基于神经网络的锂离子电池参数估计

2017 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS) Pub Date : 2017-04-01 DOI:10.1109/WITS.2017.7934652

Younes Boujoudar, H. Hemi, Hassan El Moussaoui, H. El Markhi, T. Lamhamdi

{"title":"基于神经网络的锂离子电池参数估计","authors":"Younes Boujoudar, H. Hemi, Hassan El Moussaoui, H. El Markhi, T. Lamhamdi","doi":"10.1109/WITS.2017.7934652","DOIUrl":null,"url":null,"abstract":"This paper presents an offline parameters estimations for a Lithium-ion (Li-ion) battery. Neural Network (NN) has been used to estimate Li-ion battery parameters using an experimental charge and discharge tests at different temperatures between 24°C and 40°C provided by NASA [1].","PeriodicalId":147797,"journal":{"name":"2017 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Li-ion battery parameters estimation using neural networks\",\"authors\":\"Younes Boujoudar, H. Hemi, Hassan El Moussaoui, H. El Markhi, T. Lamhamdi\",\"doi\":\"10.1109/WITS.2017.7934652\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an offline parameters estimations for a Lithium-ion (Li-ion) battery. Neural Network (NN) has been used to estimate Li-ion battery parameters using an experimental charge and discharge tests at different temperatures between 24°C and 40°C provided by NASA [1].\",\"PeriodicalId\":147797,\"journal\":{\"name\":\"2017 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WITS.2017.7934652\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WITS.2017.7934652","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 4

摘要

提出了一种锂离子(Li-ion)电池离线参数估计方法。神经网络(Neural Network, NN)已被用于估算锂离子电池参数，通过NASA提供的24°C - 40°C不同温度下的实验性充放电测试[1]。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Li-ion battery parameters estimation using neural networks

This paper presents an offline parameters estimations for a Lithium-ion (Li-ion) battery. Neural Network (NN) has been used to estimate Li-ion battery parameters using an experimental charge and discharge tests at different temperatures between 24°C and 40°C provided by NASA [1].

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

2017 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS)

自引率

0.00%

发文量