{"title":"利用模糊算法优化燃料电池汽车的控制策略","authors":"Qiong Wu;Hua Chen;Baolong Liu","doi":"10.1109/ACCESS.2024.3469912","DOIUrl":null,"url":null,"abstract":"Fuel cell vehicles have rapidly occupied the market with advantages such as environmental protection and energy conservation. However, their battery technology is insufficient and their endurance is poor, making them unsuitable for use over long distances. To address the aforementioned issues, a fuel cell vehicle energy storage system based on super-capacitors was constructed. Meanwhile, a proportional integral derivative controller based on fuzzy algorithms was established. Finally, the particle swarm optimization algorithm was used to optimize the fuzzy control strategy that integrated the fuzzy algorithm. When using the optimized fuzzy control strategy for simulation, the peak power of the fuel cell output power was reduced from 3.8kW to 2.0kW. The remaining power of the super-capacitor remained stable within a reasonable range throughout the entire operating condition. Under the new European urban road cycle, the optimized control strategy improved energy recovery performance by 4.3% and reduced hydrogen consumption by 0.9964%. Under the United States federal environmental protection agency standardized urban cycle conditions, the optimized control strategy improved the braking energy recovery efficiency index and effective braking energy recovery efficiency by 8.9% and 6.3%, respectively. The percentage reduction in hydrogen consumption was 0.9433%. Therefore, this research method can effectively reduce hydrogen consumption and improve the product economy and market competitiveness of enterprises.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10697117","citationCount":"0","resultStr":"{\"title\":\"Optimization of Control Strategy for Fuel Cell Vehicles by Integrating Fuzzy Algorithm\",\"authors\":\"Qiong Wu;Hua Chen;Baolong Liu\",\"doi\":\"10.1109/ACCESS.2024.3469912\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fuel cell vehicles have rapidly occupied the market with advantages such as environmental protection and energy conservation. However, their battery technology is insufficient and their endurance is poor, making them unsuitable for use over long distances. To address the aforementioned issues, a fuel cell vehicle energy storage system based on super-capacitors was constructed. Meanwhile, a proportional integral derivative controller based on fuzzy algorithms was established. Finally, the particle swarm optimization algorithm was used to optimize the fuzzy control strategy that integrated the fuzzy algorithm. When using the optimized fuzzy control strategy for simulation, the peak power of the fuel cell output power was reduced from 3.8kW to 2.0kW. The remaining power of the super-capacitor remained stable within a reasonable range throughout the entire operating condition. Under the new European urban road cycle, the optimized control strategy improved energy recovery performance by 4.3% and reduced hydrogen consumption by 0.9964%. Under the United States federal environmental protection agency standardized urban cycle conditions, the optimized control strategy improved the braking energy recovery efficiency index and effective braking energy recovery efficiency by 8.9% and 6.3%, respectively. The percentage reduction in hydrogen consumption was 0.9433%. Therefore, this research method can effectively reduce hydrogen consumption and improve the product economy and market competitiveness of enterprises.\",\"PeriodicalId\":13079,\"journal\":{\"name\":\"IEEE Access\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10697117\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Access\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10697117/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Access","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10697117/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Optimization of Control Strategy for Fuel Cell Vehicles by Integrating Fuzzy Algorithm
Fuel cell vehicles have rapidly occupied the market with advantages such as environmental protection and energy conservation. However, their battery technology is insufficient and their endurance is poor, making them unsuitable for use over long distances. To address the aforementioned issues, a fuel cell vehicle energy storage system based on super-capacitors was constructed. Meanwhile, a proportional integral derivative controller based on fuzzy algorithms was established. Finally, the particle swarm optimization algorithm was used to optimize the fuzzy control strategy that integrated the fuzzy algorithm. When using the optimized fuzzy control strategy for simulation, the peak power of the fuel cell output power was reduced from 3.8kW to 2.0kW. The remaining power of the super-capacitor remained stable within a reasonable range throughout the entire operating condition. Under the new European urban road cycle, the optimized control strategy improved energy recovery performance by 4.3% and reduced hydrogen consumption by 0.9964%. Under the United States federal environmental protection agency standardized urban cycle conditions, the optimized control strategy improved the braking energy recovery efficiency index and effective braking energy recovery efficiency by 8.9% and 6.3%, respectively. The percentage reduction in hydrogen consumption was 0.9433%. Therefore, this research method can effectively reduce hydrogen consumption and improve the product economy and market competitiveness of enterprises.
IEEE AccessCOMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
9.80
自引率
7.70%
发文量
6673
审稿时长
6 weeks
期刊介绍:
IEEE Access® is a multidisciplinary, open access (OA), applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE''s fields of interest.
IEEE Access will publish articles that are of high interest to readers, original, technically correct, and clearly presented. Supported by author publication charges (APC), its hallmarks are a rapid peer review and publication process with open access to all readers. Unlike IEEE''s traditional Transactions or Journals, reviews are "binary", in that reviewers will either Accept or Reject an article in the form it is submitted in order to achieve rapid turnaround. Especially encouraged are submissions on:
Multidisciplinary topics, or applications-oriented articles and negative results that do not fit within the scope of IEEE''s traditional journals.
Practical articles discussing new experiments or measurement techniques, interesting solutions to engineering.
Development of new or improved fabrication or manufacturing techniques.
Reviews or survey articles of new or evolving fields oriented to assist others in understanding the new area.