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Method for predicting state of health of battery based on numerical simulation data

机译:基于数值模拟数据的电池健康状态预测方法

摘要

The present invention relates to a method for predicting the state of health of a battery based on numerical simulation data. A method for predicting the state of health of a battery, which is performed by a battery management system, according to an embodiment of the present invention includes: a step of obtaining a verified numerical simulation database, into which solution data of the battery is extracted and stored, when a numerical analysis result is verified by an experimental result using electrical and chemical analysis of the battery; a step of counting the number of charges or discharges when a deviation between reference data read from the verified numerical simulation database and measurement data read from the battery is within a preset range and battery capacity satisfies a preset condition; and a step of predicting a state of health of the battery using the number of charges or discharges and a classifier based on a learned machine learning algorithm.
机译:本发明涉及一种基于数值模拟数据来预测电池的健康状态的方法。根据本发明的实施例的由电池管理系统执行的用于预测电池的健康状态的方法包括:获得验证的数值模拟数据库的步骤,其中提取了电池的溶液数据。当使用电池的电和化学分析通过实验结果验证数值分析结果时,将其存储;当从验证的数值模拟数据库读取的参考数据与从电池读取的测量数据之间的偏差在预设范围内并且电池容量满足预设条件时,对充电或放电次数进行计数的步骤;以及使用充电或放电的次数和基于学习的机器学习算法的分类器来预测电池的健康状态的步骤。

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