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    A new predictive electric bus model using big data for estimating battery pack capacity
    (Landesmesse Stuttgart GmbH, 2017) Yirik, Emrah; Irmak, Umut; Dericioglu, Cagla; Unal, Erdem; Cuma, Mehmet Ugras
    This paper describes a new predictive neural network model for electric buses by using big data analysis tools. Electric buses are often used for public transportation with many routes. Each route in a city has different parameters such as length, elevation, number of bus stops, traffic density which determines battery pack capacity. Moreover average number of passengers and ambient temperature are other important parameters that must be considered. In this paper, a new predictive model for electric buses is proposed using aforementioned parameters. To develop the model, the study takes the advantages of the Big Data Analysis tools by gathering the data from real vehicles. © 2017 MOBI - Mobility, Logistics and Automotive Technology Research Centre.