Induction machine parameter range constraints in genetic algorithm based efficiency estimation techniques

Estimation of induction machine equivalent circuit parameters which are commonly used in efficiency estimation and control methods can be effectively achieved by utilizing genetic algorithms (GA). One of the difficulties of using GAs for efficiency estimation is the determination of variable (parameter) constraints (ranges). A wide range of variables can cause unstable outcome. Hence, it is essential to determine an acceptable range for each variable prior to a GA run to produce stable and repeatable results. In this paper, relationships based on nameplate information and a large database of tested induction motors provided by Hydro-Québec are proposed to determine acceptable induction motor parameter ranges. The effectiveness and accuracy of the proposed method is validated by testing 4 induction machines of different power ratings.