A Review of SOH Estimation Methods in Lithium-ion Batteries for Electric Vehicle Applications

By Cheng Lin, A. Tang, Wenwei Wang. 2015

150 citations recorded by the source corpus.

Abstract Aging of lithium-ion cells is an inevitable phenomenon limiting the lifetime in electric vehicle (EV) applications. Undesirable side reactions during cycle or calendar aging may affect the performance of the batteries. This results in a decreased capacity and an increase in the cell impedance. Furthermore, the aging phenomena are highly complicated to characterize due to the coupling of different factors. In this review, various aspects of recent research and developments, on lithium-ion battery aging mechanisms, analysis and estimations are put forward. To better understand a comparison and summary of techniques, models and algorithms used for battery aging estimation (SOH,RUL), going from a detailed spectroscopy and electrochemical technique to statistical methods based on data are presented in this paper, and their respective characteristics are discussed. In addition some considerations about the ideal method that can be derived from existing methods should be discussed and reported in this paper.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8eb1ac4347f1a3b2836c284fba9009c516519667

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. Moh Yamani Idna Idris
2. Saad Mekhilef
3. Prashant Shrivastava
4. Tey Kok Soon

In Electrical and Electronic Engineering

1. Moh Yamani Idna Idris
2. Saad Mekhilef
3. Prashant Shrivastava
4. Tey Kok Soon
5. Yousef A. Mahmoud
6. Ehab F. El-Saadany
7. Mohamed A. Abdelwahed
8. Zengshi Chen

Citations in the corpus

• Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries (2019, methodology): “In this work, the four commonly used types (CCM, OCVM, MBM and MLM) of online SOC estimation methods were reviewed.”
• Advances in Batteries, Battery Modeling, Battery Management System, Battery Thermal Management, SOC, SOH, and Charge/Discharge Characteristics in EV Applications (2023, unknown): “method known as current pulse [220], [221].”