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.
Relaxation model of the open‐circuit voltage for state‐of‐charge estimation in lithium‐ion batteries
IET Electrical Systems in Transportation ; 3 , 4 ; 112-117
01.12.2013
6 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
lithium‐ion batteries , state‐of‐health , OCV , Li , long‐term rest method , secondary cells , SOC estimation , battery voltage relaxation model , open‐circuit voltage , charge‐depleting state , curve shape analysis , state‐of‐charge estimation , lithium , voltage relaxation process , adaptive model
Relaxation model of the open-circuit voltage for state-of-charge estimation in lithium-ion batteries
IET | 2013
|Open circuit voltage characterization of lithium-ion batteries
Tema Archiv | 2014
|