Technological evolution of internal combustion engine vehicle: A patent data analysis

Tiago Sinigaglia, Mario Eduardo Santos Martins and Julio Cezar Mairesse Siluk

Applied Energy, 2022, vol. 306, issue PA, No S0306261921013052

Abstract: Current mobility is highly dependent on fossil fuels which are the energy vectors of internal combustion engines, which power more than 99% of all road vehicles. In order to reduce pollutant emissions from ever growing urban centers, electric vehicles have emerged and their importance is growing steeply. However, these still face several problems regarding energy supply, storage and production, as well as life-cycle CO2 emissions. Nevertheless, there is a large fleet of vehicles with a vast majority of combustion-based power plants that need to be improved for a proper transition to total electrification. Therefore, it is essential that the remaining internal combustion engines become more efficient and sustainable energy conversion devices. For policy and business decision makers, understanding the trends of evolution is essential to making appropriate decisions. Thus, this study aimed at mapping the technological evolution of internal combustion engine and at understanding the main trends through patent data. The current stage of technological maturity was determined through a Logistics model, and the subtechnologies with the greatest potential for development and diffusion were analyzed. The search for the data was performed through Questel Orbit platform, in the United States Patent Trademark Office database. In 2018, internal combustion engine had a technological maturity rate of 81.77%. The subtechnologies that have the highest diffusion speed, among those compared, are: friction loss (32.14), water injection (21.05) and hybrid technology (20.88). It is forecast that internal combustion engines have approximately 27 years of estimated remaining time for saturation in the number of patent families.

Keywords: Internal combustion engine; Patent analysis; Technology monitoring; Technology diffusion speed; Logistic model (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (8)

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DOI: 10.1016/j.apenergy.2021.118003

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