Multi-Objective Design Optimization of a Three Phase Squirrel Cage Induction Motor for Electric Propulsion System using Genetic Algorithm

Abstract

Electric motor is one of the most important components of an Electric Vehicle (EV). The induction motor is mostly used for electric propulsion systems due to its various advantages such as low cost, robustness, etc. This paper discusses the Genetic Algorithm (GA) based multi-objective design optimization of an induction motor. The aim is to increase efficiency and to reduce the weight of an induction motor simultaneously. Different design variables and design constraints are imposed on the optimization problem within a range for design variables using Global Optimization Toolbox in MATLAB. A 7.5 kW, 4 pole, 50 Hz squirrel cage induction motor is designed conventionally and optimized using the GA. The designs obtained were validated and performance curves were obtained using their equivalent circuit parameters. Performance comparison was made between a conventionally designed motor and an optimally designed motor. The optimized design has 1.02% efficiency improvement and 1.11 kg weight reduction over the conventional design without violating the design constraints, whereas the conventional design violated the design constraints.