Optimization of Fast Charging Strategy for Lithium-Ion Batteries without Deposition Based on Electrode Equivalent Circuit Model
Zhao Yingjie1,2, Zhang Chuang1, Liu Suzhen1,2, Chen Zhanqun3, Xu Zhicheng1,2
1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin 300401 China; 2. Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province Hebei University of Technology Tianjin 300401 China; 3. Baoding UNT Electric Co. Ltd Baoding 071051 China
Abstract:Fast charging is crucial for the application of lithium-ion batteries in electric vehicles. However, traditional fast charging algorithms are prone to causing the anode potential to reach the lithium plating potential threshold (0V vs. Li/Li+). As a result, lithium ions on the anode material surface have a direct reduction reaction, leading to lithium plating, accelerating battery aging, and even causing charging safety incidents. It is necessary to study lithium-plating-free fast charging for lithium-ion batteries. This paper, based on the lithium-ion battery electrode equivalent circuit model, proposes a dual-loop lithium plating-free fast charging strategy control scheme composed of an anode potential closed-loop observer and a charging current closed-loop controller, thereby achieving safe and lithium plating-free fast charging for lithium-ion batteries. Firstly, a dual-electrode equivalent circuit model for lithium-ion batteries is established. Model parameters under various charge states are identified offline through three-electrode experiments on lithium-ion batteries. Secondly, an anode potential closed-loop observer based on the extended Kalman filter (EKF) algorithm is designed to observe the real-time anode potential, an internal state of the lithium-ion battery. Additionally, a charging current closed-loop controller based on feed forward compensation is designed, enabling online control of the charging current of the lithium-ion battery. The combined observation-control logic of the anode potential closed-loop observer and the charging current closed-loop controller is also explained. Finally, the rationality and effectiveness of the proposed lithium plating-free fast charging strategy control scheme for lithium-ion batteries are demonstrated through simulation and experimentation. Simulation and experimental results demonstrate that, for the anode potential closed-loop observer, under different operating conditions, the average observed error of the anode potential is less than 5 mV, with a maximum error of no more than 10 mV. Moreover, even during abrupt changes in charging current, the observer can rapidly correct the observed results, keeping the error low. As for the charging current closed-loop controller, during the current adjustment process, the adjustment time for the anode potential to reach and stabilize within the set threshold +1 mV range is 26 s, with a steady-state error of less than 0.05 mV, and without overshooting or oscillation. Furthermore, the charging effect of the proposed fast charging strategy is verified under conditions of two different maximum charging currents. The results indicate that, compared to 1C constant current constant voltage charging, the proposed fast charging strategy can save approximately 46% of the charging time. The minimum anode potential during charging is 4.8 mV. For batteries cycled using the proposed fast charging strategy, no lithium plating is found even after disassembling the battery, affirming that this strategy can significantly reduce charging time and effectively suppress lithium plating. It is a lithium-plating-free fast charging control scheme that simultaneously considers high precision and robustness.
赵英杰, 张闯, 刘素贞, 陈占群, 徐志成. 基于电极等效电路模型的锂离子电池无析锂快充策略优化研究[J]. 电工技术学报, 2024, 39(18): 5868-5882.
Zhao Yingjie, Zhang Chuang, Liu Suzhen, Chen Zhanqun, Xu Zhicheng. Optimization of Fast Charging Strategy for Lithium-Ion Batteries without Deposition Based on Electrode Equivalent Circuit Model. Transactions of China Electrotechnical Society, 2024, 39(18): 5868-5882.
[1] 刘素贞, 陈晶晶, 张闯, 等. 基于区域电压的锂离子电池不均匀发热模型[J]. 电工技术学报, 2022, 37(21): 5627-5636. Liu Suzhen, Chen Jingjing, Zhang Chuang, et al.Regional voltage-based uneven heating model of lithium-ion battery[J]. Transactions of China Electro- technical Society, 2022, 37(21): 5627-5636. [2] Zhang Lei, Hu Xiaosong, Wang Zhenpo, et al.Hybrid electrochemical energy storage systems: an overview for smart grid and electrified vehicle applications[J]. Renewable and Sustainable Energy Reviews, 2021, 139: 110581. [3] 王义军, 左雪. 锂离子电池荷电状态估算方法及其应用场景综述[J]. 电力系统自动化, 2022, 46(14): 193-207. Wang Yijun, Zuo Xue.Review on estimation methods for state of charge of lithium-ion battery and their application scenarios[J]. Automation of Electric Power Systems, 2022, 46(14): 193-207. [4] 刘素贞, 袁路航, 张闯, 等. 基于超声时域特征及随机森林的磷酸铁锂电池荷电状态估计[J]. 电工技术学报, 2022, 37(22): 5872-5885. Liu Suzhen, Yuan Luhang, Zhang Chuang, et al.State of charge estimation of LiFeO4 batteries based on time domain features of ultrasonic waves and random forest[J]. Transactions of China Electrotechnical Society, 2022, 37(22): 5872-5885. [5] 余佩雯, 郁亚娟, 常泽宇, 等. 相关向量机预测锂离子电池剩余有效寿命[J]. 电气技术, 2023, 24(2): 1-5. Yu Peiwen, Yu Yajuan, Chang Zeyu, et al.Remain useful life prediction of lithium-ion battery based on relevance vector machine[J]. Electrical Engineering, 2023, 24(2): 1-5. [6] Sun Bo, Zhang Chuang, Xu Zhicheng, et al.Ultrasonic diagnosis of the nonlinear aging characteristics of lithium-ion battery under high-rate discharge conditions[J]. Journal of Power Sources, 2023, 567: 232921. [7] 张闯, 孙博, 金亮, 等. 基于声波时域特征的锂离子电池荷电状态表征[J]. 电工技术学报, 2021, 36(22): 4666-4676. Zhang Chuang, Sun Bo, Jin Liang, et al.Characteri- zation of the state of charge of lithium-ion batteries based on the time-domain characteristics of acoustic waves[J]. Transactions of China Electrotechnical Society, 2021, 36(22): 4666-4676. [8] Al-Haj Hussein A, Batarseh I. A review of charging algorithms for nickel and lithium battery chargers[J]. IEEE Transactions on Vehicular Technology, 2011, 60(3): 830-838. [9] Liu Y H, Teng J H, Lin Y C.Search for an optimal rapid charging pattern for lithium-ion batteries using ant colony system algorithm[J]. IEEE Transactions on Industrial Electronics, 2005, 52(5): 1328-1336. [10] Chung S K, Andriiko A A, Mon’ko A P, et al.On charge conditions for Li-ion and other secondary lithium batteries with solid intercalation electrodes[J]. Journal of Power Sources, 1999, 79(2): 205-211. [11] Purushothaman B K, Landau U.Rapid charging of lithium-ion batteries using pulsed currents[J]. Journal of the Electrochemical Society, 2006, 153(3): A533. [12] Sun Bo, Zhang Chuang, Liu Suzhen, et al.Acoustic response characteristics of lithium cobaltate/graphite battery during cycling[J]. Journal of the Electro- chemical Society, 2022, 169(3): 030511. [13] Anseán D, Dubarry M, Devie A, et al.Operando lithium plating quantification and early detection of a commercial LiFePO4 cell cycled under dynamic driving schedule[J]. Journal of Power Sources, 2017, 356: 36-46. [14] Liu Qianqian, Du Chunyu, Shen Bin, et al.Under- standing undesirable anode lithium plating issues in lithium-ion batteries[J]. RSC Advances, 2016, 6(91): 88683-88700. [15] 郭东旭, 杨耕, 冯旭宁, 等. 计及老化路径的锂离子电池加速寿命工况自动生成方法[J]. 电工技术学报, 2022, 37(18): 4788-4797, 4806. Guo Dongxu, Yang Geng, Feng Xuning, et al.Accelerated aging profile generation method for lithium-ion batteries considering aging path[J]. Transactions of China Electrotechnical Society, 2022, 37(18): 4788-4797, 4806. [16] Petzl M, Danzer M A.Nondestructive detection, characterization, and quantification of lithium plating in commercial lithium-ion batteries[J]. Journal of Power Sources, 2014, 254: 80-87. [17] McDowell M T, Lee S W, Nix W D, et al. 25th anniversary article: understanding the lithiation of silicon and other alloying anodes for lithium-ion batteries[J]. Advanced Materials, 2013, 25(36): 4966-4985. [18] Bernd Epding, Björn Rumberg, Maximilian Mense, et al.Aging-ptimized fast charging of lithium ion cells based on three-ectrode cell measurements[J]. Energy Technology, 2020, 8(10): 2000457. [19] Pramanik S, Anwar S.Electrochemical model based charge optimization for lithium-ion batteries[J]. Journal of Power Sources, 2016, 313: 164-177. [20] Guo Zhen, Liaw B Y, Qiu Xinping, et al.Optimal charging method for lithium ion batteries using a universal voltage protocol accommodating aging[J]. Journal of Power Sources, 2015, 274: 957-964. [21] 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. [22] Doyle M, Newman J, Gozdz A S, et al.Comparison of modeling predictions with experimental data from plastic lithium ion cells[J]. Journal of the Elec- trochemical Society, 2019, 143(6): 1890-1903. [23] Xiong Rui, Sun Fengchun, Chen Zheng, et al.A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion polymer battery in electric vehicles[J]. Applied Energy, 2014, 113: 463-476. [24] 武龙星, 庞辉, 晋佳敏, 等. 基于电化学模型的锂离子电池荷电状态估计方法综述[J]. 电工技术学报, 2022, 37(7): 1703-1725. Wu Longxing, Pang Hui, Jin Jiamin, et al.A review of SOC estimation methods for lithium-ion batteries based on electrochemical model[J]. Transactions of China Electrotechnical Society, 2022, 37(7): 1703-1725. [25] Zhang Dong, Popov B, White R. Modeling lithium intercalation of a single spinel particle under potentiody- namic control[J]. Journal of the Electrochemical Society, 2000, 147: 831-838. [26] Li Changlong, Cui Naxin, Wang Chunyu, et al.Reduced-order electrochemical model for lithium-ion battery with domain decomposition and polynomial approximation methods[J]. Energy, 2021, 221: 119662. [27] Tippmann S, Walper D, Balboa L, et al.Low- emperature charging of lithium-ion cells part I: Electrochemical modeling and experimental investi- gation of degradation behavior[J]. Journal of Power Sources, 2014, 252: 305-316. [28] Chu Zhengyu, Feng Xuning, Lu Languang, et al.Non- destructive fast charging algorithm of lithium-ion batteries based on the control-oriented electrochemical model[J]. Applied Energy, 2017, 204: 1240-1250. [29] Tomaszewska A, Chu Zhengyu, Feng Xuning, et al.Lithium-ion battery fast charging: a review[J]. eTransportation, 2019, 1: 100011. [30] Zhao Tongzheng, Zheng Yuejiu, Liu Jinhai, et al.A study on half-cell equivalent circuit model of lithium- on battery based on reference electrode[J]. International Journal of Energy Research, 2021, 45(3): 4155-4169. [31] Drees R, Lienesch F, Kurrat M.Durable fast charging of lithium-ion batteries based on simulations with an electrode equivalent circuit model[J]. Batteries, 2022, 8(4): 30. [32] Drees R, Lienesch F, Kurrat M.Fast charging formation of lithium-ion batteries based on real-time negative electrode voltage control[J]. Energy Tech- nology, 2023, 11(5): 2200868. [33] Drees R, Lienesch F, Kurrat M.Fast charging lithium-ion battery formation based on simulations with an electrode equivalent circuit model[J]. Journal of Energy Storage, 2021, 36: 102345. [34] Lu Yufang, Han Xuebing, Chu Zhengyu, et al.A decomposed electrode model for real-time anode potential observation of lithium-ion batteries[J]. Journal of Power Sources, 2021, 513: 230529. [35] Johnson V H.Battery performance models in ADVISOR[J]. Journal of Power Sources, 2002, 110(2): 321-329. [36] Xu Zhicheng, Wang Jun, Fan Qi, et al.Improving the state of charge estimation of reused lithium-ion batteries by abating hysteresis using machine learning technique[J]. Journal of Energy Storage, 2020, 32: 101678. [37] Wu M S, Chiang P C J, Lin J C. Electrochemical investigations on advanced lithium-ion batteries by three-electrode measurements[J]. Journal of the Elec- trochemical Society, 2005, 152(1): A47. [38] Wassiliadis N, Adermann J, Frericks A, et al.Revisiting the dual extended Kalman filter for battery state-of-charge and state-of-health estimation: a use- case life cycle analysis[J]. Journal of Energy Storage, 2018, 19: 73-87.