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Prognosis of Inter-turn and Hall Sensor Faults of Brushless DC Motor Using ANFIS with Particle Swarm Optimization


K.V.S.H. Gayatri Sarman, T. Madhu and A. Mallikharjuna Prasad
Abstract

Nowadays usage of electric vehicles is increasing due to the zero emission of green house gases. Brushless DC motor (BLDC) is the heart of any type of electric vehicle. Fault identification and diagnosis (FID) plays a vital role in the performance of the BLDC motor. The safety and perforce of the BLDC motor is greatly depend on the FID and reduces the number of shutdowns. In this paper novel diagnosis procedure for BLDC motor is explained. This novel method shall detect faults in Hall Effect sensors and Inter turn faults by applying FUZZY, ANN-PSO and ANFIS-PSO algorithms based on Fast Fourier Transform (FFT). FFT method is used for extracting various values of voltage and current of BLDC motor. In the simulation process, fist it test the performance of the BLDC motor which is to be in fault free condition and further it identifies the Faulty conditions by applying algorithms. By using these algorithms the system can identifies the exact fault occur in the BLDC motor.

Volume 12 | 03-Special Issue

Pages: 1281-1292

DOI: 10.5373/JARDCS/V12SP3/20201377