Kinetic parameter estimation for cooling crystallization process based on cell average technique and automatic differentiation

In this paper,a cell average technique(CAT)based parameter estimation method is proposed for cooling crystallization involved with particle growth,aggregation and breakage,by establishing a more efficient and accurate solution in terms of the automatic differentiation(AD)algorithm.To overcome the deficiency of CAT that demands high computation cost for implementation,a set of ordinary differential equations(ODEs)entailed from CAT based discretized population balance equation(PBE)are solved by using the AD based high-order Taylor expansion.Moreover,an AD based trust-region reflective(TRR)algorithm and another interior-point(IP)algorithm are established for estimating the kinetic parameters associated with particle growth,aggregation and breakage.As a result,the estimation accuracy can be further improved while the computation cost can be significantly reduced,compared to the existing algorithms.Benchmark examples from the literature are used to illustrate the accuracy and efficiency of the AD-based CAT,TRR and IP algorithms in comparison with the existing algorithms.Moreover,seeded batch cooling crystallization experiments ofβform L-glutamic acid are performed to validate the proposed method.

Review on degradation mechanism and health state estimation methods of lithium-ion batteries

State of health(SOH)estimation is important for a lithium-ion battery(LIB)health state management system,and accurate estimation of SOH is influenced by the degree of degradation of the LIB.However,considering the complex electrochemical reactions within Li electrons and the influence of many external factors on internal reactions,it is difficult to accurately estimate the SOH based on the surface state characteristics of the battery(including current,voltage,and temperature).Thus,in this study,the knowledge graph method is employed to analyze keyword co-occurrences and citations in the literature on LIB degradation and SOH estimation to determine research hotspots.Based on the research trends,findings regarding the internal and external degradation mechanisms and influencing factors of(LIBs)are reorganized,and chemical and physical degradation processes,including solid electrolyte interface(SEI)layer formation,fracture,Li plating,and dendrite formation,are systematically introduced based on the modeling perspective.The interrelationships between these degradation factors and their effects on capacity and power decay as well as their correlation with SOH estimation are evaluated.Additionally,a comparative analysis of existing SOH estimation methods is presented,and the applicable scenarios and technical problems of each method are summarized.The key issues such as model simplification,estimation methods based on random data,and second-life SOH are also analyzed and discussed.The results show that the estimation results of methods mixing multiple models tend to be more accurate.Finally,the development trend of SOH estimation methods under complex degradation conditions and usage scenarios is analytically discussed.