Dataset for Predictive Models of Energy Expenditure of Electric Delivery Vehicles in Urban Service Enterprises

The purpose of this dataset is to enable the replication of the research results presented in the article: 
Izdebski Mariusz, Jacyna Marianna: Predictive Models of Energy Expenditure of Electric Delivery Vehicles in Urban Service Enterprises, Proceedings of the 14th Asia-Pacific Conference on Transportation and the Environment (APTE 2025) / Xiaobo Qu [i in.] (red.), 2025, Atlantis Press, s.199-211, ISBN 978-94-6463-972-8. DOI:10.2991/978-94-6463-972-8_19 - published online: 29 December 2025, which discusses the development of models designed to forecast the energy consumption of electric vehicles used in urban service enterprises. The aim of the study was to identify the most suitable type of predictive model for estimating the energy demand of electric delivery vehicles.

Dataset contains:

• Readme.txt: description of the dataset
• InputData.xlsx: contains the input data used in the model
• Multi_regresion_model.xlsx: contains the output data from the multiple regression model
• neural_network.xlsx: contains the output data from the neural network

The dataset was created as part of the E-Laas project (Energy optimal urban logistics As A Service).
Project implemented as part of the call ERA-NET Cofund Urban Accessibility and Connectivity (ENUAC China Call) organized by JPI Urban Europe and the National Natural Science Foundation of China (NSFC). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875022.
 E-Laas project is carried out in an international consortium. Project coordinator in Europe: Chalmers University of Technology (Sweden), project coordinator in China: Shanghai University (China), consortium members: Tsinghua University (China), Warsaw University of Technology (Poland), cooperation partners: Stockholms stad, Trafikkontoret (Sweden), ParkUnload (Spain), Metropolis GZM (Poland), Shanghai Urban-Rural Construction and Transportation Department (China), Volvo Group Trucks Technology and Operations (Sweden).
- The Chinese part of the project is funded by National Natural Science Foundation of China.
- The Swedish part of the project is funded by Swedish Energy Agency.
- The Polish part of the project is funded by the National Science Centre, Poland (project no. 2022/04/Y/ST8/00134). The value of the co-financing is PLN 878,107.00. Project duration 27/04/2023 - 26/04/2026 (36 months).