M. Safari

Multimodal Physics-Based Aging Model for Life Prediction of Li-Ion Batteries

An isothermal, multimodal, physics-based aging model for life prediction of Li-ion batteries is developed, for which a solvent-decomposition reaction leading to the growth of a solid electrolyte interphase (SEI) at the carbonaceous anode material is considered as the source of capacity fade. The rate of SEI film growth depends on both solvent diffusion through the SEI film and solvent-reduction kinetics at the carbon surface. The model is able to simulate a wide variety of battery aging profiles, e.g., open-circuit and constant-voltage storage, charge/discharge cycling, etc. An analysis of capacity-fade data from the literature reveals that the same set of aging parameters may be used for predicting cycling and constant-voltage storage. The use of this set of parameters for predicting storage under open-circuit voltage points out that part of the self-discharge is reversible.

Aging of a Commercial Graphite/LiFePO4 Cell

The aging behavior of a commercial 2.3 Ah graphite/LFP cell during a year of cycling or storage at either 25 or 45 � C is investigated. The performance decline of the cells during the aging period is monitored by non-destructive electrochemical techniques and is discussed in detail. An in-depth analysis of the aging results reveals that aging manifests itself more in terms of capacity loss rather than in terms of impedance increase, regardless of the cycling or storage conditions and of the temperature. The capacity fade is larger at 45 � C than at 25 � C, regardless of the cycling or storage conditions, and at a same temperature, cycling conditions are always more detrimental to capacity fade than storage conditions. The loss of cyclable lithium is identified as the main source of capacity fade in all cases, and for the cells aged at 45 � C, a partial loss of graphite active material is suspected as

Modeling of a Commercial Graphite/LiFePO4 Cell

An isothermal model for the electrochemical behavior of a commercial graphite/LiFePO 4 cell at 25 and 45°C is developed. Although it does not embed any special feature of the porous electrodes and of the two-phase process of the LiFePO 4 electrode, proper account of the experimental charge/discharge (from C/10 to 1C) and path-dependence effects of the commercial cell is achieved. The LiFePO 4 electrode is treated based on a resistive-reactant concept with multiple particles whereas a single-particle approach is used to model the graphite electrode. In order to refine the model parameters for each electrode, half cells are made either from the recovered LiFePO 4 or graphite electrodes vs. a Li counterelectrode. A detailed experiment/simulation analysis of half-cell and complete-cell data unfolds the impact of uniaxial pressure on the galvanostatic charge/discharge limitation and path dependence of the LiFePO 4 electrode in the coin cell and the commercial cell.

Mathematical Modeling of Lithium Iron Phosphate Electrode: Galvanostatic Charge/Discharge and Path Dependence

Based on the resistive-reactant concept, a simple mathematical model for lithium intercalation/deintercalation in a lithium iron phosphate electrode is developed. Demonstrative experiments are provided to shed light on the resistive-reactant feature of this electrode. Without embedding any special feature of the two-phase process, the model consists of regular concentration-dependent lithium diffusion inside four groups of active-material particles that have different connectivities to the conductive matrix of the electrode. Model-experiment comparisons reveal the effectiveness of the resistive-reactant concept for a quantitative description of the charge/discharge as well as the path dependence observed in lithium iron phosphate electrodes.

Life-Prediction Methods for Lithium-Ion Batteries Derived from a Fatigue Approach I. Introduction: Capacity-Loss Prediction Based on Damage Accumulation

The possibility of using mechanical-fatigue life-prognostic methods for the life prediction of Li-ion batteries is evaluated. To this end, a physics-based model of a battery experiencing a single source of aging, i.e., the growth of a solid electrolyte interphase at the carbonaceous anode material, is employed as a surrogate battery. Dummy aging data sets, consisting of current microcycles at a nearly constant state of charge, are readily generated and used to evaluate the prediction capability of damage-accumulation relationships, among which is the Palmgren-Miner (PM) rule, which is well known in the field of mechanical fatigue. The PM rule is slightly more accurate than the regular damage accumulation over time. A complete methodology for predicting the aging of a battery experiencing a complex current profile is proposed in a second paper.

Life Prediction Methods for Lithium-Ion Batteries Derived from a Fatigue Approach II. Capacity-Loss Prediction of Batteries Subjected to Complex Current Profiles

A methodology for predicting the capacity loss of a battery under a complex current profile is provided. The prediction is based upon a set of elementary aging experiments, which are herein generated by a physics-based model featuring a surrogate battery, for which the source of aging is the growth of a solid-electrolyte interphase at the anode. Empirical correlations of the capacity loss as a function of the aging time and of the aging time as a function of the capacity loss are developed based on 12 dummy elementary aging experiments under different conditions of state of charge and current. Those correlations are used together with the relationship for loss accumulation over time or the Palmgren-Miner rule (both introduced in Part I) to predict the aging of a complex current profile. The prediction accuracy is assessed by a direct simulation of the complex profile by using the physics-based model featuring the surrogate battery.

Mathematical Modeling of Aging of Li-Ion Batteries

The recent interest in full and hybrid electric vehicles powered with Li-ion batteries has prompted for in-depth battery aging characterization and prediction. This topic has become popular both in academia and industry battery research communities. Because it is an interdisciplinary topic, different methods for aging studies are being pursued, ranging from black box types of approaches from the electrical engineering community all the way to physics-based methods mainly brought about by the chemical engineering community. This chapter describes an overall methodology for aging characterization and prediction in Li-ion batteries based on physics-based modeling. In a first section, the typical aging phenomena in LIBs are reviewed along with their effects on the cell internal balancing and performance loss. In a second section, the physics-based models used for aging studies are presented, which includes both the performance models (i.e., aging-free) and aging models. In a third section, the typical aging experiments and characterization methods are introduced, along with their analysis with the physics-based models. Finally, the last section presents an outlook of physics-based aging modeling.