Experimental Validation of the Aging Model of Lithium-Ion Batteries Regardless of Deterioration Conditions

被引:0
作者
Kharche, Nitin A. [1 ]
Singh, Praveen [2 ]
Soni, N. B. [3 ]
Vekariya, Daxa [4 ]
Patil, Harshal [5 ]
Maranan, Ramya [6 ]
机构
[1] Padm Dr VB Kolte Coll Engn, Dept Mech Engn, Malkapur 443101, Maharashtra, India
[2] Graph Era Deemed Be Univ, Dept Management, Dehra Dun 248002, Uttarakhand, India
[3] Maharshi Parshuram Coll Engn, Dept Elect Engn, Velneshwar 415729, Maharashtra, India
[4] Parul Univ, Parul Inst Engn & Technol, Dept Comp Sci & Engn, Post Limda 391760, Gujarat, India
[5] Symbiosis Int Deemed Univ, Symbiosis Inst Technol, Dept Comp Sci & Engn, Pune 412115, Maharashtra, India
[6] SIMATS, Saveetha Sch Engn, Dept Res & Innovat, Chennai 602105, Tamil Nadu, India
来源
2024 5TH INTERNATIONAL CONFERENCE ON INNOVATIVE TRENDS IN INFORMATION TECHNOLOGY, ICITIIT 2024 | 2024年
关键词
Lithium-ion Batteries; Aging Model; Experimental Validation; Deterioration Conditions; Battery Degradation; Battery Performance; OF-HEALTH ESTIMATION; INTERNAL RESISTANCE; STATE;
D O I
10.1109/ICITIIT61487.2024.10580192
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This work validates, experimentally, the conformity of the electrical aging model for LiFeP04 and NMC type lithium cells by taking into account the effects of temperature, current and internal resistance on its yield. If necessary, modifications will be made to the aging model based on the experimental results. To carry out this work, the following structure was used. First, a literature review outlining the chemical principles and aging mechanisms of lithium batteries. Next, the battery aging model and everything that makes it up will be analyzed. In order to collect experimental data, lithium batteries and a test protocol will be put to the test bench. Validation will be done by comparing the simulation results of the proposed model with the experimental data obtained. This model will then be compared to another aging simulation technique. To conclude, the differences between the two simulation methods and the experiment will be analyzed to establish the validity and advantages of the proposed model.
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页数:6
相关论文
共 20 条
[1]  
Ashok Anjali, 2015, International Journal of Applied Engineering Research., V10, P4809
[2]   Online parameter and state estimation of lithium-ion batteries under temperature effects [J].
Chaoui, Hicham ;
Gualous, Hamid .
ELECTRIC POWER SYSTEMS RESEARCH, 2017, 145 :73-82
[3]   A new state-of-health estimation method for lithium-ion batteries through the intrinsic relationship between ohmic internal resistance and capacity [J].
Chen, Lin ;
Lu, Zhiqiang ;
Lin, Weilong ;
Li, Junzi ;
Pan, Haihong .
MEASUREMENT, 2018, 116 :586-595
[4]   Advanced Lithium-Ion Batteries for Practical Applications: Technology, Development, and Future Perspectives [J].
Choi, Sinho ;
Wang, Guoxiu .
ADVANCED MATERIALS TECHNOLOGIES, 2018, 3 (09)
[5]   Modeling and Applications of Electrochemical Impedance Spectroscopy (EIS) for Lithium-ion Batteries [J].
Choi, Woosung ;
Shin, Heon-Cheol ;
Kim, Ji Man ;
Choi, Jae-Young ;
Yoon, Won-Sub .
JOURNAL OF ELECTROCHEMICAL SCIENCE AND TECHNOLOGY, 2020, 11 (01) :1-13
[6]   A Robust Online Parameter Identification Method for Lithium-Ion Battery Model Under Asynchronous Sampling and Noise Interference [J].
Cui, Zhongrui ;
Cui, Naxin ;
Wang, Chunyu ;
Li, Changlong ;
Zhang, Chenghui .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 68 (10) :9550-9560
[7]  
Kumar P. Anandha, 2015, International Journal of Applied Engineering Research, V10, P4840
[8]   Electrochemical model-based state estimation for lithium-ion batteries with adaptive unscented Kalman filter [J].
Li, Weihan ;
Fan, Yue ;
Ringbeck, Florian ;
Jost, Dominik ;
Han, Xuebing ;
Ouyang, Minggao ;
Sauer, Dirk Uwe .
JOURNAL OF POWER SOURCES, 2020, 476
[9]   State-of-health estimation for Li-ion batteries by combing the incremental capacity analysis method with grey relational analysis [J].
Li, Xiaoyu ;
Wang, Zhenpo ;
Zhang, Lei ;
Zou, Changfu ;
Dorrell, David. D. .
JOURNAL OF POWER SOURCES, 2019, 410 :106-114
[10]   Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review [J].
Li, Yi ;
Liu, Kailong ;
Foley, Aoife M. ;
Zulke, Alana ;
Berecibar, Maitane ;
Nanini-Maury, Elise ;
Van Mierlo, Joeri ;
Hoster, Harry E. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2019, 113