{"title":"一种基于模型的电池充电优化框架,用于时间与退化之间的合理权衡","authors":"Sean Appleton, Abbas Fotouhi","doi":"10.1007/s42154-023-00221-8","DOIUrl":null,"url":null,"abstract":"<div><p>This study aims at developing an optimization framework for electric vehicle charging by considering different trade-offs between battery degradation and charging time. For the first time, the application of practical limitations on charging and cooling power is considered along with more detailed health models. Lithium iron phosphate battery is used as a case study to demonstrate the effectiveness of the proposed optimization framework. A coupled electro-thermal equivalent circuit model is used along with two battery health models to mathematically obtain optimal charging current profiles by considering stress factors of state-of-charge, charging rate, temperature and time. The optimization results demonstrate an improvement over the benchmark constant current–constant voltage (CCCV) charging protocol when considering both the charging time and battery health. A main difference between the optimal and the CCCV charging protocols is found to be an additional ability to apply constraints and adapt to initial conditions in the proposed optimal charging protocol. In a case study, for example, the ‘optimal time’ charging is found to take 12 min while the ‘optimal health’ charging profile suggests around 100 min for charging the battery from 25 to 75% state-of-charge. Any other trade-off between those two extreme cases is achievable using the proposed charging protocol as well.</p></div>","PeriodicalId":36310,"journal":{"name":"Automotive Innovation","volume":"6 2","pages":"204 - 219"},"PeriodicalIF":4.8000,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s42154-023-00221-8.pdf","citationCount":"0","resultStr":"{\"title\":\"A Model-Based Battery Charging Optimization Framework for Proper Trade-offs Between Time and Degradation\",\"authors\":\"Sean Appleton, Abbas Fotouhi\",\"doi\":\"10.1007/s42154-023-00221-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study aims at developing an optimization framework for electric vehicle charging by considering different trade-offs between battery degradation and charging time. For the first time, the application of practical limitations on charging and cooling power is considered along with more detailed health models. Lithium iron phosphate battery is used as a case study to demonstrate the effectiveness of the proposed optimization framework. A coupled electro-thermal equivalent circuit model is used along with two battery health models to mathematically obtain optimal charging current profiles by considering stress factors of state-of-charge, charging rate, temperature and time. The optimization results demonstrate an improvement over the benchmark constant current–constant voltage (CCCV) charging protocol when considering both the charging time and battery health. A main difference between the optimal and the CCCV charging protocols is found to be an additional ability to apply constraints and adapt to initial conditions in the proposed optimal charging protocol. In a case study, for example, the ‘optimal time’ charging is found to take 12 min while the ‘optimal health’ charging profile suggests around 100 min for charging the battery from 25 to 75% state-of-charge. Any other trade-off between those two extreme cases is achievable using the proposed charging protocol as well.</p></div>\",\"PeriodicalId\":36310,\"journal\":{\"name\":\"Automotive Innovation\",\"volume\":\"6 2\",\"pages\":\"204 - 219\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2023-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s42154-023-00221-8.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Automotive Innovation\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s42154-023-00221-8\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automotive Innovation","FirstCategoryId":"1087","ListUrlMain":"https://link.springer.com/article/10.1007/s42154-023-00221-8","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}
A Model-Based Battery Charging Optimization Framework for Proper Trade-offs Between Time and Degradation
This study aims at developing an optimization framework for electric vehicle charging by considering different trade-offs between battery degradation and charging time. For the first time, the application of practical limitations on charging and cooling power is considered along with more detailed health models. Lithium iron phosphate battery is used as a case study to demonstrate the effectiveness of the proposed optimization framework. A coupled electro-thermal equivalent circuit model is used along with two battery health models to mathematically obtain optimal charging current profiles by considering stress factors of state-of-charge, charging rate, temperature and time. The optimization results demonstrate an improvement over the benchmark constant current–constant voltage (CCCV) charging protocol when considering both the charging time and battery health. A main difference between the optimal and the CCCV charging protocols is found to be an additional ability to apply constraints and adapt to initial conditions in the proposed optimal charging protocol. In a case study, for example, the ‘optimal time’ charging is found to take 12 min while the ‘optimal health’ charging profile suggests around 100 min for charging the battery from 25 to 75% state-of-charge. Any other trade-off between those two extreme cases is achievable using the proposed charging protocol as well.
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.