Forecasting emerging technologies of low emission vehicle

The aim of this paper is to propose a patent search strategy in the case of emerging technology fields and to study the development patterns of the low emission vehicle (LEV) technologies. An Automatic Patent Classification (APC) system has been developed based on text mining techniques to facilitate the patent retrieval process. The data was collected from the Global Patent Index (GPI) database, and interviews were conducted to involve experts' opinions. The technology forecasting method utilized the collected patent data to define the technological life cycles of LEV technology. The growth curves estimates steady growth in LEV technologies including hybrid and battery electronic vehicles, and appar- ently reaching the saturation point in few decades is inevitable. Plus, patenting activity of hydrogen fuel cell vehicle technology was experiencing the infancy period so far, and further it is anticipated to reach higher growth rate in line with other energy alternatives. The proposed method can help patent researchers in terms of retrieving accurate patents based on their technology target. Moreover, the technology forecasting techniques provide an insight to investors, assisting them to allocate their resources properly. The results can benefit car industry stakeholders to anticipate the most promising technology areas in an uncertain dynamic marke