Impact of topographic data on electric vehicle energy prediction

Purpose. To assess the impact of sampling frequency and topographic data sources on the accuracy of electric vehicle (EV) driving energy consumption calculations using standardized test protocols. Methodology. The study calculates the driving energy consumption of an EV based on a theoretical model that incorporates the topographic profile of the route and the driving mode defined by the selected test protocol. The analysis was conducted for several alternative paths of the same route along European roads under varying discretization steps and topographic data sources. Findings. It was established that the sampling frequency and accuracy of topographic data significantly affect the results of energy consumption calculations. A range of discretization steps ensuring acceptable accuracy while reducing computational load was identified. Errors for different data sources were quantified depending on the characteristics of the route’s topographic profile. Originality. The study establishes the relationship between the accuracy of electric vehicle driving energy calcula-tions and both the sampling frequency and the selected topographic data source, taking into account topographic profile. Threshold conditions were identified under which increasing the discretization step or using less accurate datasets does not lead to significant errors. Practical value. The obtained results enable a well-grounded selection of the optimal discretization step and topographic data source to improve the accuracy of energy consumption forecasting for passenger EVs during route planning.