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Comparative Study of the Influence of Open Circuit Voltage Tests on State of Charge Online Estimation for Lithium-Ion Batteries
- Source :
- IEEE Access, Vol 8, Pp 17535-17547 (2020)
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- The accurate state of charge (SoC) online estimation is a significant indicator that relates to driving ranges of electric vehicles (EV). The relationship between open circuit voltage (OCV) and SoC plays an important role in SoC estimation for lithium-ion batteries. To compare with the traditional incremental OCV (IO) test and the low current OCV (LO) test, a novel OCV test which combines IO test with LO test (CIL) is proposed in this paper. Based on the reliable parameters online identification of the dual polarization (DP) battery model, two SoC estimation algorithms are compared on the accuracy, robustness and convergence speed for the entire SoC region. Meanwhile, the comparative study of the three OCV-SoC relationships fits by the corresponding OCV tests is discussed in terms of the SoC online estimation under various temperatures. The results show that the adaptive extended Kalman filter (AEKF) algorithm can better improve the accuracy and robustness of SoC estimation than that of the extended Kalman filter (EKF) algorithm. Most importantly, the OCV-SoC relationship obtains from the CIL OCV test method is applied to the AEKF algorithm, which has higher accuracy and better statistical indices of SoC estimation, especially suitable for the low temperature.
- Subjects :
- Battery (electricity)
Lithium-ion batteries
General Computer Science
adaptive extended Kalman filter algorithm
Computer science
020209 energy
Statistical index
chemistry.chemical_element
02 engineering and technology
Hardware_PERFORMANCEANDRELIABILITY
Ion
Extended Kalman filter
Robustness (computer science)
Control theory
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
open circuit voltage test
state of charge estimation
Open-circuit voltage
General Engineering
021001 nanoscience & nanotechnology
online parameters identification
State of charge
chemistry
Lithium
lcsh:Electrical engineering. Electronics. Nuclear engineering
0210 nano-technology
lcsh:TK1-9971
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....66b884a8f431ce7cf6546e5b2a27c600