基于多影响因素建立锂离子电池充电内阻的动态模型

doi:10.19595/j.cnki.1000-6753.tces.200320

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (2951 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Modeling the internal resistance of lithium-ion batteries is of great significance for the thermal management of batteries. The internal resistance of charging is affected by many factors such as temperature and charging rate. Therefore, the relationship between the battery's internal resistance change characteristics and various influencing factors (charging rate, state of charge and temperature) is analyzed. The binary polynomial method based on the least square and the cubic spline interpolation algorithm are used to calculate the battery charging internal resistance at different charging rates, SOC, and temperature. The dynamic model of the internal resistance of multi-factor dynamic charge is established, and the charging internal resistance is estimated in different states. The results show that the maximum error between the internal resistance estimated value by the dynamic model and the experimental value does not exceed 6 mΩ, which proves that the proposed method for modeling battery charging internal resistance is effective.

Key words： Charging internal resistance multiple factors internal resistance model least squares binary polynomial cubic spline

Received: 01 April 2020

PACS:

TM911

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Pan Haihong
	Zhang Mo
	Wang Huimin
	Feng Zhe
	Chen Lin

Cite this article:

Pan Haihong,Zhang Mo,Wang Huimin等. Establishing a Dynamic Model of Lithium-Ion Battery Charging Internal Resistance Based on Multiple Factors[J]. Transactions of China Electrotechnical Society, 2021, 36(10): 2199-2206.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.200320 OR https://dgjsxb.ces-transaction.com/EN/Y2021/V36/I10/2199

[1] 田华, 王伟光, 舒歌群, 等. 基于多尺度、电化学-热耦合模型的锂离子电池生热特性分析[J]. 天津大学学报(自然科学与工程技术版), 2016, 49(7): 734-741.
Tian Hua, Wang Weiguang, Shu Gequn, et al.Analysis of heat generation in a Li-ion battery based on a multi-scale and electrochemical-thermal coupled model[J]. Journal of Tianjin University (Natural Science and Engineering Technology Edition), 2016, 49(7): 734-741.
[2] 孙丙香, 刘佳, 韩智强, 等. 不同区间衰退路径下锂离子电池的性能相关性及温度适用性分析[J]. 电工技术学报, 2020, 35(9): 2063-2073.
Sun Bingxiang, Liu Jia, Han Zhiqiang, et al.Per- formance correlation and temperature applicability of Li-ion batteries under different range degradation paths[J]. Transactions of China Electrotechnical Society, 2020, 35(9): 2063-2073.
[3] 潘海鸿, 吕治强, 李君子, 等. 基于灰色扩展卡尔曼滤波的锂离子电池荷电状态估算[J]. 电工技术学报, 2017, 32(21): 198-205.
Pan Haihong, Lü Zhiqiang, Li Junzi, et al.Estimation of state of charge of lithium ion battery based on grey extended Kalman filter[J]. Transactions of China Electrotechnical Society, 2017, 32(21): 198-205.
[4] 何锡添, 孙丙香, 阮海军, 等. 锂离子电池变频变幅交流低温自加热策[J]. 电工技术学报, 2019, 34(9): 1798-1805.
Hen Xitian, Sun Bingxiang, Ruan Haijun, et al.A variable-frequency and variable-amplitude AC low- temperature self-heating strategy for lithium-ion battery[J]. Transactions of China Electrotechnical Society, 2019, 34(9): 1798-1805.
[5] Gümüşsu E, Ekici Ö, Köksal M.3-D CFD modeling and experimental testing of thermal behavior of a Li-ion battery[J]. Applied Thermal Engineering, 2017, 120: 484-495.
[6] Nazari A, Farhad S.Heat generation in lithium-ion batteries with different nominal capacities and chemistries[J]. Applied Thermal Engineering, 2017, 125: 1501-1517.
[7] Waag W, Fleischer C, Sauer D U.Adaptive on-line prediction of the available power of lithium-ion batteries[J]. Journal of Power Sources, 2013, 242: 548-559.
[8] 陈英杰, 杨耕, 祖海鹏, 等. 基于恒流实验的锂离子电池开路电压与内阻估计方法[J]. 电工技术学报, 2018, 33(17): 3976-3988.
Chen Yingjie, Yang Geng, Zu Haipeng, et al.An open circuit voltage and internal resistance estimation method of lithium-ion batteries with constant current tests[J]. Transactions of China Electrotechnical Society, 2018, 33(17): 3976-3988.
[9] 林春景, 李斌, 常国峰, 等. 不同温度下磷酸铁锂电池内阻特性实验研究[J]. 电源技术, 2015, 39(1): 22-25.
Lin Chunjing, Li Bin, Chang Guofeng, et al.Experi- mental study on internal resistance of LiFePO₄ batteries under different ambient temperatures[J]. Power Source Eechnology, 2015, 39(1): 22-25.
[10] Ratnakumar B V, Smart M C, Whitcanack L D, et al.The impedance characteristics of mars exploration rover Li-ion batteries[J]. Journal of Power Sources, 2006, 159(2): 1428-1439.
[11] Liu Xingtao, Chen Zonghai, Zhang Chenbin, et al.A novel temperature-compensated model for power Li-ion batteries with dual-particle-filter state of charge estimation[J]. Applied Energy, 2014, 123: 263-272.
[12] Waag W, Käbitz S, Sauer D U.Experimental investigation of the lithium-ion battery impedance characteristic at various conditions and aging states and its influence on the application[J]. Applied Energy, 2013, 102: 885-897.
[13] 姜久春, 时玮, 张言茹, 等. 磷酸铁锂动力电池阻抗谱参数分析[J]. 北京理工大学学报, 2014, 34(5): 470-474.
Jiang Jiuchun, Shi Wei, Zhang Yanru, et al.Impe- dance spectra investigation and parameter analysis of traction LiFePO₄ battery[J]. Journal of Beijing Institute of Technology, 2014, 34(5): 470-474.
[14] 卢艳华. 车用三元锂离子动力电池内阻特性分析[J]. 电源技术, 2017, 41(5): 702-704.
Lu Yanhua.Impedance characteristics of lithium ion power battery with NCM cathode for electric vehicles[J]. Power Source Technology, 2017, 41(5): 702-704.
[15] 韦海燕, 钟腾云, 潘海鸿, 等. 基于改进HPPC锂离子电池内阻测试方法研究[J]. 电源技术, 2019, 43(8): 1309-1311.
Wei Haiyan, Zhong Tengyun, Pan Haihong, et al.Study on measurement method of internal resistance of lithium-ion battery based on improved HPPC[J]. Power Source Eechnology, 2019, 43(8): 1309-1311.
[16] Ahmed S H, Kang X, Shrestha S O B, et al. Effects of temperature on internal resistances of lithium-ion batteries[J]. Energy Resources Technology, 2015, 137(3): 1901-1905.
[17] Zhao X, De Callafon R A. Modeling of battery dynamics and hysteresis for power delivery predi- ction and SOC estimation[J]. Applied Energy, 2016, 180: 823-833.