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.

Defining a vehicle concept during the early development phase is a challenging task, since only a limited number of design parameters are known. For battery electric vehicles (BEVs), vehicle weight is a design parameter, which needs to be estimated by using an iterative approach, thus causing weight fluctuations during the early development phase. These weight fluctuations, in turn, require other vehicle components to be redesigned and can lead to a change in their size (secondary volume change) and weight (secondary weight change). Furthermore, a change in component size can impact the available installation space and can lead to collision between components. In this paper, we focus on a component that has a high influence on the available installation space: the wheels. We model the essential components of the wheels and further quantify their secondary volume and weight changes caused by a vehicle weight fluctuation. Subsequently, we model the influence of the secondary volume changes on the available installation space at the front axle. The hereby presented approach enables an estimation of the impact of weight fluctuations on the wheels and on the available installation space, which enables a reduction in time-consuming iterations during the development process.