Optimal Design of IPMSM for Fuel Cell Electric Vehicles Using Autotuning Elliptical Niching Genetic Algorithm
Young-Rok Kang, Ji-Chang Son, Dong–Kuk Lim
Abstract
To find multimodal solutions for the optimal design of an interior permanent magnet synchronous motor (IPMSM) for fuel cell electric vehicles, an autotuning elliptical niching genetic algorithm is proposed. With conventional autotuning niching genetic algorithms, some peaks are difficult to find because of a circular niche region. The proposed algorithm solves this problem by introducing an elliptical niche. The superior performance of the proposed algorithm is verified using test functions, and it is applied to the optimal design of an IPMSM for fuel cell electric vehicles.
Topics & Concepts
Genetic algorithmAlgorithmComputer scienceFuel cellsOptimal designElectric vehicleElectric motorControl theory (sociology)EngineeringPhysicsPower (physics)Artificial intelligenceElectrical engineeringChemical engineeringControl (management)Quantum mechanicsMachine learningElectric Motor Design and AnalysisInduction Heating and Inverter TechnologyElectric and Hybrid Vehicle Technologies