Open AccessRelaxation model of the open‐circuit voltage for state‐of‐charge estimation in lithium‐ion batteries
Author(s) -
Pei Lei,
Lu Rengui,
Zhu Chunbo
Publication year - 2013
Publication title -
iet electrical systems in transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.588
H-Index - 26
ISSN - 2042-9746
DOI - 10.1049/iet-est.2013.0020
Subject(s) - state of charge , open circuit voltage , battery (electricity) , voltage , relaxation (psychology) , lithium ion battery , state of health , equivalent circuit , control theory (sociology) , engineering , lithium (medication) , electrical engineering , materials science , computer science , power (physics) , physics , thermodynamics , medicine , psychology , social psychology , endocrinology , control (management) , artificial intelligence
The open‐circuit voltage (OCV) of batteries is a crucial characteristic parameter that reflects many aspects of a battery's performance, such as capacity, state‐of‐charge (SOC) and state‐of‐health. OCV is most widely used to determine the SOC when the battery works in a charge‐depleting state. However, the application of the OCV to SOC estimation can be difficult because of the need for a long rest time for full relaxation. In this study, based on the analysis on the curve shape of battery voltage relaxation, a new adaptive model for simulating the voltage relaxation process is developed to predict the final static OCV in a few minutes instead of via the traditional long‐term rest method. Avoiding this disadvantage, the SOC can be deduced from the predicted OCV via the corresponding relationship obtained in a short amount of time. A working condition experiment is performed to validate the new methods and the results are very accurate.