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New Electro-Thermal Battery Pack Model of an Electric Vehicle

Author

Listed:
  • Muhammed Alhanouti

    (Institute of Vehicle System Technology, Karlsruhe Institute of Technology, Karlsruhe 76131, Germany)

  • Martin Gießler

    (Institute of Vehicle System Technology, Karlsruhe Institute of Technology, Karlsruhe 76131, Germany)

  • Thomas Blank

    (Institute of Data Processing and Electronics, Eggenstein-Leopoldshafen 76344, Germany)

  • Frank Gauterin

    (Institute of Vehicle System Technology, Karlsruhe Institute of Technology, Karlsruhe 76131, Germany)

Abstract

Since the evolution of the electric and hybrid vehicle, the analysis of batteries’ characteristics and influence on driving range has become essential. This fact advocates the necessity of accurate simulation modeling for batteries. Different models for the Li-ion battery cell are reviewed in this paper and a group of the highly dynamic models is selected for comparison. A new open circuit voltage (OCV) model is proposed. The new model can simulate the OCV curves of lithium iron magnesium phosphate (LiFeMgPO 4 ) battery type at different temperatures. It also considers both charging and discharging cases. The most remarkable features from different models, in addition to the proposed OCV model, are integrated in a single hybrid electrical model. A lumped thermal model is implemented to simulate the temperature development in the battery cell. The synthesized electro-thermal battery cell model is extended to model a battery pack of an actual electric vehicle. Experimental tests on the battery, as well as drive tests on the vehicle are performed. The proposed model demonstrates a higher modeling accuracy, for the battery pack voltage, than the constituent models under extreme maneuver drive tests.

Suggested Citation

  • Muhammed Alhanouti & Martin Gießler & Thomas Blank & Frank Gauterin, 2016. "New Electro-Thermal Battery Pack Model of an Electric Vehicle," Energies, MDPI, vol. 9(7), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:7:p:563-:d:74338
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    References listed on IDEAS

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    1. 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.
    2. Caiping Zhang & Jiuchun Jiang & Weige Zhang & Suleiman M. Sharkh, 2012. "Estimation of State of Charge of Lithium-Ion Batteries Used in HEV Using Robust Extended Kalman Filtering," Energies, MDPI, vol. 5(4), pages 1-18, April.
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    Cited by:

    1. 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.
    2. Zuchang Gao & Cheng Siong Chin & Wai Lok Woo & Junbo Jia, 2017. "Integrated Equivalent Circuit and Thermal Model for Simulation of Temperature-Dependent LiFePO 4 Battery in Actual Embedded Application," Energies, MDPI, vol. 10(1), pages 1-22, January.
    3. Cheng Siong Chin & Zuchang Gao, 2018. "State-of-Charge Estimation of Battery Pack under Varying Ambient Temperature Using an Adaptive Sequential Extreme Learning Machine," Energies, MDPI, vol. 11(4), pages 1-30, March.
    4. Tao Lei & Zhihao Min & Qinxiang Gao & Lina Song & Xingyu Zhang & Xiaobin Zhang, 2022. "The Architecture Optimization and Energy Management Technology of Aircraft Power Systems: A Review and Future Trends," Energies, MDPI, vol. 15(11), pages 1-37, June.
    5. Cheng Siong Chin & Zuchang Gao & Joel Hay King Chiew & Caizhi Zhang, 2018. "Nonlinear Temperature-Dependent State Model of Cylindrical LiFePO 4 Battery for Open-Circuit Voltage, Terminal Voltage and State-of-Charge Estimation with Extended Kalman Filter," Energies, MDPI, vol. 11(9), pages 1-28, September.

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