Title :
Optimal Electromagnetic Design of a Nonsalient Magnetic-Cored Superconducting Synchronous Machine Using Genetic Algorithm
Author :
Elhaminia, Pedram ; Yazdanian, Masoud ; Zolghadri, Mohammad Reza ; Fardmanesh, Mehdi
Author_Institution :
Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran, Iran
Abstract :
An optimum electromagnetic design of a nonsalient magnetic-cored superconducting synchronous machine (SSM) is presented in this paper. First, self- and mutual inductances of a nonsalient magnetic-cored SSM are calculated using the magnetic energy method and analytical equations of magnetic vector potential. Then, a design approach for an SSM machine is proposed based on the inductances of the machine. An optimal design is finally performed using a genetic algorithm, considering the machine efficiency as an objective function. The finite-element method is utilized in each step to verify the analytical results.
Keywords :
finite element analysis; genetic algorithms; inductance; magnetic cores; superconducting machines; synchronous machines; SSM machine; analytical equations; finite-element method; genetic algorithm; machine efficiency; magnetic energy method; magnetic vector potential; mutual inductance; nonsalient magnetic-cored superconducting synchronous machine; optimal electromagnetic design; self-inductance; Iron; Magnetic flux; Mathematical model; Stator windings; Superconducting magnets; Windings; Finite-element method (FEM); Genetic Algorithm and Finite Element Method; Mutual Inductance; Non-salient Magnetic-cored; Self-Inductance; Superconducting Synchronous Machine (SSM); genetic algorithm (GA); mutual inductance; nonsalient magnetic-cored; self-inductance; superconducting synchronous machine (SSM);
Journal_Title :
Applied Superconductivity, IEEE Transactions on
DOI :
10.1109/TASC.2014.2360874
