MATLAB/Simulink'te LiFePO4 hücrelerinin Şarj/Deşarj simülasyon modelleri

Yıl 2024, , 956 - 968, 15.07.2024

Mehmet Akif Kılınç , Okan Bingöl , Ali Şentürk , Remzi İnan

https://doi.org/10.28948/ngumuh.1456453

Öz

Lityum (Li) piller, özellikle elektrikli araçlarda yaygın uygulama alanı bulmaktadır. Dinamik özellikleri genellikle eşdeğer devre modelleri ile temsil edilmektedir. Bu çalışmada, LiFePO4 pillerin iki farklı ikinci dereceden eşdeğer devre modeli MATLAB/Simulink'te modellenmiş ve simüle edilmiştir. İlk model çekilen akıma bağlı olarak kapasite değişimleri sergilerken, ikincisinde sabit kapasite varsayılmaktadır. Simülasyon sonuçlarının analizi Şarj Durumu (SOC), Açık Devre Gerilimi (OCV) ve çıkış gerilimi (VT) gibi temel parametrelere odaklanmaktadır. Birinci ve ikinci batarya modelleri arasındaki karşılaştırmalı değerlendirmelerde, önceki deneysel batarya çalışmalarından elde edilen formüller kullanılmıştır. Özellikle, deşarj sırasında iki model arasında SOC'de %0.0155, OCV'de %0.00003 ve VT'de %0.00003'lük bir fark gözlenmiştir. Şarj sırasında yapılan benzer bir değerlendirmede SOC'de %0.0447, OCV'de %0.00007 ve VT'de %0.00003 hata gözlemlenmiştir. Ayrıca ilk modeldeki deşarj süreci, şarj sırasında daha yüksek değerlerin aksine daha düşük SOC, OCV ve VT değerleri göstermektedir. Bu farklılıklara rağmen, çalışmada her iki modelin de benzer sonuçlar verdiği ve Lityum pillerin çeşitli eşdeğer devre gösterimleri için referans olarak kullanılabileceği sonucuna varılmıştır.

Anahtar Kelimeler

LiFePO4 Pil, Thevenin Eşdeğer Devresi, MATLAB/Simulink Model, SOC Tahmini, Pil Kapasitesi

Charge/Discharge Simulation Models of LiFePO4 Cells in MATLAB/Simulink

Öz

Lithium (Li) cells find widespread applications, particularly in electric vehicles their dynamic characteristics are often represented through equivalent circuit models. In this study, two different second-order equivalent circuit models of LiFePO4 cells are modeled and simulated in MATLAB/Simulink. The first model exhibits capacity changes based on drawn current, while the second assumes constant capacity. The analysis of the simulations results focuses on key parameters such as State of Charge (SOC), Open Circuit Voltage (OCV), and terminal voltage (VT). Comparative evaluations between the first and second cell models utilize formulas derived from prior experimental cell studies. Specifically, a 0.0155% variance in SOC, a 0.00003% difference in OCV, and a 0.00003% distinction in VT were observed between the two models during discharge. A similar assessment during charging observed an error of 0.0447% in SOC, 0.00007% in OCV, and 0.00003% in VT. Furthermore, the discharge process in the first model demonstrates lower SOC, OCV, and VT values, contrasting with higher values during charging. Despite these variances, the study concludes that both models yield similar results, establishing them as viable references for equivalent circuit representations of Lithium cells.

Anahtar Kelimeler

LiFePO4 Cell, Thevenin Equivalent Circuit, MATLAB/Simulink Circuit, SOC Estimation, Cell Capacity

Kaynakça

• Wang, C.; Zhang, G.; Li, X.; Huang, J.; Wang, Z.; Lv, Y.; Meng, L.; Situ, W.; Rao, M., Experimental Examination of Large Capacity LiFePO4 Battery Pack at High Temperature and Rapid Discharge Using Novel Liquid Cooling Strategy. International Journal of Energy Research, 42 (3), 1172–1182, 2018. https://doi.org/10.1002/er.3916.
• Thanagasundram, S.; Arunachala, R.; Makinejad, K.; Teutsch, T.; Jossen, A. A Cell Level Model for Battery Simulation. European Electric Vehicle Congress Brussels, 2012.
• Kaba, M. Y.; Kalkan, O.; Celen, A., Elektrikli Araçlarda Kullanılan Bataryalar Ve Termal Yönetim Sistemlerinin İncelenmesi. Konya Journal of Engineering. Science, 9 (4), 1119–1136, 2021. https://doi.org/10.36306/konjes.945819.
• Chenglin, L., Huiju L., Lifang, W., A Dynamic Equivalent Circuit Model of LiFePO4 Cathode Material for Lithium-Ion Batteries on Hybrid Electric Vehicles. Institute of Electrical and Electronics Engineers, 1662-1665, 2009. https://doi.org/10.1109/VPPC.2009.5289681.
• Tran, M.-K.; Mathew, M.; Janhunen, S.; Panchal, S.; Raahemifar, K.; Fraser, R.; Fowler, M., A Comprehensive Equivalent Circuit Model for Lithium-Ion Batteries, Incorporating the Effects of State of Health, State of Charge, and Temperature on Model Parameters. Journal of Energy Storage, 43, 1-10, 2021. https://doi.org/10.1016/j.est.2021.103252.
• Panchal, S.; Dincer, I.; Agelin-Chaab, M.; Fraser, R.; Fowler, M., Experimental and Theoretical Investigations of Heat Generation Rates for a Water Cooled LiFePO4 Battery. International Journal of Heat and Mass Transfer, 101, 1093–1102, 2016. https://doi.org/10.1016/j.ijheatmasstransfer.2016.05.126.
• Yu, Q.; Dai, L.; Xiong, R.; Chen, Z.; Zhang, X.; Shen, W., Current Sensor Fault Diagnosis Method Based on an Improved Equivalent Circuit Battery Model. Applied Energy, 310, 1-15,2022. https://doi.org/10.1016/j.apenergy.2022.118588.
• Panchal, S.; Dincer, I.; Agelin-Chaab, M.; Fraser, R.; Fowler, M., Transient Electrochemical Heat Transfer Modeling and Experimental Validation of a Large Sized LiFePO4/Graphite Battery. International Journal of Heat Mass Transfer, 109, 1239–1251, 2017. https://doi.org/10.1016/j.ijheatmasstransfer.2017.03.005.
• Amir, S.; Gulzar, M.; Tarar, M. O.; Naqvi, I. H.; Zaffar, N. A.; Pecht, M. G., Dynamic Equivalent Circuit Model to Estimate State-of-Health of Lithium-Ion Batteries., 10, 18279–18288, 2022. https://doi.org/10.1109/ACCESS.2022.3148528.
• Zhang, C.; Li, K.; Deng, J.; Song, S., Improved Realtime State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model. IEEE Transactions On Industrial Electronics, 64 (1), 654–663, 2017. https://doi.org/10.1109/TIE.2016.2610398.
• Cui, Z.; Wang, L.; Li, Q.; Wang, K., A Comprehensive Review on the State of Charge Estimation for Lithium-Ion Battery Based on Neural Network. International Journal of Energy Research, 46, 5423-5440, 2021. https://doi.org/10.1002/er.7545.
• Scipioni, R.; Jørgensen, P. S.; Graves, C.; Hjelm, J.; Jensen, S. H., A Physically-Based Equivalent Circuit Model for the Impedance of a LiFePO4/Graphite 26650 Cylindrical Cell. Journal of The Electrochemical Society, 164 (9), A2017–A2030, 2017. https://doi.org/10.1149/2.1071709jes.
• Baboo, J. P.; Yatoo, M. A.; Dent, M.; Hojaji Najafabadi, E.; Lekakou, C.; Slade, R.; Hinder, S. J.; Watts, J. F., Exploring Different Binders for a LiFePO4 Battery, Battery Testing, Modeling and Simulations. Energies, 15, 2332.-2354, 2022. https://doi.org/10.3390/en15072332.
• Ates, M.; Chebil, A., Supercapacitor and Battery Performances of Multi-Component Nanocomposites: Real Circuit and Equivalent Circuit Model Analysis. Journal of Energy Storage, 53, 1-15,2022. https://doi.org/10.1016/j.est.2022.105093.
• Arianto, S.; Yunaningsih, R. Y.; Astuti, E. T.; Hafiz, S., Development of Single Cell Lithium-Ion Battery Model Using Scilab/Xcos. International Symposium on Frontier of Applied Physics (ISFAP 2015), 060007-1-06007-6, 2016. https://doi.org/10.1063/1.4941640.
• 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), 1–6,2020. https://doi.org/10.1109/KPEC47870.2020.9167659.
• Ke, M.-Y.; Chiu, Y.-H.; Wu, C.-Y., Battery Modelling and SOC Estimation of a LiFePO4 Battery. International Symposium on Computer, Consumer and Control, 208–211, 2016. https://doi.org/10.1109/IS3C.2016.63.
• Yao W.L., Aziz, J. A., High Capacity LiFePO4 Battery Model with Consideration of Nonlinear Capacity Effects. 2012 IEEE 7th International Power Electronics and Motion Control Conference-ECCE Asia. 182–187, 2012. https://doi.org/10.1109/IPEMC.2012.6258894.
• Tran, M.-K.; Mevawala, A.; Panchal, S.; Raahemifar, K.; Fowler, M.; Fraser, R., Effect of Integrating the Hysteresis Component to the Equivalent Circuit Model of Lithium-Ion Battery for Dynamic and Non-Dynamic Applications. Journal of Energy Storage, 32, 1-7, 2020. https://doi.org/10.1016/j.est.2020.101785.
• Wang, Y.; Zhang, C.; Chen, Z., A Method for State-of-Charge Estimation of LiFePO4 Batteries at Dynamic Currents and Temperatures Using Particle Filter. Journal of Power Sources, 279, 306–311, 2015. https://doi.org/10.1016/j.jpowsour.2015.01.005.
• Panchal, S.; Mcgrory, J.; Kong, J.; Fraser, R.; Fowler, M.; Dincer, I.; Agelin-Chaab, M., Cycling Degradation Testing and Analysis of a LiFePO4 Battery at Actual Conditions. International Journal of Energy Research, 41 (15), 2565–2575, 2017. https://doi.org/10.1002/er.3837.
• Mathworks Inc. Matlab Simscape. https://www.mathworks.com/products/simscape.html, Accessed 13 May 2024.
• Hu, X.; Li, S.; Peng, H., A Comparative Study of Equivalent Circuit Models for Li-Ion Batteries. Journal of Power Sources 198, 359–367, 2012. https://doi.org/10.1016/j.jpowsour.2011.10.013.
• Kim, J.; Seo, G.-S.; Chun, C.; Cho, B.-H.; Lee, S., OCV Hysteresis Effect-Based SOC Estimation in Extended Kalman Filter Algorithm for a LiFePO4/C Cell. In 2012 IEEE International Electric Vehicle Conference, 1–5, 2012. https://doi.org/10.1109/IEVC.2012.6183174.
• Gao, Z.; Chin, C.; Woo, W.; Jia, J., Integrated Equivalent Circuit and Thermal Model for Simulation of Temperature-Dependent LiFePO4 Battery in Actual Embedded Application. Energies, 10, 85- 107, 2017. https://doi.org/10.3390/en10010085.
• Feng, F.; Lu, R.; Wei, G.; Zhu, C. 2015. Online Estimation of Model Parameters and State of Charge of LiFePO4 Batteries Using a Novel Open-Circuit Voltage at Various Ambient Temperatures. Energies. 8, 2950–2976, 2015. https://doi.org/10.3390/en8042950.
• Panchal, S.; Haji Akhoundzadeh, M.; Raahemifar, K.; Fowler, M.; Fraser, R., Heat and Mass Transfer Modeling and Investigation of Multiple LiFePO4/Graphite Batteries in a Pack at Low C-Rates with Water-Cooling. International Journal of Heat and Mass Transfer, 135, 368–377, 2019. https://doi.org/10.1016/j.ijheatmasstransfer.2019.01.076.
• Yao, L. W.; Aziz, J. A.; Kong, P. Y.; Idris, N. R. N., Modeling of Lithium-Ion Battery Using MATLAB/Simulink. In IECON 2013-39th Annual Conference of the IEEE Industrial Electronics Society; IEEE, 1729–1734, 2013. https://doi.org/10.1109/IECON.2013.6699393.
• Mathworks Inc. Matlab Simulink. https://www.mathworks.com/products/simulink.html, Accessed 15 May 2024.
• Yao, L. W.; Prayun, W. A.; Abdul Aziz, M. J. B.; Sutikno, T., Battery State-of-Charge Estimation with Extended Kalman-Filter Using Third-Order Thevenin Model. TELKOMNIKA (Telecommunication Computing Electronic and Control), 13 (2), 401-412, 2015. http://doi.org/10.12928/telkomnika.v13i2.1467.