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Descripción
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| The limitation on the range of electric vehicles makes quite important to use an accurate energy consumption estimation tool. In general, estimations are based solely on the total distance, although it is known that the characteristics of the route and driving style influence significantly on energy consumption. In this paper, a tool that estimates the energy consumption of an electric vehicle in a city route taking into account such variables is shown, but without needing a deterministic knowledge of the characteristics of the vehicle or driving cycles. To do this, a neural network that takes as input data driving style and route variables is used. The validation results have been quite satisfactory to increase reliability in predicting consumption of the vehicle and enhance user confidence in the capabilities of electric vehicles. | |
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Internacional
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Si |
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Nombre congreso
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18th International IEEE Conference on Intelligent Transportation Systems - ITSC 2015 |
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Tipo de participación
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960 |
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Lugar del congreso
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Las Palmas |
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Revisores
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Si |
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ISBN o ISSN
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978-1-4673-6595-6 |
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DOI
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Fecha inicio congreso
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15/09/2015 |
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Fecha fin congreso
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18/09/2015 |
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Desde la página
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1 |
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Hasta la página
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8 |
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Título de las actas
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Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International Conference on |