IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i7p1629-d340284.html
   My bibliography  Save this article

Li-Ion Battery Performance Degradation Modeling for the Optimal Design and Energy Management of Electrified Propulsion Systems

Author

Listed:
  • Li Chen

    (Department of Mechanical Engineering, Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada)

  • Yuqi Tong

    (Department of Mechanical Engineering, Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada
    State-assigned Electric Vehicle Power Battery Center, Beijing 100072, China)

  • Zuomin Dong

    (Department of Mechanical Engineering, Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada)

Abstract

Heavy-duty hybrid electric vehicles and marine vessels need a sizeable electric energy storage system (ESS). The size and energy management strategy (EMS) of the ESS affects the system performance, cost, emissions, and safety. Traditional power-demand-based and fuel-economy-driven ESS sizing and energy management has often led to shortened battery cycle life and higher replacement costs. To consider minimizing the total lifecycle cost (LCC) of hybrid electric propulsion systems, the battery performance degradation and the life prediction model is a critical element in the optimal design process. In this work, a new Li-ion battery (LIB) performance degradation model is introduced based on a large set of cycling experiment data on LiFePO 4 (LFP) batteries to predict their capacity decay, resistance increase and the remaining cycle life under various use patterns. Critical parameters of the semi-empirical, amended equivalent circuit model were identified using least-square fitting. The model is used to calculate the investment, operation, replacement and recycling costs of the battery ESS over its lifetime. Validation of the model is made using battery cycling experimental data. The new LFP battery performance degradation model is used in optimizing the sizes of the key hybrid electric powertrain component of an electrified ferry ship with the minimum overall LCC. The optimization result presents a 12 percent improvement over the traditional power demand-driven hybrid powertrain design method. The research supports optimal sizing and EMS development of hybrid electric vehicles and vessels to achieve minimum lifecycle costs.

Suggested Citation

  • Li Chen & Yuqi Tong & Zuomin Dong, 2020. "Li-Ion Battery Performance Degradation Modeling for the Optimal Design and Energy Management of Electrified Propulsion Systems," Energies, MDPI, vol. 13(7), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1629-:d:340284
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/7/1629/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/7/1629/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hou, Cong & Ouyang, Minggao & Xu, Liangfei & Wang, Hewu, 2014. "Approximate Pontryagin’s minimum principle applied to the energy management of plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 115(C), pages 174-189.
    2. Heymans, Catherine & Walker, Sean B. & Young, Steven B. & Fowler, Michael, 2014. "Economic analysis of second use electric vehicle batteries for residential energy storage and load-levelling," Energy Policy, Elsevier, vol. 71(C), pages 22-30.
    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. Ye-Rin Kim & Jae-Myeong Kim & Jae-Jung Jung & So-Yeon Kim & Jae-Hak Choi & Hyun-Goo Lee, 2021. "Comprehensive Design of DC Shipboard Power Systems for Pure Electric Propulsion Ship Based on Battery Energy Storage System," Energies, MDPI, vol. 14(17), pages 1-28, August.
    2. Jessica Kersey & Natalie D. Popovich & Amol A. Phadke, 2022. "Rapid battery cost declines accelerate the prospects of all-electric interregional container shipping," Nature Energy, Nature, vol. 7(7), pages 664-674, July.
    3. Bo Pang & Li Chen & Zuomin Dong, 2022. "Data-Driven Degradation Modeling and SOH Prediction of Li-Ion Batteries," Energies, MDPI, vol. 15(15), pages 1-12, August.
    4. Marcin Szott & Marcin Jarnut & Jacek Kaniewski & Łukasz Pilimon & Szymon Wermiński, 2021. "Fault-Tolerant Control in a Peak-Power Reduction System of a Traction Substation with Multi-String Battery Energy Storage System," Energies, MDPI, vol. 14(15), pages 1-23, July.
    5. Feng, Yanbiao & Dong, Zuomin, 2020. "Integrated design and control optimization of fuel cell hybrid mining truck with minimized lifecycle cost," Applied Energy, Elsevier, vol. 270(C).

    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. Bizon, Nicu, 2019. "Real-time optimization strategies of Fuel Cell Hybrid Power Systems based on Load-following control: A new strategy, and a comparative study of topologies and fuel economy obtained," Applied Energy, Elsevier, vol. 241(C), pages 444-460.
    2. Peng, Fei & Zhao, Yuanzhe & Li, Xiaopeng & Liu, Zhixiang & Chen, Weirong & Liu, Yang & Zhou, Donghua, 2017. "Development of master-slave energy management strategy based on fuzzy logic hysteresis state machine and differential power processing compensation for a PEMFC-LIB-SC hybrid tramway," Applied Energy, Elsevier, vol. 206(C), pages 346-363.
    3. Bảo-Huy Nguyễn & João Pedro F. Trovão & Ronan German & Alain Bouscayrol, 2020. "Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation," Energies, MDPI, vol. 13(21), pages 1-19, October.
    4. Gur, K. & Chatzikyriakou, D. & Baschet, C. & Salomon, M., 2018. "The reuse of electrified vehicle batteries as a means of integrating renewable energy into the European electricity grid: A policy and market analysis," Energy Policy, Elsevier, vol. 113(C), pages 535-545.
    5. Chen, Zheng & Hu, Hengjie & Wu, Yitao & Zhang, Yuanjian & Li, Guang & Liu, Yonggang, 2020. "Stochastic model predictive control for energy management of power-split plug-in hybrid electric vehicles based on reinforcement learning," Energy, Elsevier, vol. 211(C).
    6. Kuang, Yanqing & Chen, Yang & Hu, Mengqi & Yang, Dong, 2017. "Influence analysis of driver behavior and building category on economic performance of electric vehicle to grid and building integration," Applied Energy, Elsevier, vol. 207(C), pages 427-437.
    7. Liang, Yanan & Kleijn, René & Tukker, Arnold & van der Voet, Ester, 2022. "Material requirements for low-carbon energy technologies: A quantitative review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    8. Anselma, Pier Giuseppe, 2022. "Computationally efficient evaluation of fuel and electrical energy economy of plug-in hybrid electric vehicles with smooth driving constraints," Applied Energy, Elsevier, vol. 307(C).
    9. Chaofeng Pan & Yanyan Liang & Long Chen & Liao Chen, 2019. "Optimal Control for Hybrid Energy Storage Electric Vehicle to Achieve Energy Saving Using Dynamic Programming Approach," Energies, MDPI, vol. 12(4), pages 1-19, February.
    10. Tang, Yanyan & Zhang, Qi & Li, Yaoming & Li, Hailong & Pan, Xunzhang & Mclellan, Benjamin, 2019. "The social-economic-environmental impacts of recycling retired EV batteries under reward-penalty mechanism," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    11. Balakumar Balasingam & Mostafa Ahmed & Krishna Pattipati, 2020. "Battery Management Systems—Challenges and Some Solutions," Energies, MDPI, vol. 13(11), pages 1-19, June.
    12. Jiang, Hongliang & Xu, Liangfei & Li, Jianqiu & Hu, Zunyan & Ouyang, Minggao, 2019. "Energy management and component sizing for a fuel cell/battery/supercapacitor hybrid powertrain based on two-dimensional optimization algorithms," Energy, Elsevier, vol. 177(C), pages 386-396.
    13. Penghui Qiang & Peng Wu & Tao Pan & Huaiquan Zang, 2021. "Real-Time Approximate Equivalent Consumption Minimization Strategy Based on the Single-Shaft Parallel Hybrid Powertrain," Energies, MDPI, vol. 14(23), pages 1-22, November.
    14. Hou, Daizheng & Sun, Qun & Bao, Chunjiang & Cheng, Xingqun & Guo, Hongqiang & Zhao, Ying, 2019. "An all-in-one design method for plug-in hybrid electric buses considering uncertain factor of driving cycles," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    15. Mostafavi Sani, Mostafa & Mostafavi Sani, Hossein & Fowler, Michael & Elkamel, Ali & Noorpoor, Alireza & Ghasemi, Amir, 2022. "Optimal energy hub development to supply heating, cooling, electricity and freshwater for a coastal urban area taking into account economic and environmental factors," Energy, Elsevier, vol. 238(PB).
    16. Yongyou Nie & Yuhan Wang & Lu Li & Haolan Liao, 2023. "Literature Review on Power Battery Echelon Reuse and Recycling from a Circular Economy Perspective," IJERPH, MDPI, vol. 20(5), pages 1-28, February.
    17. Song, Ziyou & Li, Jianqiu & Hou, Jun & Hofmann, Heath & Ouyang, Minggao & Du, Jiuyu, 2018. "The battery-supercapacitor hybrid energy storage system in electric vehicle applications: A case study," Energy, Elsevier, vol. 154(C), pages 433-441.
    18. Zhuang, Weichao & Zhang, Xiaowu & Li, Daofei & Wang, Liangmo & Yin, Guodong, 2017. "Mode shift map design and integrated energy management control of a multi-mode hybrid electric vehicle," Applied Energy, Elsevier, vol. 204(C), pages 476-488.
    19. Fengqi Zhang & Lihua Wang & Serdar Coskun & Hui Pang & Yahui Cui & Junqiang Xi, 2020. "Energy Management Strategies for Hybrid Electric Vehicles: Review, Classification, Comparison, and Outlook," Energies, MDPI, vol. 13(13), pages 1-35, June.
    20. Wu, Wei & Lin, Boqiang, 2018. "Application value of energy storage in power grid: A special case of China electricity market," Energy, Elsevier, vol. 165(PB), pages 1191-1199.

    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:7:p:1629-:d:340284. 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.