Guo Dongxu1,2, Yang Geng1, Feng Xuning2, Lu Languang2, Ouyang Minggao2
1. Department of Automation Tsinghua University Beijing 100084 China; 2. State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing 100084 China
Abstract:The lithium-ion battery (LiB) requires an aging test to ensure its reliability during long-term use. The conventional aging test is very time-consuming because the current LiB life span is thousands of cycles. Therefore, an accelerated aging test method for LiB is needed. The degradation of the LiB is path-dependent. Therefore, the constraints of designing this accelerated aging test method are: to ensure both the equivalence of LiB capacity and the invariance of its internal degradation mechanism. This paper proposes a model-based method for generating an accelerated aging profile. The objective function considering the acceleration factor and the relative error of the aging path is constructed, and the optimal solution of the objective function is obtained by a double closed-loop architecture. In the double closed-loop architecture, the outer loop is an acceleration factor optimization algorithm that aims to find the optimal acceleration factor; the inner loop is an acceleration profile search algorithm, aiming to search the optimal acceleration profile under a given acceleration factor. The accelerated aging profile of the China light-duty vehicle test cycle-passenger car (CLTC-P) is generated under the given objective function based on the proposed method. The simulation is carried out based on the semi-empirical fractional-order model considering the dominant degradation mechanism of the LiB developed by the authors, which verifies the effectiveness of the method.
[1] Lu Languang, Han Xuebing, Li Jianqiu, et al.A review on the key issues for lithium-ion battery management in electric vehicles[J]. Journal of Power Sources, 2013, 226: 272-288. [2] 严康为, 龙鑫林, 鲁军勇, 等. 高倍率磷酸铁锂电池简化机理建模与放电特性分析[J]. 电工技术学报, 2022, 37(3): 599-609. Yan Kangwei, Long Xinlin, Lu Junyong, et al.Simplified mechanism modeling and discharge characteristic analysis of high C-rate LiFePO4 battery[J]. Transactions of China Electrotechnical Society, 2022, 37(3): 599-609. [3] 肖迁, 焦志鹏, 穆云飞, 等. 基于LightGBM的电动汽车行驶工况下电池剩余使用寿命预测[J]. 电工技术学报, 2021, 36(24): 5176-5185. Xiao Qian, Jiao Zhipeng, Mu Yunfei, et al.LightGBM based remaining useful life prediction of electric vehicle lithium-ion battery under driving con- ditions[J]. Transactions of China Electrotechnical Society, 2021, 36(24): 5176-5185. [4] Han Xuebing, Lu Languang, Zheng Yuejiu, et al.A review on the key issues of the lithium ion battery degradation among the whole life cycle[J]. eTransportation, 2019, 1: 100005. [5] 王萍, 弓清瑞, 张吉昂, 等. 一种基于数据驱动与经验模型组合的锂电池在线健康状态预测方法[J]. 电工技术学报, 2021, 36(24): 5201-5212. Wang Ping, Gong Qingrui, Zhang Ji'ang, et al.An online state of health prediction method for lithium batteries based on combination of data-driven and empirical model[J]. Transactions of China Electro- technical Society, 2021, 36(24): 5201-5212. [6] 柴炜, 李征, 蔡旭, 等. 基于使用寿命模型的大容量电池储能系统变步长优化控制方法[J]. 电工技术学报, 2016, 31(14): 58-66. Chai Wei, Li Zheng, Cai Xu, et al.Variable step-size control method of large capacity battery energy storage system based on the life model[J]. Transa- ctions of China Electrotechnical Society, 2016, 31(14): 58-66. [7] 刘伟, 杨耕, 孟德越, 等.计及常用恒流工况的锂离子电池建模方法[J].电工技术学报, 2021, 36(24): 5186-5200. Liu Wei, Yang Geng, Meng Deyue, et al.Modeling method of lithium-ion battery considering commonly used constant current conditions[J]. Transactions of China Electrotechnical Society, 2021, 36(24): 5186-5200. [8] Ma Zeyu, Jiang Jiuchun, Shi Wei, et al.Investigation of path dependence in commercial lithium-ion cells for pure electric bus applications: aging mechanism identification[J]. Journal of Power Sources, 2015, 274: 29-40. [9] Su Laisuo, Zhang Jianbo, Huang Jun, et al.Path dependence of lithium ion cells aging under storage conditions[J]. Journal of Power Sources, 2016, 315: 35-46. [10] Ouyang Minggao, Feng Xuning, Han Xuebing, et al.A dynamic capacity degradation model and its applications considering varying load for a large format li-ion battery[J]. Applied Energy, 2016, 165: 48-59. [11] Li S E, Wang Baojin, Peng H, et al.An electrochemistry- based impedance model for lithium-ion batteries[J]. Journal of Power Sources, 2014, 258: 9-18. [12] Wang J, Liu Ping, Hicks-Garner J, et al.Cycle-life model for graphite-LiFePO4 cells[J]. Journal of Power Sources, 2011, 196(8): 3942-3948. [13] Simolka M, Heger J-F, Kaess H, et al.Influence of cycling profile, depth of discharge and temperature on commercial LFP/C cell ageing: post-mortem material analysis of structure, morphology and chemical composition[J]. Journal of Applied Electrochemistry, 2020, 50(11): 1101-1117. [14] Preger Y, Barkholtz H M, Fresquez A, et al.Degra- dation of commercial lithium-ion cells as a function of chemistry and cycling conditions[J]. Journal of the Electrochemical Society, 2020, 167(12): 120532. [15] Gering K L, Sazhin S V, Jamison D K, et al.Investigation of path dependence in commercial lithium-ion cells chosen for plug-in hybrid vehicle duty cycle protocols[J]. Journal of Power Sources, 2011, 196(7): 3395-3403. [16] 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. [17] 孙丙香, 任鹏博, 陈育哲, 等. 锂离子电池在不同区间下的衰退影响因素分析及任意区间的老化趋势预测[J]. 电工技术学报, 2021, 36(3): 666-674. Sun Bingxiang, Ren Pengbo, Chen Yuzhe, et al.Analysis of influencing factors of degradation under different interval stress and prediction of aging trend in any interval for lithium-ion battery[J]. Transactions of China Electrotechnical Society, 2021, 36(3): 666-674. [18] 张谦, 邓小松, 岳焕展, 等. 计及电池寿命损耗的电动汽车参与能量-调频市场协同优化策略[J]. 电工技术学报, 2022, 37(1): 72-81. Zhang Qian, Deng Xiaosong, Yue Huanzhan, et al.Coordinated optimization strategy of electric vehicle cluster participating in energy and frequency regu- lation markets considering battery lifetime degra- dation[J]. Transactions of China Electrotechnical Society, 2022, 37(1): 72-81. [19] 孙逢春, 孟祥峰, 林程, 等. 电动汽车动力电池动态测试工况研究[J]. 北京理工大学学报, 2010, 30(3): 297-301. Sun Fengchun, Meng Xiangfeng, Lin Cheng, et al.Dynamic stress test profile of power battery for electric vehicle[J]. Transactions of Beijing Institute of Technology, 2010, 30(3): 297-301. [20] 中国汽车技术研究中心有限公司. 中国汽车行驶工况第1部分: 轻型汽车[S]. 国家市场监督管理总局;中国国家标准化管理委员会, 2019. [21] 霍云龙, 杨钫, 王燕, 等. 新能源汽车能耗测试评价规程比较研究[J]. 汽车文摘, 2020(8): 11-14. Huo Yunlong, Yang Fang, Wang Yan, et al.Com- parison and study of NEV energy consumption test and evaluation procedures[J]. Automotive Digest, 2020(8): 11-14. [22] Takei K, Kumai K, Kobayashi Y, et al.Cycle life estimation of lithium secondary battery by extrapo- lation method and accelerated aging test[J]. Journal of Power Sources, 2001, 97: 697-701. [23] Saxena S, Xing Yinjiao, Kwon D, et al.Accelerated degradation model for C-rate loading of lithium-ion batteries[J]. International Journal of Electrical Power & Energy Systems, 2019, 107: 438-445. [24] Saxena S, Roman D, Robu V, et al.Battery stress factor ranking for accelerated degradation test planning using machine learning[J]. Energies, 2021, 14(3): 723. [25] Jiang Jiuchun, Gao Yang, Zhang Caiping, et al.Lifetime rapid evaluation method for lithium-ion battery with Li(NiMnCo)O2 cathode[J]. Journal of the Electrochemical Society, 2019, 166(6): 1070-1081. [26] Stroe D I, Swierczynski M, Laserna E M, et al.Accelerated aging of lithium-ion batteries based on electric vehicle mission profile[C]//IEEE Energy Conversion Congress and Exposition (ECCE), Cincinnati, 2017: 5631-5637. [27] Yurkowsky W, Schafer R, Finkelstein J M.Accelerated testing technology[R]. Hughes Aircraft CO Fullerton CA Ground Systems Group, 1967. [28] 陈志军, 王前程, 陈云霞. 基于寿命分布和贝叶斯的加速因子确定方法[J]. 系统工程与电子技术, 2015, 37(5): 1224-1228. Chen Zhijun, Wang Qiancheng, Chen Yunxia.Deter- mination method of acceleration factor based on life distribution and bayes[J]. Systems Engineering and Electronics, 2015, 37(5): 1224-1228. [29] 张栋, 张刘春, 傅正财. 基于改进禁忌算法的配电网络重构[J]. 电工技术学报, 2005, 20(11): 60-64. Zhang Dong, Zhang Liuchun, Fu Zhengcai.Network reconfiguration in distribution systems using a modified TS algorithm[J]. Transactions of China Electrotechnical Society, 2005, 20(11): 60-64. [30] 王凌. 智能优化算法及其应用[M]. 北京: 清华大学出版社, 2001. [31] Guo Dongxu, Yang Geng, Feng Xuning, et al.Physics- based fractional-order model with simplified solid phase diffusion of lithium-ion battery[J]. Journal of Energy Storage, 2020, 30: 101404. [32] Paris P, Erdogan F.A critical analysis of crack propagation laws[J]. Journal of Basic Engineering, 1963, 85(4): 528-533. [33] Deshpande R, Verbrugge M, Cheng Yang-Tse, et al.Battery cycle life prediction with coupled chemical degradation and fatigue mechanics[J]. Journal of the Electrochemical Society, 2012, 159(10): 1730-1738. [34] Safari M, Morcrette M, Teyssot A, et al.Life- prediction methods for lithium-ion batteries derived from a fatigue approach I. introduction: capacity-loss prediction based on damage accumulation[J]. Journal of the Electrochemical Society, 2010, 157(6): 713-720. [35] Safari M, Morcrette M, Teyssot A, et al.Life prediction methods for lithium-ion batteries derived from a fatigue approach II. capacity-loss prediction of batteries subjected to complex current profiles[J]. Journal of the Electrochemical Society, 2010, 157(7): 892-898. [36] Laidler K J.The development of the Arrhenius equation[J]. Journal of Chemical Education, 1984, 61(6): 494. [37] 张曼, 施树明. 面向汽车运行工况设计的马氏链非等长交叉进化算法[J]. 浙江大学学报(工学版), 2018, 52(9): 1658-1666. Zhang Man, Shi Shuming.Non-isometric crossover evolution algorithm of Markov chain for designing vehicle driving cycles[J]. Journal of Zhejiang University (Engineering Science), 2018, 52(9): 1658-1666. [38] 中国汽车技术研究中心有限公司. 中国汽车行驶工况第2部分: 重型商用车辆[S]. 国家市场监督管理总局; 中国国家标准化管理委员会, 2019. [39] 陈光, 张妍懿, 郝冬, 等. EV-TEST评价体系中性能指标的确定分析[J]. 汽车工程师, 2017(11): 14-17. Chen Guang, Zhang Yanyi, Hao Dong, et al.Defini- tion and analysis on performance items of EV-TEST evaluation system[J]. Auto Engineer, 2017(11): 14-17.