Thermal management with fast temperature convergence based on optimized fuzzy PID algorithm for electric vehicle battery

被引：19

作者：

Liu, Zhangmiaoge ^{[1
]}

Liu, Zhouxiao ^{[1
]}

Liu, Jianzhao ^{[1
]}

Wang, Ning ^{[1
]}

机构：

[1] Univ Shanghai Sci & Technol, Engn Res Ctr Opt Instrument & Syst, Shanghai Key Lab Modern Opt Syst, Minist Educ, Jungong Rd 580, Shanghai 200093, Peoples R China

来源：

APPLIED ENERGY | 2023年 / 352卷

基金：

上海市自然科学基金;

关键词：

Electric vehicle battery; Fuzzy PID algorithm; Thermal management; NEURAL-NETWORK; PACKS; DIAGNOSIS; CHIP;

D O I：

10.1016/j.apenergy.2023.121936

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

In this study, we propose an optimized fuzzy proportional-integral-differential (Fuzzy PID) algorithm used in a rapid temperature control system for automotive batteries. Based on the proposed algorithm, an intelligent thermal management system with temperature feedback mechanism is built by switchable thermoelectric (TE) devices in working mode, simultaneously offering both heating and cooling capabilities. Assisted by liquid cooling optimization, the battery pack temperature is rapidly converged by the regulation of TE devices. Experimental results demonstrate that the temperature of a thermal runaway battery pack can be lowered from 63.5 degrees C to 25 degrees C in just 280 s, while the temperature of a frozen battery pack can be raised from-10 degrees C to 25 degrees C within 185 s. Compared to multi-channel liquid cooling method, our temperature control time is reduced by approximately 76%. The innovative structure and optimized temperature control algorithm can obviously enhance the efficiency of the battery temperature control system in new energy electric vehicle field.

引用

页数：10

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