Development strategies to satisfy corporate average CO₂ emission regulations of light duty vehicles (LDVs) in Korea
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Oh, Yunjung | - |
dc.contributor.author | Park, Junhong | - |
dc.contributor.author | Lee, Jong Tae | - |
dc.contributor.author | Seo, Jigu | - |
dc.contributor.author | Park, Sungwook | - |
dc.date.accessioned | 2021-07-30T04:58:42Z | - |
dc.date.available | 2021-07-30T04:58:42Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2016-11 | - |
dc.identifier.issn | 0301-4215 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/2505 | - |
dc.description.abstract | In the present study, we generated vehicle dynamic based light-duty vehicle (LDV) models and investigated some technical strategies in order to meet the corporate average CO₂ emission (CACE) regulations of Korea, which will be applied from 2016 to 2020. Seven types of LDV simulation models (including gasoline, diesel, and hybrid cars) were generated based on the AVL CRUISE program and the LDV sales ratio was used to estimate the CACE value of five companies in Korea. The prediction accuracy of the LDV models was validated using chassis dynamometer test data. Then, the effectiveness of the CACE reduction strategies was investigated based on the developed LDV simulation models. From the results of this study, it was revealed that all of the companies cannot satisfy the 2020 CACE regulation by just adopting a single strategy. In order to solve this problem, two types of CACE plans that combined several strategies (reducing the mass drag and fuel consumption rate, and adding a hybrid module, etc.) were proposed. After implementing the two types of CACE, plan, it was predicted that five companies will be able to satisfy the 2020 CACE regulation. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCI LTD | - |
dc.title | Development strategies to satisfy corporate average CO₂ emission regulations of light duty vehicles (LDVs) in Korea | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Sungwook | - |
dc.identifier.doi | 10.1016/j.enpol.2016.08.018 | - |
dc.identifier.scopusid | 2-s2.0-84983770975 | - |
dc.identifier.wosid | 000387300300011 | - |
dc.identifier.bibliographicCitation | ENERGY POLICY, v.98, pp.121 - 132 | - |
dc.relation.isPartOf | ENERGY POLICY | - |
dc.citation.title | ENERGY POLICY | - |
dc.citation.volume | 98 | - |
dc.citation.startPage | 121 | - |
dc.citation.endPage | 132 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Business & Economics | - |
dc.relation.journalResearchArea | Energy & Fuels | - |
dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
dc.relation.journalWebOfScienceCategory | Economics | - |
dc.relation.journalWebOfScienceCategory | Energy & Fuels | - |
dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
dc.relation.journalWebOfScienceCategory | Environmental Studies | - |
dc.subject.keywordPlus | ELECTRIC VEHICLES | - |
dc.subject.keywordPlus | FUEL CONSUMPTION | - |
dc.subject.keywordPlus | TRANSPORTATION | - |
dc.subject.keywordAuthor | Light-duty vehicles (LDVs) | - |
dc.subject.keywordAuthor | Corporate average CO₂ emission (CACE) | - |
dc.subject.keywordAuthor | Vehicle dynamic model | - |
dc.subject.keywordAuthor | Hybrid electric vehicle (HEV) | - |
dc.subject.keywordAuthor | Certified CO₂ emission rate | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0301421516304347?via%3Dihub | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1365
COPYRIGHT © 2021 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.