储能锂离子电池包冷却系统的数值模拟与结构优化

doi:10.11930/j.issn.1004-9649.202306114

摘要/Abstract

摘要：

储能电池包的热管理设计是保证储能系统安全运行的重要因素。基于STAR-CCM+平台对不同冷却方式的储能电池包进行结构优化。对比分析了传统间接式液冷、浸没式冷却以及优化后浸没式模型的散热性能，为浸没式储能电池包的设计和开发提供了重要参考。通过仿真与实验对比，验证了所提模型的准确性，所提方法可为储能锂离子电池包热管理设计提供指导。

关键词: 浸没式冷却, 间接式液冷, 结构优化, 数值模拟

Abstract:

The thermal management design of energy storage battery packs is an important factor in ensuring the safe operation of energy storage systems. This article is based on the STAR-CCM+platform to optimize the structure of energy storage battery packs with different cooling methods. This article compares and analyzes the heat dissipation performance of traditional indirect liquid cooling, immersion cooling, and optimized immersion models, providing important reference for the design and development of immersion energy storage battery packs. Through simulation and experimental comparison, this article verifies the accuracy of the proposed model, which can provide guidance for the design of thermal management of energy storage lithium-ion batteries.

Key words: immersion cooling, indirect cooling, structure optimization, numerical simulation

刘周斌, 朱涛, 姜巍, 张晓波, 王炯耿, 管茜茜, 张秋实, 赵庆良. 储能锂离子电池包冷却系统的数值模拟与结构优化[J]. 中国电力, 2023, 56(10): 202-210.

Zhoubin LIU, Tao ZHU, Wei JIANG, Xiaobo ZHANG, Jionggeng WANG, Qianqian GUAN, Qiushi ZHANG, Qingliang ZHAO. Simulation Analysis and Structure Optimization of Cooling System for Energy Storage Lithium-Ion Battery Pack[J]. Electric Power, 2023, 56(10): 202-210.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202306114

https://www.electricpower.com.cn/CN/Y2023/V56/I10/202

图/表 17

图 1 间接式储能电池包模型

Fig.1 Model of indirect storage battery pack

表 1 电芯参数

Table 1 Parameters of cell

项目		数值
电芯材料		磷酸铁锂
电芯容量/Ah		280
额定电压/V		3.2
导热系数 x, y, z/(W·(m·K)^–1)		21.6, 21.6, 2.11
比热容/(J·(kg·K)^–1)		3 660
密度/(kg·m^–3)		2 120
电芯尺寸/mm		204×174×72
电芯内阻/mΩ		0.43

图 2 间接式储能电池包网格

Fig.2 Mesh of indirect storage battery pack

表 2 5种方案网格数量

Table 2 Five cases with mesh numbers

方案		1		2		3		4		5
数量/万		738		886		984		1143		1737

图 3 网格无关性验证

Fig.3 Grid independence verification

图 4 实验装置

Fig.4 Experiment equipment

图 5 温度对比

Fig.5 Temperature contrast

图 6 间接式储能电池包温度分布

Fig.6 Temperature distribution of indirect storage battery pack

图 7 浸没式储能电池包模型

Fig.7 Model of immersion storage battery pack

表 3 冷却液参数

Table 3 Parameters of coolant

项目	水-乙二醇溶液	绝缘液体
密度（20 ℃）/(kg·m^–3)	1075	820
导热系数/(W·(m·K)^–1)	0.375	0.142
比热容/(J·(kg·K)^–1)	3251	2200
运动粘度（40 ℃）/cSt	4.8	10.5

图 8 网格无关性验证

Fig.8 Grid independence verification

图 9 浸没式储能电池包温度分布

Fig.9 Temperature of immersion storage battery pack

图 10 2种冷却方式温度对比

Fig.10 Temperature contrast of two cooling method

图 11 优化后浸没式储能电池包模型

Fig.11 Optimized model of immersion storage battery pack

图 12 优化后浸没式储能电池包温度分布

Fig.12 Temperature of optimized immersion battery pack

图 13 不同模型温度对比

Fig.13 Temperature contrast of different model

表 4 压降对比

Table 4 Comparison of pressure drop

冷却方式		间接式		浸没式		优化模型
压降/kPa		66.10		3.50		1.38

参考文献 35

1	杨续来, 袁帅帅, 杨文静, 等. 锂离子动力电池能量密度特性研究进展[J]. 机械工程学报, 2023, 59 (6): 239- 254.
	YANG Xulai, YUAN Shuaishuai, YANG Wenjing, et al. Research progress on energy density of Li-ion batteries for EVs[J]. Journal of Mechanical Engineering, 2023, 59 (6): 239- 254.
2	郎伟强, 楼鑫, 叶加炜, 等. 新能源系统中的储能技术分析[J]. 电子技术, 2022, 51 (10): 172- 173.
	LANG Weiqiang, LOU Xin, YE Jiawei, et al. Analysis of energy storage technology in new energy system[J]. Electronic Technology, 2022, 51 (10): 172- 173.
3	俞恩科, 陈梁金. 大规模电力储能技术的特性与比较[J]. 浙江电力, 2011, 30 (12): 4- 8. DOI
	YU Enke, CHEN Liangjin. Characteristics and comparison of large-scale electric energy storage technologies[J]. Zhejiang Electric Power, 2011, 30 (12): 4- 8. DOI
4	刘阳, 滕卫军, 谷青发, 等. 规模化多元电化学储能度电成本及其经济性分析[J]. 储能科学与技术, 2023, 12 (1): 312- 318. DOI
	LIU Yang, TENG Weijun, GU Qingfa, et al. Scaled-up diversified electrochemical energy storage LCOE and its economic analysis[J]. Energy Storage Science and Technology, 2023, 12 (1): 312- 318. DOI
5	KIM J, OH J, LEE H. Review on battery thermal management system for electric vehicles[J]. Applied Thermal Engineering, 2019, 149, 192- 212. DOI
6	VISHNUMURTHY K A, GIRISH K H. A comprehensive review of battery technology for E-mobility[J]. Journal of the Indian Chemical Society, 2021, 98 (10): 100173. DOI
7	TERADA N, YANAGI T, ARAI S, et al. Development of lithium batteries for energy storage and EV applications[J]. Journal of Power Sources, 2001, 100 (1/2): 80- 92.
8	DOYLE M, FULLER T F, NEWMAN J. Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell[J]. Journal of the Electrochemical Society, 1993, 140 (6): 1526- 1533. DOI
9	CHEN Z Y, XIONG R, SUN F C. Research status and analysis for battery safety accidents in electric vehicles[J]. Journal of Mechanical Engineering, 2019, 55 (24): 93. DOI
10	BAI F F, CHEN M B, SONG W J, et al. Thermal management performances of PCM/water cooling-plate using for lithium-ion battery module based on non-uniform internal heat source[J]. Applied Thermal Engineering, 2017, 126, 17- 27. DOI
11	CHEN K, WU W X, YUAN F, et al. Cooling efficiency improvement of air-cooled battery thermal management system through designing the flow pattern[J]. Energy, 2019, 167, 781- 790. DOI
12	PESARAN A A. Battery thermal models for hybrid vehicle simulations[J]. Journal of Power Sources, 2002, 110 (2): 377- 382. DOI
13	FAN Y Q, BAO Y, LING C, et al. Experimental study on the thermal management performance of air cooling for high energy density cylindrical lithium-ion batteries[J]. Applied Thermal Engineering, 2019, 155, 96- 109. DOI
14	CHEN D F, JIANG J C, KIM G H, et al. Comparison of different cooling methods for lithium ion battery cells[J]. Applied Thermal Engineering, 2016, 94, 846- 854. DOI
15	ZHAO Q A, WU H W, WANG Z H, et al. Numerical research on lithium-ion battery thermal management utilizing a novel cobweb-like channel cooling plate exchanger[J]. Frontiers in Energy Research, 2022, 10, 992779. DOI
16	孔为, 金劲涛, 陆西坡, 等. 对称蛇形流道锂离子电池冷却性能[J]. 储能科学与技术, 2022, 11 (7): 2258- 2265.
	KONG Wei, JIN Jintao, LU Xipo, et al. Study on cooling performance of lithium ion batteries with symmetrical serpentine channel[J]. Energy Storage Science and Technology, 2022, 11 (7): 2258- 2265.
17	WU M S, HUNG Y H, WANG Y Y, et al. Heat dissipation behavior of the nickel/metal hydride battery[J]. Journal of the Electrochemical Society, 2000, 147 (3): 930. DOI
18	WU W X, WANG S F, WU W, et al. A critical review of battery thermal performance and liquid based battery thermal management[J]. Energy Conversion and Management, 2019, 182, 262- 281. DOI
19	ROE C, FENG X N, WHITE G, et al. Immersion cooling for lithium-ion batteries-a review[J]. Journal of Power Sources, 2022, 525, 231094. DOI
20	NELSON P, DEES D, AMINE K, et al. Modeling thermal management of lithium-ion PNGV batteries[J]. Journal of Power Sources, 2002, 110 (2): 349- 356. DOI
21	DENG Y W, FENG C L, JIAQIANG E, et al. Effects of different coolants and cooling strategies on the cooling performance of the power lithium ion battery system: a review[J]. Applied Thermal Engineering, 2018, 142, 10- 29. DOI
22	田钧, 高帅. 基于浸没式技术的纯电动汽车电池包热管理方案解析[J]. 汽车电器, 2023, (5): 6- 8. DOI
	TIAN Jun, GAO Shuai. Solution analysis of battery pack thermal management for pure electric vehicle based on immersion technology[J]. Auto Electric Parts, 2023, (5): 6- 8. DOI
23	CHEN S C, WAN C C, WANG Y Y. Thermal analysis of lithium-ion batteries[J]. Journal of Power Sources, 2005, 140 (1): 111- 124. DOI
24	JARRETT A, KIM I Y. Design optimization of electric vehicle battery cooling plates for thermal performance[J]. Journal of Power Sources, 2011, 196 (23): 10359- 10368. DOI
25	路帅. 锂离子动力电池模组热场仿真及散热控制[D]. 吉林: 东北电力大学, 2021.
	LU Shuai. Thermal field simulation and heat dissipation control of lithium ion power battery module[D]. Jilin: Northeast Dianli University, 2021.
26	BERNARDI D, PAWLIKOWSKI E, NEWMAN J. A general energy balance for battery systems[J]. Journal of the Electrochemical Society, 1985, 132 (1): 5- 12. DOI
27	吕超, 张爽, 朱世怀, 等. 储能锂离子电池包强制风冷系统热仿真分析与优化[J]. 电力系统保护与控制, 2021, 49 (12): 48- 55. DOI
	LÜ Chao, ZHANG Shuang, ZHU Shihuai, et al. Thermal simulation analysis and optimization of forced air cooling system for energy storage lithium-ion battery pack[J]. Power System Protection and Control, 2021, 49 (12): 48- 55. DOI
28	王明强, 郭月明, 许淘淘, 等. 锂离子动力电池组发热功率试验研究[J]. 汽车零部件, 2020, (5): 69- 72. DOI
	WANG Mingqiang, GUO Yueming, XU Taotao, et al. Experiment research on the heating power of lithium-ion battery module[J]. Automobile Parts, 2020, (5): 69- 72. DOI
29	HUO Y T, RAO Z H, LIU X J, et al. Investigation of power battery thermal management by using mini-channel cold plate[J]. Energy Conversion and Management, 2015, 89, 387- 395. DOI
30	STERN F, WILSON R V, COLEMAN H W, et al. Comprehensive approach to verification and validation of CFD simulations—part 1: methodology and procedures[J]. Journal of Fluids Engineering, 2001, 123 (4): 793- 802. DOI
31	安富强, 赵洪量, 程志, 等. 纯电动车用锂离子电池发展现状与研究进展[J]. 工程科学学报, 2019, 41 (1): 22- 42.
	AN Fuqiang, ZHAO Hongliang, CHENG Zhi, et al. Development status and research progress of power battery for pure electric vehicles[J]. Chinese Journal of Engineering, 2019, 41 (1): 22- 42.
32	卢子敬, 李子寿, 郭相国, 等. 基于多目标人工蜂鸟算法的电-氢混合储能系统最优配置[J]. 中国电力, 2023, 56 (7): 33- 42.
	LU Zijing, LI Zishou, GUO Xiangguo, et al. Optimal configuration of electricity-hydrogen hybrid energy storage system based on multi-objective artificial hummingbird algorithm[J]. Electric Power, 2023, 56 (7): 33- 42.
33	张媛, 夏向阳, 岳家辉, 等. 基于电池簇放电电量的电池堆不一致性在线监测方法[J]. 中国电力, 2023, 56 (7): 207- 215, 227.
	ZHANG Yuan, XIA Xiangyang, YUE Jiahui, et al. Online monitoring method of battery stack inconsistency based on discharge quantity of battery clusters[J]. Electric Power, 2023, 56 (7): 207- 215, 227.
34	余斌, 宋兴荣, 周挺, 等. 基于梅尔倒谱系数特征集的储能变流器开路故障诊断方法[J]. 中国电力, 2022, 55 (12): 34- 42.
	YU Bin, SONG Xingrong, ZHOU Ting, et al. Open circuit fault diagnosis method of energy storage converter based on Mel cepstrum coefficient feature set[J]. Electric Power, 2022, 55 (12): 34- 42.
35	黎冲, 王成辉, 王高, 等. 基于数据驱动的锂离子电池健康状态估计技术[J]. 中国电力, 2022, 55 (8): 73- 86, 95.
	LI Chong, WANG Chenghui, WANG Gao, et al. Technology of lithium-ion battery state-of-health assessment based on data-driven[J]. Electric Power, 2022, 55 (8): 73- 86, 95.

[1]	耿直, 鲁向武, 王剑利, 石天庆, 常绪成, 顾煜炯. CPC 集热器冷却通道结构优化及换热流动数值模拟[J]. 中国电力, 2023, 56(9): 206-214.
[2]	张顺, 王振国, 姜文东, 徐枫, 段忠东. 特高压输电塔龙卷风荷载特性的数值模拟[J]. 中国电力, 2023, 56(10): 153-163.
[3]	王宇航, 王文玲, 周绪红, 王康, 罗崯滔. 海上风电机组格构式浮式基础结构优化及响应分析[J]. 中国电力, 2022, 55(5): 21-31.
[4]	潘晓伟, 彭烁, 李硕, 周贤, 王长军, 刘峻, 王瑞元. 余热锅炉烟气低温余热回收塔流场均匀性研究[J]. 中国电力, 2022, 55(3): 159-166.
[5]	雷嗣远, 李海浩, 李乐田, 倪贵东, 孔凡海, 吴国勋, 卞子君. SCR脱硝低负荷投运烟气调温旁路改造设计[J]. 中国电力, 2019, 52(9): 179-184.
[6]	陈海杰, 马务, 刘贡祎, 高攀. W火焰锅炉SNCR脱硝及其对SCR入口流场的影响[J]. 中国电力, 2019, 52(7): 146-153.
[7]	闫俊伏, 赵学斌. SCR催化剂的磨损试验与数值模拟研究[J]. 中国电力, 2019, 52(5): 170-175.
[8]	肖育军, 邹毅辉, 李彩亭, 周雪斌. SCR系统结构模型与数值模型的适用性分析[J]. 中国电力, 2019, 52(3): 146-152,160.
[9]	刘含笑, 陈招妹, 郭高飞, 王剑波, 崔盈, 孟银灿, 刘美玲. 烟气脱汞活性炭干粉喷射实验及喷射效果数值模拟[J]. 中国电力, 2019, 52(10): 138-143,170.
[10]	佘晓利, 潘卫国, 王程瑶, 倪迎春, 秦岭. 脱硫废水旁路塔雾化蒸发数值模拟[J]. 中国电力, 2019, 52(1): 129-136.
[11]	周玲妹, 张冠军, 朱宪然, 李皓宇, 焦开明. 600 MW机组锅炉掺烧劣质煤技术经济性研究[J]. 中国电力, 2018, 51(9): 1-7.
[12]	马君华, 陆一鸣, 袁文广, 王磊, 黄文瑞, 延星. 能源互联网评价体系研究[J]. 中国电力, 2018, 51(8): 38-42.
[13]	雷鉴琦. 降低燃煤机组SCR脱硝系统催化剂磨损的流场优化[J]. 中国电力, 2018, 51(7): 152-156,169.
[14]	杨来顺, 徐明海, 陈秋实. 管式除雾器开孔对除雾性能影响的数值模拟研究[J]. 中国电力, 2018, 51(7): 178-184.
[15]	叶侠丰, 丁红蕾, 潘卫国, 潘衍行. 带拓展面椭圆管束的换热、积灰及磨损特性研究[J]. 中国电力, 2018, 51(6): 26-32.