Efficient design of an operation profile for wireless charging electric tram systems. (January 2019)

• Record Type: Journal Article
• Authors: Ko, Young Dae; Jang, Young Jae
• Is Part Of: Computers & industrial engineering. Volume 127(2019)
• Page Start: 1193
• Page End: 1202
• Publication Date: 2019-01
• Subjects: Mathematical model -- Wireless charging -- Electric tram -- Operation profile -- Operations research -- Regenerative braking; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2018.03.042
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: This study introduces the innovative wireless charging electric tram system. A method for designing an operational profile (velocity) of the tram system is presented. The optimization method considers to evaluate the optimal size of battery of the tram. Genetic algorithm is designed to optimally design the operation profile. Numerical case study validates the method and approach. Abstract: Recently, electric trams have been used as an eco-friendly mode of transport in urban areas. Of the various types of electric trams, this study deals with wireless charging electric trams. A wireless charging electric tram can draw electricity wirelessly from a wireless charging infrastructure installed on a railway line and store any excess electricity in its battery. Therefore, we can eliminate the power supply line of conventional electric trams and use smaller batteries than those necessary for battery-powered electric trams. Even when two wireless charging electric trams are operated for the same amount of time, their electricity consumption rates may differ depending on their speed, acceleration, and time spent at stations. Therefore, this study deals with the efficient design of an operation profile (velocity) for wireless charging electric trams that can minimize variations in the battery charge according to electricity consumption, considering the installed wireless charging infrastructure. Mathematical model–based optimization is adopted to derive an efficient design for the operation profile, and an appropriate solution procedure is proposed considering the features of the developed mathematical model. The proposed model and solution procedure are tested using data from Pangyo, Gyeonggi Province, Korea.