TY  - CHAP
A1  - Leise, Philipp
A1  - Altherr, Lena
A1  - Simon, Nicolai
A1  - Pelz, Peter F.
T1  - Finding global-optimal gearbox designs for battery electric vehicles
T2  - Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019
N2  - In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements.
KW  - Powertrain
KW  - Gearbox
KW  - Optimization
KW  - BEV
KW  - WLTP
Y1  - 2019
SN  - 978-3-030-21802-7
U6  - http://dx.doi.org/10.1007/978-3-030-21803-4_91
SP  - 916
EP  - 925
PB  - Springer
CY  - Cham
ER  -