Abstract
City bus transport electrification has a strong potential of improving city air quality, reducing noise pollution and increasing passenger satisfaction. Since the city bus operation is rather deterministic and intermittent, the driving range- and charging-related concerns may be effectively overcome by means of fast charging at end stations and/or slow charging in depot. In order to support decision making processes, a simulation tool for planning of city bus transport electrification has been developed and it is presented in this paper. The tool is designed to use real/recorded driving cycles and techno-economic data, in order to calculate the optimal type and number of e-buses and chargers, and predict the total cost of ownership including investment and exploitation cost. The paper focuses on computationally efficient e-bus fleet simulation including powertrain control and charging management aspects, which is illustrated through main results of a pilot study of bus transport electrification planning for the city of Dubrovnik.
Highlights
Due to environmental concerns, there is a strong tendency of electrifying road transport systems by means of introducing different types of electric vehicles [1]
The simulated electricity consumptions of plug-in hybrid electric vehicles (PHEV)- and BEV-type buses are close to recorded ones documented in the ZeEUS project report [25] for Volvo 7900 bus series (Table 3)
In the PHEV case, the simulated fuel consumption is by 30% higher than the ZeEUS recorded one, but this discrepancy is compensated for by 26% higher recorded electricity consumption when compared to the simulated one
Summary
There is a strong tendency of electrifying road transport systems by means of introducing different types of electric vehicles [1]. To the best of the authors’ knowledge, studies dealing with extensive virtual simulations of different e-bus-type fleets based on real-life driving cycles and concerning spatially-distributed charging management and related TCO analyses have not been considered in the literature far. The tool consists of four modules aimed at (i) post-processing and statistical analysis of a large set of recorded driving cycles, (ii) simulation of conventional (CONV) and different types of e-buses (HEV, PHEV and BEV), (iii) virtual simulation of e-bus fleets over recorded driving cycles including user-defined setting of charging station locations and charging management itself and (iv) techno-economic analyses.
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