IEEE Transactions on Magnetics · 2008 · 109 citations · 14 references
EngineeringElectrical EngineeringDesign OptimizationElectric MachinesMachine DesignElectric MotorsInduction MachinesLinear Electric MachinesEfficiencyGenetic Algorithm OptimizationLinear Induction MotorsLinear MotorsMotor Efficiency AnalysisMotor PerformanceMotor Performance EvaluationPower Factor
Although linear electrical motors (LMs) are increasingly used in industry to develop linear motion, they suffer from two major drawbacks: low efficiency and low power factor. These drawbacks cause high energy consumption and a rise in input current, and occupy transmission line capacity. We present a multiobjective optimization method to improve both efficiency and power factor, simultaneously. Our method uses an analytical model of the machine to calculate the efficiency and power factor. It allows us to investigate the effects of various motor specifications on the efficiency and the power factor. Motor parameters and dimensions can then be optimized by using a genetic algorithm in an appropriate objective function. The results show an enhancement in motor performance. We have used 2-D and 3-D time-stepping finite-element methods to evaluate the analytical results. A comparison of results validates our optimization method.
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Genetic algorithms in search, optimization, and machine learning
Choice Reviews Online · 1989 · 49.3K citations