Phumiphak, Punyaphat
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Preferred name
Phumiphak, Punyaphat
Alternative Name
Phumiphak, P.
Phumiphak, Phunyaphat
Main Affiliation
Email
punyaphat.ph@kmitl.ac.th
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Item type:Publication, Performance evaluation of three-leg voltage source inverter fed unsymmetrical two-phase induction motor based on genetic algorithm for parameter estimation(2019-12-01); This paper presents an evaluation method of performance characteristics in terms of loss, currents and electromagnetic torque of an unsymmetrical two-phase induction motor driven by a three-leg Voltage Source Inverter (VSI) providing unbalanced two-phase voltages. The model parameters for consideration of loss and dynamic performance of the motor are estimated by using Genetic Algorithm (GA). Also, synthesized winding current waveforms based on a super-position method and frequency domain of known harmonic voltages are investigated. The methodology of the proposed GA applied to parameter estimation of the unsymmetrical two-phase induction motor is fully given. Carrier-based unbalanced Space Vector Pulse With Modulation (SVPWM) is employed and implemented on a low-cost microcontroller. In order to prove the validity of the model with the parameters obtained by GA, performance comparison with the experiment and the model with the parameters obtained by conventional test in laboratory has been made. The results of simulation with the proposed parameters and experiment are in good agreement. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optimal capacitances compensation for short-shunt self-excited induction generator under inductive load(2009-12-01); Chat-uthai, C.This paper presents a technique for evaluating the optimal values of capacitances necessary to maintain the power quality of voltage regulation of the short-shunt self-excited induction generator (SEIG) feeding to the desired pu load under various lagging power factor conditions. The optimal values of shunt and series capacitances, and the optimal relation of ratio of air gap voltage to frequency with magnetizing reactance for the minimum voltage regulation of SEIG are evaluated by using the technique of genetic algorithm (GA) based on the equivalent circuit parameters of machine. Experimental results of 0.75 kW, short-shunt SEIG are performed to confirm the effectiveness of this proposed technique. The results are experimentally verified, which illustrate that the voltage regulations of SEIG under different inductive loads are within the limit of ± 0.06 pu.