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PARAMETRIC MODELLING OF WEIGHT AND VOLUME EFFECTS IN BATTERY ELECTRIC VEHICLES, WITH FOCUS ON THE GEARBOX

Published online by Cambridge University Press:  27 July 2021

Lorenzo Nicoletti ,
Peter Köhler ,
Adrian König ,
Maximilian Heinrich  and
Markus Lienkamp
Lorenzo Nicoletti*
Affiliation:
Technical University of Munich
Peter Köhler
Affiliation:
Technical University of Munich
Adrian König
Affiliation:
Technical University of Munich
Maximilian Heinrich
Affiliation:
AUDI AG
Markus Lienkamp
Affiliation:
Technical University of Munich
*
Nicoletti, Lorenzo, Technical University of Munich, Institute of Automotive Technology, Germany, nicoletti@ftm.mw.tum.de

Abstract

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The modeling of battery electric vehicles (BEVs) still represents a challenge for vehicle manufacturers. The installation of the new types of components needed for BEVs gives rise to uncertainties in the quantification of parameters like the vehicle's weight. Indeed, vehicle weight plays a key role, since it has a drastic effect on the vehicle's range, which is an important selling point for BEVs. Uncertainties in weight estimation create weight fluctuations during the early development phase and the need to resize components like the electric machine or battery. This in turn affects the components' volume and weight. However, such resizing can also lead to component collision and unfeasibility of the vehicle architecture. To solve this problem and to support concept engineers during the early development phase, an iterative approach is required that is capable of estimating weight and volume fluctuations in the relevant components. The approach should also consider the geometrical interdependencies of the components, to ensure that no collisions occur between them. Taking the gearbox as an example application, this paper presents a novel approach that satisfies these requirements.

Keywords

Battery electric vehiclesParametric modelingDesign engineeringProduct architectureOptimisation
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 2389 - 2398
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

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