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Li-Ion Pil Termal Parametre Tanımlama ve Çekirdek Sıcaklık Tahmini

Yıl 2023, Cilt: 26 Sayı: 4, 1495 - 1504, 01.12.2023
https://doi.org/10.2339/politeknik.1161986

Öz

Pil çekirdeği ve yüzey sıcaklığı, Li-ion pillerin termal yönetimi ve güvenli kullanımı için çok önemlidir. Onlar, hücrenin fiziksel özelliklerini etkilerler ve pil şarj durumu (SOC) ve sağlık durumu (SOH) gibi bazı temel durumları ile güçlü bir korelasyona sahiptirler. Bu nedenle, pil çekirdeğinin ve yüzey sıcaklığının doğru bir tahmini, performansı artıracak ve pilin ömrünü uzatacaktır. Bu çalışma, pil çekirdeği ve yüzey sıcaklığı için bir tahmin sistemi önerilmektedir. Pil SOC'sini, çekirdek ve yüzey sıcaklığını yakalamak için basitleştirilmiş bir sözde iki boyutlu model tanıtılmış, sonrasında bu çalışmada elde edilen sonuçları doğrulamak ve modellemek için kullanılmıştır. Ardından, iki durumlu bir termal pil modeli (TSM) sunulmuş ve incelenmiştir. Pilin termal parametrelerini tanımlamak için özyinelemeli en küçük kareler (RLS) algoritması benimsenmiştir. Daha sonra, TSM; COMSOL Multiphysics simülasyon yazılımı kullanılarak doğrulanmış ve sonrasında termal parametreler, pil çekirdek sıcaklığını tahmin etmek için Kalman filtresine (KF) uygulanmıştır. Sonuç olarak, pil çekirdek sıcaklığı tahmini sonuçlarının doğruluğu 0.037K'lık bir ortalama karekök hatasıyla doğrulanmıştır.

Kaynakça

  • Ismail N.H.F., Toha S.F., Azubir N.A.M., Ishak N.H.M., Hassan I.D.M.K., Ibrahim B.S.K., “Simplified heat generation model for lithium ion battery used in electric vehicle”, IOP Conference Series: Materials Science and Engineering, 53: 012014, (2013).
  • Pan Y.-W., Hua Y., Zhou S., He R., Zhang Y., Yang S., Liu X., Lian Y., Yan X., Wu B., “A computational multi-node electro-thermal model for large prismatic lithium-ion batteries”, Journal of Power Sources 459: 228070, (2020)
  • Ko S. T., Ahn J. H., Lee B.K., “Enhanced equivalent circuit modeling for li-ion battery using recursive parameter correction”, Journal of Electrical Engineering and Technology, 13: 1147-1155, (2018).
  • He W., Pecht M.G., Flynn D., Dinmohammadi F., “A Physics-Based Electrochemical Model for Lithium-Ion Battery State-of-Charge Estimation Solved by an Optimised Projection-Based Method and Moving-Window Filtering”. Energies, 11, 8: 2120, (2018).
  • Zhou J., Xing B., Wang C. “A review of lithium ion batteries electrochemical models for electric vehicles”, E3S Web of Conferences, 185: 04001, (2020).
  • Kemper P., Li S.E., Kum D., “Simplification of pseudo two-dimensional battery model using dynamic profile of lithium concentration”, Journal of Power Sources, 286: 510-525, (2015).
  • Ghalkhani M., Bahiraei F., Nazri G.A., Saif M., “Electrochemical–thermal model of pouch-type lithium-ion batteries”, Electrochimica Acta, 247: 569-587, (2017).
  • Damay, N., Forgez, C., Bichat, M.-P., & Friedrich, G., “Thermal modeling of large prismatic LiFePO 4 /graphite battery”, Coupled thermal and heat generation models for characterization and simulation, Journal of Power Sources, 283: 37-45, (2015).
  • Saw L. H., Poon H. M., Thiam H. S., Cai Z., Chong W. T., Pambudi N. A., King Y. J., “Novel thermal management system using mist cooling for lithium-ion battery packs”, Applied Energy, 223: 146-158, (2018).
  • Liu B., Yin S., Xu J., “Integrated computation model of lithium-ion battery subject to nail penetration”, Applied Energy, 183: 278-289, (2016).
  • Surya S., Samanta A., Williamson S., “Smart Core and Surface Temperature Estimation Techniques for Health-conscious Lithium-ion Battery Management Systems: A Model-to-Model Comparison”, Preprints, (2021).
  • Forgez C., Vinh Do D., Friedrich G., Morcrette M., Delacourt C. “Thermal modeling of a cylindrical LiFePO4/graphite lithium-ion battery”. Journal of Power Sources, 195: 2961-2968, (2010).
  • Chen L., Hu M., Cao K., Li S., Su Z., Jin G., Fu C., “Core temperature estimation based on electro‐thermal model of lithium‐ion batteries”, International Journal of Energy Research, 44(7): 5320–5333, (2020).
  • Richardson R. R., Ireland P. T., Howey D. A., “Battery internal temperature estimation by combined impedance and surface temperature measurement”, Journal of Power Sources, 265: 254–261, (2014).
  • Jiang Y., Yu Y., Huang J., Cai W., Marco J., “Li-ion battery temperature estimation based on recurrent neural networks”, Science China Technological Sciences, 64(6): 1335-1344, (2021).
  • Surya S., Marcis V., Williamson S., “Core Temperature Estimation for a Lithium ion 18650 Cell”, Energies, 14(1): 87, (2020).
  • Jang K.-W., Chung G.-B., “A SOC Estimation using Kalman Filter for Lithium-Polymer Battery”, The Transactions of the Korean Institute of Power Electronics, 17, 3: 222–229, (2012).
  • Saqli K., Bouchareb H., M'Sirdi N. K., Aziz N. , Oudghiri M., “Electric and Thermal Model of Li-ion battery pack with cylindrical components”. REDEC'20 the International Conference on Renewable Energy for Developing Countries, (2020).
  • Zhou W., Zheng Y., Pan Z., Lu Q., “Review on the Battery Model and SOC Estimation Method”, Processes, 9: 1685, (2021).
  • Torchio, M., Magni, L., Gopaluni, R. B., Braatz, R. D., Raimondo, D. M., “LIONSIMBA: A Matlab Framework Based on a Finite Volume Model Suitable for Li-Ion Battery Design, Simulation, and Control”, Journal of The Electrochemical Society, 163(7), A1192–A1205, (2016).
  • Thomas, K. E., Newman, J., “Thermal Modeling of Porous Insertion Electrodes”. Journal of The Electrochemical Society, 150, 2: A176, (2003).
  • Bernardi, D., Newman J., Pawlikowski E., “A General Energy Balance for Battery Systems”, Journal of The Electrochemical Society, 132(1): 5, (1985).
  • Doyle, M., Thomas F. F., Newman J., “Modeling of Galvanostatic Charge and Discharge of the Lithium/Polymer/Insertion Cell”, Journal of The Electrochemical Society, 140(6): 1526, (1993).

Lithium-Ion Battery Thermal Parameter Identification and Core Temperature Estimation

Yıl 2023, Cilt: 26 Sayı: 4, 1495 - 1504, 01.12.2023
https://doi.org/10.2339/politeknik.1161986

Öz

Battery core and surface temperature are crucial for the thermal management and safety usage of Li-ion batteries. They affect the cell's physical properties and strongly correlate with some of its key states, such as the battery state of charge (SOC) and state of health (SOH). Therefore, an accurate estimate of the battery core and surface temperature will enhance the performance and prolong the battery's life. This study proposes an estimation system of the battery core and surface temperature. A simplified pseudo-two-dimensional model is introduced to capture the battery SOC, core and surface temperature that will be used later in this study to model and validate the results' accuracy. Then, a two-state thermal battery model (TSM) is presented and studied. The recursive least square (RLS) algorithm is adopted to identify the thermal parameters of the battery. Next, the TSM is validated using COMSOL Multiphysics simulation software and the thermal parameters are then fed to the Kalman filter (KF) to estimate the battery core temperature. Finally, the accuracy of the battery core temperature estimated results are validated with a root mean square error of 0.037K.

Kaynakça

  • Ismail N.H.F., Toha S.F., Azubir N.A.M., Ishak N.H.M., Hassan I.D.M.K., Ibrahim B.S.K., “Simplified heat generation model for lithium ion battery used in electric vehicle”, IOP Conference Series: Materials Science and Engineering, 53: 012014, (2013).
  • Pan Y.-W., Hua Y., Zhou S., He R., Zhang Y., Yang S., Liu X., Lian Y., Yan X., Wu B., “A computational multi-node electro-thermal model for large prismatic lithium-ion batteries”, Journal of Power Sources 459: 228070, (2020)
  • Ko S. T., Ahn J. H., Lee B.K., “Enhanced equivalent circuit modeling for li-ion battery using recursive parameter correction”, Journal of Electrical Engineering and Technology, 13: 1147-1155, (2018).
  • He W., Pecht M.G., Flynn D., Dinmohammadi F., “A Physics-Based Electrochemical Model for Lithium-Ion Battery State-of-Charge Estimation Solved by an Optimised Projection-Based Method and Moving-Window Filtering”. Energies, 11, 8: 2120, (2018).
  • Zhou J., Xing B., Wang C. “A review of lithium ion batteries electrochemical models for electric vehicles”, E3S Web of Conferences, 185: 04001, (2020).
  • Kemper P., Li S.E., Kum D., “Simplification of pseudo two-dimensional battery model using dynamic profile of lithium concentration”, Journal of Power Sources, 286: 510-525, (2015).
  • Ghalkhani M., Bahiraei F., Nazri G.A., Saif M., “Electrochemical–thermal model of pouch-type lithium-ion batteries”, Electrochimica Acta, 247: 569-587, (2017).
  • Damay, N., Forgez, C., Bichat, M.-P., & Friedrich, G., “Thermal modeling of large prismatic LiFePO 4 /graphite battery”, Coupled thermal and heat generation models for characterization and simulation, Journal of Power Sources, 283: 37-45, (2015).
  • Saw L. H., Poon H. M., Thiam H. S., Cai Z., Chong W. T., Pambudi N. A., King Y. J., “Novel thermal management system using mist cooling for lithium-ion battery packs”, Applied Energy, 223: 146-158, (2018).
  • Liu B., Yin S., Xu J., “Integrated computation model of lithium-ion battery subject to nail penetration”, Applied Energy, 183: 278-289, (2016).
  • Surya S., Samanta A., Williamson S., “Smart Core and Surface Temperature Estimation Techniques for Health-conscious Lithium-ion Battery Management Systems: A Model-to-Model Comparison”, Preprints, (2021).
  • Forgez C., Vinh Do D., Friedrich G., Morcrette M., Delacourt C. “Thermal modeling of a cylindrical LiFePO4/graphite lithium-ion battery”. Journal of Power Sources, 195: 2961-2968, (2010).
  • Chen L., Hu M., Cao K., Li S., Su Z., Jin G., Fu C., “Core temperature estimation based on electro‐thermal model of lithium‐ion batteries”, International Journal of Energy Research, 44(7): 5320–5333, (2020).
  • Richardson R. R., Ireland P. T., Howey D. A., “Battery internal temperature estimation by combined impedance and surface temperature measurement”, Journal of Power Sources, 265: 254–261, (2014).
  • Jiang Y., Yu Y., Huang J., Cai W., Marco J., “Li-ion battery temperature estimation based on recurrent neural networks”, Science China Technological Sciences, 64(6): 1335-1344, (2021).
  • Surya S., Marcis V., Williamson S., “Core Temperature Estimation for a Lithium ion 18650 Cell”, Energies, 14(1): 87, (2020).
  • Jang K.-W., Chung G.-B., “A SOC Estimation using Kalman Filter for Lithium-Polymer Battery”, The Transactions of the Korean Institute of Power Electronics, 17, 3: 222–229, (2012).
  • Saqli K., Bouchareb H., M'Sirdi N. K., Aziz N. , Oudghiri M., “Electric and Thermal Model of Li-ion battery pack with cylindrical components”. REDEC'20 the International Conference on Renewable Energy for Developing Countries, (2020).
  • Zhou W., Zheng Y., Pan Z., Lu Q., “Review on the Battery Model and SOC Estimation Method”, Processes, 9: 1685, (2021).
  • Torchio, M., Magni, L., Gopaluni, R. B., Braatz, R. D., Raimondo, D. M., “LIONSIMBA: A Matlab Framework Based on a Finite Volume Model Suitable for Li-Ion Battery Design, Simulation, and Control”, Journal of The Electrochemical Society, 163(7), A1192–A1205, (2016).
  • Thomas, K. E., Newman, J., “Thermal Modeling of Porous Insertion Electrodes”. Journal of The Electrochemical Society, 150, 2: A176, (2003).
  • Bernardi, D., Newman J., Pawlikowski E., “A General Energy Balance for Battery Systems”, Journal of The Electrochemical Society, 132(1): 5, (1985).
  • Doyle, M., Thomas F. F., Newman J., “Modeling of Galvanostatic Charge and Discharge of the Lithium/Polymer/Insertion Cell”, Journal of The Electrochemical Society, 140(6): 1526, (1993).
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Khadija Saqli 0000-0003-2920-0359

Houda Bouchareb Bu kişi benim 0000-0001-9548-9870

Mohammed Oudghiri Bu kişi benim 0000-0002-9641-0770

Kouider Nacer M'sırdı Bu kişi benim 0000-0002-9485-6429

Yayımlanma Tarihi 1 Aralık 2023
Gönderilme Tarihi 15 Ağustos 2022
Yayımlandığı Sayı Yıl 2023 Cilt: 26 Sayı: 4

Kaynak Göster

APA Saqli, K., Bouchareb, H., Oudghiri, M., M’sırdı, K. N. (2023). Lithium-Ion Battery Thermal Parameter Identification and Core Temperature Estimation. Politeknik Dergisi, 26(4), 1495-1504. https://doi.org/10.2339/politeknik.1161986
AMA Saqli K, Bouchareb H, Oudghiri M, M’sırdı KN. Lithium-Ion Battery Thermal Parameter Identification and Core Temperature Estimation. Politeknik Dergisi. Aralık 2023;26(4):1495-1504. doi:10.2339/politeknik.1161986
Chicago Saqli, Khadija, Houda Bouchareb, Mohammed Oudghiri, ve Kouider Nacer M’sırdı. “Lithium-Ion Battery Thermal Parameter Identification and Core Temperature Estimation”. Politeknik Dergisi 26, sy. 4 (Aralık 2023): 1495-1504. https://doi.org/10.2339/politeknik.1161986.
EndNote Saqli K, Bouchareb H, Oudghiri M, M’sırdı KN (01 Aralık 2023) Lithium-Ion Battery Thermal Parameter Identification and Core Temperature Estimation. Politeknik Dergisi 26 4 1495–1504.
IEEE K. Saqli, H. Bouchareb, M. Oudghiri, ve K. N. M’sırdı, “Lithium-Ion Battery Thermal Parameter Identification and Core Temperature Estimation”, Politeknik Dergisi, c. 26, sy. 4, ss. 1495–1504, 2023, doi: 10.2339/politeknik.1161986.
ISNAD Saqli, Khadija vd. “Lithium-Ion Battery Thermal Parameter Identification and Core Temperature Estimation”. Politeknik Dergisi 26/4 (Aralık 2023), 1495-1504. https://doi.org/10.2339/politeknik.1161986.
JAMA Saqli K, Bouchareb H, Oudghiri M, M’sırdı KN. Lithium-Ion Battery Thermal Parameter Identification and Core Temperature Estimation. Politeknik Dergisi. 2023;26:1495–1504.
MLA Saqli, Khadija vd. “Lithium-Ion Battery Thermal Parameter Identification and Core Temperature Estimation”. Politeknik Dergisi, c. 26, sy. 4, 2023, ss. 1495-04, doi:10.2339/politeknik.1161986.
Vancouver Saqli K, Bouchareb H, Oudghiri M, M’sırdı KN. Lithium-Ion Battery Thermal Parameter Identification and Core Temperature Estimation. Politeknik Dergisi. 2023;26(4):1495-504.
 
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