Abstract

Shuai Zhou¹, Dazhi Wang^1,*, Mingtian Du², Ye Li¹, Shuo Cao³

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3391-3404, 2023, DOI:10.32604/cmc.2023.033397 - 31 October 2022

Abstract The parameters of permanent magnet synchronous motor (PMSM) affect the performance of vector control servo system. Because of the complexity of nonlinear model of PMSM, it is very difficult to identify the parameters of PMSM. Aiming at the problems of large amount of data calculation, low identification accuracy and poor robustness in the process of multi parameter identification of permanent magnet synchronous motor, this paper proposes a weighted differential evolutionary particle swarm optimization algorithm based on double update strategy. By introducing adaptive judgment factor to control the proportion of weighted difference evolution (WDE) algorithm and… More >

R. Senthil Rama¹, C. R. Edwin Selva Rex², N. Herald Anantha Rufus^3,*, J. Annrose⁴

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2325-2336, 2023, DOI:10.32604/iasc.2023.028930 - 19 July 2022

Abstract Any nonlinear behavior of the system is analyzed by a useful way of Total Harmonic Distortion (THD) technique. Reduced THD achieves lower peak current, higher efficiency and longer equipment life span. Simulated annealing (SA) is applied due to the effectiveness of locating solutions that are close to ideal and to challenge large-scale combinatorial optimization for Permanent Magnet Synchronous Machine (PMSM). The parameters of direct torque controllers (DTC) for the drive are automatically adjusted by the optimization algorithm. Advantages of the PI-Fuzzy-SA algorithm are retained when used together. It also improves the rate of system convergence. More >

Kaihui Zhao^1,2, Wenchang Liu¹, Tonghuan Yin³, Ruirui Zhou⁴, Wangke Dai¹ and Gang Huang^5,*

Energy Engineering, Vol.119, No.2, pp. 767-780, 2022, DOI:10.32604/EE.2021.018617 - 24 January 2022

Abstract This paper presents a novel model-free sliding mode control (MFSMC) method to improve the speed response of permanent magnet synchronous machine (PMSM) drive system. The ultra-local model (ULM) is first derived based on the input and the output of the PMSM. Then, the novel MFSMC method is presented, and the controller is designed based on ULM and MFSMC. A sliding mode observer (SMO) is constructed to estimate the unknown part of the ULM. The estimated unknown part is feedbacked to MFSMC controller to perform compensation for parameter perturbations and external disturbances. Compared with the sliding More >