Transport Properties of LiPF[sub 6]-Based Li-Ion Battery Electrolytes

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171

Consumer electronics, wearable and personal health devices, power networks, microgrids, and hybrid electric vehicles (HEVs) are some of the many applications of lithium-ion batteries. Their optimal design and management are important for safe and profitable operations. The use of accurate mathematical models can help in achieving the best performance. This article provides a detailed description of a finite volume method (FVM) for a pseudo-two-dimensional (P2D) Li-ion battery model suitable for the development of model-based advanced battery management systems. The objectives of this work are to provide: (i) a detailed description of the model formulation, (ii) a parametrizable Matlab framework for battery design, simulation, and control of Li-ion cells or battery packs, (iii) a validation of the proposed numerical implementation with respect to the COMSOL MultiPhysics commercial software and the Newman's DUALFOIL code, and (iv) some demonstrative simulations involving thermal dynamics, a hybrid charge-discharge cycle emulating the throttle of an HEV, a model predictive control of state of charge, and a battery pack simulation. The increasing demand for portable devices (e.g., smartphones) and hybrid electric vehicles (HEVs) calls for the design and management of storage devices of high power density and reduced size and weight. During the many decades of research, different chemistries of batteries have been developed, such as Nickel Cadmium (NiCd), Nickel Metal Hydride (NiMH), Lead Acid and Lithium ion (Li-ion) and Lithium ion Polymer (Li-Poly) (e.g., see Refs. 1-4). Among electrochemical accumulators, Li-ion batteries provide one of the best tradeoff in terms of power density, low weight, cell voltage, and low self-discharge. 5 Mathematical models can support the design of new batteries as well as the development of new advanced battery management systems (ABMS). [6][7][8] According to the literature, mathematical models for Li-ion battery dynamics fall within two main categories: Equivalent Circuit Models (ECMs) and Electrochemical Models (EMs). ECMs use only electrical components to model the dynamic behavior of the battery. ECMs include (i) the R int model where only a resistance and a voltage source are used to model the battery, (ii) the RC model (introduced by the company SAFT 9 ) where capacitor dynamics have been added to the R int model, 10 and (iii) the Thevenin model, which is an extension of the RC model (e.g., see Refs. 11, 12 and references therein). In contrast, EMs explicitly represent the chemical processes that take place in the battery. While ECMs have the advantage of simplicity, EMs are more accurate due to their ability to describe detailed physical phenomena. 13 The most widely used EM in the literature is the porous electrode theory-based pseudo-two-dimensional (P2D) model, 14 which is described by a set of tightly coupled and highly nonlinear partial differential-algebraic equations (PDAEs). In order to exploit the model for simulation and design purposes, the set of PDAEs are reformu...

Section: Battery Modelmentioning

confidence: 99%

LIONSIMBA: A Matlab Framework Based on a Finite Volume Model Suitable for Li-Ion Battery Design, Simulation, and Control

Torchio

Magni

Gopaluni

et al. 2016

221

171

“…Still, we face a limitation in terms of using measured transport parameters from the electrolyte applied to the cell. In this study, a comparable set of fitted parameters from literature 31 is transferred to our cell setup, assuming sufficient representation of any concentration dependent electrolyte transport limitation. Further, although the OCV of both electrodes was measured with coin cells versus lithium, the initial stoichiometry remains a fitting parameter.…”

Section: Temperature Dependency-inmentioning

confidence: 99%

Simulation and Measurement of the Current Density Distribution in Lithium-Ion Batteries by a Multi-Tab Cell Approach

Erhard

Oßwald

Keil

et al. 2017

A single-layered NMC/graphite pouch cell is investigated by means of differential local potential measurements during various operation scenarios. 44 tabs in total allow for a highly resolved potential measurement along the electrodes whilst the single layer configuration guarantees the absence of superimposed thermal gradients. By applying a multi-dimensional model framework to this cell, the current density and SOC distribution are analyzed quantitatively. The study is performed for four C-rates (0.1C, 0.5C, 1C, 2C) at three temperatures (5 • C, 25 • C, 40 • C). The maximum potential drop as well the corresponding SOC deviation are characterized.The results indicate that cell inhomogeneity is positively coupled to temperature, i.e. the lower the temperature, the more uniform the electrodes will be utilized. Within the past decades, demand for lithium-ion batteries in mobile applications has significantly increased. Due to their well proven performance as well as their stability in long-term usage, lithium-ion batteries became the technology of choice for electrochemical energy storage devices.1,2 Still, the specific energy density as well as cycle life are constantly being optimized by either commercializing new active materials, electrolytes and additives or by reducing the fraction of non-active parts within a battery. Often, this corresponds to thicker electrodes or larger form factors leading to capacities of up to 100 Ah per cell. In these large format cells, severe gradients in current density and temperature distribution can occur along the electrode stack, 3-9 which might provoke a performance loss during operation due to inhomogeneous utilization. Also non-properly adapted thermal conditioning can have a crucial impact on the performance of larger cells. [10][11][12] Modeling of internal distributions of potential and temperature along the electrodes is quite challenging, since even to calculate only a few cycles, a lot of computational resources are required for fully resolved models. In literature, there are many examples for spatially resolved multi-dimensional modeling approaches, 8,9,[13][14][15][16] which aim at representing the cell's internal behavior in terms of potential, current density, state of charge (SOC) and temperature distribution. Unfortunately, all of these examples lack a detailed, i.e. spatially resolved experimental validation, which is capable of tracking internal variables instead of measuring the surface temperature at a few spots and considering the overall battery's terminal voltage. Also, only a few examples of direct measurements of the internal current density distribution were published so far. Zhang et al.6,7 built a specific LFP/graphite prototype cell for this purpose. A segmented cathode was used for analyzing the current distribution during discharge at varying C-rates and temperatures. This setup allows for a precise monitoring of the current of each electrode element individually. Large deviations in SOC of up to several percent were identified during the process...

“…Moreover, the lithium diffusion coefficient in the solid phase, the reaction-rate constant and the electrolyte properties are taken to be dependent on the lithium concentration, which is in harmony with experimental facts. [31][32][33][34][35] Indeed, the assumption of parameter invariance with concentration falls short for high-loading electrodes where large concentration gradients form even at moderate C-rate in the liquid phase across the cell and in the solid phase across the electrodes. However, composition-dependent properties may complicate the model convergence, hence calling for an increase of the number of nodes across the cell sandwich and/or across the radial dimension of the active particles, along with a decrease of the time step, which is at the expense of simulation time.…”

mentioning

confidence: 99%

Experimental and Modeling Analysis of Graphite Electrodes with Various Thicknesses and Porosities for High-Energy-Density Li-Ion Batteries

Malifarge

Delobel

Delacourt

2018

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. 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 s...