| Issue |
E3S Web of Conf.
Volume 406, 2023
2023 9th International Conference on Energy Materials and Environment Engineering (ICEMEE 2023)
|
|
|---|---|---|
| Article Number | 02040 | |
| Number of page(s) | 4 | |
| Section | Energy Conservation Technology and Energy Sustainability | |
| DOI | https://doi.org/10.1051/e3sconf/202340602040 | |
| Published online | 31 July 2023 | |
Extended Kalman Filter-Based SOC Estimation for Lithium Battery Packs
Anhui Water Conservancy Technical College, 18 Hema Road, Feidong County, Hefei City, Anhui Province, China
* Corresponding author: 260714155@qq.com
With the continuous reduction of energy and aggravation of environmental damage, the wind and solar complementary power generation system has received wide attention, among which the lithium battery pack is one of the most concerned components of the whole system. Accurate and effective estimation of the state of charge (SOC) of lithium battery pack not only can ensure the rational use of resources and reduce costs, but also ensure the safe and reliable operation of the system. Since the normal operation of Li-ion battery pack has strong nonlinearity, a general nonlinear equivalent circuit model is selected, the charge/discharge multiplier and ambient temperature are fully considered, the Fourier function is used to effectively fit the model parameters, and the extended Kalman filter algorithm (EKF) is used to dynamically estimate the SOC of Li-ion battery pack in combination with the traditional ampere-time integration method, and the simulation is verified by MATLAB software. The results show that the extended Kalman filter algorithm selected in the paper can effectively track the SOC of the lithium battery pack and control the tracking error below 1%.
© The Authors, published by EDP Sciences, 2023
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