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关于内燃机汽车(ICEV)、混合动力汽车(HEV)和纯电动汽车(BEV)的车辆动力系统的全球专利数据集。

The global patents dataset on the vehicle powertrains of ICEV, HEV, and BEV.

作者信息

Mirzadeh Phirouzabadi Amir, Savage David, Blackmore Karen, Juniper James

机构信息

Faculty of Law & Business, The University of Newcastle, 409 Hunter Street, Newcastle NSW 2300 Australia.

School of Electrical Engineering and Computing, The University of Newcastle, University Drive, Callaghan NSW 2308 Australia.

出版信息

Data Brief. 2020 Jul 20;32:106042. doi: 10.1016/j.dib.2020.106042. eCollection 2020 Oct.

Abstract

Patent bibliometrics data are the most reliable business performance metric for applied research and development activities when investigating the knowledge domains or the technological evolution of vehicle powertrain technologies in the automotive industry. Our paper describes a global patents dataset for the internal combustion engine vehicles (ICEV), hybrid electric vehicles (HEV) and battery electric vehicles (BEV) over 1985-2016. We extracted the patents granted in each powertrain field from Thomson Reuters' Derwent Innovations Index (DII). We applied a combined search strategy of international patent classifications (IPCs) and keywords as well as 'patent families' and 'priority dates' to construct our global patents dataset. This strategy returned a total of 78,732 patents, within which we identified 49,154 ICEV patents; 10,888 HEV patents; and 18,690 BEV patents. Our database includes numerous descriptive features of each patent such as title, abstract, claim, priority, application and publication dates, IPCs, assignees/applicants, inventors, and cited references. These data are associated with the research article 'The evolution of dynamic interactions between the knowledge development of powertrain systems' [1]. The full dataset, which is attached to this article, may be useful to both researchers and practitioners interested in investigating, modelling or forecasting the complexity and evolution of the technical and knowledge domains of the vehicle powertrains, across a variety of instruments such as social network analysis and regression models.

摘要

在研究汽车行业车辆动力总成技术的知识领域或技术演变时,专利文献计量数据是应用研究与开发活动中最可靠的商业绩效指标。我们的论文描述了1985年至2016年期间内燃机车辆(ICEV)、混合动力电动汽车(HEV)和电池电动汽车(BEV)的全球专利数据集。我们从汤森路透的德温特创新索引(DII)中提取了每个动力总成领域授予的专利。我们应用了国际专利分类(IPC)、关键词以及“专利家族”和“优先权日期”的组合搜索策略来构建我们的全球专利数据集。该策略共返回78732项专利,其中我们识别出49154项ICEV专利;10888项HEV专利;以及18690项BEV专利。我们的数据库包括每项专利的众多描述性特征,如标题、摘要、权利要求、优先权、申请和公布日期、IPC、受让人/申请人、发明人以及被引用参考文献。这些数据与研究论文《动力总成系统知识发展之间动态相互作用的演变》[1]相关。本文所附的完整数据集可能对有兴趣通过社会网络分析和回归模型等各种工具研究、建模或预测车辆动力总成技术和知识领域的复杂性与演变的研究人员和从业者都有用。

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