End-of-discharge prediction for satellite lithium-ion battery based on evidential reasoning rule

IF 0.5 4区 物理与天体物理 Q4 ASTRONOMY & ASTROPHYSICS Open Astronomy Pub Date : 2022-01-01 DOI:10.1515/astro-2022-0031
Dao Zhao, Zhijie Zhou, P. Zhang, Yijun Zhang, Haibin Qin, Shan Gao
{"title":"End-of-discharge prediction for satellite lithium-ion battery based on evidential reasoning rule","authors":"Dao Zhao, Zhijie Zhou, P. Zhang, Yijun Zhang, Haibin Qin, Shan Gao","doi":"10.1515/astro-2022-0031","DOIUrl":null,"url":null,"abstract":"Abstract To ensure the safety of the power supply for an in-orbit satellite, it is of great significance to accurately predict the end-of-discharge time of lithium-ion batteries for making a reasonable flight plan. Constrained by development time and experimental environment, it is usually difficult to obtain many full discharge voltage curves of satellite batteries from ground experiments as historical data. Because of insufficient data, the prediction accuracy of the single time series prediction method is low. To solve this problem, this paper takes the voltage of the discharge process as the time series and uses the evidential reasoning rule algorithm to fuse the outputs of three typical prediction models to improve the prediction accuracy. The result can be expressed as a form of belief degree distribution with the ability to express uncertainty. Using the NASA battery dataset, the effectiveness of the proposed method is verified, and the end-of-discharge of an in-orbit satellite battery is predicted by the telemetry data.","PeriodicalId":19514,"journal":{"name":"Open Astronomy","volume":"31 1","pages":"256 - 267"},"PeriodicalIF":0.5000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Astronomy","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1515/astro-2022-0031","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ASTRONOMY & ASTROPHYSICS","Score":null,"Total":0}
引用次数: 1

Abstract

Abstract To ensure the safety of the power supply for an in-orbit satellite, it is of great significance to accurately predict the end-of-discharge time of lithium-ion batteries for making a reasonable flight plan. Constrained by development time and experimental environment, it is usually difficult to obtain many full discharge voltage curves of satellite batteries from ground experiments as historical data. Because of insufficient data, the prediction accuracy of the single time series prediction method is low. To solve this problem, this paper takes the voltage of the discharge process as the time series and uses the evidential reasoning rule algorithm to fuse the outputs of three typical prediction models to improve the prediction accuracy. The result can be expressed as a form of belief degree distribution with the ability to express uncertainty. Using the NASA battery dataset, the effectiveness of the proposed method is verified, and the end-of-discharge of an in-orbit satellite battery is predicted by the telemetry data.
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
基于证据推理规则的卫星锂离子电池放电终期预测
摘要为保证在轨卫星供电安全,准确预测锂离子电池放电结束时间对于制定合理的飞行计划具有重要意义。由于研制时间和实验环境的限制,卫星电池的许多完全放电电压曲线作为历史数据很难从地面实验中得到。由于数据不足,单一时间序列预测方法的预测精度较低。针对这一问题,本文以放电过程的电压为时间序列,采用证据推理规则算法对三种典型预测模型的输出进行融合,以提高预测精度。结果可以表示为具有不确定性表达能力的置信度分布形式。利用NASA电池数据验证了所提方法的有效性,并利用遥测数据预测了在轨卫星电池的终放电时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Open Astronomy
Open Astronomy Physics and Astronomy-Astronomy and Astrophysics
CiteScore
1.30
自引率
14.30%
发文量
37
审稿时长
16 weeks
期刊介绍: The journal disseminates research in both observational and theoretical astronomy, astrophysics, solar physics, cosmology, galactic and extragalactic astronomy, high energy particles physics, planetary science, space science and astronomy-related astrobiology, presenting as well the surveys dedicated to astronomical history and education.
期刊最新文献
A novel autonomous navigation constellation in the Earth–Moon system Asteroids discovered in the Baldone Observatory between 2017 and 2022: The orbits of asteroid 428694 Saule and 330836 Orius Intelligent collision avoidance strategy for all-electric propulsion GEO satellite orbit transfer control Stability of granular media impacts morphological characteristics under different impact conditions Parallel observations process of Tianwen-1 orbit determination
×
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