Voltage relaxation curve‐based state of charge estimation method with reduced measurement time

Abstract

This paper proposes a method for estimating a battery's State of Charge using voltage relaxation curves. This method offers advantages over the conventional State of Charge estimation methods by reducing the measurement time of the Open Circuit Voltage method and eliminating the need for specialized equipment required in Electrochemical Impedance Spectroscopy. The influence of battery parameters on voltage relaxation curve was analyzed through simulations, and based on this relationship, battery parameters were obtained by fitting the voltage relaxation curve. The State of Charge was estimated using the battery parameter look‐up table for each State of Charge prepared in advance, and the measurement time could be shortened through graph fitting for the initial section of the voltage relaxation curve. The proposed method allows for a reduction in measurement time compared to the traditional Open Circuit Voltage method, while achieving State of Charge estimation with an error rate of less than 5.00 percentage.

A Review of the Resourceful Utilization Status for Decommissioned Power Batteries

“…Among them, offline estimation has the advantages of simplicity and low computation, but it demands strict requirements on the test environment, and the experiments are too time-consuming. In recent years, researchers have proposed some online estimation methods based on offline estimation, such as the slip film observer method [37], voltage curve fitting method [38,39], neural network method [40], and fuzzy logic inference method [41,42], which can realize real-time online estimation of SOH. Nevertheless, SOH evaluation is still difficult due to the many factors affecting the SOH state, including ambient temperature, charge/discharge multiplier, depth of discharge, and charge/discharge cycle, and SOH is a highly nonlinear time-varying system [43].…”