engleski

Data-driven Approaches for e-Mobility: Range Anxiety, Vehicle Data Simulation, and Contextual Routing

The transportation sector is considered as one of the main contributors to the overall global greenhouse gas emissions. One of the possibilities to overcome this problem is so- called e-Mobility, i.e. the development of electric vehicles (EVs). Even though EVs gained an increase in popularity over the past few years they are still not widely used. Current trends in electromobility, auto-motive industry, research regarding alternative fueled vehicles (AFV), as well as the constantly increasing environmental concerns suggest that the transition from traditional internal combustion engine (ICE) vehicles to electric vehicles (EVs) is inevitable. There is still one major obstacle for EVs to reach their full market potential, a phenomenon known as the range anxiety, a fear of running out of electricity before reaching another available charging station. EVs generate big amount of data that can be collected and analyzed in order to achieve high performance EV smart routing. In case of insufficient amount of data, it can be simulated based on the data collected from the real word. In continuation, some interesting and important challenges and data-driven approaches in the field of EVs will be mentioned.

e-Mobility ; Data ; Simulations ; Range Anxiety ; Vehicle Routing

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