Optimal calculation of induction heater capacitance with smart bacteria foraging algorithm

M. Asadi Z, E. Daryabeigi
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Abstract

In design of 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 the function of equivalent series resistance (ESR), optimal capacitance is calculated. The induction heating resonance capacitor is achieved by using Smart Bacteria Foraging Algorithm (SBFA) under voltage and frequency constraints for minimizing cost function that is including: increasing the output power, 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. 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.
基于智能细菌觅食算法的感应加热器电容优化计算
在并联谐振式感应加热系统的设计中,选择合适的谐振电路电容是非常重要的。电容影响谐振频率、输出功率、加热效率和功率因数。本文考虑等效串联电阻(ESR)的函数,计算了最优电容。采用智能细菌觅食算法(Smart Bacteria Foraging Algorithm, SBFA)在电压和频率约束下实现感应加热谐振电容器的成本函数最小化,即提高感应加热器的输出功率和效率,同时降低电容器的功率损耗。该算法模拟大肠杆菌的趋化行为来优化参数。该算法具有个体智能和社会智能。基于感应加热系统的等效电路模型,计算了感应加热系统的输出功率和电容损耗。通过计算机仿真验证了该方法的有效性,并与经典细菌觅食算法BFA进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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