Optimum regulation of THD profile in multilevel inverter using parameter-less AI technique for electrical vehicle application

Kaushal Bhatt, Sandeep Chakravorty
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引用次数: 2

Abstract

This article proposes investigation on harmonic profile improvement using a novel fitness function in the multiphase multilevel inverter. For the proposed study in this paper, three-phase, seven-level cascaded H-bridge (CHB) multilevel inverter (MLI) is considered. Modulation of the stepped waveform output of the MLI is done using selective harmonic elimination (SHE) method. Many algorithms are proposed for solving the set of nonlinear transcendental trigonometric equations for SHE methods. Teaching learning-based optimisation (TLBO) algorithm is a parameter less optimisation technique. Due to the lack of controlling parameters, the proposed algorithm is most robust among the family of artificial intelligence (AI) techniques. In this paper, an investigation is carried out on a novel fitness function proposed for controlling total harmonic distortion (THD) for the proposed inverter. It is observed that the proposed fitness function improves THD profile below IEEE standards. It is also observed that THD profile obtained through this method is far better than THD profile obtained through various proposed methods so far. The results of THD profile from the MATLAB Simulink simulations are verified experimentally using seven-level three-phase hardware controlled by Arduino MEGA 2560 low-cost controller.
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基于无参数人工智能技术的电动汽车多电平逆变器THD曲线优化调节
本文提出了利用一种新的适应度函数改善多相多电平逆变器谐波轮廓的研究。本文研究的是三相七电平级联h桥(CHB)多电平逆变器(MLI)。采用选择性谐波消除(SHE)方法对MLI的阶跃波形输出进行调制。在SHE方法中,提出了许多求解非线性超越三角方程组的算法。基于教学的优化算法(TLBO)是一种无参数优化技术。由于缺乏控制参数,该算法在人工智能(AI)技术家族中是最鲁棒的。本文研究了一种控制逆变器总谐波失真(THD)的适应度函数。观察到所提出的适应度函数改善了低于IEEE标准的THD曲线。还观察到,通过该方法获得的THD剖面远优于目前提出的各种方法获得的THD剖面。在Arduino MEGA 2560低成本控制器控制的七电平三相硬件上,对MATLAB Simulink仿真所得的THD轮廓进行了实验验证。
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来源期刊
International Journal of Power Electronics
International Journal of Power Electronics Engineering-Electrical and Electronic Engineering
CiteScore
1.30
自引率
0.00%
发文量
84
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