TY - JOUR A1 - Schweizer, Manuel A1 - Stöckl, Martin A1 - Tutunaru, Robin A1 - Holzhammer, Uwe T1 - Influence of heating, air conditioning and vehicle automation on the energy and power demand of electromobility JF - Energy Conversion and Management: X N2 - With the increasing number of electric vehicles in the transport sector, the relevance of accurate energy and power demand predictions of electromobility is growing. Thereby, different vehicle functions, especially heating and air conditioning and vehicle automation, have a significant influence. In accordance with the upcoming Euro-7 emissions standard, the energy consumption for heating even has to be contained in the manufacturer’s consumption data in the future. To increase the accuracy of energy and power demand predictions of electromobility, the energy consumption of vehicle functions such as heating and air conditioning as well as the energy savings through vehicle automation must be considered. This paper presents approaches for modeling and simulation the energy consumption of heating, air conditioning and vehicle automation which can be used as an extension of electric vehicles WLTP (Worldwide Harmonized Light-Duty Vehicles Test Procedure) consumption simulation on the level of vehicle classes. The Germany-wide results of the electric vehicles energy demand for heating and air conditioning on the level of NUTS3-areas (Nomenclature of territorial units for statistics) and vehicle classes show regionally different results and confirm the relevance of the research approach. Vehicle automation results are described on the level of the five SAE automation levels (Society of Automotive Engineers automation levels) and the vehicle classes. The approaches and results can be used for single vehicles or assumed vehicle fleets. UR - https://doi.org/10.1016/j.ecmx.2023.100443 KW - Energy system modelling KW - Electromobility KW - Heating and air conditioning KW - Vehicle automation KW - Energy demand KW - Power demand Y1 - 2023 UR - https://doi.org/10.1016/j.ecmx.2023.100443 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-38868 SN - 2590-1745 VL - 2023 IS - 20 PB - Elsevier CY - Amsterdam ER -