A morphological and energy-dispersive x-ray spectroscopy (EDS) investigation of separator-grade cellophane

1994 ◽  
Vol 52 ◽  
pp. 430-431
Author(s):  
Michael E. Rock ◽  
Vern Kennedy ◽  
Bhaskar Deodhar ◽  
Thomas G. Stoebe
Keyword(s):  
Extrusion Process ◽  
Morphological Characterization ◽  
Energy Dispersive ◽  
Regenerated Cellulose ◽  
Battery System ◽  
X Ray ◽  
Functional Differences ◽  
Transmission Electron ◽  
Separator Material ◽  
Underwater Target

Cellophane is a composite polymer material, made up of regenerated cellulose (usually derived from wood pulp) which has been chemically transformed into "viscose", then formed into a (1 mil thickness) transparent sheet through an extrusion process. Although primarily produced for the food industry, cellophane's use as a separator material in the silver-zinc secondary battery system has proved to be another important market. We examined 14 samples from five producers of cellophane, which are being evaluated as the separator material for a silver/zinc alkaline battery system in an autonomous underwater target vehicle. Our intent was to identify structural and/or chemical differences between samples which could be related to the functional differences seen in the lifetimes of these various battery separators. The unused cellophane samples were examined by transmission electron microscopy (TEM) and energy dispersive X-ray spectroscopy (EDS). Cellophane samples were cross sectioned (125-150 nm) using a diamond knife on a RMC MT-6000 ultramicrotome. Sections were examined in a Philips 430-T TEM at 200 kV. Analysis included morphological characterization, and EDS (for chemical composition). EDS was performed using an EDAX windowless detector.

A HIGH ENERGY DENSITY ZINC/OXYGEN BATTERY SYSTEM

1966 ◽  
Author(s):  
S. CHODOSH ◽  
E. KATSOULIS ◽  
M. ROSANSKY
Keyword(s):  
Energy Density ◽  
High Energy ◽  
High Energy Density ◽  
Battery System

MATLAB MODELLING AND SIMULATION OF RECONFIGURABLE SOLAR CONVERTER: A SINGLE-STAGE POWER CONVERSION PV-BATTERY SYSTEM

2019 ◽  
Vol 12 (4) ◽  
pp. 30
Author(s):  
POTDAR AMARDEEP ◽  
GHUTKE PRATIK ◽  
POTDAR DISHA ◽  
TEKALE ANIL ◽  
◽  
...  
Keyword(s):  
Power Conversion ◽  
Modelling And Simulation ◽  
Single Stage ◽  
Battery System

ADAPTIVE ALGORITHMS OF CONTROLLING THE SMART LI-ION BATTERY CONTROLLER

2018 ◽  
pp. 104-110
Author(s):  
I. A. Borovoy ◽  
O. V. Danishevskiy ◽  
A. V. Parfenov
Keyword(s):  
Power Supply ◽  
Power Supply System ◽  
Electric Energy ◽  
Lithium Ion ◽  
Control Device ◽  
Control Algorithms ◽  
Battery System ◽  
Electronic Control Device ◽  
Li Ion ◽  
Cell Balancing

The article substantiates the necessity of organizing the control system of modern lithium-ion batteries. Passive and active methods of cell balancing are described. The method of increase of efficiency of modes of accumulation of electric energy by means of the special electronic control device (the intellectual controller) and its further use for power supply of the functional equipment is considered. The structure of the intelligent controller as a part of the autonomous power supply system with the description of its main functional units and purpose is presented. Practical results of application in the intellectual controller of original adaptive control algorithms defining modes of operation of lithium-ion drives depending on various environmental conditions are resulted. The results of the analysis obtained by the results of experimental operation of the battery system, reflecting the qualitative and quantitative advantages of the proposed method.

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.

Sign in / Sign up

Export Citation Format

Share Document