Fuzzy Based Health Monitoring of Electric Vehicle Motor using Time Domain Analysis

Detection of low-level electrical winding faults in Squirrel Cage Induction Motor (SCIM) is prime importance in Electric Vehicle (EVs). This analysis is carried out to predict flux distribution inside and outside of SCIM using Finite Element Analysis (FEA). In FEA, time domain analysis is performed to determine flux at the instant of fault with respect to time whereas steady state analysis will not give such a results. Flux distribution provides significant information about the behavior of SCIM. For analyzing the leakage flux in the surface vicinity of SCIM a 15kW machine is chosen. The analysis indicates magnetic flux distribution and ideal location of flux sensor. From FEM model, leakage flux on the surface of SCIM is captured and exported to MATLAB for health monitoring. Fuzzy rule base is developed for mapping the flux with health monitoring of SCIM used in Electric Vehicle (EV). Continuous health monitoring of the machine is captured by fuzzy controller and displayed in EV or vehicle monitoring centre.