CHARGING STATE ESTIMATION DEVICE FOR SECONDARY BATTERY, ABNORMALITY DETECTION DEVICE, AND MANAGEMENT SYSTEM FOR SECONDARY BATTERY

• Main Authors: TOYOTAKA KOHEI, TAKAHASHI KEI
• Format: Patent
• Language: English; Japanese
• Published: 29.08.2019
• Subjects: BASIC ELECTRIC ELEMENTS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER; ELECTRICITY; GENERATION; MEASURING; MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES; PHYSICS; PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSIONOF CHEMICAL INTO ELECTRICAL ENERGY; SYSTEMS FOR STORING ELECTRIC ENERGY; TESTING

To provide a management system for a secondary battery which also predicts other parameters (e.g.internal resistance, SOC) with high accuracy while performing abnormality detection.SOLUTION: A management system for a secondary battery estimates an internal resistance and SOC of the secondary battery by performing computational processing using a regression model (regressive formula), such as regression analysis, Kalman filter or multiple regression analysis as a method for estimating the internal resistance and the SOC, while correcting any prediction errors determined to be abnormal into normal predication errors without directly inputting them to the Kalman filter, so as to enhance accuracy in estimation at calculation of the internal resistance and the SOC for the secondary battery, without using abnormal values.SELECTED DRAWING: Figure 1 【課題】異常検知をおこないつつ、他のパラメータ（内部抵抗やＳＯＣなど）も高い精度で予測する二次電池の管理システムを提供する。【解決手段】二次電池の内部抵抗及びＳＯＣを推定する方法として、回帰モデル（回帰的な式）、例えば、回帰分析や、カルマンフィルタや、重回帰分析で計算処理して内部抵抗やＳＯＣを推定する。異常と判断した予測誤差をそのままカルマンフィルタに入力せずに正常な予測誤差に修正する。異常値を用いず二次電池の内部抵抗及びＳＯＣを算出することで推定の精度を高める。【選択図】図１