A Critical Comparison of Empirical Models and Datasets for Aging in Lithium-Ion Cells

Lithium-ion cells are often viewed as an enabling technology for plug-in hybrid electric vehicles and battery electric vehicles due to their high energy and power densities. Beyond these applications, lithium-ion battery packs are also candidates for hybrid-electric passenger aircraft and vertical takeoff and landing applications. However, lithium-ion cells have been observed to degrade with time and usage. Degradation effects are seen primarily in capacity fade, a reduction in the cell's capacity, and power fade, an increase in the cell's internal resistance. Both of these degradation effects can occur while the cell is in use (cycling aging), or while the cell is being stored (calendar aging). To design a battery pack to be able to meet application requirements over the lifetime of the application, pack designers must be able to predict and design for future cell aging. Although a number of empirical aging models are available in literature, no form has been identified as a standard. The objective of this work is to compare aging models and datasets from aging campaigns to evaluate the strengths and limitations of each. It was identified that models which describe both capacity and power fade resulting from calendar and cycling aging were applicable to the greatest number of applications. Two of the identified models considered the effects of the most relevant operating conditions (temperature, state-of-charge, current, and time) on aging for capacity and power fade. However, the structures of both models resulted in a challenging calibration process. This indicated a need for an aging model which captures all critical operating conditions and degradation effects while offering a straight-forward calibration process. A generalized empirical aging model form is presented in this work which aims to satisfy this need. This model was calibrated and validated using a subset of the compared aging datasets. This contribution will offer pack designers a generalized model form which can be applied to a greater range of operating conditions to facilitate a faster comparison of multiple cells and pack designs.The Ohio State University College of EngineeringA one-year embargo was granted for this item.Academic Major: Mechanical Engineerin