Improved ANN for Estimation of Power Consumption of EV for Real-Time Battery Diagnosis

カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門（英文）

発行日: 2019/05/01

タイトル(英語): Improved ANN for Estimation of Power Consumption of EV for Real-Time Battery Diagnosis

著者名: Minella Bezha (Doshisha University, Graduate School of Science and Engineering, Power System Analysis Laboratory), Naoto Nagaoka (Doshisha University, Graduate School of Science and Engineering, Power System Analysis Laboratory)

著者名(英語): Minella Bezha (Doshisha University, Graduate School of Science and Engineering, Power System Analysis Laboratory), Naoto Nagaoka (Doshisha University, Graduate School of Science and Engineering, Power System Analysis Laboratory)

キーワード: ANN，electric vehicle (EV)，lithium-ion battery (Li-Ion)，state of charge (SOC) estimation，fast adaptive estimation

要約(英語): In this paper, an artificial neural network (ANN), which estimates the power consumption of an electric vehicle (EV) during the deterioration process of power storage is described. This network provides important information for real-time battery diagnosis, such as state of charge of a Li-Ion battery for an EV or HEV. The data are retrieved from a scaled experiment, based on the JC08 test cycle. The network is presented as a practical alternative to analytical and empirical methods. It can predict the power consumption by an optimal solution and categorize the deterioration of the power storage with high estimation precision and within short time.

本誌: IEEJ Journal of Industry Applications Vol.8 No.3 （2019） Special Issue on “IPEC-Niigata 2018”

本誌掲載ページ: 532-538 p

原稿種別: 論文／英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejjia/8/3/8_532/_article/-char/ja/