An On-line Detection Method for Single-Phase Inter-Turn Fault Occurring in High-Speed PMSM

Bao, Liwen; Yao, Gengsheng; Chen, Songtao; Wang, Zhimin; Hu, Xiangping; Huang, Yunkai

doi:10.23919/icems50442.2020.9290898

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…Also, the phase signal residual is utilized to isolate the detected faults. The suggested technique in [69] utilizes the resistance and inductance obtained from online parameter estimation, along with the second harmonic of control voltage, as fault indicators. In the case of the demagnetization fault, flux linkage is usually considered a fault indicator, and it is mainly estimated based on d-axis and q-axis inductances.…”

Section: Fault Detection and Diagnosis Of Electric Motor Drivesmentioning

confidence: 99%

Fault Detection and Diagnosis of the Electric Motor Drive and Battery System of Electric Vehicles

2023

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Fault detection and diagnosis (FDD) is of utmost importance in ensuring the safety and reliability of electric vehicles (EVs). The EV’s power train and energy storage, namely the electric motor drive and battery system, are critical components that are susceptible to different types of faults. Failure to detect and address these faults in a timely manner can lead to EV malfunctions and potentially catastrophic accidents. In the realm of EV applications, Permanent Magnet Synchronous Motors (PMSMs) and lithium-ion battery packs have garnered significant attention. Consequently, fault detection methods for PMSMs and their drives, as well as for lithium-ion battery packs, have become a prominent area of research. An effective FDD approach must possess qualities such as accuracy, speed, sensitivity, and cost-effectiveness. Traditional FDD techniques include model-based and signal-based methods. However, data-driven approaches, including machine learning-based methods, have recently gained traction due to their promising capabilities in fault detection. This paper aims to provide a comprehensive overview of potential faults in EV motor drives and battery systems, while also reviewing the latest state-of-the-art research in EV fault detection. The information presented herein can serve as a valuable reference for future endeavors in this field.

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Section: Fault Detection and Diagnosis Of Electric Motor Drivesmentioning

confidence: 99%

Fault Detection and Diagnosis of the Electric Motor Drive and Battery System of Electric Vehicles

2023

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“…In this case, the magnetic flux of serial connection of two coils is denoted by variable λ a ij . ( 1) can be rewritten into (2).…”

Section: Dual Three-phase Pmsm Modelmentioning

confidence: 99%

“…In recent years, many publications have dealt with the problem of modeling motors under electrical or mechanical fault. The models can be beneficial for fault detection algorithms [2]. Most studies present motor winding as one coil with mutual inductances only to other phase windings.…”

Section: Introductionmentioning

confidence: 99%

Interturn short circuit modelling in dual three-phase PMSM

Kozovský

Buchta

Blaha

2022

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society

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In this study, model of a multi-phase permanent magnet synchronous motor is demonstrated. The model is designed to allow simulations of inter-turn short circuit faults of various severity. The considered multi-phase motor is connected as a dual three-phase system. In this case, stator windings are divided into two electrically separated sub-systems. Nevertheless, the magnetic coupling between sub-systems needs to be taken into account in general. The motor model is designed to take into account the exact stator coils distribution. In this case motor uses combination of serial and parallel connections. Model is implemented in MATLAB/Simulink using SimScape environment. The paper also shows a comparison of the behavior of a real PMS motor and derived model behavior.

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Sensorless Control Using Model Reference Adaptive System Based on Power Balance Model for High-speed Permanent Magnet Synchronous Motor

Cui

Huang

2022

2022 25th International Conference on Electrical Machines and Systems (ICEMS)

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An On-line Detection Method for Single-Phase Inter-Turn Fault Occurring in High-Speed PMSM

Cited by 5 publications

References 19 publications

Fault Detection and Diagnosis of the Electric Motor Drive and Battery System of Electric Vehicles

Fault Detection and Diagnosis of the Electric Motor Drive and Battery System of Electric Vehicles

Interturn short circuit modelling in dual three-phase PMSM

Sensorless Control Using Model Reference Adaptive System Based on Power Balance Model for High-speed Permanent Magnet Synchronous Motor

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