A Novel Battery State of Health Estimation Method Based on Outlier Detection Algorithm

Abstract

-A novel battery SOH estimation algorithm based on outlier detection has been presented.The Battery state of health (SOH) is one of the most important parameters that describes the usability state of the power battery system. Firstly, a battery system model with lifetime fading characteristic was established, and the battery characteristic parameters were acquired from the lifetime fading process. Then, the outlier detection method based on angular distribution was used to identify the outliers among the battery behaviors. Lastly, the functional relationship between battery SOH and the outlier distribution was obtained by polynomial fitting method. The experimental results show that the algorithm can identify the outliers accurately, and the absolute error between the SOH estimation value and true value is less than 3%.

A Review on State of Health Estimation for Lithium-ion Batteries

“…Hu extracted sample entropy of voltage sequence under hybrid pulse power characterization profile, and then calculating SOH by a cubic function [27]. Piao tested battery under economic commission for Europe and extra urban driving cycle, and determined the abnormal points in the operation data based on the angular distribution outlier detection method so as to estimate SOH [28]. The above methods all apply special profile on battery, but these methods are impractical for on-board circumstance due to the lack of testing equipment.…”