Modelling of squirrel cage induction motors for a bio‐inspired multi‐objective optimal design

Abstract

The design of efficient three-phase induction motors is a challenge for engineering; therefore, new design techniques are continually being proposed. For example, efficiency is in conflict with manufacturing cost, which leads to the use of multi-objective optimisation techniques to solve this engineering problem. Nevertheless, this study shows that the way of accurately modelling the behaviour of the motor is as important as the optimisation method itself. Thus, the study discusses fundamental considerations in the motor model as part of a proposed methodology for the design of highly efficient three-phase squirrel cage induction motors. For this purpose, the motor is modelled in two ways: an analytical equivalent circuit and the finite element method, which are validated with data obtained from laboratory tests. The main contribution of this study is to show for the first time the required characteristics of the analytical model used as part of a multi-objective optimisation problem to have a suitable accuracy with a competitive runtime. Moreover, the problem is solved using three bio-inspired optimisation algorithms: non-dominated sorting genetic algorithms II, non-dominated sorting particle swarm optimisation and bacterial chemotaxis multi-objective optimisation algorithm. The methodology is tested in the optimal redesign of a two-pole, 3.7 kW, IE2 efficiency motor, for which the efficiency and cost were improved.