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Energy Management of Parallel-Connected Cells in Electric Vehicles Based on Fuzzy Logic Control

Author

Listed:
  • Chuanxue Song

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

  • Yulong Shao

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

  • Shixin Song

    (School of Mechanical Science and Engineering, Jilin University, Changchun 130022, China)

  • Cheng Chang

    (College of Automotive Engineering, Jilin University, Changchun 130022, China)

  • Fang Zhou

    (College of Automotive Engineering, Jilin University, Changchun 130022, China)

  • Silun Peng

    (College of Automotive Engineering, Jilin University, Changchun 130022, China)

  • Feng Xiao

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

Abstract

Inconsistencies that are associated with parallel-connected cells used in electric vehicles induce varied states of charge ( SOCs ) in each cell. Thus, loop current in the battery pack is inevitable, and this reduces overall capacity, energy utilization rate, and pack lifetime. However, no method is available to address loop current. To reduce loop current and the resulting battery inconsistency, a parallel-connected cell pack (PCCP) model that considers thermal effects is established, and a novel Simscape model that is based on PCCP is successfully constructed. Furthermore, the strategy of parallel-connected cell energy management (PCCEM) is proposed to utilize fuzzy logic control (FLC) strategy, which automatically adjusts the number of cells in a circuit in accordance with the load demand, and turns on the first N switches in the corresponding SOC order. The New European Driving Cycle (NEDC) driving cycle simulation shows that the PCCEM strategy considerably reduces loop current and improves the consistency of battery performance and the utilization rate of battery power.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:3:p:404-:d:93610
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    References listed on IDEAS

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    1. Kim, Jonghoon & Cho, B.H., 2013. "Screening process-based modeling of the multi-cell battery string in series and parallel connections for high accuracy state-of-charge estimation," Energy, Elsevier, vol. 57(C), pages 581-599.
    2. Wang, Limei & Cheng, Yong & Zhao, Xiuliang, 2015. "A LiFePO4 battery pack capacity estimation approach considering in-parallel cell safety in electric vehicles," Applied Energy, Elsevier, vol. 142(C), pages 293-302.
    3. Dong, Guangzhong & Wei, Jingwen & Zhang, Chenbin & Chen, Zonghai, 2016. "Online state of charge estimation and open circuit voltage hysteresis modeling of LiFePO4 battery using invariant imbedding method," Applied Energy, Elsevier, vol. 162(C), pages 163-171.
    4. Jip Kim & Seung Wan Kim & Young Gyu Jin & Jong-Keun Park & Yong Tae Yoon, 2016. "Optimal Coordinated Management of a Plug-In Electric Vehicle Charging Station under a Flexible Penalty Contract for Voltage Security," Energies, MDPI, vol. 9(7), pages 1-15, July.
    5. Xiangwei Guo & Longyun Kang & Yuan Yao & Zhizhen Huang & Wenbiao Li, 2016. "Joint Estimation of the Electric Vehicle Power Battery State of Charge Based on the Least Squares Method and the Kalman Filter Algorithm," Energies, MDPI, vol. 9(2), pages 1-16, February.
    6. Dongqi Liu & Yaonan Wang & Yongpeng Shen, 2016. "Electric Vehicle Charging and Discharging Coordination on Distribution Network Using Multi-Objective Particle Swarm Optimization and Fuzzy Decision Making," Energies, MDPI, vol. 9(3), pages 1-17, March.
    7. 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.
    8. Wang, Shunli & Shang, Liping & Li, Zhanfeng & Deng, Hu & Li, Jianchao, 2016. "Online dynamic equalization adjustment of high-power lithium-ion battery packs based on the state of balance estimation," Applied Energy, Elsevier, vol. 166(C), pages 44-58.
    9. He, Hongwen & Xiong, Rui & Zhao, Kai & Liu, Zhentong, 2013. "Energy management strategy research on a hybrid power system by hardware-in-loop experiments," Applied Energy, Elsevier, vol. 112(C), pages 1311-1317.
    10. Xiaopeng Tang & Boyang Liu & Furong Gao & Zhou Lv, 2016. "State-of-Charge Estimation for Li-Ion Power Batteries Based on a Tuning Free Observer," Energies, MDPI, vol. 9(9), pages 1-12, August.
    11. 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.
    12. Jun Xu & Siqi Li & Chris Mi & Zheng Chen & Binggang Cao, 2013. "SOC Based Battery Cell Balancing with a Novel Topology and Reduced Component Count," Energies, MDPI, vol. 6(6), pages 1-15, May.
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    Cited by:

    1. Bizhong Xia & Zheng Zhang & Zizhou Lao & Wei Wang & Wei Sun & Yongzhi Lai & Mingwang Wang, 2018. "Strong Tracking of a H-Infinity Filter in Lithium-Ion Battery State of Charge Estimation," Energies, MDPI, vol. 11(6), pages 1-20, June.
    2. Phuong-Ha La & Sung-Jin Choi, 2020. "Novel Dynamic Resistance Equalizer for Parallel-Connected Battery Configurations," Energies, MDPI, vol. 13(13), pages 1-17, June.
    3. Liu, Xuze & Fotouhi, Abbas & Auger, Daniel J., 2020. "Optimal energy management for formula-E cars with regulatory limits and thermal constraints," Applied Energy, Elsevier, vol. 279(C).
    4. Saiteja, Pemmareddy & Ashok, B., 2022. "Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    5. Neha Bhushan & Saad Mekhilef & Kok Soon Tey & Mohamed Shaaban & Mehdi Seyedmahmoudian & Alex Stojcevski, 2022. "Overview of Model- and Non-Model-Based Online Battery Management Systems for Electric Vehicle Applications: A Comprehensive Review of Experimental and Simulation Studies," Sustainability, MDPI, vol. 14(23), pages 1-31, November.

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