Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data

Abstract This article studies and investigate the magnetic characteristics of a surface mounted permanent magnet (SPM)‐type brushless direct current (BLDC) motor when subjected to demagnetisation fault conditions. The proposed research subjugates the limitation of estimating the State of Health (SoH...

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Main Authors: Adil Usman, Vivek. K. Sharma, Bharat. S. Rajpurohit
Format: Article
Language:English
Published: Wiley 2021-12-01
Series:IET Energy Systems Integration
Subjects:
Online Access:https://doi.org/10.1049/esi2.12024
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author Adil Usman
Vivek. K. Sharma
Bharat. S. Rajpurohit
author_facet Adil Usman
Vivek. K. Sharma
Bharat. S. Rajpurohit
author_sort Adil Usman
collection DOAJ
description Abstract This article studies and investigate the magnetic characteristics of a surface mounted permanent magnet (SPM)‐type brushless direct current (BLDC) motor when subjected to demagnetisation fault conditions. The proposed research subjugates the limitation of estimating the State of Health (SoH) of a BLDC motor drive when deployed in electric vehicle (EV) applications. Demagnetisation faults adversely affect the performance of a machine and indirectly the EV drive system, bringing significant transformation in the machine’s characteristics and quantities. The novel method of measuring the radial magnetic field (Bg) across the machine airgap assists in diagnosing and estimating the % severity of faults under the subjected fault conditions. A numerical co‐simulation‐based model of a BLDC motor is developed to investigate the performance of the machine under both healthy and fault conditions. The BLDC motor being studied is operated using a field programmable gate array (FPGA) based control drive adopting a hysteresis current control (HCC) technique. The experimental investigation of a complete BLDC motor test drive is carried out with an FPGA‐based algorithm developed on the Xilinx ISE tool. The outcomes obtained are validated with the numerical results obtained through a finite element (FE) analysis. The proposed study uses a fluxgate sensor for experimental measurement of the flux density of a BLDC motor drive, which is vital for estimating the fault severity and scheduling the maintenance accordingly. The experimental investigations are found to be in validation with the proposed techniques in estimating the health of a BLDC motor‐driven EV drive system.
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spelling doaj.art-d4522f462e51423697c26c2a7f398b5d2022-12-22T03:13:54ZengWileyIET Energy Systems Integration2516-84012021-12-013443745010.1049/esi2.12024Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement dataAdil Usman0Vivek. K. Sharma1Bharat. S. Rajpurohit2School of Computing and Electrical Engineering Indian Institute of Technology Mandi Kamand IndiaSchool of Computing and Electrical Engineering Indian Institute of Technology Mandi Kamand IndiaSchool of Computing and Electrical Engineering Indian Institute of Technology Mandi Kamand IndiaAbstract This article studies and investigate the magnetic characteristics of a surface mounted permanent magnet (SPM)‐type brushless direct current (BLDC) motor when subjected to demagnetisation fault conditions. The proposed research subjugates the limitation of estimating the State of Health (SoH) of a BLDC motor drive when deployed in electric vehicle (EV) applications. Demagnetisation faults adversely affect the performance of a machine and indirectly the EV drive system, bringing significant transformation in the machine’s characteristics and quantities. The novel method of measuring the radial magnetic field (Bg) across the machine airgap assists in diagnosing and estimating the % severity of faults under the subjected fault conditions. A numerical co‐simulation‐based model of a BLDC motor is developed to investigate the performance of the machine under both healthy and fault conditions. The BLDC motor being studied is operated using a field programmable gate array (FPGA) based control drive adopting a hysteresis current control (HCC) technique. The experimental investigation of a complete BLDC motor test drive is carried out with an FPGA‐based algorithm developed on the Xilinx ISE tool. The outcomes obtained are validated with the numerical results obtained through a finite element (FE) analysis. The proposed study uses a fluxgate sensor for experimental measurement of the flux density of a BLDC motor drive, which is vital for estimating the fault severity and scheduling the maintenance accordingly. The experimental investigations are found to be in validation with the proposed techniques in estimating the health of a BLDC motor‐driven EV drive system.https://doi.org/10.1049/esi2.12024rotorsfield programmable gate arrayselectric current controldemagnetisationcondition monitoringair gaps
spellingShingle Adil Usman
Vivek. K. Sharma
Bharat. S. Rajpurohit
Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
IET Energy Systems Integration
rotors
field programmable gate arrays
electric current control
demagnetisation
condition monitoring
air gaps
title Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
title_full Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
title_fullStr Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
title_full_unstemmed Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
title_short Condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
title_sort condition monitoring and severity estimation of rotor demagnetisation fault using magnetic flux measurement data
topic rotors
field programmable gate arrays
electric current control
demagnetisation
condition monitoring
air gaps
url https://doi.org/10.1049/esi2.12024
work_keys_str_mv AT adilusman conditionmonitoringandseverityestimationofrotordemagnetisationfaultusingmagneticfluxmeasurementdata
AT vivekksharma conditionmonitoringandseverityestimationofrotordemagnetisationfaultusingmagneticfluxmeasurementdata
AT bharatsrajpurohit conditionmonitoringandseverityestimationofrotordemagnetisationfaultusingmagneticfluxmeasurementdata