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https://doi.org/10.13044/j.sdewes.2014.02.0018

Modelling Inductive Charging of Battery Electric Vehicles using an Agent-Based Approach

Zain Ul Abedin ; Department of Transportation and Traffic Engineering TUM CREATE, Singapore
Rashid Ahmed Waraich ; Institute for Transport Planning and Systems ETH Zurich, Switzerland


Puni tekst: engleski pdf 723 Kb

str. 219-233

preuzimanja: 476

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Sažetak

The introduction of battery electric vehicles (BEVs) could help to reduce dependence on fossil fuels and emissions from transportation and as such increase energy security and foster sustainable use of energy resources. However a major barrier to the introduction of BEVs is their limited battery capacity and long charging durations. To address these issues of BEVs several solutions are proposed such as battery swapping and fast charging stations. However apart from these stationary modes of charging, recently a new mode of charging has been introduced which is called inductive charging. This allows charging of BEVs as they drive along roads without the need of plugs, using induction. But it is unclear, if and how such technology could be utilized best. In order to investigate the possible impact of the introduction of such inductive charging infrastructure, its potential and its optimal placement, a framework for simulating BEVs using a multi-agent transport simulation was used. This framework was extended by an inductive charging module and initial test runs were performed. In this paper we present the simulation results of these preliminary tests together with analysis which suggests that battery sizes of BEVs could be reduced even if inductive charging technology is implemented only at a small number of high traffic volume links. The paper also demonstrates that our model can effectively support policy and decision making for deploying inductive charging infrastructure.

Ključne riječi

Inductive charging; Battery electric vehicles; Agent-based modelling

Hrčak ID:

126189

URI

https://hrcak.srce.hr/126189

Datum izdavanja:

30.9.2014.

Posjeta: 1.272 *