TY - EJOUR
AU - Emanian, Amin
AU - Daryabeigi, Ehsan
AU - Zeidabadi, Morteza Asadi
PY - 2024
DA - February
TI - Optimal Calculation of Induction Heater Capacitance with Developed Bacteria Foraging Algorithm
T2 - Majlesi Journal of Electrical Engineering
VL - 6
L1 - https://oiccpress.com/Majlesi-Journal-of-Electrical-Engineering/article/optimal-calculation-of-induction-heater-capacitance-with-developed-bacteria-foraging-algorithm/
N2 - In designing a parallel resonant induction heating system, choosing a proper capacitance for the resonant circuit is quite important.  The capacitance affects the resonant frequency, output power, heating efficiency and power factor. In this paper, with consideration to function of the equivalent series resistance (ESR), optimal capacitance is calculated. The induction heating resonance capacitor is achieved using Smart Bacteria Foraging Algorithm (SBFA) under voltage and frequency constraints for minimizing cost function that is including: increasing the output power and efficiency of an induction heater, while decreasing the power loss of the capacitor. The proposed algorithm mimics chemotactic behavior of  E.Coli bacteria to optimize parameters. The proposed algorithm enjoys individual and social intelligence, so that it can search influx ways among hidden layers of the problem.  Based on the equivalent circuit model of an induction heating system, the output power, and the capacitor losses are calculated. The effectiveness of the proposed method is verified by computer simulations, also improving the obtained results using SBFA are compared to classical bacteria foraging algorithm BFA. 
IS - 4
PB - OICC Press
KW - Cloud computing, DDoS attacks, Machine Learning, deep learning techniques, . , 
EN -