Optimal charging of Li-ion batteries using sparse identification of nonlinear dynamics

被引:0
|
作者
Bhadriraju, Bhavana [1 ,2 ]
Lee, Jooyoung [4 ]
Pahari, Silabrata [1 ,2 ]
Yu, Choongho [4 ]
Khan, Faisal [1 ,3 ]
Kwon, Joseph Sang-Il [1 ,2 ]
机构
[1] Texas A&M Univ, Artie McFerrin Dept Chem Engn, College Stn, TX 77845 USA
[2] Texas A&M Univ, Texas A&M Energy Inst, College Stn, TX 77845 USA
[3] Texas A&M Univ, Mary Kay OConnor Proc Safety Ctr, College Stn, TX 77845 USA
[4] Texas A&M Univ, J Mike Walker Dept Mech Engn 66, College Stn, TX 77845 USA
关键词
Li-ion battery; Charge optimization; Sparse modeling; Mixed-integer quadratic programming (MIQP); Remaining lifetime; Charge time; Battery degradation; REGRESSION; REFORMULATION; FRAMEWORK; SELECTION; MODELS;
D O I
10.1016/j.cej.2024.155015
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Optimal charging of Li-ion batteries requires careful management of charge rates, as high rates can lead to accelerated degradation, while low rates significantly extend charging times. Traditional methods for determining charge rates often rely on rule-based approaches, which typically fail to effectively balance battery performance with charging duration. To address this, we introduce a novel optimization approach that directly integrates the dual objectives of minimizing charge time and maximizing battery lifetime into the optimization process. Unlike most existing charge optimization methods that do not directly track battery lifetime and charge time simultaneously, our method employs a data-driven model that facilitates direct and dynamic estimation of both battery lifetime and charge time at each step of the optimization process. Specifically, we utilize the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm to predict battery capacity and voltage dynamics, which informs the calculations of lifetime and charge time required to solve the optimization problem. This approach provides a balanced optimization strategy that enhances the effectiveness of battery's performance while maintaining the efficiency of the charging process. We applied this method to a novel next-generation NMC811 battery, featuring a cathode comprised of 80% nickel, 10% manganese, and 10% cobalt, and a lithium metal foil anode - a combination not extensively studied previously. Experimental validation demonstrated that when optimized charge rates are applied every 10 cycles in a 100-cycle operation, the method leads to more stable cycling and improved capacity retention of approximately 7.4% over the nominal charge rate, demonstrating the potential of the developed approach.
引用
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页数:12
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