A Novel Methodology for Estimating State-Of-Charge of Li-Ion Batteries Using Advanced Parameters Estimation

Abstract

State-of-charge (SOC) estimations of Li-ion batteries have been the focus of many research studies in previous years. Many articles discussed the dynamic model's parameters estimation of the Li-ion battery, where the fixed forgetting factor recursive least square estimation methodology is employed. However, the change rate of each parameter to reach the true value is not taken into consideration, which may tend to poor estimation. This article discusses this issue, and proposes two solutions to solve it. The first solution is the usage of a variable forgetting factor instead of a fixed one, while the second solution is defining a vector of forgetting factors, which means one factor for each parameter. After parameters estimation, a new idea is proposed to estimate state-of-charge (SOC) of the Li-ion battery based on Newton's method. Also, the error percentage and computational cost are discussed and compared with that of nonlinear Kalman filters. This methodology is applied on a 36 V 30 A Li-ion pack to validate this idea. Keywords: dynamic model of Li-ion battery; variable forgetting factor recursive least square (RLS) estimator; multiple forgetting factors RLS estimator; state-of-charge (SOC) estimation using Newton's method

Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation

“…The RLS and its variants have been used widely to determine the parameters of Li-ion battery model [124][125][126][127][128][129][130][131][132][133]. The RLS has been applied to identify the characteristic of the battery for a 1 st order ECM [124,129,132].…”

“…The fading KF (FKF) was also implemented for SOC estimation [126]. The exponential and variable forgetting factor RLS methods were also used to estimate the SOC [127,128,130]. Table 11 lists the performance of the RLS SOC estimation method.…”

“…Table 11 lists the performance of the RLS SOC estimation method. [128] ≤± 3% Duong et al 2017 [129] ≤± 1.8% Xia et al 2017 [130] ≤± 1.41% Ali et al 2018 [132] ≤± 1.93% Zhang et al 2018 [133] ≤± 1%…”

Simulation of the lithium-ion accumullator pulse discharge mode

“…Recommended Одна из наиболее зарекомендовавших себя схем замещения аккумуляторного элемента [5][6][7] представлена на рис. 1, где U ocv -напряжение разомкнутой цепи (НРЦ); R int -внутреннее омическое сопротивление; C PA , R PA -емкость и сопротивление активационной поляризации, соответственно; C PC , R PC -емкость и сопротивление концентрационной поляризации соответственно; U T -напряжение на выводах батареи.…”

On the Compatibility of Electric Equivalent Circuit Models for Enhanced Flooded Lead Acid Batteries Based on Electrochemical Impedance Spectroscopy

“…EEC models consist only from simple electric elements have been considered in the literature both for lead acid batteries [22,23] and for other chemistries [13,[27][28][29] as well. In addition to SOC and SOH estimations there are applications of these models as a thermal model for batteries [30].…”