ANN based On-board Fault Diagnostic for Induction Motor Drive in Low-Cost Electric Vehicles

Research output: Contribution to conferencePaperpeer-review

20 Scopus citations

Abstract

The defect in the stator winding turns causes a fluctuation in stator resistance, which leads to an incorrect assessment of the stator flux location, which can lead to the failure of the entire drive system. This study describes a novel artificial neural network (ANN) approach for identifying stator short-circuit failures in three-phase induction motors utilizing feature extraction and categorization. Delayed stator current signals are used in the first stage to estimate the mutual information, which is then used as input to decision trees and multilayer perceptron neural networks in the second step. This paper also employs a direct Torque Control (DTC) based fault-tolerant operation (FTO) for the induction motor drive. Voltage imbalance, load torque variations, and short-circuit levels ranging from 1% to 10% are reported in the offline and online experimental tests.

Original languageBritish English
Pages153-158
Number of pages6
DOIs
StatePublished - 2022
Event37th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2022 - Houston, United States
Duration: 20 Mar 202224 Mar 2022

Conference

Conference37th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2022
Country/TerritoryUnited States
CityHouston
Period20/03/2224/03/22

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