The impact of Artificial Intelligence (AI) on different sectors, including railways, is now widely recognized. This paper shares the findings of a comprehensive literature review on how AI affects regenerative braking in railway transportation. The review focuses on various areas of regenerative braking, such as energy storage system, timetabling, and reversible substation.
In the literature review, it was found that 57 scientific papers were published from 2017 to December 2022. The majority of these papers, specifically 70.2%, utilized AI to optimize the effectiveness of regenerative braking. However, the use of AI in reversible substation and a combination of methods for regenerative braking is still limited, even though several methods exist. With the continuous development of new AI innovations, it is anticipated that new strategies will be created to enhance energy efficiency in regenerative braking, particularly in rail transportation.
Keywords: Artificial Intelligence, Regenerative Braking, Railway.
