Performance Comparison of Long Short-Term Memory and a Temporal Convolutional Network for State of Health Estimation of a Lithium-Ion Battery using Its Charging Characteristics

Performance Comparison of Long Short-Term Memory and a Temporal Convolutional Network for State of Health Estimation of a Lithium-Ion Battery using Its Charging Characteristics

The market for eco-friendly batteries is increasing owing to population growth, environmental pollution, and energy crises. The widespread application of lithium-ion batteries necessitates their state of health (SOH) estimation, which is a popular and difficult area of research. In general, the capa...

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Bibliographic Details
Main Authors:	Bi, J. (Author), Lee, J.-C (Author), Liu, H. (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	Brain Charging (batteries) charging properties Charging property Convolution Energy policy Health Ions Lithium ions lithium-ion Lithium-ion batteries Long short-term memory long short-term memory (LSTM) Performance comparison Population statistics Remaining useful life remaining useful life (RUL) Remaining useful lives State of health state of health (SOH) Temporal convolution network temporal convolution network (TCN) Testing Time series Times series
Online Access:	View Fulltext in Publisher

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