IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i17p6239-d1226960.html
   My bibliography  Save this article

HPPC Test Methodology Using LFP Battery Cell Identification Tests as an Example

Author

Listed:
  • Tadeusz Białoń

    (Department of Electrical Engineering and Computer Science, Faculty of Electrical Engineering, Silesian University of Technology, 44-100 Gliwice, Poland
    Łukasiewicz Research Network—Institute of Innovative Technologies EMAG, 40-189 Katowice, Poland)

  • Roman Niestrój

    (Department of Electrical Engineering and Computer Science, Faculty of Electrical Engineering, Silesian University of Technology, 44-100 Gliwice, Poland
    Łukasiewicz Research Network—Institute of Innovative Technologies EMAG, 40-189 Katowice, Poland)

  • Wojciech Skarka

    (Department of Fundamentals of Machinery Design, Faculty of Mechanical Engineering, Silesian University of Technology, 44-100 Gliwice, Poland
    Bumech S.A., 40-389 Katowice, Poland)

  • Wojciech Korski

    (Łukasiewicz Research Network—Institute of Innovative Technologies EMAG, 40-189 Katowice, Poland)

Abstract

The aim of this research was to create an accurate simulation model of a lithium-ion battery cell, which will be used in the design process of the traction battery of a fully electric load-hull-dump vehicle. Discharge characteristics tests were used to estimate the actual cell capacity, and hybrid pulse power characterization (HPPC) tests were used to identify the Thevenin equivalent circuit parameters. A detailed description is provided of the methods used to develop the HPPC test results. Particular emphasis was placed on the applied filtration and optimization techniques as well as the assessment of the quality and the applicability of the acquired measurement data. As a result, a simulation model of the battery cell was created. The article gives the full set of parameter values needed to build a fully functional simulation model. Finally, a charge-depleting cycle test was performed to verify the created simulation model.

Suggested Citation

  • Tadeusz Białoń & Roman Niestrój & Wojciech Skarka & Wojciech Korski, 2023. "HPPC Test Methodology Using LFP Battery Cell Identification Tests as an Example," Energies, MDPI, vol. 16(17), pages 1-21, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6239-:d:1226960
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/17/6239/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/17/6239/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Spyros Giannelos & Stefan Borozan & Marko Aunedi & Xi Zhang & Hossein Ameli & Danny Pudjianto & Ioannis Konstantelos & Goran Strbac, 2023. "Modelling Smart Grid Technologies in Optimisation Problems for Electricity Grids," Energies, MDPI, vol. 16(13), pages 1-15, June.
    2. Diego Castanho & Marcio Guerreiro & Ludmila Silva & Jony Eckert & Thiago Antonini Alves & Yara de Souza Tadano & Sergio Luiz Stevan & Hugo Valadares Siqueira & Fernanda Cristina Corrêa, 2022. "Method for SoC Estimation in Lithium-Ion Batteries Based on Multiple Linear Regression and Particle Swarm Optimization," Energies, MDPI, vol. 15(19), pages 1-21, September.
    3. Roman Niestrój & Tomasz Rogala & Wojciech Skarka, 2020. "An Energy Consumption Model for Designing an AGV Energy Storage System with a PEMFC Stack," Energies, MDPI, vol. 13(13), pages 1-31, July.
    4. Quanqing Yu & Changjiang Wan & Junfu Li & Lixin E & Xin Zhang & Yonghe Huang & Tao Liu, 2021. "An Open Circuit Voltage Model Fusion Method for State of Charge Estimation of Lithium-Ion Batteries," Energies, MDPI, vol. 14(7), pages 1-22, March.
    5. Krzysztof Mateja & Wojciech Skarka & Magdalena Peciak & Roman Niestrój & Maik Gude, 2023. "Energy Autonomy Simulation Model of Solar Powered UAV," Energies, MDPI, vol. 16(1), pages 1-31, January.
    6. 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.
    7. Zhiguo Tang & Anqi Song & Shoucheng Wang & Jianping Cheng & Changfa Tao, 2020. "Numerical Analysis of Heat Transfer Mechanism of Thermal Runaway Propagation for Cylindrical Lithium-ion Cells in Battery Module," Energies, MDPI, vol. 13(4), pages 1-18, February.
    8. Oriol Raventós & Julian Bartels, 2020. "Evaluation of Temporal Complexity Reduction Techniques Applied to Storage Expansion Planning in Power System Models," Energies, MDPI, vol. 13(4), pages 1-18, February.
    9. Spyros Giannelos & Predrag Djapic & Danny Pudjianto & Goran Strbac, 2020. "Quantification of the Energy Storage Contribution to Security of Supply through the F-Factor Methodology," Energies, MDPI, vol. 13(4), pages 1-15, February.
    10. Piotr Szewczyk & Andrzej Łebkowski, 2022. "Comparative Studies on Batteries for the Electrochemical Energy Storage in the Delivery Vehicle," Energies, MDPI, vol. 15(24), pages 1-28, December.
    11. Nan Li & Haining Zhang & Xiangcheng Zhang & Xue Ma & Sen Guo, 2020. "How to Select the Optimal Electrochemical Energy Storage Planning Program? A Hybrid MCDM Method," Energies, MDPI, vol. 13(4), pages 1-20, February.
    12. Steffen Kiemel & Simon Glöser-Chahoud & Lara Waltersmann & Maximilian Schutzbach & Alexander Sauer & Robert Miehe, 2021. "Assessing the Application-Specific Substitutability of Lithium-Ion Battery Cathode Chemistries Based on Material Criticality, Performance, and Price," Resources, MDPI, vol. 10(9), pages 1-27, August.
    Full references (including those not matched with items on IDEAS)

    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. Tadeusz Białoń & Roman Niestrój & Wojciech Korski, 2023. "PSO-Based Identification of the Li-Ion Battery Cell Parameters," Energies, MDPI, vol. 16(10), pages 1-22, May.
    2. Aaron Shmaryahu & Nissim Amar & Alexander Ivanov & Ilan Aharon, 2021. "Sizing Procedure for System Hybridization Based on Experimental Source Modeling for Electric Vehicles," Energies, MDPI, vol. 14(17), pages 1-21, August.
    3. Shehzar Shahzad Sheikh & Mahnoor Anjum & Muhammad Abdullah Khan & Syed Ali Hassan & Hassan Abdullah Khalid & Adel Gastli & Lazhar Ben-Brahim, 2020. "A Battery Health Monitoring Method Using Machine Learning: A Data-Driven Approach," Energies, MDPI, vol. 13(14), pages 1-16, July.
    4. 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.
    5. Sandra Castano-Solis & Daniel Serrano-Jimenez & Lucia Gauchia & Javier Sanz, 2017. "The Influence of BMSs on the Characterization and Modeling of Series and Parallel Li-Ion Packs," Energies, MDPI, vol. 10(3), pages 1-13, February.
    6. Ming Cai & Weijie Chen & Xiaojun Tan, 2017. "Battery State-Of-Charge Estimation Based on a Dual Unscented Kalman Filter and Fractional Variable-Order Model," Energies, MDPI, vol. 10(10), pages 1-16, October.
    7. Ruben Zieba Falama & Wojciech Skarka & Serge Yamigno Doka, 2022. "Optimal Design and Comparative Analysis of a PV/Mini-Hydropower and a PV/Battery Used for Electricity and Water Supply," Energies, MDPI, vol. 16(1), pages 1-22, December.
    8. Ozkurt, Celil & Camci, Fatih & Atamuradov, Vepa & Odorry, Christopher, 2016. "Integration of sampling based battery state of health estimation method in electric vehicles," Applied Energy, Elsevier, vol. 175(C), pages 356-367.
    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. Spyros Giannelos & Anjali Jain & Stefan Borozan & Paola Falugi & Alexandre Moreira & Rohit Bhakar & Jyotirmay Mathur & Goran Strbac, 2021. "Long-Term Expansion Planning of the Transmission Network in India under Multi-Dimensional Uncertainty," Energies, MDPI, vol. 14(22), pages 1-27, November.
    11. Thanh-Tung Nguyen & Abdul Basit Khan & Younghwi Ko & Woojin Choi, 2020. "An Accurate State of Charge Estimation Method for Lithium Iron Phosphate Battery Using a Combination of an Unscented Kalman Filter and a Particle Filter," Energies, MDPI, vol. 13(17), pages 1-15, September.
    12. 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.
    13. Poolla, Chaitanya & Ishihara, Abraham K. & Milito, Rodolfo, 2019. "Designing near-optimal policies for energy management in a stochastic environment," Applied Energy, Elsevier, vol. 242(C), pages 1725-1737.
    14. Chivon Choeung & Meng Leang Kry & Young Il Lee, 2018. "Robust Tracking Control of a Three-Phase Charger under Unbalanced Grid Conditions," Energies, MDPI, vol. 11(12), pages 1-16, December.
    15. Wang, Yujie & Sun, Zhendong & Chen, Zonghai, 2019. "Energy management strategy for battery/supercapacitor/fuel cell hybrid source vehicles based on finite state machine," Applied Energy, Elsevier, vol. 254(C).
    16. Jiang, Yunfeng & Xia, Bing & Zhao, Xin & Nguyen, Truong & Mi, Chris & de Callafon, Raymond A., 2017. "Data-based fractional differential models for non-linear dynamic modeling of a lithium-ion battery," Energy, Elsevier, vol. 135(C), pages 171-181.
    17. Ali Reza Kheirkhah & Carlos Frederico Meschini Almeida & Nelson Kagan & Jonatas Boas Leite, 2023. "Optimal Probabilistic Allocation of Photovoltaic Distributed Generation: Proposing a Scenario-Based Stochastic Programming Model," Energies, MDPI, vol. 16(21), pages 1-18, October.
    18. 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.
    19. Qi Wang & Tian Gao & Xingcan Li, 2022. "SOC Estimation of Lithium-Ion Battery Based on Equivalent Circuit Model with Variable Parameters," Energies, MDPI, vol. 15(16), pages 1-15, August.
    20. Ashikur Rahman & Xianke Lin & Chongming Wang, 2022. "Li-Ion Battery Anode State of Charge Estimation and Degradation Monitoring Using Battery Casing via Unknown Input Observer," Energies, MDPI, vol. 15(15), pages 1-19, August.

    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:16:y:2023:i:17:p:6239-:d:1226960. 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.