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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 30, Number 3(2) (2018)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 551-558
S&M1517 Research Paper of Special Issue https://doi.org/10.18494/SAM.2018.1825 Published: March 23, 2018 Research on the Prediction of the State-of-health of Starting Batteries of Diesel Engines [PDF] Tung-Chou Lin and Liang-Ruei Chen (Received November 12, 2017; Accepted December 19, 2017) Keywords: state-of-health, AC impedance, sensing system, linear regression
A study of state-of-health (SOH) prediction for diesel engine generator starting batteries is presented, the main purpose of which is to analyze the battery’s state using the relationship between AC impedance and voltage. A sensing system capable of detecting battery open-circuit voltage and discharge current has been designed. The respective AC impedances at 100 and 50% battery SOH were obtained from a monitoring system, and linear regression was used to predict battery SOH. A new GS GTX7A-12B lead acid battery was used in the experiments and the results showed that there was a 11.265% difference between the actual battery SOH and that predicted by linear regression.
Corresponding author: Tung-Chou Lin Cite this article Tung-Chou Lin and Liang-Ruei Chen, Research on the Prediction of the State-of-health of Starting Batteries of Diesel Engines, Sens. Mater., Vol. 30, No. 3, 2018, p. 551-558. |
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