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Identification of LFP cell equivalent circuit parameters using HPPC methodology
Języki publikacji
Abstrakty
W artykule opisano sposób prowadzenia testów identyfikacyjnych celi baterii litowo-jonowej, mających na celu wyznaczenie wartości parametrów jej schematu zastępczego. Do oszacowania rzeczywistej pojemności ogniwa wykorzystano testy charakterystyki rozładowania, a do określenia parametrów schematu zastępczego Thevenina wykorzystano testy HPPC (Hybrid Pulse Power Characterization). Podano szczegółowy opis metod stosowanych do opracowania wyników testu HPPC. Szczególny nacisk położono na stosowane techniki filtracji i optymalizacji oraz ocenę jakości i przydatności pozyskiwanych danych pomiarowych. W artykule podano komplet uzyskanych parametrów, umożliwiający czytelnikowi stworzenie własnego, w pełni funkcjopnalnego modelu symulacyjnego celi. Uzyskany model symulacyjny zweryfikowano pomiarowo w teście CDC (Charge Depleting Cycle).
The article describes the method of conducting identification tests of a lithium-ion battery cell, aimed at determining the values of its equivalent circuit parameters. To estimate the actual capacity of the cell, discharge characteristics tests were used, and HPPC (Hybrid Pulse Power Characterization) tests were used to determine the Thevenin equivalent circuit parameters. A detailed description of the methods used to develop HPPC test results is given. Particular emphasis was placed on the applied filtration and optimization techniques as well as the assessment of the quality and usefulness of the acquired measurement data. The article provides a complete set of obtained parameters, enabling the reader to create his own, fully functional simulation model of the cell. The obtained simulation model was verified by measurements in the CDC (Charge Depleting Cycle) test.
Wydawca
Czasopismo
Rocznik
Tom
Strony
228--234
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
autor
- Politechnika Śląska, Wydział Elektryczny, Katedra Elektrotechniki i Informatyki, ul. Akademicka 10, 44-100 Gliwice
- Sieć Badawcza Łukasiewicz – Instytut Technik Innowacyjnych EMAG, ul. Leopolda 31, 40-189 Katowice
autor
- Politechnika Śląska, Wydział Elektryczny, Katedra Elektrotechniki i Informatyki, ul. Akademicka 10, 44-100 Gliwice
- Sieć Badawcza Łukasiewicz – Instytut Technik Innowacyjnych EMAG, ul. Leopolda 31, 40-189 Katowice
autor
- Politechnika Śląska, Wydział Mechaniczny Technologiczny, Katedra Podstaw Konstrukcji Maszyn, Konarskiego 18A, 44-100 Gliwice
- BUMECH S.A. Katowice, ul. Krakowska 191, 40-389 Katowice
autor
- Sieć Badawcza Łukasiewicz – Instytut Technik Innowacyjnych EMAG, ul. Leopolda 31, 40-189 Katowice
Bibliografia
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- [2] Rahmoun A., Biechl H. Modelling of li-ion batteries using equivalent circuit diagrams. Przegląd Elektrotechniczny, 2012, 2, 152–156.
- [3] Chen S.X., Tseng K.J., Choi S.S. Modeling of Lithium-Ion Battery for Energy Storage System Simulation. Asia-Pacific Power and Energy Engineering Conference, Wuhan, China, 28–30 March 2009, pp. 1–4. https://doi.org/10.1109/APPEEC.2009.4918501.
- [4] Huang K., Wang Y., Feng J. Research on equivalent circuit Model of Lithium-ion battery for electric vehicles. World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM), Shanghai, China, 4–6 December 2020, pp. 492–496. https://doi.org/10.1109/WCMEIM52463.2020.00109.
- [5] Wu W., Qin L., Wu G. State of power estimation of power lithium-ion battery based on an equivalent circuit model. J. Energy Storage 2022, 51, 104538. https://doi.org/10.1016/j.est.2022.104538.
- [6] Khattak A.A., Khan A.N., Safdar M., Basit A., Zaffar N.A. A Hybrid Electric Circuit Battery Model Capturing Dynamic Battery Characteristics. IEEE Kansas Power and Energy Conference (KPEC), Manhattan, KS, USA, 13–14 July 2020, pp. 1–6. https://doi.org/10.1109/KPEC47870.2020.9167659.
- [7] Sibi Krishnan K., Pathiyil P., Sunitha R. Generic Battery model covering self-discharge and internal resistance variation. IEEE 6th International Conference on Power Systems (ICPS), New Delhi, India, 4–6 March 2016, pp. 1–5. https://doi.org/10.1109/ICPES.2016.7584003.
- [8] Zhang Q., Shang Y., Li Y., Cui N., Duan B., Zhang C. A novel fractional variable-order equivalent circuit model and parameter identification of electric vehicle Li-ion batteries. ISA Trans. 2020, 97, 448–457. https://doi.org/10.1016/j.isatra.2019.08.004.
- [9] He H., Xiong R., Fan J. Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach. Energies 2011, 4, 582–598. https://doi.org/10.3390/en4040582.
- [10] Baczyńska A., Niewiadomski W., Gonçalves A., Almeida P., Luís R. Li-NMC Batteries Model Evaluation with Experimental Data for Electric Vehicle Application. Batteries 2018, 4, 11. https://doi.org/10.3390/batteries4010011.
- [11] Somakettarin N., Funaki T. Study on Factors for Accurate Open Circuit Voltage Characterizations in Mn-Type Li-Ion Batteries. Batteries 2017, 3, 8. https://doi.org/10.3390/batteries3010008.
- [12] Cipin R., Toman M., Prochazka P., Pazdera I. Identification of Li-ion Battery Model Parameters. International Conference on Electrical Drives & Power Electronics (EDPE), The High Tatras, Slovakia, 24–26 September 2019, pp. 225–229. https://doi.org/10.1109/EDPE.2019.8883926.
- [13] Nemes R., Ciornei S., Ruba M., Hedesiu H., Martis C. Modeling and simulation of first-order Li-Ion battery cell with experimental validation. International Conference on Modern Power Systems (MPS), Cluj-Napoca, Cluj, Romania, 21–23 May 2019, pp. 1–6. https://doi.org/10.1109/MPS.2019.8759769.
- [14] Li Z., Shi X., Shi M., Wei C., Di F., Sun H. Investigation on the Impact of the HPPC Profile on the Battery ECM Parameters’ Offline Identification. Asia Energy and Electrical Engineering Symposium (AEEES), Chengdu, China, 28–31 May 2020, pp. 753–757. https://doi.org/10.1109/AEEES48850.2020.9121487.
- [15] Deng S.D., Liu S.Y., Wang L., Xia L.L., Chen L. An improved second-order electrical equivalent modeling method for the online high power Li-ion battery state of charge estimation. IEEE 12th Energy Conversion Congress & Exposition—Asia (ECCE-Asia), Singapore, 24–27 May 2021, pp. 1725–1729. https://doi.org/10.1109/ECCE-Asia49820.2021.9479017.
- [16] Parthasarathy C., Laaksonen H., Halagi P. Characterisation and Modelling Lithium Titanate Oxide Battery Cell by Equivalent Circuit Modelling Technique. IEEE PES Innovative Smart Grid Technologies—Asia (ISGT Asia), Brisbane, Australia, 5–8 December 2021, pp. 1–5. https://doi.org/10.1109/ISGTAsia49270.2021.9715566.
- [17] Navas S.J., Cabello González G.M., Pino F.J., Guerra J.J. Modelling Li-ion batteries using equivalent circuits for renewable energy applications. Energy Rep. 2023, 9, 4456– 4465. https://doi.org/10.1016/j.egyr.2023.03.103.
- [18] Wang J., Jia Y., Yang N., Lu Y., Shi M., Ren X., Lu D. Precise equivalent circuit model for Li-ion battery by experimental improvement and parameter optimization. J. Energy Storage 2022, 52, 104980. https://doi.org/10.1016/j.est.2022.104980.
- [19] Haghjoo Y., Khaburi D.A. Modeling, simulation, and parameters identification of a lithium-ion battery used in electric vehicles. Iranian Conference on Renewable Energy & Distributed Generation (ICREDG), Mashhad, Iran, 23–24 February 2022, pp. 1–7. https://doi.org/10.1109/ICREDG54199.2022.9804546.
- [20] Tang A., Gong P., Li J., Zhang K., Zhou Y., Zhang Z. A State-of-Charge Estimation Method Based on Multi-Algorithm Fusion. World Electr. Veh. J. 2022, 13, 70. https://doi.org/10.3390/wevj13040070.
- [21] Jarrraya I., Degaa L., Rizoug N., Chabchoub M.H., Trabelsi H. Comparison study between hybrid Nelder-Mead particle swarm optimization and open circuit voltage-Recursive least square for the battery parameters estimation. J. Energy Storage 2022, 50, 104424. https://doi.org/10.1016/j.est.2022.104424.
- [22] Castanho D., Guerreiro M., Silva L., Eckert J., Antonini Alves T., Tadano Y.d.S., Stevan S.L. Jr., Siqueira H.V., Corrêa F.C. Method for SoC Estimation in Lithium-Ion Batteries Based on Multiple Linear Regression and Particle Swarm Optimization. Energies 2022, 15, 6881. https://doi.org/10.3390/en15196881.
- [23] Pizarro-Carmona V., Castano-Solís S., Cortés-Carmona M., Fraile-Ardanuy J., Jimenez-Bermejo G. GA-based approach to optimize an equivalent electric circuit model of a Li-ion battery-pack. Expert Syst. Appl. 2021, 172, 114647. https://doi.org/10.1016/j.eswa.2021.114647.
- [24] Wang C., Xu M., Zhang Q., Feng J., Jiang R., Wei Y., Liu Y. Parameters identification of Thevenin model for lithium-ion batteries using self-adaptive Particle Swarm Optimization Differential Evolution algorithm to estimate state of charge. J. Energy Storage 2021, 44, 103244. https://doi.org/10.1016/j.est.2021.103244.
- [25] Shi J., Guo H., Chen D. Parameter identification method for lithium-ion batteries based on recursive least square with sliding window difference forgetting factor. J. Energy Storage 2021, 44, 103485. https://doi.org/10.1016/j.est.2021.103485.
- [26] Yang Z., Wang X. An improved parameter identification method considering multi-timescale characteristics of lithium-ion batteries. J. Energy Storage 2023, 59, 106462. https://doi.org/10.1016/j.est.2022.106462.
- [27] Białoń T., Niestrój R., Korski W. PSO-Based Identification of the Li-Ion Battery Cell Parameters. Energies 2023, 16, 3995. https://doi.org/10.3390/en16103995
- [28] Baccouche I., Jemmali S., Manai B., Omar N., Amara N.E.B. Improved OCV Model of a Li-Ion NMC Battery for Online SOC Estimation Using the Extended Kalman Filter. Energies 2017, 10, 764. https://doi.org/10.3390/en10060764.
- [29] Belt J.R. Battery Test Manual for Plug-In Hybrid Electric Vehicles, 2nd ed., U.S. Department of Energy Vehicle Technologies Program, USA, 2010. https://doi.org/10.2172/991910
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6707cfc2-f967-400f-98a0-cea85efc6e2d
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