The State of Charge Estimating Methods for Battery: A Review

By Wen-Yeau Chang. 2013

641 citations recorded by the source corpus.

An overview of new and current developments in state of charge (SOC) estimating methods for battery is given where the focus lies upon mathematical principles and practical implementations. As the battery SOC is an important parameter, which reflects the battery performance, so accurate estimation of SOC cannot only protect battery, prevent overcharge or discharge, and improve the battery life, but also let the application make rationally control strategies to achieve the purpose of saving energy. This paper gives a literature survey on the categories and mathematical methods of SOC estimation. Based on the assessment of SOC estimation methods, the future development direction of SOC estimation is proposed.

Subfields: Automotive Engineering, Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4d9a5210c0c4c0dbd152709cc112515c490629d7

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

1. Najoua Essoukri Ben Amara
2. Bilal Manai
3. Sabeur Jemmali
4. Ines Baccouche
5. Noshin Omar

In Control and Systems Engineering

1. Najoua Essoukri Ben Amara
2. Bilal Manai
3. Sabeur Jemmali
4. Ines Baccouche
5. Noshin Omar

In Electrical and Electronic Engineering

1. Najoua Essoukri Ben Amara
2. Bilal Manai
3. Sabeur Jemmali
4. Ines Baccouche
5. Noshin Omar

Citations in the corpus

• Improved OCV Model of a Li-Ion NMC Battery for Online SOC Estimation Using the Extended Kalman Filter (2017, methodology): “The Principle of EKF Kalman filtering is an adaptive technique consisting of estimating a nonlinear dynamical system state, used in several fields for the purpose of tracking, navigation and control [8].”