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リチウムイオン蓄電池の常時状態解析技術に関する研究
立命館大学・理工学研究科・電子システム専攻
・研究背景
EVや据え置きなどにより高容量LIBの需要が拡大
問題点:発火の危険性 高価
電池の内部状態を常時知ることで劣化や異常を
解析、検知し実現可能
より長くより安全に運用
・交流インピーダンス解析
交流インピーダンス値から等価回路を
推定し内部状態を推定する手法
推
定
測定データ
・課題:組み込み化と測定時間
(内部状態を知る手段の一つ)
・組み込み化
大規模な測定装置と恒温槽が必要 専用LSIの開発
温度補正
・実際の機器に搭載できる
コストとサイズ
・劣化による変化解析のため
測定温度による変化を補正
企業との共同研究
補正
組込み可能な
コストとサイズ
恒温槽なし(自由な測定温度で)
・測定時間短縮
測定時間がトータルで1時間近くかかる
高周波ー>高速
低周波ー>測定時間大
高周波
既存方法
低周波
別手法(RLS)
高速かつ広域で正確な値の取得
・別手法(RLS)の利点と欠点 RLS:逐次最小二乗法
+駆動波形からの推定
(計測時間なし、組み込みが容易)
-高周波の推定は困難
-高精度化が困難
原因
予想
回路モデルの精度
駆動波形への依存性
駆動波形の特性(周波数)を解析することで高精度化を図れるのでは….
2つを
組み合
わせる
企業が開発
自身が開発
RLSによる同定の特性
・電流値(指令値)をスペクトル解析
・その周波数の値のみ取り出す
・RLSで拡散、それ以外を周波数掃引で計測
実験結果 上記のバラバラなデータ
に比べほぼ一致
推定値(半円)がバラバラ
真値に近い点
が抜き出せる
まとめ
今後の展望
・専用LSIと温度補償のシステムを構築
・RLSとの組み合わせにより測定時間の短縮(数十秒)を実現
・劣化の解析利用の具体化を行い残価値推定、残寿命推定、異常
検知を行うシステムの構築
リアルタイムデータ取得システムの実現
劣化データの測定
2021年
春
2021年
夏
2021年
秋
解析の実装
評価・検証・改善
国内2件
国際1件
特許出願1件

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