Abstract
Lithium-ion (Li-ion) batteries undergo complex electrochemical and mechanical degradation. This complexity is pronounced in applications such as electric vehicles, where highly demanding cycles of operation and varying environmental conditions lead to non-trivial interactions of ageing stress factors. This work presents the framework for an ageing diagnostic tool based on identifying and then tracking the evolution of model parameters of a fundamental electrochemistry-based battery model from non-invasive voltage/current cycling tests. In addition to understanding the underlying mechanisms for degradation, the optimisation algorithm developed in this work allows for rapid parametrisation of the pseudo-two dimensional (P2D), Doyle-Fuller-Newman, battery model. This is achieved through exploiting the embedded symbolic manipulation capabilities and global optimisation methods within MapleSim. Results are presented that highlight the significant reductions in the computational resources required for solving systems of coupled non-linear partial differential equations.
Highlights
Since the commercialisation of lithium-ion (Li-ion) batteries, significant improvements in energy density and power capability have made Li-ion batteries the preferred solution for low carbon mobility for the 10–15 years [1]
The growth of solid electrolyte interphase (SEI) is a well-established-well-studied degradation mechanism and provides a method for corroborating the results presented in this work
Comparing results derived from the identification technique presented here with established trends for electrochemical impedance spectroscopy (EIS) growth in the literature provides a level of validation, which is otherwise difficult to achieve in such a context
Summary
Since the commercialisation of lithium-ion (Li-ion) batteries, significant improvements in energy density and power capability have made Li-ion batteries the preferred solution for low carbon mobility for the 10–15 years [1]. The change in behaviour of Li-ion batteries over a vehicle lifetime can have a significant detrimental effect on vehicle performance and lifetime [2,3]. Understanding battery ageing is convoluted since many factors from environmental conditions to vehicle utilization interact to generate different ageing effects [4]. Battery degradation is accelerated with factors that include, but are not constrained too: the frequency of cycling, large change in state of charge (∆SoC), large current magnitudes during both charge and discharge, elevated temperatures, and elevated voltage exposure [2]. The resulting physical degradation [4] can broadly manifest itself in two ways that an energy storage systems engineer is interested in: capacity fade that affects the range of the vehicle and power fade, which is the increase in the internal resistance or impedance of the cell and limits the Batteries 2016, 2, 13; doi:10.3390/batteries2020013 www.mdpi.com/journal/batteries
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