A New Health Assessment Approach of Lithium-Ion Batteries Under Variable Operation Conditions

Abstract

The monitoring information of the Lithium-ion batteries is influenced by variable operation conditions. Many health assessment approaches acquire the battery monitoring information to assess the battery health status. However, these approaches have poor adaptability under variable operation conditions. This paper presents a new health assessment approach of the Lithium-ion batteries under variable operation conditions. Specifically, it extracts the geometrical characteristics of charging and discharging curves of the lithium-ion batteries. Furthermore, it adapts a multiple dimensionality reduction approach based on the locally linear embedding and Isomap. Moreover, the synthetical correlation coefficient is proposed to evaluate the ability of the method to be immune to variable operation conditions. Finally, the example illustrates the effectiveness of the proposed method.