IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i14p3532-d382111.html
   My bibliography  Save this article

Calibration Optimization Methodology for Lithium-Ion Battery Pack Model for Electric Vehicles in Mining Applications

Author

Listed:
  • Majid Astaneh

    (Department of Mechanics and Maritime Sciences, Chalmers University of Technology, 412 96 Göteborg, Sweden)

  • Jelena Andric

    (Department of Mechanics and Maritime Sciences, Chalmers University of Technology, 412 96 Göteborg, Sweden)

  • Lennart Löfdahl

    (Department of Mechanics and Maritime Sciences, Chalmers University of Technology, 412 96 Göteborg, Sweden)

  • Dario Maggiolo

    (Department of Mechanics and Maritime Sciences, Chalmers University of Technology, 412 96 Göteborg, Sweden)

  • Peter Stopp

    (Gamma Technologies GmbH, Danneckerstrasse 37, D-70182 Stuttgart, Germany)

  • Mazyar Moghaddam

    (Northvolt, Gamla Brogatan 26, 111 20 Stockholm, Sweden)

  • Michel Chapuis

    (Northvolt, Gamla Brogatan 26, 111 20 Stockholm, Sweden)

  • Henrik Ström

    (Department of Mechanics and Maritime Sciences, Chalmers University of Technology, 412 96 Göteborg, Sweden)

Abstract

Large-scale introduction of electric vehicles (EVs) to the market sets outstanding requirements for battery performance to extend vehicle driving range, prolong battery service life, and reduce battery costs. There is a growing need to accurately and robustly model the performance of both individual cells and their aggregated behavior when integrated into battery packs. This paper presents a novel methodology for Lithium-ion (Li-ion) battery pack simulations under actual operating conditions of an electric mining vehicle. The validated electrochemical-thermal models of Li-ion battery cells are scaled up into battery modules to emulate cell-to-cell variations within the battery pack while considering the random variability of battery cells, as well as electrical topology and thermal management of the pack. The performance of the battery pack model is evaluated using transient experimental data for the pack operating conditions within the mining environment. The simulation results show that the relative root mean square error for the voltage prediction is 0.7–1.7% and for the battery pack temperature 2–12%. The proposed methodology is general and it can be applied to other battery chemistries and electric vehicle types to perform multi-objective optimization to predict the performance of large battery packs.

Suggested Citation

  • Majid Astaneh & Jelena Andric & Lennart Löfdahl & Dario Maggiolo & Peter Stopp & Mazyar Moghaddam & Michel Chapuis & Henrik Ström, 2020. "Calibration Optimization Methodology for Lithium-Ion Battery Pack Model for Electric Vehicles in Mining Applications," Energies, MDPI, vol. 13(14), pages 1-27, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3532-:d:382111
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/14/3532/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/14/3532/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ruifeng Zhang & Bizhong Xia & Baohua Li & Libo Cao & Yongzhi Lai & Weiwei Zheng & Huawen Wang & Wei Wang & Mingwang Wang, 2018. "A Study on the Open Circuit Voltage and State of Charge Characterization of High Capacity Lithium-Ion Battery Under Different Temperature," Energies, MDPI, vol. 11(9), pages 1-17, September.
    2. Feng, Yanbiao & Dong, Zuomin, 2019. "Optimal control of natural gas compression engine hybrid electric mining trucks for balanced fuel efficiency and overall emission improvement," Energy, Elsevier, vol. 189(C).
    3. Krystian Pietrzak & Oliwia Pietrzak, 2020. "Environmental Effects of Electromobility in a Sustainable Urban Public Transport," Sustainability, MDPI, vol. 12(3), pages 1-21, February.
    4. Caiping Zhang & Jiuchun Jiang & Linjing Zhang & Sijia Liu & Leyi Wang & Poh Chiang Loh, 2016. "A Generalized SOC-OCV Model for Lithium-Ion Batteries and the SOC Estimation for LNMCO Battery," Energies, MDPI, vol. 9(11), pages 1-16, November.
    5. Wei He & Michael Pecht & David Flynn & Fateme Dinmohammadi, 2018. "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, MDPI, vol. 11(8), pages 1-23, August.
    6. Liu, Xinhua & Ai, Weilong & Naylor Marlow, Max & Patel, Yatish & Wu, Billy, 2019. "The effect of cell-to-cell variations and thermal gradients on the performance and degradation of lithium-ion battery packs," Applied Energy, Elsevier, vol. 248(C), pages 489-499.
    7. James Marco & Neelu Kumari & W. Dhammika Widanage & Peter Jones, 2015. "A Cell-in-the-Loop Approach to Systems Modelling and Simulation of Energy Storage Systems," Energies, MDPI, vol. 8(8), pages 1-19, August.
    8. Simone Barcellona & Luigi Piegari, 2017. "Lithium Ion Battery Models and Parameter Identification Techniques," Energies, MDPI, vol. 10(12), pages 1-24, December.
    9. Kotub Uddin & Alessandro Picarelli & Christopher Lyness & Nigel Taylor & James Marco, 2014. "An Acausal Li-Ion Battery Pack Model for Automotive Applications," Energies, MDPI, vol. 7(9), pages 1-26, August.
    10. Elham Hosseinzadeh & James Marco & Paul Jennings, 2017. "Electrochemical-Thermal Modelling and Optimisation of Lithium-Ion Battery Design Parameters Using Analysis of Variance," Energies, MDPI, vol. 10(9), pages 1-22, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yao Ahoutou & Adrian Ilinca & Mohamad Issa, 2022. "Electrochemical Cells and Storage Technologies to Increase Renewable Energy Share in Cold Climate Conditions—A Critical Assessment," Energies, MDPI, vol. 15(4), pages 1-30, February.
    2. Anandh Ramesh Babu & Jelena Andric & Blago Minovski & Simone Sebben, 2021. "System-Level Modeling and Thermal Simulations of Large Battery Packs for Electric Trucks," Energies, MDPI, vol. 14(16), pages 1-15, August.
    3. Astaneh, Majid & Andric, Jelena & Löfdahl, Lennart & Stopp, Peter, 2022. "Multiphysics simulation optimization framework for lithium-ion battery pack design for electric vehicle applications," Energy, Elsevier, vol. 239(PB).
    4. Heewon Choi & Nam-gyu Lim & Seong Jun Lee & Jungsoo Park, 2020. "Feasibility Study for Sustainable Use of Lithium-Ion Batteries Considering Different Positive Electrode Active Materials under Various Driving Cycles by Using Cell to Electric Vehicle (EV) Simulation," Sustainability, MDPI, vol. 12(22), pages 1-29, November.
    5. Kim, Kyunghyun & Choi, Jung-Il, 2023. "Effect of cell-to-cell variation and module configuration on the performance of lithium-ion battery systems," Applied Energy, Elsevier, vol. 352(C).
    6. Dongcheul Lee & Seohee Kang & Chee Burm Shin, 2022. "Modeling the Effect of Cell Variation on the Performance of a Lithium-Ion Battery Module," Energies, MDPI, vol. 15(21), pages 1-15, October.
    7. García, Antonio & Monsalve-Serrano, Javier & Ponce-Mora, Alberto & Fogué-Robles, Álvaro, 2023. "Development of a calibration methodology for fitting the response of a lithium-ion cell P2D model using real driving cycles," Energy, Elsevier, vol. 271(C).
    8. Oliwia Pietrzak & Krystian Pietrzak, 2021. "The Economic Effects of Electromobility in Sustainable Urban Public Transport," Energies, MDPI, vol. 14(4), pages 1-28, February.
    9. Krystian Pietrzak & Oliwia Pietrzak, 2022. "Tram System as a Challenge for Smart and Sustainable Urban Public Transport: Effects of Applying Bi-Directional Trams," Energies, MDPI, vol. 15(15), pages 1-29, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shrivastava, Prashant & Soon, Tey Kok & Idris, Mohd Yamani Idna Bin & Mekhilef, Saad, 2019. "Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    2. Shahjalal, Mohammad & Roy, Probir Kumar & Shams, Tamanna & Fly, Ashley & Chowdhury, Jahedul Islam & Ahmed, Md. Rishad & Liu, Kailong, 2022. "A review on second-life of Li-ion batteries: prospects, challenges, and issues," Energy, Elsevier, vol. 241(C).
    3. Yoon Koo Lee, 2019. "The Effect of Active Material, Conductive Additives, and Binder in a Cathode Composite Electrode on Battery Performance," Energies, MDPI, vol. 12(4), pages 1-19, February.
    4. Astaneh, Majid & Andric, Jelena & Löfdahl, Lennart & Stopp, Peter, 2022. "Multiphysics simulation optimization framework for lithium-ion battery pack design for electric vehicle applications," Energy, Elsevier, vol. 239(PB).
    5. Nickolay I. Shchurov & Sergey I. Dedov & Boris V. Malozyomov & Alexander A. Shtang & Nikita V. Martyushev & Roman V. Klyuev & Sergey N. Andriashin, 2021. "Degradation of Lithium-Ion Batteries in an Electric Transport Complex," Energies, MDPI, vol. 14(23), pages 1-33, December.
    6. Angeles Cabañero, Maria & Altmann, Johannes & Gold, Lukas & Boaretto, Nicola & Müller, Jana & Hein, Simon & Zausch, Jochen & Kallo, Josef & Latz, Arnulf, 2019. "Investigation of the temperature dependence of lithium plating onset conditions in commercial Li-ion batteries," Energy, Elsevier, vol. 171(C), pages 1217-1228.
    7. Vladimír Konečný & Jozef Gnap & Tomáš Settey & František Petro & Tomáš Skrúcaný & Tomasz Figlus, 2020. "Environmental Sustainability of the Vehicle Fleet Change in Public City Transport of Selected City in Central Europe," Energies, MDPI, vol. 13(15), pages 1-23, July.
    8. Dawei Song & Shiqian Wang & Li Di & Weijian Zhang & Qian Wang & Jing V. Wang, 2023. "Lithium-Ion Battery Life Prediction Method under Thermal Gradient Conditions," Energies, MDPI, vol. 16(2), pages 1-13, January.
    9. Takyi-Aninakwa, Paul & Wang, Shunli & Zhang, Hongying & Yang, Xiao & Fernandez, Carlos, 2023. "A hybrid probabilistic correction model for the state of charge estimation of lithium-ion batteries considering dynamic currents and temperatures," Energy, Elsevier, vol. 273(C).
    10. Takyi-Aninakwa, Paul & Wang, Shunli & Zhang, Hongying & Yang, Xiaoyong & Fernandez, Carlos, 2022. "An optimized long short-term memory-weighted fading extended Kalman filtering model with wide temperature adaptation for the state of charge estimation of lithium-ion batteries," Applied Energy, Elsevier, vol. 326(C).
    11. Liu, Yongjie & Huang, Zhiwu & Wu, Yue & Yan, Lisen & Jiang, Fu & Peng, Jun, 2022. "An online hybrid estimation method for core temperature of Lithium-ion battery with model noise compensation," Applied Energy, Elsevier, vol. 327(C).
    12. Qin, Yudi & Du, Jiuyu & Lu, Languang & Gao, Ming & Haase, Frank & Li, Jianqiu & Ouyang, Minggao, 2020. "A rapid lithium-ion battery heating method based on bidirectional pulsed current: Heating effect and impact on battery life," Applied Energy, Elsevier, vol. 280(C).
    13. Jing Hou & He He & Yan Yang & Tian Gao & Yifan Zhang, 2019. "A Variational Bayesian and Huber-Based Robust Square Root Cubature Kalman Filter for Lithium-Ion Battery State of Charge Estimation," Energies, MDPI, vol. 12(9), pages 1-23, May.
    14. He, Xitian & Sun, Bingxiang & Zhang, Weige & Su, Xiaojia & Ma, Shichang & Li, Hao & Ruan, Haijun, 2023. "Inconsistency modeling of lithium-ion battery pack based on variational auto-encoder considering multi-parameter correlation," Energy, Elsevier, vol. 277(C).
    15. Awab Baqar & Mamadou Baïlo Camara & Brayima Dakyo, 2022. "Energy Management in the Multi-Source Systems," Energies, MDPI, vol. 15(8), pages 1-4, April.
    16. Artur Jaworski & Vasyl Mateichyk & Hubert Kuszewski & Maksymilian Mądziel & Paweł Woś & Bożena Babiarz & Mirosław Śmieszek & Sławomir Porada, 2023. "Towards Cleaner Cities: An Analysis of the Impact of Bus Fleet Decomposition on PM and NO X Emissions Reduction in Sustainable Public Transport," Energies, MDPI, vol. 16(19), pages 1-18, October.
    17. Marcio L. M. Amorim & Gabriel Augusto Ginja & João Paulo Carmo & Melkzedekue Moraes Alcântara Moreira & Adriano Almeida Goncalves Siqueira & Jose A. Afonso, 2022. "Low-Cost/High-Precision Smart Power Supply for Data Loggers," Energies, MDPI, vol. 16(1), pages 1-27, December.
    18. Robaina, Margarita & Neves, Ana, 2021. "Complete decomposition analysis of CO2 emissions intensity in the transport sector in Europe," Research in Transportation Economics, Elsevier, vol. 90(C).
    19. Van Quan Dao & Minh-Chau Dinh & Chang Soon Kim & Minwon Park & Chil-Hoon Doh & Jeong Hyo Bae & Myung-Kwan Lee & Jianyong Liu & Zhiguo Bai, 2021. "Design of an Effective State of Charge Estimation Method for a Lithium-Ion Battery Pack Using Extended Kalman Filter and Artificial Neural Network," Energies, MDPI, vol. 14(9), pages 1-20, May.
    20. Prarthana Pillai & Sneha Sundaresan & Pradeep Kumar & Krishna R. Pattipati & Balakumar Balasingam, 2022. "Open-Circuit Voltage Models for Battery Management Systems: A Review," Energies, MDPI, vol. 15(18), pages 1-25, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3532-:d:382111. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.