Résumé
The influence of the negative electrode design on its electrochemical performance with regard to Li insertion/de-insertion is analyzed in this work. A combined experimental/modeling approach is undertaken relying on Newman continuum model. Various designs of industry-grade graphite electrodes (2-6 mAh cm −2) were previously characterized by measuring geometric and physical parameters that are used as input parameters in the present model analysis. The half-cell model is successfully validated against rate-capability experiments without any further parameter fitting. The various polarization contributions are then identified based on the model analysis of rate-capability tests on the various electrodes. It emerges that low-loading electrodes suffer from larger particle-scale limitations (mainly solid-diffusion limitation) than high-loading electrodes because of a lower active surface area per geometric area. However, high-loading electrodes undergo large liquid-phase limitations at medium to high current densities: a large overpotential develops because of the formation of a large salt concentration gradient across the cell. Finally, the graphite electrode model is used into a full-cell model vs. LiNi 0.33 Mn 0.33 Co 0.33 O 2 (NMC) as the positive electrode. Simulations allow for a forecast of the occurrence of Li plating for various cell designs with the constraint of a constant ratio of negative to positive electrode loading. As of today, electric vehicles (EV) are being promoted as a substitute to internal-combustion-engine (ICE) vehicles in an effort to mitigate CO 2 , NO x and particulate matter (PM) emissions from the road transportation sector. Although the effectiveness of EV market penetration toward mitigating air pollution strongly depends upon the source of electricity production (e.g., fossil vs. nuclear or renewable), it may still improve air quality in cities and thereby citizens' health. In fact, the annual cost of air pollution was evaluated to over US$ 1.431 trillion in Europe by the World Health Organization in 2010. 1 Nonetheless, the effectiveness of EV market penetration relies on whether consumers are willing to shift from ICE to electric vehicles. Among factors refraining citizens from shifting to EVs are the high price, the vehicle charging time and the driving range. The most straightforward way to tackle both the high price and limited driving range, with state-of-the-art Lithium-ion technology, is to increase electrode loading. Packing more active material in the electrode increases the cell energy density and decreases the amount of inactive material in a Lithium-ion battery pack. Fewer electrodes per stack are needed in a single cell, hence less current collector is used. However , high-loading electrodes suffer large power limitations, which might preclude fast charging of the EV battery pack. Power limitations mostly arise from lithium-ion transport limitations across the electrode porosity filled with the electrolyte and are known to increase with the electrode thickness and/or with a decrease in porosity. 2-4 Accordingly , an optimization of the porous electrode design is necessary to achieve a high energy density while retaining enough power for the targeted application. Yet, electrode design optimization is not straightforward, as it requires performance analysis of a number of different electrode designs. Moreover, a lithium-ion battery (LIB) is a closed system from which only a small number of operating variables can be set and/or measured, e.g., the voltage, the current, and the surface temperature. Electrochemical techniques such as rate-capability tests (galvanos-tatic charge/discharge at different current densities), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry are regular methods to shed light on cell performance limitations but are unable to give definite insight on any concentration and/or potential gradients forming inside the cell. The experimental investigation of * Electrochemical Society Student Member. z E-mail: charles.delacourt@u-picardie.fr the influence of electrode loading and density on cell performance is rather scarce in the published literature. Fongy et al. characterized LiFePO 4 (LFP) electrodes with different thicknesses, porosity values and binder content by analyzing rate-capability experiments using Prosini's approach. 5,6 An optimal design was found that balances electronic and ionic limitations that appear at high and low porosity values, respectively. Zheng et al. studied separately the influence of electrode composition, calendering and loading of Li(Ni 1/3 Mn 1/3 Co 1/3)O 2 (NMC 111) cathodes by carrying out rate-capability tests and EIS experiments. 7-9 Ogihara et al. performed EIS on symmetric cells based on graphite electrodes with different loadings, and obtained estimation of charge transfer and ionic resistances. 10 Shim and Striebel observed that an increased electrode density induces a slight reduction in both the reversible and irreversible capacity for the first cycle of natural graphite. 11 Buqa et al. examined electrode loadings (1.5-10 mg cm −2) from different synthetic graphites with relatively high electrode porosity (50-80%). 12 They showed that the limitation at high Crate stems from electrode design and not from the graphite material itself. Singh et al. compared rate-capability performance of cathodes and anodes with various loadings. 13,14 Gallagher et al. also studied cathodes and anodes with various loadings (2.2-6.6 mAh cm −2) and presented a physics-based quantitative relationship to link electrode thickness and rate of operation to performance losses. 15 Beside studies based on electrochemical techniques, imaging techniques of operando and in-situ cells were developed and allow to provide additional information on local state of charge (SoC) and salt concentration gradient across the cell. 16-23 However, the analysis turns out to be tedious when screening a large panel of electrode designs. Mathematical models represent a relevant alternative over experimental time-consuming methods. LIB models are a fast, low-cost and accurate tool to perform electrode design optimization. Providing that model equations represent the underlying physics well enough and that corresponding input parameters are accurate, a LIB model enables to predict what is actually happening inside a cell in terms of, e.g., local SoC and temperature, solid and liquid phase potentials , electronic and ionic current densities and solid/liquid lithium concentration gradients. Moreover, simulated data are easy to handle or display, and power-limitation sources are readily identified by switching on or off the corresponding physical phenomena. Among LIB continuum models, the so-called Newman model offers the best compromise between computation speed and physical significance. It is a pseudo-2D (P2D) model that relies on porous electrode theory and) unless CC License in place (see abstract). ecsdl.org/site/terms_use address. Redistribution subject to ECS terms of use (see 194.57.107.121 Downloaded on 2018-07-16 to IP