Li-ion battery parameter identification with low pass filter for measurement noise rejection

Abstract

The advent of Energy Management (EM) and Electric Vehicles (EV) have completely changed the use of batteries. Accurately estimating the remaining power in batteries has become increasingly important. In order to estimate precise battery state of charge (SOC)/state of health (SOH) value, accurate parameter identification is essential when constructing an accurate battery model. Even though we are able to exactly identify battery parameters offline, the precision of online parameter identification usually suffers from measurement noise, which is an unavoidable phenomenon. In this paper we investigate how battery parameter identification is influenced by measurement noise. The selection of a low pass filter is also discussed and a fourth order Butterworth filter is adopted to effectively reject high frequency measurement noise. This algorithm can help with the identification of battery parameter that rejects measurement noise and maintains the accuracy of online battery parameter identification for future online model-based battery SOC/SOH estimation.