基于改进萤火虫算法的固体氧化物电池荷电状态分数PID控制参数优化

Tao Zhang, Honglin Li, Xu-Yen Tu, Huizhen Pang, Yu Huang
{"title":"基于改进萤火虫算法的固体氧化物电池荷电状态分数PID控制参数优化","authors":"Tao Zhang, Honglin Li, Xu-Yen Tu, Huizhen Pang, Yu Huang","doi":"10.1109/IAI53119.2021.9619450","DOIUrl":null,"url":null,"abstract":"Aiming at the parameter optimization problem of the state of charge (SOC) PID adjustment method of the soild oxide fuel cell (SOFC), in the analysis of the SOFC adjustment system characteristics and PID parameter optimization fitness function based on the improved firefly algorithm, a fractional PID parameter optimization model of SOC control is established. For the 6.6% voltage disturbance simulation test without external load and the 25% external load current disturbance test, the optimal solutions of fractional PID and conventional PID under the improved Firefly algorithm and the standard Firefly algorithm are obtained. The research shows that the optimal solution of fractional PID parameters obtained by the improved Firefly algorithm not only has a smaller overshoot under disturbance, but also a shorter transition process time, which is more conducive to SOC control.","PeriodicalId":106675,"journal":{"name":"2021 3rd International Conference on Industrial Artificial Intelligence (IAI)","volume":"338 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimization of SOC fractional PID control parameters for solid oxide battery based on improved firefly algorithm\",\"authors\":\"Tao Zhang, Honglin Li, Xu-Yen Tu, Huizhen Pang, Yu Huang\",\"doi\":\"10.1109/IAI53119.2021.9619450\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the parameter optimization problem of the state of charge (SOC) PID adjustment method of the soild oxide fuel cell (SOFC), in the analysis of the SOFC adjustment system characteristics and PID parameter optimization fitness function based on the improved firefly algorithm, a fractional PID parameter optimization model of SOC control is established. For the 6.6% voltage disturbance simulation test without external load and the 25% external load current disturbance test, the optimal solutions of fractional PID and conventional PID under the improved Firefly algorithm and the standard Firefly algorithm are obtained. The research shows that the optimal solution of fractional PID parameters obtained by the improved Firefly algorithm not only has a smaller overshoot under disturbance, but also a shorter transition process time, which is more conducive to SOC control.\",\"PeriodicalId\":106675,\"journal\":{\"name\":\"2021 3rd International Conference on Industrial Artificial Intelligence (IAI)\",\"volume\":\"338 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 3rd International Conference on Industrial Artificial Intelligence (IAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAI53119.2021.9619450\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Conference on Industrial Artificial Intelligence (IAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAI53119.2021.9619450","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

针对固体氧化物燃料电池(SOFC)荷电状态(SOC) PID调节方法的参数优化问题,在分析SOFC调节系统特性和基于改进萤火虫算法的PID参数优化适应度函数的基础上,建立了分数阶PID荷电状态控制参数优化模型。对于无外负载的6.6%电压扰动模拟试验和25%外负载电流扰动试验,得到了改进Firefly算法和标准Firefly算法下分数阶PID和常规PID的最优解。研究表明,改进的Firefly算法得到的分数阶PID参数最优解不仅在扰动下超调量较小,而且过渡过程时间更短,更有利于SOC控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Optimization of SOC fractional PID control parameters for solid oxide battery based on improved firefly algorithm
Aiming at the parameter optimization problem of the state of charge (SOC) PID adjustment method of the soild oxide fuel cell (SOFC), in the analysis of the SOFC adjustment system characteristics and PID parameter optimization fitness function based on the improved firefly algorithm, a fractional PID parameter optimization model of SOC control is established. For the 6.6% voltage disturbance simulation test without external load and the 25% external load current disturbance test, the optimal solutions of fractional PID and conventional PID under the improved Firefly algorithm and the standard Firefly algorithm are obtained. The research shows that the optimal solution of fractional PID parameters obtained by the improved Firefly algorithm not only has a smaller overshoot under disturbance, but also a shorter transition process time, which is more conducive to SOC control.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Research on self-maintenance strategy of CNC machine tools based on case-based reasoning An Improved RRT* Algorithm Combining Motion Constraint and Artificial Potential Field for Robot-Assisted Flexible Needle Insertion in 3D Environment Relative Stability Analysis Method of Systems Based on Goal Seek Operation Optimization of Park Integrated Energy System Considering the Response of Electricity and Cooling Demand Privacy-Preserving Push-sum Average Consensus Algorithm over Directed Graph Via State Decomposition
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1