An All-Region State-of-Charge Estimator Based on Global Particle Swarm Optimization and Improved Extended Kalman Filter for Lithium-Ion Batteries

Abstract

In this paper, a novel model parameter identification method and a state-of-charge (SOC) estimator for lithium-ion batteries (LIBs) are proposed to improve the global accuracy of SOC estimation in the all SOC range (0–100%). Firstly, a subregion optimization method based on particle swarm optimization is developed to find the optimal model parameters of LIBs in each subregion, and the optimal number of subregions is investigated from the perspective of accuracy and computation time. Then, to solve the problem of a low accuracy of SOC estimation caused by large model error in the low SOC range, an improved extended Kalman filter (IEKF) algorithm with variable noise covariance is proposed. Finally, the effectiveness of the proposed methods are verified by experiments on two kinds of batteries under three working cycles, and case studies show that the proposed IEKF has better accuracy and robustness than the traditional extended Kalman filter (EKF) in the all SOC range.

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

“…PSO has been used to identify the model parameters of a Li-ion battery [180][181][182][183][184][185][186]. Recently, an improved EKF SOC estimator has been proposed in which PSO was utilized to identify the time varying parameters of the Li-ion battery [187]. Their proposed estimator produced a better result compared to the traditional EKF.…”

“…Sheikhan et al 2012 [178] ≤± 1.9% Aung et al 2015 [185] ME ≤ ± 3.35% Yu et al 2017 [183] Unspecified Ye et al 2017 [186] ME ≤ ± 1.0% Lai et al 2018 [187] ME ≤ ± 1.0%…”

Applications of Power Electronics

“…The reduction of battery cell inconsistency using a composite equalizer to improve overall system performance is addressed in [49]. Improvements of state-of-charge (SoC) estimation using optimization and proper filtering methods are introduced in [50]. Lastly, a review and future challenges of SoC estimation for lithium-ion batteries are provided in [51].…”

A Novel Composite Equalizer Based on an Additional Cell for Series-Connected Lithium-Ion Cells

“…As shown in Table 1, the charging time increases when charging with equalization, indicating that the capacity of the battery pack increases after charging with equalization. Our previous studies [33,34] show the relationship between pack capacity and cell capacities is:…”

“…Generally, the energy transfer between the cells is a function of the voltage difference between cells. As a result, when the voltage difference is low, the equalization speed decreases and cells can remain unbalanced [22,30,32], and the balancing efficiency needs to be further improved [33]. Through the analysis above, we know that both active and passive equalizers have their own advantages and disadvantages.…”