Multiobjective Optimization of Electrical Machine, a State of the Art Study

This paper presents a literal study of Multiobjective optimization (MO) in general used in electrical machine optimization in the recent years. A set of a set of nonlinear constraints (modeling availability of resources) with a set of nonlinear objective functions (modeling several performance criteria) is solved with the help of Multi objective optimization (MO). The MO problem has several applications in science, engineering, finance, etc. It is normally not possible to find an optimal solution in MO, since the various objective functions in the problem are usually in conflict with each other. Therefore, the objective in MO is to find the Pareto front of efficient solutions that provide a substitution between the various objectives. The paper will summon up some of the work done using Multiobjective optimization on electric machines in the last years. An overview of methods used will be given and the conclusion of the different papers will be presented.

[1]  V. Kamaraj,et al.  Evolutionary computation based multi-objective pole shape optimization of switched reluctance machine , 2012 .

[2]  W. I. Davisson.  Public Investment Criteria , 1964 .

[3]  R. G. Harley,et al.  A Novel Method for Multiobjective Design and Optimization of Three Phase Induction Machines , 2011, IEEE Transactions on Industry Applications.

[4]  R. Bhuvaneswari,et al.  Multi-objective parameter estimation of induction motor using particle swarm optimization , 2010, Eng. Appl. Artif. Intell..

[5]  Mehmet Çunkaş,et al.  Design Optimization of Electric Motors by Multiobjective Fuzzy Genetic Algorithms , 2008 .

[6]  Andrzej Ameljańczyk,et al.  Multicriteria Optimization in Engineering Design , 1994 .

[7]  Matthias Ehrgott,et al.  Multicriteria Optimization , 2005 .

[8]  Theodor J. Stewart.  Convergence and Validation of Interactive Methods in MCDM: Simulation Studies , 1997 .

[9]  Ka Wai Eric Cheng,et al.  Multi-Objective Optimization Design of In-Wheel Switched Reluctance Motors in Electric Vehicles , 2010, IEEE Transactions on Industrial Electronics.

[10]  Lotfi A. Zadeh,et al.  Optimality and non-scalar-valued performance criteria , 1963 .

[11]  Ivo F. Sbalzariniy,et al.  Multiobjective optimization using evolutionary algorithms , 2000 .

[12]  D. H. Marks,et al.  A review and evaluation of multiobjective programing techniques , 1975 .

[13]  Kaisa Miettinen,et al.  Nonlinear multiobjective optimization , 1998, International series in operations research and management science.

[14]  Pil-Wan Han,et al.  Multiobjective optimization of three-phase induction motor design based on genetic algorithm , 2008, 2008 18th International Conference on Electrical Machines.

[15]  Abbas Shiri,et al.  Multi-objective optimal design of low-speed linear induction motor using genetic algorithm , 2012 .

[16]  R. Kannan,et al.  MULTIOBJECTIVE OPTIMAL DESIGN OF THREE-PHASE INDUCTION GENERATOR USING SIMULATED ANNEALING TECHNIQUE , 2010 .

[17]  Mahdi Ashabani,et al.  Multiobjective Shape Optimization of Segmented Pole Permanent-Magnet Synchronous Machines With Improved Torque Characteristics , 2011, IEEE Transactions on Magnetics.

[18]  Johannes Jahn,et al.  Vector optimization - theory, applications, and extensions , 2004 .

[19]  L Parsa,et al.  Multiobjective Design Optimization of Five-Phase Halbach Array Permanent-Magnet Machine , 2011, IEEE Transactions on Magnetics.

[20]  Susana Cecilia Esquivel.  Evolutionary algorithms for solving multi-objetive problems . Carlos A. Coello Coello, David A. van Veldhuizen and Gary R., Lamont , 2002 .

[21]  Lawrence J. Fogel,et al.  Artificial Intelligence through Simulated Evolution , 1966 .

[22]  Gary B. Lamont,et al.  Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.

[23]  David B. Fogel,et al.  Evolutionary Computation: The Fossil Record , 1998 .

[24]  S Kafandaris,et al.  Essays in Decision Making: A Volume in Honour of Stanley Zionts , 2011, J. Oper. Res. Soc..