Paper Abstract and Keywords |
Presentation |
2018-11-13 13:50
A Study of Degradation Diagnosis of Lithium-ion Battery Using Neural Networks Masahito Arima, Lei Lin, Masahiro Fukui (Ritsumeikan Univ.) CAS2018-73 MSS2018-49 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The battery aggregation of lithium-ion battery is studied in order to solve the problem of output fluctuation and time maldistribution of renewable battery, for example, photovoltaic energy. It is necessary for the operational economic efficiency of lithium-ion battery to predict the charge-discharge energy by degradation diagnosis. In this study, we investigated the method of degradation diagnosis using neural networks and decrease the number of the charge-discharge times which needs to be carried out in advance. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Lithium-ion battery / Charge-discharge curve / degradation diagnosis / Econimic efficiency prediction / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 295, CAS2018-73, pp. 111-114, Nov. 2018. |
Paper # |
CAS2018-73 |
Date of Issue |
2018-11-05 (CAS, MSS) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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CAS2018-73 MSS2018-49 |
Conference Information |
Committee |
MSS CAS IPSJ-AL |
Conference Date |
2018-11-12 - 2018-11-13 |
Place (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
CAS |
Conference Code |
2018-11-MSS-CAS-AL |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A Study of Degradation Diagnosis of Lithium-ion Battery Using Neural Networks |
Sub Title (in English) |
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Keyword(1) |
Lithium-ion battery |
Keyword(2) |
Charge-discharge curve |
Keyword(3) |
degradation diagnosis |
Keyword(4) |
Econimic efficiency prediction |
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1st Author's Name |
Masahito Arima |
1st Author's Affiliation |
Ritsumeikan University (Ritsumeikan Univ.) |
2nd Author's Name |
Lei Lin |
2nd Author's Affiliation |
Ritsumeikan University (Ritsumeikan Univ.) |
3rd Author's Name |
Masahiro Fukui |
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Ritsumeikan University (Ritsumeikan Univ.) |
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Speaker |
Author-1 |
Date Time |
2018-11-13 13:50:00 |
Presentation Time |
25 minutes |
Registration for |
CAS |
Paper # |
CAS2018-73, MSS2018-49 |
Volume (vol) |
vol.118 |
Number (no) |
no.295(CAS), no.296(MSS) |
Page |
pp.111-114 |
#Pages |
4 |
Date of Issue |
2018-11-05 (CAS, MSS) |
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