NDLI: The Estimation of the Capacity of Lead-Acid Storage Battery Using Artificial Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Chao-Rong Chen Kuo-Hua Huang Hsiang-Chung Teng
Copyright Year	2006
Description	Author affiliation: Nat. Taipei Univ. of Technol., Taipei (Chao-Rong Chen; Hsiang-Chung Teng)
Abstract	The capacity of lead-acid storage battery for communication system has been long estimated by constant current discharge method in the past. It spends a lot of time and labor and wastes more energy. This paper proposes a new method combining the measured data of battery discharge and the back-propagation neural network. After they are trained and learned, the back-propagation neural network can estimate the capacity of lead-acid storage battery after half hour discharge test. Therefore, the advantages of this paper are less discharge time of storage battery, less working hour and saving energy. The practical results show that the method has good performances.
Starting Page	1575
Ending Page	1579
File Size	2689900
Page Count	5
File Format	PDF
ISBN	1424400996
DOI	10.1109/ICSMC.2006.384942
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-08
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Batteries Artificial neural networks Voltage Electrodes Power supplies Lead compounds Dielectrics and electrical insulation Neural networks Gravity Cybernetics Lead-Acid Storage Battery Back-propagation Artificial neural network (BP ANN) Battery Capacity
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Non-conventional Transformers Cost Estimation Using Neural Network

Estimating the weight of main material for 63/20kV transformers with Artificial Neural Network (ANN)

Prediction of lead-acid storage battery's remaining capacity based on LM-BP neural network

SOC estimation algorithm of power lithium battery based on AFSA-BP neural network

Modeling of lead-acid battery capacity loss in a photovoltaic application

Artificial neural network for transformer insulation aging diagnosis

Online State-of-Health Estimation of Lithium-Ion Battery Based on Incremental Capacity Curve and BP Neural Network

A neural networks based controller for Electron Beam welding power supply

Control of battery storage to improve voltage profile in autonomous microgrid

The Estimation of the Capacity of Lead-Acid Storage Battery Using Artificial Neural Networks

Similar Documents

Non-conventional Transformers Cost Estimation Using Neural Network

Estimating the weight of main material for 63/20kV transformers with Artificial Neural Network (ANN)

Prediction of lead-acid storage battery's remaining capacity based on LM-BP neural network

SOC estimation algorithm of power lithium battery based on AFSA-BP neural network

Modeling of lead-acid battery capacity loss in a photovoltaic application

Artificial neural network for transformer insulation aging diagnosis

Online State-of-Health Estimation of Lithium-Ion Battery Based on Incremental Capacity Curve and BP Neural Network

A neural networks based controller for Electron Beam welding power supply

Control of battery storage to improve voltage profile in autonomous microgrid

The Estimation of the Capacity of Lead-Acid Storage Battery Using Artificial Neural Networks