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Online Estimation of Peak Power Capability of Li-Ion Batteries in Electric Vehicles by a Hardware-in-Loop Approach

Author

Listed:
  • Rui Xiong

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Hongwen He

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Fengchun Sun

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Kai Zhao

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

Abstract

Battery peak power capability estimations play an important theoretical role for the proper use of the battery in electric vehicles. To address the failures in relaxation effects and real-time ability performance, neglecting the battery’s design limits and other issues of the traditional peak power capability calculation methods, a new approach based on the dynamic electrochemical-polarization (EP) battery model, taking into consideration constraints of current, voltage, state of charge (SoC) and power is proposed. A hardware-in-the-loop (HIL) system is built for validating the online model-based peak power capability estimation approach of batteries used in hybrid electric vehicles (HEVs) and a HIL test based on the Federal Urban Driving Schedules (FUDS) is used to verify and evaluate its real-time computation performance, reliability and robustness. The results show the proposed approach gives a more accurate estimate compared with the hybrid pulse power characterization (HPPC) method, avoiding over-charging or over-discharging and providing a powerful guarantee for the optimization of HEVs power systems. Furthermore, the HIL test provides valuable data and critical guidance to evaluate the accuracy of the developed battery algorithms.

Suggested Citation

  • Rui Xiong & Hongwen He & Fengchun Sun & Kai Zhao, 2012. "Online Estimation of Peak Power Capability of Li-Ion Batteries in Electric Vehicles by a Hardware-in-Loop Approach," Energies, MDPI, vol. 5(5), pages 1-15, May.
    • Handle: RePEc:gam:jeners:v:5:y:2012:i:5:p:1455-1469:d:17748
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    References listed on IDEAS

    as
    1. Sun, Fengchun & Xiong, Rui & He, Hongwen & Li, Weiqing & Aussems, Johan Eric Emmanuel, 2012. "Model-based dynamic multi-parameter method for peak power estimation of lithium–ion batteries," Applied Energy, Elsevier, vol. 96(C), pages 378-386.
    2. Meirong Su & Chen Liang & Bin Chen & Shaoqing Chen & Zhifeng Yang, 2012. "Low-Carbon Development Patterns: Observations of Typical Chinese Cities," Energies, MDPI, vol. 5(2), pages 1-14, February.
    3. 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.
    4. Hong-Wen He & Rui Xiong & Yu-Hua Chang, 2010. "Dynamic Modeling and Simulation on a Hybrid Power System for Electric Vehicle Applications," Energies, MDPI, vol. 3(11), pages 1-10, November.
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