Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation

Abstract Accurate capacity estimation is crucial for the reliable and safe operation of lithium-ion batteries. A transfer learning model is then developed by adding a featured linear transformation to the base model.

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• 1 In particular, exploiting the relaxation voltage curve features could enable battery capacity estimation without additional cycling information.
• 2 Here, we report the study of three datasets comprising 130 commercial lithium-ion cells cycled under various conditions to evaluate the capacity estimation approach.
• 3 One dataset is collected for model building from batteries with LiNi 0.86 Co 0.11 Al 0.03 O 2 -based positive electrodes.

This work deepens our understanding of the fundamental laws governing the universe, from subatomic particles to cosmic structures.

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