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

被引:0
|
作者
Li, Guanru [1 ,2 ]
Zhong, Yangfan [3 ]
Bao, Chujin [4 ]
Chen, Yongping [1 ,2 ]
Zhang, Chengbin [1 ,2 ]
机构
[1] Southeast Univ, Sch Energy & Environm, Nanjing 210096, Peoples R China
[2] Suzhou Univ Sci & Technol, Key Lab Efficient Low Carbon Energy Convers & Util, Suzhou 215009, Peoples R China
[3] Alibaba Cloud Comp Co Ltd, Hangzhou 311121, Peoples R China
[4] Zhejiang Immertech Co Ltd, Hangzhou 310000, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
temperature control; battery thermal management; model-free controller; fuzzy logic control; THERMAL MANAGEMENT-SYSTEM; POWER BATTERY; HEAT-TRANSFER; DESIGN;
D O I
10.1007/s11630-024-2013-1
中图分类号
O414.1 [热力学];
学科分类号
摘要
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 similar to 0.2 degrees C (regular condition) and similar to 0.5 degrees C (extreme condition) compared with similar to 1.1 degrees C (regular condition) and similar to 1.6 degrees 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.
引用
收藏
页码:1794 / 1808
页数:15
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