Modelling and Temperature Control of Liquid Cooling Process for Lithium-Ion Battery

  • LI Guanru ,
  • ZHONG Yangfan ,
  • BAO Chujin ,
  • CHEN Yongping ,
  • ZHANG Chengbin
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  • 1. School of Energy and Environment, Southeast University, Nanjing 210096, China
    2. Key Laboratory of Efficient Low-Carbon Energy Conversion and Utilization of Jiangsu Provincial Higher Education Institutions, Suzhou University of Science and Technology, Suzhou 215009, China
    3. Alibaba Cloud Computing Co. Ltd., Hangzhou 311121, China
    4. Zhejiang Immertech Co. Ltd., Hangzhou 310000, China

Online published: 2024-09-08

Supported by

This work was supported by the National Key R&D Program of China (2021YFB3803200) and the National Natural Science Foundation of China (Grant No. U2241253).

Copyright

Science Press, Institute of Engineering Thermophysics, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2024

Abstract

Efficient thermal management of lithium-ion battery, working under extremely rapid charging-discharging, is of widespread interest to avoid the battery degradation due to temperature rise, resulting in the enhanced lifespan. Herein, thermal management of lithium-ion battery has been performed via a liquid cooling theoretical model integrated with thermoelectric model of battery packs and single-phase heat transfer. Aiming to alleviate the battery temperature fluctuation by automatically manipulating the flow rate of working fluid, a nominal model-free controller, i.e., fuzzy logic controller is designed. An optimized on-off controller based on pump speed optimization is introduced to serve as the comparative controller. Thermal control simulations are conducted under regular operating and extreme operating conditions, and two controllers are applied to control battery temperature with proper intervals which is conducive to enhance the battery charge-discharge efficiency. The results indicate that, for any operating condition, the fuzzy logic controller shows excellence in terms of the tracking accuracy of set-point of battery temperature. Thanks to the establishment of fuzzy set and fuzzy behavioral rules, the battery temperature has been throughout maintained near the set point, and the temperature fluctuation amplitude is highly reduced, with better temperature control accuracy of ~0.2°C (regular condition) and ~0.5°C (extreme condition) compared with ~1.1°C (regular condition) and ~1.6°C (extreme condition) of optimized on-off controller. While in the case of extreme operating condition, the proposed optimized on-off controller manifests the hysteresis in temperature fluctuation, which is ascribed to the set of dead-band for the feedback temperature. The simulation results cast new light on the utilization and development of model-free temperature controller for the thermal management of lithium-ion battery.

Cite this article

LI Guanru , ZHONG Yangfan , BAO Chujin , CHEN Yongping , ZHANG Chengbin . Modelling and Temperature Control of Liquid Cooling Process for Lithium-Ion Battery[J]. Journal of Thermal Science, 2024 , 33(5) : 1794 -1808 . DOI: 10.1007/s11630-024-2013-1

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