Data-Driven ICA-Bi-LSTM-Combined Lithium Battery SOH Estimation

• Published in: Mathematical problems in engineering Vol. 2022; pp. 1 - 8
• Main Authors: Sun, Hanlei, Sun, Jianrui, Zhao, Kun, Wang, Licheng, Wang, Kai
• Format: Journal Article
• Language: English
• Published: New York Hindawi 28.03.2022; John Wiley & Sons, Inc
• Subjects: Accuracy; Aging; Artificial neural networks; Back propagation; Back propagation networks; Battery chargers; Charging; Correlation coefficients; Deep learning; Electric potential; Energy; Engineering; Lithium; Lithium batteries; Lithium-ion batteries; Machine learning; Mathematical models; Methods; Neural networks; Parameters; Power; Random variables; Rechargeable batteries; Recurrent neural networks; Standard deviation; Support vector machines; Voltage

Lithium battery state of health (SOH) is a key parameter to characterize the actual battery life. SOH cannot be directly measured. In order to further improve the accuracy of SOH estimation of lithium batteries, a model combining incremental capacity analysis (ICA) and bidirectional long- and short-...