锂离子电池低温复合加热策略及优化

doi:10.19799/j.cnki.2095-4239.2022.0205

储能科学与技术 ›› 2022, Vol. 11 ›› Issue (10): 3191-3199.doi: 10.19799/j.cnki.2095-4239.2022.0205

锂离子电池低温复合加热策略及优化

李夔宁¹^,²(), 王靖鸿¹^,², 谢翌³, 刘彬¹^,², 刘江岩¹^,², 刘召婷¹^,²

^1.重庆大学低品位能源利用技术及系统教育部重点实验室
^2.重庆大学能源与动力工程学院
^3.重庆大学机械与运载工程学院，重庆 400044

收稿日期:2022-04-15 修回日期:2022-05-10 出版日期:2022-10-05 发布日期:2022-10-10
通讯作者: 李夔宁 E-mail:leekn@cqu.edu.cn
作者简介:李夔宁（1970—），男，博士，教授，博士生导师，从事制冷与空调新技术、汽车热系统/热环境控制技术的研究，E-mail：leekn@cqu.edu.cn。
基金资助:
广东省重点领域研发计划(2020B0909030001);国家自然基金面上项目(52072052);国家自然科学基金重点支持项目(U20A20310)

Low-temperature compound-heating strategy and optimization of lithium-ion battery

Kuining LI¹^,²(), Jinghong WANG¹^,², Yi XIE³, Bin LIU¹^,², Jiangyan LIU¹^,², Zhaoting LIU¹^,²

^1.Key Laboratory of Low-grade Energy Utilization Technologies and Systems, Ministry of Education of China, Chongqing University
^2.School of Energy and Power Engineering, Chongqing University
^3.College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China

Received:2022-04-15 Revised:2022-05-10 Online:2022-10-05 Published:2022-10-10
Contact: Kuining LI E-mail:leekn@cqu.edu.cn

摘要/Abstract

摘要：

电动汽车因为节能环保和能量转化效率高等特性在近年来发展迅速。在低温下，作为动力来源的锂离子电池的放电功率和容量等性能严重衰减，影响着电动汽车在北方极寒地区的发展和普及。因此，如何在低温下对锂离子电池进行可靠、高效、安全地低温加热显得尤为重要。以三元锂方块电池为研究对象，通过测试电池在不同工况下的低温特性，得出了电池电特性和热特性参数。建立单体电池低温电热耦合模型，通过神经网络方法拟合实验数据，得到电池低温加热仿真模型。通过电池不同工况下的温升实验，验证了仿真模型的精度。本文提出了电池多段恒流复合加热方法，建立了电池老化、加热时间、容量收益的多目标非线性优化模型，揭示了电池老化、加热时间和容量收益之间的关系，得到了评价加权权重矩阵。利用非支配排序遗传算法-?Ⅱ(NSGA-Ⅱ)和优劣解距离法(TOPSIS)，得到单体电池平衡加热策略，探究了电池不同初始状态对优化目标的影响规律。根据电池的不同初始状态以平衡加热策略为基础建立了单体电池加热电流数据库。电池初始温度为-20 ℃时，加热到10 ℃，所需加热时间为253 s，容量收益为4.72 Ah，电池老化为0.482?，峰值功率收益为1104 W。

关键词: 锂离子电池, 低温电热耦合模型, 复合加热方法, 加热策略

Abstract:

Recently, electric vehicles have developed due to their energy-saving, environmental protection, and high energy-conversion efficiency. At low temperatures, the performance of lithium-ion batteries, such as discharge power and capacity, is attenuated. This has affected the development and popularization of electric vehicles in the cold areas of north China. Therefore, it is important to understand how lithium-ion batteries reliably, efficiently, and safely heat at low temperatures. The electrical and thermal characteristics of the battery are obtained using the ternary lithium prismatic battery as the research objectives by testing the low-temperature characteristics of the battery under different working conditions. The cell electrothermal-coupling model is established, and a low-temperature heating-simulation model of the battery is obtained by fitting experimental data with the neural network method. The accuracy of the simulation model is verified using the temperature-rise experiments for the battery under different working conditions. A multistage constant-current composite-heating method is proposed, and a multiobjective nonlinear optimization model of battery aging, heating time, and capacity gain is established. The relationship between battery aging, heating time, and capacity gain is revealed, and the evaluation weighting matrix is obtained. The balanced heating strategy of the cell is obtained using the nondominated sorting genetic algorithm-?Ⅱ(NSGA-?Ⅱ) and technique for order preference by similarity to ideal solution (TOPSIS), and the effect of different initial states of the battery on the optimization objective is explored. According to the different initial states of the battery, the heating-current database of the cell is established based on the balanced heating strategy. When the initial temperature of the battery is -20 ℃, the heating time to 10 ℃ is 253 s, the capacity gain is 4.72 Ah, the battery aging is 0.482?, and the peak power gain is 1104 W.

Key words: lithium-ion battery, low-temperature electrothermal coupling model, composite heating method, heating strategy

中图分类号:

TM 912

李夔宁, 王靖鸿, 谢翌, 刘彬, 刘江岩, 刘召婷. 锂离子电池低温复合加热策略及优化[J]. 储能科学与技术, 2022, 11(10): 3191-3199.

Kuining LI, Jinghong WANG, Yi XIE, Bin LIU, Jiangyan LIU, Zhaoting LIU. Low-temperature compound-heating strategy and optimization of lithium-ion battery[J]. Energy Storage Science and Technology, 2022, 11(10): 3191-3199.

图/表 19

表1

图1

图2

图3

表2

图4

图5

图6

表3

图7

表4

表5

图8

图9

图10

表6

表7

图11

表8

参考文献 21

1	SUN F C, XIONG R, HE H W. A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique[J]. Applied Energy, 2016, 162: 1399-1409.
2	SAW L H, POON H M, THIAM H S, et al. Novel thermal management system using mist cooling for lithium-ion battery packs[J]. Applied Energy, 2018, 223: 146-158.
3	JI Y, ZHANG Y C, WANG C Y. Li-ion cell operation at low temperatures[J]. Journal of the Electrochemical Society, 2013, 160(4): A636-A649.
4	LI J, YUAN C F, GUO Z H, et al. Limiting factors for low-temperature performance of electrolytes in LiFePO₄/Li and graphite/Li half cells[J]. Electrochimica Acta, 2012, 59: 69-74.
5	ZHANG S S, XU K, JOW T R. Low temperature performance of graphite electrode in Li-ion cells[J]. Electrochimica Acta, 2002, 48(3): 241-246.
6	ZHANG S S, XU K, JOW T R. A new approach toward improved low temperature performance of Li-ion battery[J]. Electrochemistry Communications, 2002, 4(11): 928-932.
7	FAN J, TAN S. Studies on charging lithium-ion cells at low temperatures[J]. Journal of the Electrochemical Society, 2006, 153(6): A1081.
8	NAGASUBRAMANIAN G. Electrical characteristics of 18650 Li-ion cells at low temperatures[J]. Journal of Applied Electrochemistry, 2001, 31: 99-104.
9	SUN B X, JIANG J C, ZHENG F D, et al. Practical state of health estimation of power batteries based on Delphi method and grey relational grade analysis[J]. Journal of Power Sources, 2015, 282: 146-157.
10	CHO H M, CHOI W S, GO J Y, et al. A study on time-dependent low temperature power performance of a lithium-ion battery[J]. Journal of Power Sources, 2012, 198: 273-280.
11	SHANG Y L, ZHU C, FU Y H, et al. An integrated heater equalizer for lithium-ion batteries of electric vehicles[J]. IEEE Transactions on Industrial Electronics, 2019, 66(6): 4398-4405.
12	GHADBEIGI L, DAY B, LUNDGREN K, et al. Cold temperature performance of phase change material based battery thermal management systems[J]. Energy Reports, 2018, 4: 303-307.
13	HUANG D Y, CHEN Z Q, ZHOU S Y. Model prediction-based battery-powered heating method for series-connected lithium-ion battery pack working at extremely cold temperatures[J]. Energy, 2021, 216: doi:10.1016/j.energy.2020.119236.
14	YANG X G, GE S, WU N, et al. All-climate battery technology for electric vehicles: Inching closer to the mainstream adoption of automated driving[J]. IEEE Electrification Magazine, 2019, 7(1): 12-21.
15	WANG C Y, ZHANG G S, GE S H, et al. Lithium-ion battery structure that self-heats at low temperatures[J]. Nature, 2016, 529(7587): 515-518.
16	RUAN H J, JIANG J C, SUN B X, et al. A rapid low-temperature internal heating strategy with optimal frequency based on constant polarization voltage for lithium-ion batteries[J]. Applied Energy, 2016, 177: 771-782.
17	MOHAN S, SIEGEL J B, STEFANOPOULOU A G, et al. An energy-optimal warm-up strategy for Li-ion batteries and its approximations[J]. IEEE Transactions on Control Systems Technology, 2019, 27(3): 1165-1180.
18	GUO S S, XIONG R, SHEN W X, et al. Aging investigation of an echelon internal heating method on a three-electrode lithium ion cell at low temperatures[J]. Journal of Energy Storage, 2019, 25: doi:10.1016/j.est.2019.100878.
19	JIANG J C, RUAN H J, SUN B X, et al. A low-temperature internal heating strategy without lifetime reduction for large-size automotive lithium-ion battery pack[J]. Applied Energy, 2018, 230: 257-266.
20	XIE Y, LI W, YANG Y, et al. A novel resistance-based thermal model for lithium-ion batteries[J]. International Journal of Energy Research, 2018, 42(14): 4481-4498
21	李夔宁, 何铖, 谢翌, 等. 大倍率放电工况下48 V软包电池包的热管理[J]. 储能科学与技术, 2021, 10(2): 679-688.
	LI K N, HE C, XIE Y, et al. Thermal management of a 48 V pouch lithium-ion battery pack based on high rate discharge condition[J]. Energy Storage Science and Technology, 2021, 10(2): 679-688.

参数	值
动力电池类型	方形
材料体系	三元(镍钴锰)
额定容量/Ah	50
充电终止电压/V	4.25
放电截止电压/V	2.75

实验种类	T/℃	SOC	放电倍率/C
容量	10,0,-5,-10,-15,-20	1	1,0.7,0.5,0.3
HPPC	10,0,-5,-10,-15,-20	1,0.95,0.9,0.7,0.5,0.3,0.1,0	1,0.7,0.5,0.3
换热系数	-20	—	—

温度/℃	放电倍率/C	RMSE/℃
0	0.5	0.46
0	1.0	0.83
-10	0.5	0.61
-10	1.0	0.45
-20	0.5	0.56
-20	1.0	0.51

初始SOC	T₀/℃	t/s	Q_gain/Ah	Q_loss/‱	初始SOC	T₀/℃	t/s	Q_gain/Ah	Q_loss/‱
1.0	0	53	1.44	0.322	0.4	0	52	0.37	0.324
1.0	-5	128	2.06	0.351	0.4	-5	112	0.49	0.360
1.0	-10	161	2.88	0.402	0.4	-10	155	0.70	0.407
1.0	-15	248	3.86	0.448	0.4	-15	212	0.92	0.444
1.0	-20	253	4.72	0.482	0.4	-20	267	1.17	0.479
0.7	0	52	0.91	0.324	0.1	0	52	-0.16	0.320
0.7	-5	115	1.28	0.359	0.1	-5	109	-0.29	0.356
0.7	-10	167	1.78	0.403	0.1	-10	149	-0.37	0.403
0.7	-15	233	2.34	0.444	0.1	-15	198	-0.45	0.440
0.7	-20	273	2.89	0.477	0.1	-20	243	-0.52	0.475

初始SOC	T₀/℃
初始SOC	0	-5	-10	-15	-20
1	469	596	943	1005	1104
0.7	292	324	616	670	749
0.4	270	351	508	571	632
0.1	146	163	307	326	366

锂离子电池低温复合加热策略及优化

Low-temperature compound-heating strategy and optimization of lithium-ion battery

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 19

参考文献 21

相关文章 15

编辑推荐

Metrics

本文评价

[1]	邓林旺, 冯天宇, 舒时伟, 张子峰, 郭彬. 锂离子电池快充策略技术研究进展[J]. 储能科学与技术, 2022, 11(9): 2879-2890.
[2]	栗志展, 秦金磊, 梁嘉宁, 李峥嵘, 王瑞, 王得丽. 高镍三元层状锂离子电池正极材料：研究进展、挑战及改善策略[J]. 储能科学与技术, 2022, 11(9): 2900-2920.
[3]	牛少军, 吴凯, 朱国斌, 王艳, 曲群婷, 郑洪河. 锂离子电池硅基负极循环过程中的膨胀应力[J]. 储能科学与技术, 2022, 11(9): 2989-2994.
[4]	陈晓宇, 耿萌萌, 王乾坤, 沈佳妮, 贺益君, 马紫峰. 基于电化学阻抗特征选择和高斯过程回归的锂离子电池健康状态估计方法[J]. 储能科学与技术, 2022, 11(9): 2995-3002.
[5]	张群斌, 董陶, 李晶晶, 刘艳侠, 张海涛. 废旧电池电解液回收及高值化利用研发进展[J]. 储能科学与技术, 2022, 11(9): 2798-2810.
[6]	贡淑雅, 王跃, 李萌, 邱景义, 王洪, 文越华, 徐斌. 锂离子电池负极材料TiNb₂O₇ 的研究进展[J]. 储能科学与技术, 2022, 11(9): 2921-2932.
[7]	卓萍, 朱艳丽, 齐创, 王聪杰, 高飞. 锂离子电池组过充燃烧爆炸特性[J]. 储能科学与技术, 2022, 11(8): 2471-2479.
[8]	曹志成, 周开运, 朱家立, 刘高明, 严慜, 汤舜, 曹元成, 程时杰, 张炜鑫. 锂离子电池储能系统消防技术的中国专利分析[J]. 储能科学与技术, 2022, 11(8): 2664-2670.
[9]	张越, 孔得朋, 平平. 液冷板抑制锂离子电池组热失控蔓延性能及优化设计[J]. 储能科学与技术, 2022, 11(8): 2432-2441.
[10]	徐成善, 鲁博瑞, 张梦启, 王淮斌, 金昌勇, 欧阳明高, 冯旭宁. 储能锂离子电池预制舱热失控烟气流动研究[J]. 储能科学与技术, 2022, 11(8): 2418-2431.
[11]	韦荣阳, 毛阗, 高晗, 彭建仁, 杨健. 基于TWP-SVR的锂离子电池健康状态估计[J]. 储能科学与技术, 2022, 11(8): 2585-2599.
[12]	马勇, 李晓涵, 孙磊, 郭东亮, 杨景刚, 刘建军, 肖鹏, 钱广俊. 基于三维电化学热耦合析锂模型的锂离子电池参数设计[J]. 储能科学与技术, 2022, 11(8): 2600-2611.
[13]	唐亮, 尹小波, 吴候福, 刘鹏杰, 王青松. 电化学储能产业发展对安全标准的需求[J]. 储能科学与技术, 2022, 11(8): 2645-2652.
[14]	霍丽萍, 栾伟玲, 庄子贤. 锂离子电池储能安全技术的发展态势[J]. 储能科学与技术, 2022, 11(8): 2671-2680.
[15]	王洋, 卢旭, 张宇新, 刘龙. 动力电池热失控排气策略[J]. 储能科学与技术, 2022, 11(8): 2480-2487.

T₁/℃	T₂/℃	I/A
-20	-15	I₁
-15	-10	I₂
-10	-5	I₃
-5	0	I₄
0	10	I₅