Abstract
The article presents the concept of a predictive model of electric range changes of a refrigerated vehicle. The authors presented a literature analysis of the parameters affecting the range of an electric vehicle in terms of its drive. The analysis was supplemented with parameters influencing the energy consumption of the cooling device of the vehicle for the transport of refrigerated loads. On this basis, the main parameters that limit the range were selected and associated with geographic coordinates and the season and time of day. The proposed predictive model is implemented through a neural network extended by a knowledge base containing information on the topography of the area as well as weather and traffic statistics.
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