用于在线指示的汽车电池SoH统计建模

N. Khare, S. Chandra, R. Govil
{"title":"用于在线指示的汽车电池SoH统计建模","authors":"N. Khare, S. Chandra, R. Govil","doi":"10.1109/INTLEC.2008.4664086","DOIUrl":null,"url":null,"abstract":"Battery health is always a challenge for heavy mobile or any portable system, as it is one of the prime factors affecting the system reliability. An indication of remaining battery life facilitates timely action taken proactively in alarming conditions, reducing the risk of running into a disaster. State of health (SoH) of battery is defined as remaining life of the battery to support load in question. Normally, the SoH of a battery is modeled as Ampere- hour (Ah) capacity with the age of the battery where terminal voltage is the only observable parameter employed in the model. This dose not provides an overall behavior model and not at all advisable to rely on in case of critical applications. In the present paper we propose a statistical modeling technique which uses stepwise regression on discharge profile of automotive battery to model SoH of the battery as a function of ageing and on- time (run- time) consumption. Ageing can be inferred from battery parameters such as Internal Resistance (IR), Terminal Voltage (OCV) and Specific Gravity (SG). These parameters are not independent and have problem of autocorrelation. An attempt has been made to develop a model free from the problem of autocorrelation and which provides a clue to the relative importance of each of the parameters in modeling the behavior of dependent variables. The objective of the study is to develop an online device to indicate the SoH of an automotive battery with the use of optimum observation needs.Run-time consumption can be seen from the discharged ampere-hour (A-h) capacity and ageing can be inferred from various slopes of battery parameters such as internal resistance, terminal voltage and specific gravity. The regression model when employed on discharge profile of automobile battery indicates correlation between these battery parameters (variables). The paper covers stepwise regression, effect of interaction between dependent variables on the model and autocorrelation effect on the model of SoH of a battery. This work is an attempt to design & develop an online device to indicate SoH of battery which can be put on the panel of an automobile to enable to actuate a preventive action.","PeriodicalId":431368,"journal":{"name":"INTELEC 2008 - 2008 IEEE 30th International Telecommunications Energy Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Statistical modeling of SoH of an automotive battery for online indication\",\"authors\":\"N. Khare, S. Chandra, R. Govil\",\"doi\":\"10.1109/INTLEC.2008.4664086\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Battery health is always a challenge for heavy mobile or any portable system, as it is one of the prime factors affecting the system reliability. An indication of remaining battery life facilitates timely action taken proactively in alarming conditions, reducing the risk of running into a disaster. State of health (SoH) of battery is defined as remaining life of the battery to support load in question. Normally, the SoH of a battery is modeled as Ampere- hour (Ah) capacity with the age of the battery where terminal voltage is the only observable parameter employed in the model. This dose not provides an overall behavior model and not at all advisable to rely on in case of critical applications. In the present paper we propose a statistical modeling technique which uses stepwise regression on discharge profile of automotive battery to model SoH of the battery as a function of ageing and on- time (run- time) consumption. Ageing can be inferred from battery parameters such as Internal Resistance (IR), Terminal Voltage (OCV) and Specific Gravity (SG). These parameters are not independent and have problem of autocorrelation. An attempt has been made to develop a model free from the problem of autocorrelation and which provides a clue to the relative importance of each of the parameters in modeling the behavior of dependent variables. The objective of the study is to develop an online device to indicate the SoH of an automotive battery with the use of optimum observation needs.Run-time consumption can be seen from the discharged ampere-hour (A-h) capacity and ageing can be inferred from various slopes of battery parameters such as internal resistance, terminal voltage and specific gravity. The regression model when employed on discharge profile of automobile battery indicates correlation between these battery parameters (variables). The paper covers stepwise regression, effect of interaction between dependent variables on the model and autocorrelation effect on the model of SoH of a battery. This work is an attempt to design & develop an online device to indicate SoH of battery which can be put on the panel of an automobile to enable to actuate a preventive action.\",\"PeriodicalId\":431368,\"journal\":{\"name\":\"INTELEC 2008 - 2008 IEEE 30th International Telecommunications Energy Conference\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"INTELEC 2008 - 2008 IEEE 30th International Telecommunications Energy Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INTLEC.2008.4664086\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"INTELEC 2008 - 2008 IEEE 30th International Telecommunications Energy Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTLEC.2008.4664086","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

摘要

电池健康一直是重型移动或任何便携式系统面临的挑战,因为它是影响系统可靠性的主要因素之一。电池剩余寿命的指示有助于在警报条件下及时采取主动行动,降低发生灾难的风险。电池的健康状态(SoH)定义为电池支持相关负载的剩余寿命。通常,电池的SoH被建模为安培小时(Ah)容量与电池的年龄,其中终端电压是模型中唯一可观察的参数。这并不能提供一个整体的行为模型,在关键应用程序的情况下,完全不建议依赖它。在本文中,我们提出了一种统计建模技术,利用逐步回归对汽车电池的放电曲线,将电池的SoH作为老化和运行时消耗的函数进行建模。老化可以从电池的内阻(IR)、终端电压(OCV)和比重(SG)等参数来推断。这些参数不是相互独立的,存在自相关问题。人们试图建立一个不存在自相关问题的模型,该模型为因变量行为建模中每个参数的相对重要性提供了线索。本研究的目的是开发一种在线装置,以显示汽车电池的SoH,并使用最佳观察需求。从放电的安培小时(A-h)容量可以看出运行消耗,从电池内阻、端电压、比重等参数的各种斜率可以推断老化。将回归模型应用于汽车电池的放电曲线,表明了这些电池参数(变量)之间的相关性。本文讨论了逐步回归、因变量间相互作用对模型的影响以及自相关对电池SoH模型的影响。本工作是尝试设计和开发一种在线显示电池SoH的装置,该装置可以放置在汽车面板上,以便启动预防措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical modeling of SoH of an automotive battery for online indication
Battery health is always a challenge for heavy mobile or any portable system, as it is one of the prime factors affecting the system reliability. An indication of remaining battery life facilitates timely action taken proactively in alarming conditions, reducing the risk of running into a disaster. State of health (SoH) of battery is defined as remaining life of the battery to support load in question. Normally, the SoH of a battery is modeled as Ampere- hour (Ah) capacity with the age of the battery where terminal voltage is the only observable parameter employed in the model. This dose not provides an overall behavior model and not at all advisable to rely on in case of critical applications. In the present paper we propose a statistical modeling technique which uses stepwise regression on discharge profile of automotive battery to model SoH of the battery as a function of ageing and on- time (run- time) consumption. Ageing can be inferred from battery parameters such as Internal Resistance (IR), Terminal Voltage (OCV) and Specific Gravity (SG). These parameters are not independent and have problem of autocorrelation. An attempt has been made to develop a model free from the problem of autocorrelation and which provides a clue to the relative importance of each of the parameters in modeling the behavior of dependent variables. The objective of the study is to develop an online device to indicate the SoH of an automotive battery with the use of optimum observation needs.Run-time consumption can be seen from the discharged ampere-hour (A-h) capacity and ageing can be inferred from various slopes of battery parameters such as internal resistance, terminal voltage and specific gravity. The regression model when employed on discharge profile of automobile battery indicates correlation between these battery parameters (variables). The paper covers stepwise regression, effect of interaction between dependent variables on the model and autocorrelation effect on the model of SoH of a battery. This work is an attempt to design & develop an online device to indicate SoH of battery which can be put on the panel of an automobile to enable to actuate a preventive action.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信