Overview of Lithium-Ion battery modeling methods for state-of-charge estimation in electrical vehicles

By Jinhao Meng, Guangzhao Luo, Mattia Ricco, Maciej Swierczynski, Daniel-Ioan Stroe, Remus Teodorescu. 2018

330 citations recorded by the source corpus.

As a critical indictor in the Battery Management System (BMS), State of Charge (SOC) is closely related to the reliable and safe operation of lithium-ion (Li-ion) batteries. Model-based methods are an effective solution for accurate and robust SOC estimation, the performance of which heavily relies on the battery model. This paper mainly focuses on battery modeling methods, which have the potential to be used in a model-based SOC estimation structure. Battery modeling methods are classified into four categories on the basis of their theoretical foundations, and their expressions and features are detailed. Furthermore, the four battery modeling methods are compared in terms of their pros and cons. Future research directions are also presented. In addition, after optimizing the parameters of the battery models by a Genetic Algorithm (GA), four typical battery models including a combined model, two RC Equivalent Circuit Model (ECM), a Single Particle Model (SPM), and a Support Vector Machine (SVM) battery model are compared in terms of their accuracy and execution time.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/48723f6791b3b0d70fba5233f088fdeac7ba13b4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

In Electrical and Electronic Engineering

Citations in the corpus

Advances in Batteries, Battery Modeling, Battery Management System, Battery Thermal Management, SOC, SOH, and Charge/Discharge Characteristics in EV Applications (2023, methodology): “Resistance-Capacitance (RC) network-based models are among the several ECM models explored in the literature that have found widespread use for online applications.”
Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries (2019, methodology): “The Shepherd model, Unnewehr universal model and Nernst model are the main categories of EM [28].”