An Estimation of the Lightweight Potential of Battery Electric Vehicles

Lorenzo Nicoletti, Andrea Romano, Adrian König, Peter Köhler, Maximilian Heinrich and Markus Lienkamp
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Lorenzo Nicoletti: Department of Mechanical Engineering, School of Engineering and Design, Technical University of Munich, Boltzmannstr. 15, 85748 Garching, Germany
Andrea Romano: Technical University of Munich, Boltzmannstr. 15, 85748 Garching, Germany
Adrian König: Department of Mechanical Engineering, School of Engineering and Design, Technical University of Munich, Boltzmannstr. 15, 85748 Garching, Germany
Peter Köhler: Technical University of Munich, Boltzmannstr. 15, 85748 Garching, Germany
Maximilian Heinrich: Audi AG, I-EG/A22 Konzeptauslgung Baukasten/Plattform Elektrifiziert, 85055 Ingolstadt, Germany
Markus Lienkamp: Department of Mechanical Engineering, School of Engineering and Design, Technical University of Munich, Boltzmannstr. 15, 85748 Garching, Germany

Energies, 2021, vol. 14, issue 15, 1-29

Abstract: Although battery electric vehicles (BEVs) are locally emission-free and assist automakers in reducing their carbon footprint, two major disadvantages are their shorter range and higher production costs compared to combustion engines. These drawbacks are primarily due to the battery, which is generally the heaviest and most expensive component of a BEV. Lightweight measures (strategies to decrease vehicle mass, e.g., by changing materials or downsizing components) lower energy consumption and reduce the amount of battery energy required (and in turn battery costs). Careful selection of lightweight measures can result in their costs being balanced out by a commensurate reduction in battery costs. This leads to a higher efficiency vehicle, but without affecting its production and development costs. In this paper, we estimate the lightweight potential of BEVs, i.e., the cost limit below which a lightweight measure is fully compensated by the cost savings it generates. We implement a parametric energy consumption and mass model and apply it to a set of BEVs. Subsequently, we apply the model to quantify the lightweight potential range (in €/kg) of BEVs. The findings of this paper can be used as a reference for the development of cheaper, lighter, and more energy-efficient BEVs.

Keywords: parametric modeling; battery electric vehicles; lightweight measures (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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