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Maximum power point tracking of a proton exchange membrane fuel cell system using PSO-PID controller

机译:使用PSO-PID控制器跟踪质子交换膜燃料电池系统的最大功率点

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摘要

Fuel cells output power depends on the operating conditions, including cell temperature, oxygen partial pressure, hydrogen partial pressure, and membrane water content. In each particular condition, there is only one unique operating point for a fuel cell system with the maximum output. Thus, a maximum power point tracking (MPPT) controller is needed to increase the efficiency of the fuel cell systems. In this paper an efficient method based on the particle swarm optimization (PSO) and PID controller (PSO-PID) is proposed for MPPT of the proton exchange membrane (PEM) fuel cells. The closed loop system includes the PEM fuel cell, boost converter, battery and PSO-PID controller. PSO-PID controller adjusts the operating point of the PEM fuel cell to the maximum power by tuning of the boost converter duty cycle. To demonstrate the performance of the proposed algorithm, simulation results are compared with perturb and observe (P&O) and sliding mode (SM) algorithms under different operating conditions. PSO algorithm with fast convergence, high accuracy and very low power fluctuations tracks the maximum power point of the fuel cell system. (C) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
机译:燃料电池的输出功率取决于运行条件,包括电池温度,氧气分压,氢气分压和膜水含量。在每种特定条件下,最大输出的燃料电池系统只有一个唯一的工作点。因此,需要最大功率点跟踪(MPPT)控制器来提高燃料电池系统的效率。本文提出了一种基于粒子群优化(PSO)和PID控制器(PSO-PID)的高效方法来质子交换膜(PEM)燃料电池的MPPT。闭环系统包括PEM燃料电池,升压转换器,电池和PSO-PID控制器。 PSO-PID控制器通过调整升压转换器的占空比,将PEM燃料电池的工作点调整为最大功率。为了证明所提算法的性能,将仿真结果与扰动观测(P&O)算法和滑模(SM)算法在不同工况下进行了比较。具有快速收敛性,高精度和极低功率波动的PSO算法可跟踪燃料电池系统的最大功率点。 (C)2017氢能出版物有限公司。由Elsevier Ltd.出版。保留所有权利。

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