多層AI分析と品質工学MT法を用いた2次利用蓄電池の高精度迅速性能選別手法の提案

カテゴリ: 部門大会

論文No: 22

グループ名: 【B】令和4年電気学会電力・エネルギー部門大会

発行日: 2022/08/26

タイトル(英語): Proposal of High Accuracy and Rapid Performance Selection Method for 2nd Life Battery Using Multi-layer AI Analysis and MT System on Taguchi Method

著者名: 林田淳（北海道立総合研究機構），白土博康（北海道立総合研究機構），原亮一（北海道大学）

著者名(英語): Atsushi Hayashida (Hokkaido Research Organization), Hiroyasu Shirato (Hokkaido Research Organization), Ryoichi Hara (Hokkaido University)

キーワード: 2次利用蓄電池|性能選別|AI|性能ばらつき|クラスタリング|品質工学MTシステムMT法|2nd life battery|performance selection|AI|performance variation|clustering|MT system on Taguchi Method

要約(英語): Performance selection is key technology for renewable energy development using 2nd life battery which has a performance variation. Proposal method, which includes multi-layer AI analysis and MT system based on Taguchi method, determine whether the capacity, as the measure of battery performance, exceeds the threshold. The method analyzing internal impedance of 2nd life battery was able to select about 30 times faster than conventional method using discharge and as high accuracy as conventional one.

PDFファイルサイズ: 703 Kバイト