TY - GEN
T1 - An Open-Source Modular Quasi-Static Longitudinal Simulation for Full Electric Vehicles
AU - Konig, Adrian
AU - Nicoletti, Lorenzo
AU - Kalt, Svenja
AU - Muller, Korbinban
AU - Koch, Alexander
AU - Lienkamp, Markus
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/10
Y1 - 2020/9/10
N2 - Battery electric vehicles (BEVs) are becoming more and more important for customers and manufacturers because they are locally emission-free and help companies to comply with increasingly strict regulations. However, electrification leads to a change in the vehicle as we know it from the last decades. The small machine and the big and heavy energy storage challenge manufacturers in developing cars with similar properties like internal combustion vehicles. Therefore, engineers use virtual tools to find optimal solutions in terms of package, performance, and efficiency in the very early stage of the development process. One of those tools is the longitudinal dynamic simulation that is used for sizing the battery and powertrain. In this paper, the authors present a longitudinal dynamic simulation with a low computing time, which helps the user to estimate acceleration, maximum speed, and energy consumption of a full-electric vehicle. The efficiency diagrams for the electric machines are computed by an electric machine design tool instead of scaling one diagram. Both the longitudinal simulation and the efficiency diagrams tools will be provided open source to make it usable for the scientific community and improve it over time.
AB - Battery electric vehicles (BEVs) are becoming more and more important for customers and manufacturers because they are locally emission-free and help companies to comply with increasingly strict regulations. However, electrification leads to a change in the vehicle as we know it from the last decades. The small machine and the big and heavy energy storage challenge manufacturers in developing cars with similar properties like internal combustion vehicles. Therefore, engineers use virtual tools to find optimal solutions in terms of package, performance, and efficiency in the very early stage of the development process. One of those tools is the longitudinal dynamic simulation that is used for sizing the battery and powertrain. In this paper, the authors present a longitudinal dynamic simulation with a low computing time, which helps the user to estimate acceleration, maximum speed, and energy consumption of a full-electric vehicle. The efficiency diagrams for the electric machines are computed by an electric machine design tool instead of scaling one diagram. Both the longitudinal simulation and the efficiency diagrams tools will be provided open source to make it usable for the scientific community and improve it over time.
KW - BEV
KW - electric machines
KW - longitudinal dynamics simulation
KW - powertrain design
UR - http://www.scopus.com/inward/record.url?scp=85096646992&partnerID=8YFLogxK
U2 - 10.1109/EVER48776.2020.9242981
DO - 10.1109/EVER48776.2020.9242981
M3 - Conference contribution
AN - SCOPUS:85096646992
T3 - 2020 15th International Conference on Ecological Vehicles and Renewable Energies, EVER 2020
BT - 2020 15th International Conference on Ecological Vehicles and Renewable Energies, EVER 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Ecological Vehicles and Renewable Energies, EVER 2020
Y2 - 10 September 2020 through 12 September 2020
ER -