Premium
Challenges in data‐based degradation models for lithium‐ion batteries
Author(s) -
Galatro Daniela,
Silva Carlos Da,
Romero David A.,
Trescases Olivier,
Amon Cristina H.
Publication year - 2020
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.5196
Subject(s) - lithium (medication) , degradation (telecommunications) , cycling , work (physics) , quadratic equation , kinetic energy , test data , function (biology) , trajectory , computer science , reliability engineering , algorithm , thermodynamics , mathematics , engineering , physics , medicine , telecommunications , geometry , archaeology , quantum mechanics , astronomy , evolutionary biology , biology , history , programming language , endocrinology
Summary This work summarizes the findings resulting from applying an aging modeling approach to four different capacity loss experimental datasets of lithium‐ion batteries (LIBs). This approach assumes that the degradation trajectory of the capacity is a function of three variables: time, kinetic constant, and time‐dependent factor. The analysis shows that the time‐dependent factor α is cell‐chemistry dependent and cannot be averaged for calendar and cycling modes and combined modes. This factor was also found to be a function of the stress factors. A quadratic model was used to obtain the kinetic constants per test, and statistical metrics were provided to evaluate the quality of the fitting, which was significantly affected when using averaged values of α and refitted kinetic constants. A set of test matrices is proposed for calendar, cycling, and mixed aging modes to overcome the challenges of data‐based models developed from accelerated test approaches for modeling aging in LIBs. This work also proposes a methodology to develop these data‐based aging models.