The dataset of Japanese patents and patents’ holding firms in green vehicle powertrains field

Jiaming Jiang, Kensuke Baba, Yu Zhao, Junshi Feng, Sou Kumagai

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


In 2020, the Government of Japan declared “2050 carbon neutral” and launched a long-term strategy to create a “virtuous cycle of economy and environment”. Japanese firms possess many technologies that contribute to decarbonization, which is important to expand investment for Green Technology (environmental technology) development. As automobiles are major contributors to greenhouse gas emissions [1], the technological shift towards vehicle powertrain systems is an attempt to lower problems like emissions of carbon dioxide, nitrogen oxides [2]. On the other hand, patent data are the most reliable business performance for applied research and development activities when investigating the knowledge domains or the technology evolution (Wand, 1997). Our paper describes a Japanese patents dataset of the vehicle powertrain systems for hybrid electric vehicle (HEV), battery electric vehicle (BEV) and fuel cell electric vehicles (FCEV). In this paper we create a method of bombinating international patent classification (IPC) and keywords to define “green” patents in vehicle powertrains field, using patent data which were applied to Japan Patent Office recorded on EPO's PATSTAT database during 2010∼2019 year. When analyze patents, it is necessary to consider the social situation of each country including language background, we collect patents description documents (abstracts and titles) not only written in English but also in Japanese. Finally, we build a database includes 6025 green patents’ description documents and 266 patents’ holding firms. With which we then identify 3756 HEV patents, 1716 BEV patents, and 553 FCEV patents. Data about patent holding firms is also appended. The full dataset may be useful to researchers who would like to do further search like natural language processing and machine learning on patent description documents, statistical data analysis for empirical economics.

Original languageEnglish
Article number108524
JournalData in Brief
Publication statusPublished - Oct 2022


  • Battery electric vehicle
  • Fuel cell electric vehicles
  • Green innovation
  • Hybrid electric vehicle
  • Patents
  • Vehicle powertrain

ASJC Scopus subject areas

  • General


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