Potentiometric Measurement to Probe Solvation Energy and Its Correlation to Lithium Battery Cyclability

2021 ◽  
Author(s):  
Sang Cheol Kim ◽  
Xian Kong ◽  
Rafael A. Vilá ◽  
William Huang ◽  
Yuelang Chen ◽  
...  
Keyword(s):  
Lithium Battery ◽  
Solvation Energy ◽  
Potentiometric Measurement

Diffraction analysis of the lithium battery cathode material Li1.2Mn0.4Ni0.3Co0.1O2

2007 ◽  
Vol 2007 (suppl_26) ◽  
pp. 483-488
Author(s):  
P. S. Whitfield ◽  
I. J. Davidson ◽  
P. W. Stephens ◽  
L. M. D. Cranswick ◽  
I. P. Swainson
Keyword(s):  
Cathode Material ◽  
Diffraction Analysis ◽  
Lithium Battery

High-rate non-aqueous lithium battery

1970 ◽  
Author(s):  
M. EISENBERG ◽  
K. WONG
Keyword(s):  
Lithium Battery ◽  
High Rate

Computational Parameters in Correlation Analysis: Gas-Water Distribution Coefficient

1999 ◽  
Vol 64 (11) ◽  
pp. 1727-1747 ◽  
Author(s):  
George R. Famini ◽  
Dalia Benyamin ◽  
Christina Kim ◽  
Rattiporn Veerawat ◽  
Leland Y. Wilson
Keyword(s):  
Correlation Analysis ◽  
Distribution Coefficient ◽  
Water Distribution ◽  
Solvation Energy ◽  
Linear Solvation Energy Relationships ◽  
Linear Solvation Energy Relationship ◽  
Energy Relationships ◽  
Linear Solvation Energy ◽  
Water Equilibrium ◽  
Linear Solvation

Theoretical linear solvation energy relationships (TLSER) combine computational molecular parameters with the linear solvation energy relationship (LSER) of Kamlet and Taft to characterize and predict properties of compounds. This paper examines the correlation of the gas-water equilibrium constant for 423 compounds with the TLSER parameters. Also, it describes new parameters designed to improve the TLSER information content.

scholarly journals Potentiometric measurement of membrane action potentials in frog muscle fibres

1966 ◽  
Vol 183 (1) ◽  
pp. 152-166 ◽  
Author(s):  
B. Frankenhaeuser ◽  
B. D. Lindley ◽  
R. S. Smith
Keyword(s):  
Action Potentials ◽  
Frog Muscle ◽  
Muscle Fibres ◽  
Membrane Action ◽  
Potentiometric Measurement

Organosulfide‐Based Deep Eutectic Electrolyte for Lithium Battery

2021 ◽  
Author(s):  
Jiahan Song ◽  
Yubing Si ◽  
Wei Guo ◽  
Donghai Wang ◽  
Yongzhu Fu
Keyword(s):  
Lithium Battery

scholarly journals Estimation of the Hot Swap Circulation Current of a Multiple Parallel Lithium Battery System with an Artificial Neural Network Model

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1448
Author(s):  
Nam-Gyu Lim ◽  
Jae-Yeol Kim ◽  
Seongjun Lee
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Lithium Battery ◽  
Battery Pack ◽  
Battery Management ◽  
Ann Model ◽  
Battery System ◽  
Load Current ◽  
Circulating Current ◽  
Artificial Neural

Battery applications, such as electric vehicles, electric propulsion ships, and energy storage systems, are developing rapidly, and battery management issues are gaining attention. In this application field, a battery system with a high capacity and high power in which numerous battery cells are connected in series and parallel is used. Therefore, research on a battery management system (BMS) to which various algorithms are applied for efficient use and safe operation of batteries is being conducted. In general, maintenance/replacement of multi-series/multiple parallel battery systems is only possible when there is no load current, or the entire system is shut down. However, if the circulating current generated by the voltage difference between the newly added battery and the existing battery pack is less than the allowable current of the system, the new battery can be connected while the system is running, which is called hot swapping. The circulating current generated during the hot-swap operation is determined by the battery’s state of charge (SOC), the parallel configuration of the battery system, temperature, aging, operating point, and differences in the load current. Therefore, since there is a limit to formulating a circulating current that changes in size according to these various conditions, this paper presents a circulating current estimation method, using an artificial neural network (ANN). The ANN model for estimating the hot-swap circulating current is designed for a 1S4P lithium battery pack system, consisting of one series and four parallel cells. The circulating current of the ANN model proposed in this paper is experimentally verified to be able to estimate the actual value within a 6% error range.

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