Research Article

Online estimation of state-of-charge using auxiliary load

Volume: 8 Number: 2 June 30, 2024
EN

Online estimation of state-of-charge using auxiliary load

Abstract

Numerous approaches and methodologies have been established for online (while the load is supplied) estimation of the State-of-Charge of Lithium-ion cells and batteries. However, as battery load consumption fluctuates in real time because of delivered device operations, obtaining a precise online state of charge estimation remains a challenging task. This work proposes a new technique for online open circuit voltage measurement to estimate state of charge of batteries. This novel technique proposes the addition of an auxiliary regulated load that may be utilized to temporarily force specifically defined forms of the battery's current curve under particular conditions, which results in improving and simplifying online open circuit voltage computations. The effectiveness of the proposed technique was successfully validated through several experimental tests. The acquired findings demonstrated its efficiency with an acceptable online state of charge estimation accuracy. Typically, an estimation error of less than 2% was recorded in most tests, while the error was less than 1% when the battery’s state of charge was high.

Keywords

References

  1. [1] Espedal IB, Jinasena A, Burheim OS, Lamb JJ. Current Trends for State-of-Charge (SoC) Estimation in Lithium-Ion Battery Electric Vehicles. Energies 2021; 14(11):3284. doi:10.3390/en14113284.
  2. [2] Abdi H, Mohammadi-ivatloo B, Javadi S, Khodaei AR, Dehnavi E. Energy Storage Systems. In: Distributed Generation Systems. Elsevier; 2017:333-368. doi:10.1016/B978-0-12-804208-3.00007-8.
  3. [3] Azaroual M, Ouassaid M, Maaroufi M. Model predictive control-based energy management strategy for grid-connected residential photovoltaic–wind–battery system. In: Renewable Energy Systems. Elsevier; 2021:89-109. doi:10.1016/B978-0-12-820004-9.00014-0.
  4. [4] Uğurlu A, Gökçöl C. A case study of PV-wind-diesel-battery hybrid system. J Energy Syst. 2017; 1(4):138-147. doi:10.30521/jes.348335.
  5. [5] Wang K, Wang W, Wang L, Li L. An Improved SOC Control Strategy for Electric Vehicle Hybrid Energy Storage Systems. Energies 2020; 13(20):5297. doi:10.3390/en13205297.
  6. [6] Zhang R, Xia B, Li B, et al. State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles. Energies 2018; 11(7): 1820. doi:10.3390/en11071820.
  7. [7] Zhang L, Peng H, Ning Z, Mu Z, Sun C. Comparative Research on RC Equivalent Circuit Models for Lithium-Ion Batteries of Electric Vehicles. Appl Sci. 2017; 7(10): 1002. doi:10.3390/app7101002.
  8. [8] Belaidi H, Bentarzi H, Rabiai Z, Abdelmoumene A. Multi-agent System for Voltage Regulation in Smart Grid. In: Hatti M, ed. Artificial Intelligence and Renewables Towards an Energy Transition. Vol 174. Lecture Notes in Networks and Systems. Springer International Publishing; 2021:487-499. doi:10.1007/978-3-030-63846-7_46.

Details

Primary Language

English

Subjects

Electrical Energy Storage

Journal Section

Research Article

Early Pub Date

June 23, 2024

Publication Date

June 30, 2024

Submission Date

August 9, 2023

Acceptance Date

March 7, 2024

Published in Issue

Year 2024 Volume: 8 Number: 2

APA
Zermout, A., Belaıdı, H., & Maache, A. (2024). Online estimation of state-of-charge using auxiliary load. Journal of Energy Systems, 8(2), 101-115. https://doi.org/10.30521/jes.1339832
AMA
1.Zermout A, Belaıdı H, Maache A. Online estimation of state-of-charge using auxiliary load. Journal of Energy Systems. 2024;8(2):101-115. doi:10.30521/jes.1339832
Chicago
Zermout, Abdelaziz, Hadjira Belaıdı, and Ahmed Maache. 2024. “Online Estimation of State-of-Charge Using Auxiliary Load”. Journal of Energy Systems 8 (2): 101-15. https://doi.org/10.30521/jes.1339832.
EndNote
Zermout A, Belaıdı H, Maache A (June 1, 2024) Online estimation of state-of-charge using auxiliary load. Journal of Energy Systems 8 2 101–115.
IEEE
[1]A. Zermout, H. Belaıdı, and A. Maache, “Online estimation of state-of-charge using auxiliary load”, Journal of Energy Systems, vol. 8, no. 2, pp. 101–115, June 2024, doi: 10.30521/jes.1339832.
ISNAD
Zermout, Abdelaziz - Belaıdı, Hadjira - Maache, Ahmed. “Online Estimation of State-of-Charge Using Auxiliary Load”. Journal of Energy Systems 8/2 (June 1, 2024): 101-115. https://doi.org/10.30521/jes.1339832.
JAMA
1.Zermout A, Belaıdı H, Maache A. Online estimation of state-of-charge using auxiliary load. Journal of Energy Systems. 2024;8:101–115.
MLA
Zermout, Abdelaziz, et al. “Online Estimation of State-of-Charge Using Auxiliary Load”. Journal of Energy Systems, vol. 8, no. 2, June 2024, pp. 101-15, doi:10.30521/jes.1339832.
Vancouver
1.Abdelaziz Zermout, Hadjira Belaıdı, Ahmed Maache. Online estimation of state-of-charge using auxiliary load. Journal of Energy Systems. 2024 Jun. 1;8(2):101-15. doi:10.30521/jes.1339832

Cited By

Journal of Energy Systems is licensed under CC BY-NC 4.0