Multi-Objective Optimization Design of Standard Industrial Motor
Main Article Content
Abstract
This paper presents a method to optimally design electrical machines. Unlike the traditional design method “tries-and-errors iterative process”, the optimal design approach consists of combining optimization algorithms and multi-physics models to reach the optimum design. A case study of designing a standard industrial motor of 6 HP with multi-objectives and constraints is chosen in order to test this optimization methodology. The Pareto solution results of two conflicting objectives between the efficiency and the active mass of this machine are reached to help designers and customers selecting the best compromised design of motor of 6 HP in terms of cost and consuming energy.
Keywords
Optimal design, standard industrial motor, asynchronous motor, TEFC (totally enclosed fan cooled) machine, optimization
Article Details
References
[1] H. Mikami, K. Ide, Y. Shimizu, M. Seno, H. Seki, Historical Evolution of Motor Technology, Hitachi Review Vol. 60, No. 1, (2011), 38-45.
[2] M. Centner, Basics and application of motor design optimization in an industrial environment, 21th International Conference on Electrical Machines (ICEM), in Berlin, Germany, (2014), 1008-1012.
[3] D. Zarko, D. Ban, D. Gooricki, Improvement of a Servo Motor Design Including Optimization and Cost Analysis, 12th International conference on Power Electronics and Motion Control Conference (EPE-PEMC), in Portoroz, Slovenia, (2006), 302-307.
[4] Y. Oda, T. Okubo, M. Takata, Recent Development of Non-Oriented Electrical Steel in JFE Steel, JFE Technical Report, No. 21, (2016), 7-13.
[5] J. Buschbeck, M. Vogelsberger, A. Orellano, Erich Schmidt, Pareto Optimization in Terms of Electromagnetic and Thermal Characteristics of Air-Cooled Asynchronous Induction Machines Applied in Railway Traction Drives, IEEE Transactions on Magnetics, Vol. 52, Issue 3, (2016), 1-4.
[6] T. V. Tran, S. Kreuawan, P. Somsiri, K. Tungpimolrut, H. P. Nguyen, Switched Reluctance Motor and Induction Machine for E-Scooter Based on Driving Cycles Design Comparisons, IEE Transactions on Electrical and Electronic Engineering, Vol. 15, Issue 6, (2020), 931-938.
[7] S. Sivaraju, F. Ferreira, N. Devarajan, Genetic algorithm based design optimization of a three-phase multiflux Induction Motor, XXth International Conference on Electrical Machines (ICEM), (2012), 288-294.
[8] T. V. Tran, S. Brisset, P. Brochet, Combinatorial and Multi-level Optimizations of a Safety Isolating Transformer, International Journal of Applied Electromagnetics and Mechanics, Vol. 26, No. 3-4, (2007), 201-208.
[9] S. Stipetic, W. Miebach, D. Zarko, Optimization in design of electric machines: Methodology and workflow, International Aegean Conference on Electrical Machines and Power Electronics and Advanced Electromechanical Motion Systems (ACEMP – OPTIM – ELECTROMOTION), Turkey, (2015), 441-448.
[10] Y. Duan, R. G. Harley, A Novel Method for Multi-objective Design and Optimization of Three Phase Induction Machines, IEEE Transactions on Industry Applications, Vol. 47, Issue 4, (2011), 1707-1715.
[11] T. V. Tran, Problèmes combinatoires et modèles multi-niveaux pour la conception optimale des machines électriques, Ph.D. dissertation, École Centrale de Lille, France, (2009).
[12] J. S. Arora, Introduction to Optimum Design, Publisher Elsevier Science & Technology (2004).
[13] P. Venkataraman, Applied Optimization with Matlab Programming, A Wiley – Interscience publication, John Wiley & Sons, New York, (2002).
[14] C. A. Coello, G. B. Lamont, Application of Multi-Objective Evolutionary Algorithms, Advances in Natural Computation - Vol. 1, World Scientific Publishing Co. Pte. Ltd., (2004).
[15] K. Deb, S. Agrawal, A. Pratap, T. Meyarivan, A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II, IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2, (2002), 182-197.
[2] M. Centner, Basics and application of motor design optimization in an industrial environment, 21th International Conference on Electrical Machines (ICEM), in Berlin, Germany, (2014), 1008-1012.
[3] D. Zarko, D. Ban, D. Gooricki, Improvement of a Servo Motor Design Including Optimization and Cost Analysis, 12th International conference on Power Electronics and Motion Control Conference (EPE-PEMC), in Portoroz, Slovenia, (2006), 302-307.
[4] Y. Oda, T. Okubo, M. Takata, Recent Development of Non-Oriented Electrical Steel in JFE Steel, JFE Technical Report, No. 21, (2016), 7-13.
[5] J. Buschbeck, M. Vogelsberger, A. Orellano, Erich Schmidt, Pareto Optimization in Terms of Electromagnetic and Thermal Characteristics of Air-Cooled Asynchronous Induction Machines Applied in Railway Traction Drives, IEEE Transactions on Magnetics, Vol. 52, Issue 3, (2016), 1-4.
[6] T. V. Tran, S. Kreuawan, P. Somsiri, K. Tungpimolrut, H. P. Nguyen, Switched Reluctance Motor and Induction Machine for E-Scooter Based on Driving Cycles Design Comparisons, IEE Transactions on Electrical and Electronic Engineering, Vol. 15, Issue 6, (2020), 931-938.
[7] S. Sivaraju, F. Ferreira, N. Devarajan, Genetic algorithm based design optimization of a three-phase multiflux Induction Motor, XXth International Conference on Electrical Machines (ICEM), (2012), 288-294.
[8] T. V. Tran, S. Brisset, P. Brochet, Combinatorial and Multi-level Optimizations of a Safety Isolating Transformer, International Journal of Applied Electromagnetics and Mechanics, Vol. 26, No. 3-4, (2007), 201-208.
[9] S. Stipetic, W. Miebach, D. Zarko, Optimization in design of electric machines: Methodology and workflow, International Aegean Conference on Electrical Machines and Power Electronics and Advanced Electromechanical Motion Systems (ACEMP – OPTIM – ELECTROMOTION), Turkey, (2015), 441-448.
[10] Y. Duan, R. G. Harley, A Novel Method for Multi-objective Design and Optimization of Three Phase Induction Machines, IEEE Transactions on Industry Applications, Vol. 47, Issue 4, (2011), 1707-1715.
[11] T. V. Tran, Problèmes combinatoires et modèles multi-niveaux pour la conception optimale des machines électriques, Ph.D. dissertation, École Centrale de Lille, France, (2009).
[12] J. S. Arora, Introduction to Optimum Design, Publisher Elsevier Science & Technology (2004).
[13] P. Venkataraman, Applied Optimization with Matlab Programming, A Wiley – Interscience publication, John Wiley & Sons, New York, (2002).
[14] C. A. Coello, G. B. Lamont, Application of Multi-Objective Evolutionary Algorithms, Advances in Natural Computation - Vol. 1, World Scientific Publishing Co. Pte. Ltd., (2004).
[15] K. Deb, S. Agrawal, A. Pratap, T. Meyarivan, A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II, IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2, (2002), 182-197.