Data-Driven BEV Modeling for Realistic Consumption Calculation in Traffic Simulation

One of the major research and development efforts in the automotive industry worldwide is the introduction of new innovative and efficient electrified drivetrains to meet the increasing environmental, social and legal challenges of future individual mobility. Over the last few years Battery Electric Vehicles (BEVs) have become a growing alternative for internal combustion engine (ICE) vehicles. It is difficult however to estimate the actual power consumption performance of EVs in real world traffic scenarios. The chair of mechatronics has gathered real world data within the project PREMIUM from a fleet of BMW i3 Battery Electric Vehicles and in this paper a method for using this data to create a simulation model for the use in traffic simulation overcoming this problem is presented. SUMO (Simulation of Urban Mobility) is a portable open source simulator with multi-modal traffic feature capabilities. This work extends these capabilities by statistically analyzing the real-world data and deriving a respective mathematical model that is subsequently implemented into the software. Consequently, it is possible to simulate valid energy consumption profiles for a state-of-the-art BEV that is fully extendable and adaptable when further data is available.