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Lithium Ion Batteries—Development of Advanced Electrical Equivalent Circuit Models for Nickel Manganese Cobalt Lithium-Ion

Author

Listed:
  • Alexandros Nikolian

    (Department Mobility, Logistics and Automotive Technology Research Centre, Vrije Universiteit Brussels, Pleinlaan 2, Brussels 1050, Belgium)

  • Yousef Firouz

    (Department Mobility, Logistics and Automotive Technology Research Centre, Vrije Universiteit Brussels, Pleinlaan 2, Brussels 1050, Belgium)

  • Rahul Gopalakrishnan

    (Department Mobility, Logistics and Automotive Technology Research Centre, Vrije Universiteit Brussels, Pleinlaan 2, Brussels 1050, Belgium)

  • Jean-Marc Timmermans

    (Department Mobility, Logistics and Automotive Technology Research Centre, Vrije Universiteit Brussels, Pleinlaan 2, Brussels 1050, Belgium)

  • Noshin Omar

    (Department Mobility, Logistics and Automotive Technology Research Centre, Vrije Universiteit Brussels, Pleinlaan 2, Brussels 1050, Belgium)

  • Peter Van den Bossche

    (Department Mobility, Logistics and Automotive Technology Research Centre, Vrije Universiteit Brussels, Pleinlaan 2, Brussels 1050, Belgium)

  • Joeri Van Mierlo

    (Department Mobility, Logistics and Automotive Technology Research Centre, Vrije Universiteit Brussels, Pleinlaan 2, Brussels 1050, Belgium)

Abstract

In this paper, advanced equivalent circuit models (ECMs) were developed to model large format and high energy nickel manganese cobalt (NMC) lithium-ion 20 Ah battery cells. Different temperatures conditions, cell characterization test (Normal and Advanced Tests), ECM topologies (1st and 2nd Order Thévenin model), state of charge (SoC) estimation techniques (Coulomb counting and extended Kalman filtering) and validation profiles (dynamic discharge pulse test (DDPT) and world harmonized light vehicle profiles) have been incorporated in the analysis. A concise state-of-the-art of different lithium-ion battery models existing in the academia and industry is presented providing information about model classification and information about electrical models. Moreover, an overview of the different steps and information needed to be able to create an ECM model is provided. A comparison between begin of life (BoL) and aged (95%, 90% state of health) ECM parameters (internal resistance (R o ), polarization resistance (R p ), activation resistance (R p2 ) and time constants (τ) is presented. By comparing the BoL to the aged parameters an overview of the behavior of the parameters is introduced and provides the appropriate platform for future research in electrical modeling of battery cells covering the ageing aspect. Based on the BoL parameters 1st and 2nd order models were developed for a range of temperatures (15 °C, 25 °C, 35 °C, 45 °C). The highest impact to the accuracy of the model (validation results) is the temperature condition that the model was developed. The 1st and 2nd order Thévenin models and the change from normal to advanced characterization datasets, while they affect the accuracy of the model they mostly help in dealing with high and low SoC linearity problems. The 2nd order Thévenin model with advanced characterization parameters and extended Kalman filtering SoC estimation technique is the most efficient and dynamically correct ECM model developed.

Suggested Citation

  • Alexandros Nikolian & Yousef Firouz & Rahul Gopalakrishnan & Jean-Marc Timmermans & Noshin Omar & Peter Van den Bossche & Joeri Van Mierlo, 2016. "Lithium Ion Batteries—Development of Advanced Electrical Equivalent Circuit Models for Nickel Manganese Cobalt Lithium-Ion," Energies, MDPI, vol. 9(5), pages 1-23, May.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:5:p:360-:d:69837
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    References listed on IDEAS

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    1. Noshin Omar & Peter Van den Bossche & Thierry Coosemans & Joeri Van Mierlo, 2013. "Peukert Revisited—Critical Appraisal and Need for Modification for Lithium-Ion Batteries," Energies, MDPI, vol. 6(11), pages 1-17, October.
    2. Hongwen He & Rui Xiong & Jinxin Fan, 2011. "Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach," Energies, MDPI, vol. 4(4), pages 1-17, March.
    3. Noshin Omar & Mohamed Daowd & Omar Hegazy & Grietus Mulder & Jean-Marc Timmermans & Thierry Coosemans & Peter Van den Bossche & Joeri Van Mierlo, 2012. "Standardization Work for BEV and HEV Applications: Critical Appraisal of Recent Traction Battery Documents," Energies, MDPI, vol. 5(1), pages 1-19, January.
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    2. Yasser Diab & François Auger & Emmanuel Schaeffer & Moutassem Wahbeh, 2017. "Estimating Lithium-Ion Battery State of Charge and Parameters Using a Continuous-Discrete Extended Kalman Filter," Energies, MDPI, vol. 10(8), pages 1-19, July.
    3. Woo-Yong Kim & Pyeong-Yeon Lee & Jonghoon Kim & Kyung-Soo Kim, 2019. "A Nonlinear-Model-Based Observer for a State-of-Charge Estimation of a Lithium-Ion Battery in Electric Vehicles," Energies, MDPI, vol. 12(17), pages 1-20, September.
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    5. Thomas R. B. Grandjean & Andrew McGordon & Paul A. Jennings, 2017. "Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries," Energies, MDPI, vol. 10(1), pages 1-16, January.
    6. Yasser Ghoulam & Tedjani Mesbahi & Peter Wilson & Sylvain Durand & Andrew Lewis & Christophe Lallement & Christopher Vagg, 2022. "Lithium-Ion Battery Parameter Identification for Hybrid and Electric Vehicles Using Drive Cycle Data," Energies, MDPI, vol. 15(11), pages 1-15, May.
    7. Chuanxue Song & Yulong Shao & Shixin Song & Cheng Chang & Fang Zhou & Silun Peng & Feng Xiao, 2017. "Energy Management of Parallel-Connected Cells in Electric Vehicles Based on Fuzzy Logic Control," Energies, MDPI, vol. 10(3), pages 1-13, March.
    8. Nicola Campagna & Vincenzo Castiglia & Rosario Miceli & Rosa Anna Mastromauro & Ciro Spataro & Marco Trapanese & Fabio Viola, 2020. "Battery Models for Battery Powered Applications: A Comparative Study," Energies, MDPI, vol. 13(16), pages 1-26, August.
    9. Chuanxue Song & Yulong Shao & Shixin Song & Silun Peng & Fang Zhou & Cheng Chang & Da Wang, 2017. "Insulation Resistance Monitoring Algorithm for Battery Pack in Electric Vehicle Based on Extended Kalman Filtering," Energies, MDPI, vol. 10(5), pages 1-13, May.
    10. Abraham Alem Kebede & Md Sazzad Hosen & Theodoros Kalogiannis & Henok Ayele Behabtu & Towfik Jemal & Joeri Van Mierlo & Thierry Coosemans & Maitane Berecibar, 2022. "Model Development for State-of-Power Estimation of Large-Capacity Nickel-Manganese-Cobalt Oxide-Based Lithium-Ion Cell Validated Using a Real-Life Profile," Energies, MDPI, vol. 15(18), pages 1-15, September.
    11. Adrian Chmielewski & Jakub Możaryn & Piotr Piórkowski & Krzysztof Bogdziński, 2018. "Comparison of NARX and Dual Polarization Models for Estimation of the VRLA Battery Charging/Discharging Dynamics in Pulse Cycle," Energies, MDPI, vol. 11(11), pages 1-28, November.
    12. Ines Baccouche & Sabeur Jemmali & Bilal Manai & Noshin Omar & Najoua Essoukri Ben Amara, 2017. "Improved OCV Model of a Li-Ion NMC Battery for Online SOC Estimation Using the Extended Kalman Filter," Energies, MDPI, vol. 10(6), pages 1-22, May.
    13. Giulio Barletta & Piera DiPrima & Davide Papurello, 2022. "Thévenin’s Battery Model Parameter Estimation Based on Simulink," Energies, MDPI, vol. 15(17), pages 1-10, August.
    14. Gaizka Saldaña & José Ignacio San Martín & Inmaculada Zamora & Francisco Javier Asensio & Oier Oñederra, 2019. "Analysis of the Current Electric Battery Models for Electric Vehicle Simulation," Energies, MDPI, vol. 12(14), pages 1-27, July.
    15. Luke Farrier & Richard Bucknall, 2020. "Investigating the Performance Capability of a Lithium-ion Battery System When Powering Future Pulsed Loads," Energies, MDPI, vol. 13(6), pages 1-15, March.
    16. Ivana Semanjski & Sidharta Gautama, 2016. "Forecasting the State of Health of Electric Vehicle Batteries to Evaluate the Viability of Car Sharing Practices," Energies, MDPI, vol. 9(12), pages 1-17, December.
    17. Liang Zhang & Shunli Wang & Daniel-Ioan Stroe & Chuanyun Zou & Carlos Fernandez & Chunmei Yu, 2020. "An Accurate Time Constant Parameter Determination Method for the Varying Condition Equivalent Circuit Model of Lithium Batteries," Energies, MDPI, vol. 13(8), pages 1-12, April.

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