Convolutional Neural Network-Based False Battery Data Detection and Classification for Battery Energy Storage Systems
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, H. | - |
dc.contributor.author | Kim, K. | - |
dc.contributor.author | Park, J. | - |
dc.contributor.author | Bere, G. | - |
dc.contributor.author | Ochoa, J.J. | - |
dc.contributor.author | Kim, T. | - |
dc.date.available | 2021-03-23T03:40:10Z | - |
dc.date.created | 2021-03-23 | - |
dc.date.issued | 2021-12 | - |
dc.identifier.issn | 0885-8969 | - |
dc.identifier.uri | http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/40715 | - |
dc.description.abstract | Battery energy storage systems (BESSs) rely on battery sensor data and communication. It is crucial to evaluate the trustworthiness of battery sensor and communication data in (BESS) since inaccurate battery data caused by sensor faults, communication failures, and even cyber-attacks can not only impose serious damages to BESSs, but also threaten the overall reliability of BESS-based applications (e.g., electric vehicles (EVs), power grids). This paper proposes a battery data trust framework that enables detect and classify false battery sensor data and communication data by using a deep learning algorithm. The proposed convolutional neural network (CNN)-based false battery data detection and classification (FBD<sup>2</sup>C) model could potentially improve safety and reliability of the BESSs. The proposed algorithm is validated by simulation and experimental results. IEEE | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.relation.isPartOf | IEEE Transactions on Energy Conversion | - |
dc.title | Convolutional Neural Network-Based False Battery Data Detection and Classification for Battery Energy Storage Systems | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/TEC.2021.3061493 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | IEEE Transactions on Energy Conversion, v.36, no.4, pp.3108 - 3117 | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000724528500053 | - |
dc.identifier.scopusid | 2-s2.0-85101754078 | - |
dc.citation.endPage | 3117 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 3108 | - |
dc.citation.title | IEEE Transactions on Energy Conversion | - |
dc.citation.volume | 36 | - |
dc.contributor.affiliatedAuthor | Park, J. | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.subject.keywordAuthor | Batteries | - |
dc.subject.keywordAuthor | Battery energy storage systems | - |
dc.subject.keywordAuthor | Circuit faults | - |
dc.subject.keywordAuthor | communication failure | - |
dc.subject.keywordAuthor | Convolution | - |
dc.subject.keywordAuthor | convolutional neural network | - |
dc.subject.keywordAuthor | cyber-attacks | - |
dc.subject.keywordAuthor | Data models | - |
dc.subject.keywordAuthor | deep learning | - |
dc.subject.keywordAuthor | false data inject attack | - |
dc.subject.keywordAuthor | fault diagnosis | - |
dc.subject.keywordAuthor | Safety | - |
dc.subject.keywordAuthor | sensor fault | - |
dc.subject.keywordAuthor | State of charge | - |
dc.subject.keywordAuthor | Temperature sensors | - |
dc.subject.keywordPlus | Classification (of information) | - |
dc.subject.keywordPlus | Convolution | - |
dc.subject.keywordPlus | Convolutional neural networks | - |
dc.subject.keywordPlus | Deep learning | - |
dc.subject.keywordPlus | Digital storage | - |
dc.subject.keywordPlus | Electric power transmission networks | - |
dc.subject.keywordPlus | Learning algorithms | - |
dc.subject.keywordPlus | Network security | - |
dc.subject.keywordPlus | Secondary batteries | - |
dc.subject.keywordPlus | Battery energy storage systems | - |
dc.subject.keywordPlus | Communication data | - |
dc.subject.keywordPlus | Communication failure | - |
dc.subject.keywordPlus | Cyber-attacks | - |
dc.subject.keywordPlus | Data detection | - |
dc.subject.keywordPlus | Electric Vehicles (EVs) | - |
dc.subject.keywordPlus | Sensor fault | - |
dc.subject.keywordPlus | Trust frameworks | - |
dc.subject.keywordPlus | Battery storage | - |
dc.relation.journalResearchArea | Energy & Fuels | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Energy & Fuels | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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