Title: Three-criteria numerical optimisation as a base for designing induction mass heating

Authors: Yu Pleshivtseva; E. Rapoport; B. Nacke; A. Nikanorov; P. Di Barba; E. Sieni; M. Forzan; S. Lupi

Addresses: Samara State Technical University, Molodogvardeyskaya Str., 244, Samara, 443100, Russia ' Samara State Technical University, Molodogvardeyskaya Str., 244, Samara, 443100, Russia ' Institute of Electrotechnology, Leibniz University, Wilhelm-Busch-Str. 4, Hannover, D-30167, Germany ' Institute of Electrotechnology, Leibniz University, Wilhelm-Busch-Str. 4, Hannover, D-30167, Germany ' Department of Electrical Engineering, University of Pavia, via Ferrata 5, Pavia, 27100 Italy ' Department of Industrial Engineering, University of Padua, via Gradenigo, 6/A, Padova, 35131, Italy ' Department of Industrial Engineering, University of Padua, via Gradenigo, 6/A, Padova, 35131, Italy ' Department of Industrial Engineering, University of Padua, via Gradenigo, 6/A, Padova, 35131, Italy

Abstract: The work contains the results of the researches carried out by the authors during past years in the field of multiple-criteria optimisation of induction heaters' design based on numerical coupled electromagnetic and temperature fields' analysis. The main goal of the studies is the application of different optimisation methods and numerical finite element method (FEM) codes to solve the multi-criteria optimisation problems formulated mathematically in terms of the typical optimisation criteria: maximum temperature uniformity, minimum heating time, maximum energy efficiency and minimum scale formation. Standard genetic algorithm, non-dominated sorting genetic algorithm NSGA-II, migration NSGA algorithm, and alternance method of the optimal control theory are applied as effective optimisation tools in practically oriented applications. The developed optimisation procedures are planned to be used for solving the wide range of real-life problems of the optimal design and control of different induction heating devices and systems.

Keywords: multi-objective optimisation; design; induction heating; genetic algorithm; NSGA-II; MNSGA-II; alternance method; optimal control theory.

DOI: 10.1504/IJMMP.2018.093286

International Journal of Microstructure and Materials Properties, 2018 Vol.13 No.1/2, pp.54 - 72

Received: 06 Nov 2017
Accepted: 12 Feb 2018
Published online: 24 Jul 2018 *

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