scholarly journals Multiscale Electrolyte Transport Simulations for Lithium Ion Batteries

Author(s):  
Felix Hanke ◽  
Nils Modrow ◽  
Reinier Akkermans ◽  
Ivan Korotkin ◽  
Felix Mocanu ◽  
...  

Establishing a link between atomistic processes and battery cell behavior is a major challenge for lithium ion batteries. Focusing on liquid electrolytes, we describe parameter-free molecular dynamics predictions of their mass and charge transport properties. The simulations agree quantitatively with experiments across the full range of relevant ion concentrations and for different electrolyte compositions. We introduce a simple analytic form to describe the transport properties. Our results are used in an extended Newman electrochemical model, including a cell temperature prediction. This multi-scale approach provides quantitative agreement between calculated and measured discharge voltage of a battery and enables the computational optimization of the electrolyte formulation.

2019 ◽  
Author(s):  
Felix Hanke ◽  
Nils Modrow ◽  
Reinier Akkermans ◽  
Ivan Korotkin ◽  
Felix Mocanu ◽  
...  

Establishing a link between atomistic processes and battery cell behavior is a major challenge for lithium ion batteries. Focusing on liquid electrolytes, we describe parameter-free molecular dynamics predictions of their mass and charge transport properties. The simulations agree quantitatively with experiments across the full range of relevant ion concentrations and for different electrolyte compositions. We introduce a simple analytic form to describe the transport properties. Our results are used in an extended Newman electrochemical model, including a cell temperature prediction. This multi-scale approach provides quantitative agreement between calculated and measured discharge voltage of a battery and enables the computational optimization of the electrolyte formulation.


Author(s):  
Xia Hua ◽  
Alan Thomas

Lithium-ion batteries are being increasingly used as the main energy storage devices in modern mobile applications, including modern spacecrafts, satellites, and electric vehicles, in which consistent and severe vibrations exist. As the lithium-ion battery market share grows, so must our understanding of the effect of mechanical vibrations and shocks on the electrical performance and mechanical properties of such batteries. Only a few recent studies investigated the effect of vibrations on the degradation and fatigue of battery cell materials as well as the effect of vibrations on the battery pack structure. This review focused on the recent progress in determining the effect of dynamic loads and vibrations on lithium-ion batteries to advance the understanding of lithium-ion battery systems. Theoretical, computational, and experimental studies conducted in both academia and industry in the past few years are reviewed herein. Although the effect of dynamic loads and random vibrations on the mechanical behavior of battery pack structures has been investigated and the correlation between vibration and the battery cell electrical performance has been determined to support the development of more robust electrical systems, it is still necessary to clarify the mechanical degradation mechanisms that affect the electrical performance and safety of battery cells.


2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Jules-Adrien Capitaine ◽  
Qing Wang

This paper presents a novel design for a test platform to determine the state of health (SOH) of lithium-ion batteries (LIBs). The SOH is a key parameter of a battery energy storage system and its estimation remains a challenging issue. The batteries that have been tested are 18,650 Li-ion cells as they are the most commonly used batteries on the market. The test platform design is detailed from the building of the charging and discharging circuitry to the software. Data acquired from the testing circuitry are stored and displayed in LabVIEW to obtain the charging and discharging curves. The resulting graphs are compared to the outcome predicted by the battery datasheets, to verify that the platform delivers coherent values. The SOH of the battery is then calculated using a Coulomb counting method in LabVIEW. The batteries will be discharged through various types of resistive circuits, and the differences in the resulting curves will be discussed. A single battery cell will also be tested over 30 cycles and the decrease in the SOH will be clearly identified.


Batteries ◽  
2019 ◽  
Vol 5 (3) ◽  
pp. 57 ◽  
Author(s):  
Seyed Madani ◽  
Erik Schaltz ◽  
Søren Knudsen Kær

The determination of coulombic efficiency of the lithium-ion batteries can contribute to comprehend better their degradation behavior. In this research, the coulombic efficiency and capacity loss of three lithium-ion batteries at different current rates (C) were investigated. Two new battery cells were discharged and charged at 0.4 C and 0.8 C for twenty times to monitor the variations in the aging and coulombic efficiency of the battery cell. In addition, prior cycling was applied to the third battery cell which consist of charging and discharging with 0.2 C, 0.4 C, 0.6 C, and 0.8 C current rates and each of them twenty times. The coulombic efficiency of the new battery cells was compared with the cycled one. The experiments demonstrated that approximately all the charge that was stored in the battery cell was extracted out of the battery cell, even at the bigger charging and discharging currents. The average capacity loss rates for discharge and charge during 0.8 C were approximately 0.44% and 0.45% per cycle, correspondingly.


Author(s):  
Jules-Adrien Capitaine ◽  
Qing Wang

This paper presents a novel design for a test platform to determine the State of Health (SOH) of lithium-ion batteries. The SOH is a key parameter of a battery energy storage system and its estimation remains a challenging issue. The batteries that have been tested are 18650 li-ion cells as they are the most commonly used batteries on the market. The test platform design is detailed from the building of the charging and discharging circuitry to the software. Data acquired from the testing circuitry is stored and displayed in LabView to obtain charging and discharging curves. The resulting graphs are compared to the outcome predicted by the battery datasheets, to verify the platform delivers coherent values. The SOH of the battery is then calculated using a Coulomb Counting method in LabView. The batteries will be discharged through various types of resistive circuits, and the differences in the resulting curves will be discussed. A single battery cell will also be tested over 30 cycles and the decrease in the SOH will be clearly pointed out.


Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4284
Author(s):  
Damoon Soudbakhsh ◽  
Mehdi Gilaki ◽  
William Lynch ◽  
Peilin Zhang ◽  
Taeyoung Choi ◽  
...  

Lithium-ion batteries have found various modern applications due to their high energy density, long cycle life, and low self-discharge. However, increased use of these batteries has been accompanied by an increase in safety concerns, such as spontaneous fires or explosions due to impact or indentation. Mechanical damage to a battery cell is often enough reason to discard it. However, if an Electric Vehicle is involved in a crash, there is no means to visually inspect all the cells inside a pack, sometimes consisting of thousands of cells. Furthermore, there is no documented report on how mechanical damage may change the electrical response of a cell, which in turn can be used to detect damaged cells by the battery management system (BMS). In this research, we investigated the effects of mechanical deformation on electrical responses of Lithium-ion cells to understand what parameters in electrical response can be used to detect damage where cells cannot be visually inspected. We used charge-discharge cycling data, capacity fade measurement, and Electrochemical Impedance Spectroscopy (EIS) in combination with advanced modeling techniques. Our results indicate that many cell parameters may remain unchanged under moderate indentation, which makes detection of a damaged cell a challenging task for the battery pack and BMS designers.


2015 ◽  
Vol 3 (39) ◽  
pp. 19728-19737 ◽  
Author(s):  
Ying Xie ◽  
Hai-Tao Yu ◽  
Ting-Feng Yi ◽  
Qi Wang ◽  
Qing-Shan Song ◽  
...  

LiFeSO4F and FeSO4F exhibit high thermodynamic stability, excellent ionic conductance and poor electronic conductivities.


2019 ◽  
Vol 91 (8) ◽  
pp. 1361-1381 ◽  
Author(s):  
Victor Chaudoy ◽  
Johan Jacquemin ◽  
François Tran-Van ◽  
Michaël Deschamps ◽  
Fouad Ghamouss

Abstract In this work, the physical, transport and electrochemical properties of various electrolytic solutions containing the 1-propyl-1-methylpyrrolidinium bis[fluorosulfonyl]imide ([C3C1pyr][FSI]) mixed with the lithium bis[(trifluoromethyl)sulfonyl]imide (Li[TFSI]) over a wide range of compositions are reported as a function of temperature at atmospheric pressure. First, the ionicity, lithium transference number, and transport properties (viscosity and conductivity) as well as the volumetric properties (density and molar volume) were determined as a function of lithium salt concentration from 293 to 343 K. Second, the self-diffusion coefficient of each ion in solution was measured by nuclear magnetic resonance (NMR) spectroscopy with pulsed field gradients (PFG). Moreover, an analysis of the collected nuclear Overhauser effect (NOE) data along with ab initio and COSMO-RS calculations was conducted to depict intra and intermolecular neighbouring within the electrolytic mixtures. Based on this analysis, and as expected, all activation energies increase with the Li[TFSI] concentration in solution, and all activation energies were determined from the self-diffusion data for all ions. Interestingly, regardless of the composition in solution, these activation energies were similar, except for those determined for the [FSI]− anion. The activation energy of [FSI]− self-diffusion relatively decreases compared to the other ions as the lithium salt concentration increases. Furthermore, the lithium transference was strongly affected by the lithium salt concentration, reaching an optimal value and an ionicity of approximately 50 % at a molality close to 0.75 mol · kg−1. Finally, these electrolytes were used in lithium-ion batteries (i.e. Li/NMC and LTO/NMC), demonstrating a clear relationship between the electrolyte formulation, its transport parameters and battery performance.


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