基于人工智能技术的低温固体氧化物燃料电池性能分析

Y. Liu
{"title":"基于人工智能技术的低温固体氧化物燃料电池性能分析","authors":"Y. Liu","doi":"10.1109/ACAIT56212.2022.10137934","DOIUrl":null,"url":null,"abstract":"In order to solve the problems of poor output performance and large output oscillation of traditional low-temperature solid oxide fuel cells, artificial intelligence technology was introduced in this paper to analyze the performance of low-temperature solid oxide fuel cells. Firstly, the steady-state control system of the battery was constructed, and the three-dimensional structure design and electrical performance optimization of the battery were realized. Then, the electrode potential induction analysis model was constructed to analyze the carbon / metal oxide electrode materials with stable mechanical and electrochemical properties. Thirdly, combined with the three-phase regulation of the battery electrode, the microstructure area in the fuel cell electric field is controlled. Finally, according to the fuel cell output voltage, the fuel cell ion mass conservation model is constructed. Artificial intelligence is used to obtain the optimal solution of fuel cell voltage output, so as to complete the analysis of fuel cell steady-state performance. The simulation results show that this method can control the output of the low-temperature solid oxide fuel cell well and reduce the output oscillation of the cell, which has a certain theoretical reference significance for the performance of the cell.","PeriodicalId":398228,"journal":{"name":"2022 6th Asian Conference on Artificial Intelligence Technology (ACAIT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance Analysis of Low Temperature Solid Oxide Fuel Cell Based on Artificial Intelligence Technology\",\"authors\":\"Y. Liu\",\"doi\":\"10.1109/ACAIT56212.2022.10137934\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve the problems of poor output performance and large output oscillation of traditional low-temperature solid oxide fuel cells, artificial intelligence technology was introduced in this paper to analyze the performance of low-temperature solid oxide fuel cells. Firstly, the steady-state control system of the battery was constructed, and the three-dimensional structure design and electrical performance optimization of the battery were realized. Then, the electrode potential induction analysis model was constructed to analyze the carbon / metal oxide electrode materials with stable mechanical and electrochemical properties. Thirdly, combined with the three-phase regulation of the battery electrode, the microstructure area in the fuel cell electric field is controlled. Finally, according to the fuel cell output voltage, the fuel cell ion mass conservation model is constructed. Artificial intelligence is used to obtain the optimal solution of fuel cell voltage output, so as to complete the analysis of fuel cell steady-state performance. The simulation results show that this method can control the output of the low-temperature solid oxide fuel cell well and reduce the output oscillation of the cell, which has a certain theoretical reference significance for the performance of the cell.\",\"PeriodicalId\":398228,\"journal\":{\"name\":\"2022 6th Asian Conference on Artificial Intelligence Technology (ACAIT)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 6th Asian Conference on Artificial Intelligence Technology (ACAIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACAIT56212.2022.10137934\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 6th Asian Conference on Artificial Intelligence Technology (ACAIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACAIT56212.2022.10137934","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

为了解决传统低温固体氧化物燃料电池输出性能差、输出振荡大的问题,本文引入人工智能技术对低温固体氧化物燃料电池的性能进行分析。首先,构建了电池稳态控制系统,实现了电池的三维结构设计和电性能优化。然后,建立电极电位感应分析模型,对力学性能和电化学性能稳定的碳/金属氧化物电极材料进行分析。第三,结合电池电极的三相调节,对燃料电池电场中的微结构区域进行控制。最后,根据燃料电池输出电压,建立了燃料电池离子质量守恒模型。利用人工智能获得燃料电池电压输出的最优解,从而完成燃料电池稳态性能的分析。仿真结果表明,该方法可以很好地控制低温固体氧化物燃料电池的输出,减小电池的输出振荡,对电池的性能具有一定的理论参考意义。
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
Performance Analysis of Low Temperature Solid Oxide Fuel Cell Based on Artificial Intelligence Technology
In order to solve the problems of poor output performance and large output oscillation of traditional low-temperature solid oxide fuel cells, artificial intelligence technology was introduced in this paper to analyze the performance of low-temperature solid oxide fuel cells. Firstly, the steady-state control system of the battery was constructed, and the three-dimensional structure design and electrical performance optimization of the battery were realized. Then, the electrode potential induction analysis model was constructed to analyze the carbon / metal oxide electrode materials with stable mechanical and electrochemical properties. Thirdly, combined with the three-phase regulation of the battery electrode, the microstructure area in the fuel cell electric field is controlled. Finally, according to the fuel cell output voltage, the fuel cell ion mass conservation model is constructed. Artificial intelligence is used to obtain the optimal solution of fuel cell voltage output, so as to complete the analysis of fuel cell steady-state performance. The simulation results show that this method can control the output of the low-temperature solid oxide fuel cell well and reduce the output oscillation of the cell, which has a certain theoretical reference significance for the performance of the cell.
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
Transformer with Global and Local Interaction for Pedestrian Trajectory Prediction The Use of Explainable Artificial Intelligence in Music—Take Professor Nick Bryan-Kinns’ “XAI+Music” Research as a Perspective Playing Fight the Landlord with Tree Search and Hidden Information Evaluation Evaluation Method of Innovative Economic Benefits of Enterprise Human Capital Based on Deep Learning An Attribute Contribution-Based K-Nearest Neighbor Classifier
×
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