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Modelling and fault diagnosis of lithium-ion battery for electric powertrain

Year 2023, Volume: 7 Issue: 3, 234 - 247, 30.09.2023
https://doi.org/10.30939/ijastech..1295130

Abstract

In this study, an overall modelling of a lithium-ion battery pack is performed using a Matlab-Simulink interface. The model can simulate the performance of the individual cells and the battery pack. For each single cell, the model simulates the electrical behavior during the cycling phase and the relaxation phase thanks to an equivalent circuit model. The ageing behavior is also simulated, both at the cell and battery pack level. All the battery cell information is summarized in a vector and calculated using Kirchhoff’s law. A fault diagnosis strategy was also included in this model to simulate the continuous degradation and determine the current/voltage behavior of a lithium-ion battery pack following the malfunction of a cell.

References

  • [1] O’Connell A, Pavlenko N, Bieker G, Searle S. A comparison of the life-cycle greenhouse gas emissions of european heavy-duty vehicles and fuels. 2023 févr. (The International Council on Clean Transportation).
  • [2] Regulation (EU) 2019/631 of the European Parliament and of the council of 17 April 2019 setting CO2 emission perfor-mance standards for new passenger cars and for new light commercial vehicles, and repealing Regulations (EC) No 443/2009 and (EU) No 510/2011. 2019. (Official Journal of the European Union).
  • [3] Liu K, Li K, Peng Q, Zhang C. A brief review on key tech-nologies in the battery management system of electric vehi-cles. Front Mech Eng. 2019;14(1):47‑64.
  • [4] Singh KV, Bansal HO, Singh D. A comprehensive review on hybrid electric vehicles: architectures and components. J Mod Transport. 2019;27(2):77‑107.
  • [5] Hu X, Xu L, Lin X, Pecht M. Battery Lifetime Prognostics. Joule. 2020;4(2):310‑46.
  • [6] Ouyang T, Xu P, Chen J, Lu J, Chen N. Improved parameters identification and state of charge estimation for lithium-ion battery with real-time optimal forgetting factor. Electrochim Acta. 2020;353:136576.
  • [7] Fellner C, Newman J. High-power batteries for use in hybrid vehicles. J Power Sources. 2000;85(2):229‑36.
  • [8] Miao Y, Hynan P, von Jouanne A, Yokochi A. Current Li-Ion Battery Technologies in Electric Vehicles and Opportunities for Advancements. Energies. 2019;12(6):1074.
  • [9] Zeng X, Li M, Abd El‐Hady D, Alshitari W, Al‐Bogami AS, Lu J, et al. Commercialization of Lithium Battery Technolo-gies for Electric Vehicles. Adv Energy Mater. juill 2019;9(27):1900161.
  • [10] Redondo-Iglesias E, Venet P, Pelissier S. Modélisation du vieillissement calendaire de cellules lithium-ion (gra-phite/LiFePO4) avec prise en compte de la dérive de leur état de charge. In: Symposium de Génie Electrique (SGE’16). Grenoble, France; 2016.
  • [11] Badey Q. Étude des mécanismes et modélisation du vieillis-sement des batteries lithium-ion dans le cadre d’un usage automobile. [Paris XI]: Université Paris-Sud; 2012.
  • [12] Jalkanen K, Karppinen J, Skogström L, Laurila T, Nisula M, Vuorilehto K. Cycle aging of commercial NMC/graphite pouch cells at different temperatures. Appl Energy. sept 2015;154:160‑72.
  • [13] Gao Y, Jiang J, Zhang C, Zhang W, Ma Z, Jiang Y. Lithium-ion battery aging mechanisms and life model under different charging stresses. J Power Sources. 2017;356:103‑14.
  • [14] Eom SW, Kim MK, Kim IJ, Moon SI, Sun YK, Kim HS. Life prediction and reliability assessment of lithium secondary batteries. J Power Sources. 2007;174(2):954‑8.
  • [15] Ganjeizadeh F, Tapananon T, Lei H. Predicting Reliability of Lithium Ion Batteries. International Journal of Engineering Research and Technology. 2014;3(8):1189‑92.
  • [16] Lee S, Kim J, Lee J, Cho BH. State-of-charge and capacity estimation of lithium-ion battery using a new open-circuit voltage versus state-of-charge. J Power Sources. 2008;185(2):1367‑73.
  • [17] 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(4):582‑98.
  • [18] Madani S, Schaltz E, Knudsen Kær S. An Electrical Equiva-lent Circuit Model of a Lithium Titanate Oxide Battery. Batte-ries. 2019;5(1):31.
  • [19] Li A. Analyse expérimentale et modélisation d’éléments de batterie et de leurs assemblages : application aux véhicules électriques et hybrides [Energie électrique]. Université Claude Bernard - Lyon I; 2013.
  • [20] Łebkowski A. Temperature, Overcharge and Short-Circuit Studies of Batteries used in Electric Vehicles. Prz Elektrotech. 2017;1(5):69‑75.
  • [21] Amine K, Liu J, Belharouak I. High-temperature storage and cycling of C-LiFePO4/graphite Li-ion cells. Electrochem Commun. 2005;7(7):669‑73.
  • [22] Lin X, Perez HE, Mohan S, Siegel JB, Stefanopoulou AG, Ding Y, et al. A lumped-parameter electro-thermal model for cylindrical batteries. J Power Sources. juill 2014;257:1‑11.
  • [23] Keil P, Schuster SF, Wilhelm J, Travi J, Hauser A, Karl RC, et al. Calendar Aging of Lithium-Ion Batteries: I. Impact of the Graphite Anode on Capacity Fade. J Electrochem Soc. 2016;163(9):A1872‑80.
  • [24] Ben-Marzouk M, Chaumond A, Redondo-Iglesias E, Montaru M, Pélissier S. Experimental Protocols and First Results of Calendar and/or Cycling Aging Study of Lithium-Ion Batter-ies – the MOBICUS Project. WEVJ. 24 juin 2016;8(2):388‑97.
  • [25] Yuksel T, Michalek J. Development of a Simulation Model to Analyze the Effect of Thermal Management on Battery Life. In 2012. p. 2012-01‑0671.
  • [26] Redondo Iglesias E. Étude du vieillissement des batteries lithium-ion dans les applications « “véhicule électrique” »: combinaison des effets de vieillissement calendaire et de cy-clage. Université de Lyon 1; 2017.
  • [27] Zarrin H, Farhad S, Hamdullahpur F, Chabot V, Yu A, Fowler M, et al. Effects of Diffusive Charge Transfer and Salt Con-centration Gradient in Electrolyte on Li-ion Battery Energy and Power Densities. Electrochimica Acta. avr 2014;125:117‑23.
  • [28] Karthikeyan DK, Sikha G, White RE. Thermodynamic model development for lithium intercalation electrodes. Journal of Power Sources. déc 2008;185(2):1398‑407.
Year 2023, Volume: 7 Issue: 3, 234 - 247, 30.09.2023
https://doi.org/10.30939/ijastech..1295130

Abstract

References

  • [1] O’Connell A, Pavlenko N, Bieker G, Searle S. A comparison of the life-cycle greenhouse gas emissions of european heavy-duty vehicles and fuels. 2023 févr. (The International Council on Clean Transportation).
  • [2] Regulation (EU) 2019/631 of the European Parliament and of the council of 17 April 2019 setting CO2 emission perfor-mance standards for new passenger cars and for new light commercial vehicles, and repealing Regulations (EC) No 443/2009 and (EU) No 510/2011. 2019. (Official Journal of the European Union).
  • [3] Liu K, Li K, Peng Q, Zhang C. A brief review on key tech-nologies in the battery management system of electric vehi-cles. Front Mech Eng. 2019;14(1):47‑64.
  • [4] Singh KV, Bansal HO, Singh D. A comprehensive review on hybrid electric vehicles: architectures and components. J Mod Transport. 2019;27(2):77‑107.
  • [5] Hu X, Xu L, Lin X, Pecht M. Battery Lifetime Prognostics. Joule. 2020;4(2):310‑46.
  • [6] Ouyang T, Xu P, Chen J, Lu J, Chen N. Improved parameters identification and state of charge estimation for lithium-ion battery with real-time optimal forgetting factor. Electrochim Acta. 2020;353:136576.
  • [7] Fellner C, Newman J. High-power batteries for use in hybrid vehicles. J Power Sources. 2000;85(2):229‑36.
  • [8] Miao Y, Hynan P, von Jouanne A, Yokochi A. Current Li-Ion Battery Technologies in Electric Vehicles and Opportunities for Advancements. Energies. 2019;12(6):1074.
  • [9] Zeng X, Li M, Abd El‐Hady D, Alshitari W, Al‐Bogami AS, Lu J, et al. Commercialization of Lithium Battery Technolo-gies for Electric Vehicles. Adv Energy Mater. juill 2019;9(27):1900161.
  • [10] Redondo-Iglesias E, Venet P, Pelissier S. Modélisation du vieillissement calendaire de cellules lithium-ion (gra-phite/LiFePO4) avec prise en compte de la dérive de leur état de charge. In: Symposium de Génie Electrique (SGE’16). Grenoble, France; 2016.
  • [11] Badey Q. Étude des mécanismes et modélisation du vieillis-sement des batteries lithium-ion dans le cadre d’un usage automobile. [Paris XI]: Université Paris-Sud; 2012.
  • [12] Jalkanen K, Karppinen J, Skogström L, Laurila T, Nisula M, Vuorilehto K. Cycle aging of commercial NMC/graphite pouch cells at different temperatures. Appl Energy. sept 2015;154:160‑72.
  • [13] Gao Y, Jiang J, Zhang C, Zhang W, Ma Z, Jiang Y. Lithium-ion battery aging mechanisms and life model under different charging stresses. J Power Sources. 2017;356:103‑14.
  • [14] Eom SW, Kim MK, Kim IJ, Moon SI, Sun YK, Kim HS. Life prediction and reliability assessment of lithium secondary batteries. J Power Sources. 2007;174(2):954‑8.
  • [15] Ganjeizadeh F, Tapananon T, Lei H. Predicting Reliability of Lithium Ion Batteries. International Journal of Engineering Research and Technology. 2014;3(8):1189‑92.
  • [16] Lee S, Kim J, Lee J, Cho BH. State-of-charge and capacity estimation of lithium-ion battery using a new open-circuit voltage versus state-of-charge. J Power Sources. 2008;185(2):1367‑73.
  • [17] 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(4):582‑98.
  • [18] Madani S, Schaltz E, Knudsen Kær S. An Electrical Equiva-lent Circuit Model of a Lithium Titanate Oxide Battery. Batte-ries. 2019;5(1):31.
  • [19] Li A. Analyse expérimentale et modélisation d’éléments de batterie et de leurs assemblages : application aux véhicules électriques et hybrides [Energie électrique]. Université Claude Bernard - Lyon I; 2013.
  • [20] Łebkowski A. Temperature, Overcharge and Short-Circuit Studies of Batteries used in Electric Vehicles. Prz Elektrotech. 2017;1(5):69‑75.
  • [21] Amine K, Liu J, Belharouak I. High-temperature storage and cycling of C-LiFePO4/graphite Li-ion cells. Electrochem Commun. 2005;7(7):669‑73.
  • [22] Lin X, Perez HE, Mohan S, Siegel JB, Stefanopoulou AG, Ding Y, et al. A lumped-parameter electro-thermal model for cylindrical batteries. J Power Sources. juill 2014;257:1‑11.
  • [23] Keil P, Schuster SF, Wilhelm J, Travi J, Hauser A, Karl RC, et al. Calendar Aging of Lithium-Ion Batteries: I. Impact of the Graphite Anode on Capacity Fade. J Electrochem Soc. 2016;163(9):A1872‑80.
  • [24] Ben-Marzouk M, Chaumond A, Redondo-Iglesias E, Montaru M, Pélissier S. Experimental Protocols and First Results of Calendar and/or Cycling Aging Study of Lithium-Ion Batter-ies – the MOBICUS Project. WEVJ. 24 juin 2016;8(2):388‑97.
  • [25] Yuksel T, Michalek J. Development of a Simulation Model to Analyze the Effect of Thermal Management on Battery Life. In 2012. p. 2012-01‑0671.
  • [26] Redondo Iglesias E. Étude du vieillissement des batteries lithium-ion dans les applications « “véhicule électrique” »: combinaison des effets de vieillissement calendaire et de cy-clage. Université de Lyon 1; 2017.
  • [27] Zarrin H, Farhad S, Hamdullahpur F, Chabot V, Yu A, Fowler M, et al. Effects of Diffusive Charge Transfer and Salt Con-centration Gradient in Electrolyte on Li-ion Battery Energy and Power Densities. Electrochimica Acta. avr 2014;125:117‑23.
  • [28] Karthikeyan DK, Sikha G, White RE. Thermodynamic model development for lithium intercalation electrodes. Journal of Power Sources. déc 2008;185(2):1398‑407.
There are 28 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Adrien Soloy 0000-0003-4582-6335

Thomas Bartoli 0000-0002-9460-9639

Fatima Haidar 0000-0003-4805-844X

Publication Date September 30, 2023
Submission Date May 11, 2023
Acceptance Date July 7, 2023
Published in Issue Year 2023 Volume: 7 Issue: 3

Cite

APA Soloy, A., Bartoli, T., & Haidar, F. (2023). Modelling and fault diagnosis of lithium-ion battery for electric powertrain. International Journal of Automotive Science And Technology, 7(3), 234-247. https://doi.org/10.30939/ijastech..1295130
AMA Soloy A, Bartoli T, Haidar F. Modelling and fault diagnosis of lithium-ion battery for electric powertrain. IJASTECH. September 2023;7(3):234-247. doi:10.30939/ijastech.1295130
Chicago Soloy, Adrien, Thomas Bartoli, and Fatima Haidar. “Modelling and Fault Diagnosis of Lithium-Ion Battery for Electric Powertrain”. International Journal of Automotive Science And Technology 7, no. 3 (September 2023): 234-47. https://doi.org/10.30939/ijastech. 1295130.
EndNote Soloy A, Bartoli T, Haidar F (September 1, 2023) Modelling and fault diagnosis of lithium-ion battery for electric powertrain. International Journal of Automotive Science And Technology 7 3 234–247.
IEEE A. Soloy, T. Bartoli, and F. Haidar, “Modelling and fault diagnosis of lithium-ion battery for electric powertrain”, IJASTECH, vol. 7, no. 3, pp. 234–247, 2023, doi: 10.30939/ijastech..1295130.
ISNAD Soloy, Adrien et al. “Modelling and Fault Diagnosis of Lithium-Ion Battery for Electric Powertrain”. International Journal of Automotive Science And Technology 7/3 (September 2023), 234-247. https://doi.org/10.30939/ijastech. 1295130.
JAMA Soloy A, Bartoli T, Haidar F. Modelling and fault diagnosis of lithium-ion battery for electric powertrain. IJASTECH. 2023;7:234–247.
MLA Soloy, Adrien et al. “Modelling and Fault Diagnosis of Lithium-Ion Battery for Electric Powertrain”. International Journal of Automotive Science And Technology, vol. 7, no. 3, 2023, pp. 234-47, doi:10.30939/ijastech. 1295130.
Vancouver Soloy A, Bartoli T, Haidar F. Modelling and fault diagnosis of lithium-ion battery for electric powertrain. IJASTECH. 2023;7(3):234-47.


International Journal of Automotive Science and Technology (IJASTECH) is published by Society of Automotive Engineers Turkey

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