In this paper we analyze which are the design options that would impact a free floating electric car sharing system performance and costs, studying how the system would scale with an increase in the intensity of the demand. We consider the case study of the city of Turin, for which we leverage hundred of thousands of actual rentals from a (combustion-based) car sharing system to derive an accurate demand model. Armed with this, we consider the transition to electric cars and the need to deploy a charging station infrastructure.Using a realistic simulator, we present the impact of system design options, like the number of charging poles, their allotment, and the number of cars. We first consider performance indicators, like fraction of satisfied demand and working hours system has to spend to bring to charge vehicles. Then we map these figures into revenues and costs, projecting economical indicators. At last, we investigate the scalability of the whole system, i.e., how performance and costs scale when the demand increases. Our results show that concentrating the charging stations in key places is instrumental to optimize car distribution in the city to better intercept the demand. Considering system scalability, the charging infrastructure must intuitively grow proportionally with the mobility demand. Interestingly instead, the fleet size can grow much slower, showing some nice economy of scale gains.

On Scalability of Electric Car Sharing in Smart Cities / Barulli, Michelangelo; Ciociola, Alessandro; Cocca, Michele; Vassio, Luca; Giordano, Danilo; Mellia, Marco. - (2020), pp. 1-8. ((Intervento presentato al convegno 2020 IEEE International Smart Cities Conference (ISC2) nel 28 Sept.-1 Oct. 2020 [10.1109/ISC251055.2020.9239086].

On Scalability of Electric Car Sharing in Smart Cities

Barulli, Michelangelo;Ciociola, Alessandro;Cocca, Michele;Vassio, Luca;Giordano, Danilo;Mellia, Marco
2020

Abstract

In this paper we analyze which are the design options that would impact a free floating electric car sharing system performance and costs, studying how the system would scale with an increase in the intensity of the demand. We consider the case study of the city of Turin, for which we leverage hundred of thousands of actual rentals from a (combustion-based) car sharing system to derive an accurate demand model. Armed with this, we consider the transition to electric cars and the need to deploy a charging station infrastructure.Using a realistic simulator, we present the impact of system design options, like the number of charging poles, their allotment, and the number of cars. We first consider performance indicators, like fraction of satisfied demand and working hours system has to spend to bring to charge vehicles. Then we map these figures into revenues and costs, projecting economical indicators. At last, we investigate the scalability of the whole system, i.e., how performance and costs scale when the demand increases. Our results show that concentrating the charging stations in key places is instrumental to optimize car distribution in the city to better intercept the demand. Considering system scalability, the charging infrastructure must intuitively grow proportionally with the mobility demand. Interestingly instead, the fleet size can grow much slower, showing some nice economy of scale gains.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2852620