Modeling and Decentralized Predictive Control of Ejector Circulation-Based PEM Fuel Cell Anode System for Vehicular Application

IF 4.8 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Bo Zhang, Dong Hao, Jinrui Chen, Caizhi Zhang, Bin Chen, Zhongbao Wei, Yaxiong Wang
{"title":"Modeling and Decentralized Predictive Control of Ejector Circulation-Based PEM Fuel Cell Anode System for Vehicular Application","authors":"Bo Zhang,&nbsp;Dong Hao,&nbsp;Jinrui Chen,&nbsp;Caizhi Zhang,&nbsp;Bin Chen,&nbsp;Zhongbao Wei,&nbsp;Yaxiong Wang","doi":"10.1007/s42154-022-00190-4","DOIUrl":null,"url":null,"abstract":"<div><p>The dynamic response of fuel cell vehicle is greatly affected by the pressure of reactants. Besides, the pressure difference between anode and cathode will also cause mechanical damage to proton exchange membrane. For maintaining the relative stability of anode pressure, this study proposes a decentralized model predictive controller (DMPC) to control the anodic supply system composed of a feeding and returning ejector assembly. Considering the important influence of load current on the system, the piecewise linearization approach and state space with current-induced disturbance compensation are comparatively analyzed. Then, an innovative switching strategy is proposed to prevent frequent switching of the sub-model-based controllers and to ensure the most appropriate predictive model is applied. Finally, simulation results demonstrate the better stability and robustness of the proposed control schemes compared with the traditional proportion integration differentiation controller under the step load current, variable target and purge disturbance conditions. In particular, in the case of the DC bus load current of a fuel cell hybrid vehicle, the DMPC controller with current-induced disturbance compensation has better stability and target tracking performance with an average error of 0.15 kPa and root mean square error of 1.07 kPa.</p></div>","PeriodicalId":36310,"journal":{"name":"Automotive Innovation","volume":"5 3","pages":"333 - 345"},"PeriodicalIF":4.8000,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s42154-022-00190-4.pdf","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automotive Innovation","FirstCategoryId":"1087","ListUrlMain":"https://link.springer.com/article/10.1007/s42154-022-00190-4","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 9

Abstract

The dynamic response of fuel cell vehicle is greatly affected by the pressure of reactants. Besides, the pressure difference between anode and cathode will also cause mechanical damage to proton exchange membrane. For maintaining the relative stability of anode pressure, this study proposes a decentralized model predictive controller (DMPC) to control the anodic supply system composed of a feeding and returning ejector assembly. Considering the important influence of load current on the system, the piecewise linearization approach and state space with current-induced disturbance compensation are comparatively analyzed. Then, an innovative switching strategy is proposed to prevent frequent switching of the sub-model-based controllers and to ensure the most appropriate predictive model is applied. Finally, simulation results demonstrate the better stability and robustness of the proposed control schemes compared with the traditional proportion integration differentiation controller under the step load current, variable target and purge disturbance conditions. In particular, in the case of the DC bus load current of a fuel cell hybrid vehicle, the DMPC controller with current-induced disturbance compensation has better stability and target tracking performance with an average error of 0.15 kPa and root mean square error of 1.07 kPa.

Abstract Image

基于喷射器循环的车用PEM燃料电池阳极系统建模与分散预测控制
燃料电池汽车的动态响应受反应物压力的影响很大。此外,阳极和阴极之间的压力差也会对质子交换膜造成机械损伤。为了保持阳极压力的相对稳定性,本文提出了一种分散模型预测控制器(DMPC)来控制由进料和回料喷射器组件组成的阳极供应系统。考虑到负载电流对系统的重要影响,比较分析了分段线性化方法和带电流扰动补偿的状态空间方法。然后,提出了一种新颖的切换策略,以防止基于子模型的控制器频繁切换,并确保应用最合适的预测模型。仿真结果表明,在阶跃负载电流、变目标和吹扫干扰条件下,所提出的控制方案比传统的比例积分微分控制器具有更好的稳定性和鲁棒性。特别是在燃料电池混合动力汽车直流母线负载电流情况下,采用电流诱导扰动补偿的DMPC控制器具有更好的稳定性和目标跟踪性能,平均误差为0.15 kPa,均方根误差为1.07 kPa。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Automotive Innovation
Automotive Innovation Engineering-Automotive Engineering
CiteScore
8.50
自引率
4.90%
发文量
36
期刊介绍: Automotive Innovation is dedicated to the publication of innovative findings in the automotive field as well as other related disciplines, covering the principles, methodologies, theoretical studies, experimental studies, product engineering and engineering application. The main topics include but are not limited to: energy-saving, electrification, intelligent and connected, new energy vehicle, safety and lightweight technologies. The journal presents the latest trend and advances of automotive technology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信