Average Temperature Estimation for Lithium-Ion Batteries at Variable Environment Temperature

doi:10.16183/j.cnki.jsjtu.2019.230

Abstract

Abstract:

The performance of lithium-ion batteries is greatly affected by the temperature change. Therefore, it is of great significance to get the temperature information to develop the thermal management system. In order to solve the problem that the local temperature caused by the traditional temperature sensor arrangement cannot replace the overall average temperature, it is necessary to conduct studies of average temperature estimation for 10 A·h ternary nicke clobalt manganese lithium-ion batteries at variable environment temperature. First, a lithium-ion battery is modeled and the experimental platform is built to obtain the parameters which are necessary for modeling. Then, an average temperature estimation method for lithium-ion batteries based on recursive least squares and the extended Kalman filter algorithm is proposed. Finally, to verify the effectiveness of the proposed method, the experimental data of the battery at variable environment temperature is obtained under improved hybrid pulse power characteristic (IHPPC). The results show that the proposed method can estimate the average temperature of lithium-ion batteries in real time. The maximum error of the temperature estimation model after the algorithm convergence is 1.8 ℃, and the average error is only 1 ℃.

Key words: lithium-ion battery, time-varying environment temperature, improved hybrid pulse power characteristic (IHPPC), average temperature estimation

CLC Number:

TM912

JIANG Yu, CHEN Ziqiang. Average Temperature Estimation for Lithium-Ion Batteries at Variable Environment Temperature[J]. Journal of Shanghai Jiao Tong University, 2021, 55(7): 781-790.

Figures/Tables 17

Fig.1

Fig.2

Tab.1

Tab.2

Fig.3

Fig.4

Fig.5

Tab.3

Fig.6

Fig.7

Fig.8

Fig.9

Fig.10

Fig.11

Fig.12

Fig.13

Tab.4

References 15

[1]	戴国群, 陈性保, 胡晨. 锂离子电池在深潜器上的应用现状及发展趋势[J]. 电源技术, 2015, 39(8): 1768-1772.
	DAI Guoqun, CHEN Xingbao, HU Chen. Current status and development trend of lithium-ion battery in underwater vehicle[J]. Chinese Journal of Power Sources, 2015, 39(8): 1768-1772.
[2]	WANG K K, GAO F, ZHU Y L, et al. Internal resistance and heat generation of soft package Li₄Ti₅O₁₂ battery during charge and discharge[J]. Energy, 2018, 149:364-374. doi: 10.1016/j.energy.2018.02.052 URL
[3]	王腾. 动力电池组分层风冷式热管理系统研究[D]. 北京: 北京理工大学, 2016.
	WANG Teng. Study on layered air cooling thermal management for lithium-ion battery pack[D]. Beijing: Beijing Institute of Technology, 2016.
[4]	孙金磊, 朱春波, 李磊, 等. 电动汽车动力电池温度在线估计方法[J]. 电工技术学报, 2017, 32(7): 197-203.
	SUN Jinlei, ZHU Chunbo, LI Lei, et al. Online temperature estimation method for electric vehicle power battery[J]. Transactions of China Electrotechnical Society, 2017, 32(7): 197-203.
[5]	XIONG R, HE H W, SUN F C, et al. Evaluation on state of charge estimation of batteries with adaptive extended Kalman filter by experiment approach[J]. IEEE Transactions on Vehicular Technology, 2013, 62(1): 108-117. doi: 10.1109/TVT.2012.2222684 URL
[6]	ANSARI F, YUAN L B. Mechanics of bond and interface shear transfer in optical fiber sensors[J]. Journal of Engineering Mechanics, 1998, 124(4): 385-394. doi: 10.1061/(ASCE)0733-9399(1998)124:4(385) URL
[7]	李斌, 常国峰, 林春景, 等. 车用动力锂电池产热机理研究现状[J]. 电源技术, 2014, 38(2): 378-381.
	LI Bin, CHANG Guofeng, LIN Chunjing, et al. Research on heat generate mechanism of Li-ion batteries for electric vehicles[J]. Chinese Journal of Power Sources, 2014, 38(2): 378-381.
[8]	赵学娟. 锂离子电池在绝热条件下的循环产热研究[D]. 合肥: 中国科学技术大学, 2014.
	ZHAO Xuejuan. Heat generation of lithium ion battery during cycling under adiabatic condition[D]. Hefei: University of Science and Technology of China, 2014.
[9]	罗宗鸿. 电动汽车电池热特性及电池组风冷散热研究[D]. 南昌: 南昌航空大学, 2018.
	LUO Zonghong. Research on battery thermal characteristics and air cooling heat dissipation of battery packs for electric vehicles[D]. Nanchang: Nanchang Hangkong University, 2018.
[10]	黄德扬, 陈自强, 郑昌文. 时变温度环境下锂离子电池自适应SOC估计方法[J]. 装备环境工程, 2018, 15(12): 28-34.
	HUANG Deyang, CHEN Ziqiang, ZHENG Changwen. SOC adaptive estimation method for Li-ion ba-ttery applied in temperature-varying condition[J]. Equipment Environmental Engineering, 2018, 15(12): 28-34.
[11]	姜余, 陈自强. 锂离子电池热特性参数测量方法研究[J]. 装备环境工程, 2018, 15(12): 60-64.
	JIANG Yu, CHEN Ziqiang. Measurement methods for thermal characteristic parameters of lithium-ion battery[J]. Equipment Environmental Engineering, 2018, 15(12): 60-64.
[12]	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: 10.1149/1.2113792 URL
[13]	EDDAHECH A, BRIAT O, VINASSA J M. Thermal characterization of a high-power lithium-ion battery: Potentiometric and calorimetric measurement of entropy changes[J]. Energy, 2013, 61:432-439. doi: 10.1016/j.energy.2013.09.028 URL
[14]	王康康, 高飞, 杨凯, 等. 不同健康状态等级的储能磷酸铁锂电池熵变系数及放电产热研究[J]. 高电压技术, 2017, 43(7): 2241-2248.
	WANG Kangkang, GAO Fei, YANG Kai, et al. Research of LiFePO₄/C energy storage batteriesê entropy coefficient and discharge heat generation based on the state of health[J]. High Voltage Engineering, 2017, 43(7): 2241-2248.
[15]	赵奕凡. 电动汽车锂离子动力电池状态估算方法研究[D]. 武汉: 武汉理工大学, 2014.
	ZHAO Yifan. Research on state estimation method of lithium ion power battery for electric vehicles[D]. Wuhan: Wuhan University of Technology, 2014.

参数	拟合结果
SSR	0.000439
R	0.99933
p₅	2.40621
p₄	-7.65815
p₃	9.17574
p₂	-4.43497
p₁	1.23171
p₀	3.4598

参数	取值
电池容量/(A·h)	10
额定电压/V	3.7
上截止电压/V	4.2
下截止电压/V	3.0
电池质量/g	200
电池密度/(kg·m^-3)	2430
长,宽,高/mm	112, 92, 8

温度传感器	位置
T1	电池正极
T2	电池负极
T3	电池正面
T4	电池反面
T5	电池侧面
T6	电池底面
T7	环境温度1
T8	环境温度2

项目	算法	收敛时间/s	最大误差	最小误差	均方根误差
SOC估计(SOC₀=0)	RLS-EKF	205	1.070%	0.055%	0.274%
	RLS-UKF	214	1.263%	0.067%	0.384%
温度估计(T₀=25 ℃)	RLS-EKF	210	1.8 ℃	0.56 ℃	0.83 ℃
	RLS-UKF	223	2.0 ℃	0.63 ℃	0.94 ℃