Application of artificial intelligence in internal combustion engines – bibliometric analysis on progress and future research priorities

Abstract

Artificial intelligence (AI) techniques are increasingly used in internal combustion engines (ICEs) and hybrid electric vehicles (HEV) research, mainly for pre-diction, control, optimization, and classification task. The present study is a bibliometric-based review involving analyzing 1,800 documents using VOSviewer (v1.6.19) and Excel sourced from the Scopus database between 2014 and 2023. The VOSviewer methodology involved importing bibliographic data to analyze the most prolific countries, authors and construct co-occurrences of keywords. The most influential publication was attributed to Das, H.S.; Li, S.; Rahman, M. M. and Tan, C. W. with the highest number of citations of 446, published in 2020. Applied Energy emerges as the most prolific journal, with 1508 citations across 34 documents. Similarly, the United States, leading with 298 publications, also has the highest number of citations at 4118. China follows closely, with 262 publications and 3667 citations, securing the second position. Italy ranks third, contributing 149 publications that garnered 2236 citations. The keyword analysis portrayed that the emerging trend was found to correlate majorly with ‘machine learning algorithms’, ‘hybrid electric vehicles’, ‘control’ and ‘multi-objective optimization’.