Abstract:

A traditional state of health (SoH) estimation method was proposed based on online big data online platform to break through the limitations of SoH estimation methods caused by insufficient battery management system (BMS) storage and computing power. The effects of data discrete characteristics and battery cell
consistency on the method were studied. The method was integrated into specific big-data platform, and the batteries’ SoH decrease were verified in muti-dimensions such as different vehicle brands, different locations and different time. The results show that this method can effectively estimate SoH of single power battery system and its variation, as well as integrate within other data in muti-dimensions and analyze the big data image of power batteries.

Key words: power battery , capacity decrease , state of health (SoH) ,  big data