The derivation of a battery electric vehicle (BEV) architecture represents a challenging task for car manufacturers. For the early development of combustion engine architectures, the required design parameters can be derived from the analysis of previously-built model series. Regarding BEV architectures, the manufacturers do not yet have a reference series of vehicles on the basis of which they can derive the essential design parameters. Therefore, these parameters are mainly estimated at high cost in the early development phase. To avoid cost-intensive changes in the further course of development it is crucial to choose the right set of design parameters. For this reason, the aim of this paper is the identification of a minimum set of design parameters, derived from the current state-of-the-art of vehicle development by a structured literature comparison. We group the results according to our definition of vehicle architecture and discuss each identified parameter to explain its relevance. The sum of all parameters presented in this paper builds a minimum set of design parameters, which can be employed as a guideline for the definition of BEV architectures in the early development stage.

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.

Driving maneuvers try to objectify user needs regarding the driving dynamics for a vehicle concept. As autonomous vehicles will not be driven by people, the driving style that merges the individual aspects of driving dynamics, like user comfort, will be part of the vehicle concept itself. New driving maneuvers are, therefore, necessary to objectify the driving style of autonomous vehicle concepts with all its interdependencies relating to the individual aspects. This paper presents a methodology to design such driving maneuvers and includes a pilot study and a user study. As an example, the methodology was applied to the parameters of user comfort and travel time. The driven maneuvers resulted in statistical equations to objectify the interdependencies of these two aspects. Finally, this paper provides an outlook for needed maneuvers in order to tackle the entire driving style with its multidimensional facets.

Dimensional chains are the basis for testing the feasibility of vehicle architectures in the early development phase since they allow for parametrical vehicle modeling. Parametrical modeling is employed in the early development of the vehicle in order to enable the estimation of the space available for powertrain components. For battery electric vehicles (BEVs), new dimensional chains have increased relevance because of the geometrical interdependencies between the traction battery and the passenger compartment. The passenger compartment and traction battery share the same position in the vehicle, i.e., between the axles, which leads to a conflict between these two components. Furthermore, the passenger compartment dimensions are needed to size components like heating, ventilation, and air conditioning (HVAC), the energy consumption of which in turn influences the required battery capacity. In order to describe these interdependencies, we identify a set of dimensional chains and derive a passenger compartment volume estimation model that can be employed in the early development phase of the vehicle design. We further analyze the single elements of the dimensional chain and present typical values for each element.

Rapid prototyping has become increasingly popular over the past years. However, its application is heavily confined to a part size that fits the small build volume of additive machines. This paper presents a universal design method to overcome this limitation while preserving the economic advantages of rapid prototyping over conventional processes. It segments large, thin-walled parts and joins the segments. The method aims to produce an assembly with minimal loss to the performance and characteristics of a solid part. Based on a set of requirements, a universal segmentation approach and a novel hybrid joint design combining adhesive bonding and press fitting are developed. This design allows for the force transmission, positioning, and assembly of the segments adaptive to their individual geometry. The method is tailored to fused deposition modeling (FDM) by minimizing the need for support structures and actively compensating for manufacturing tolerances. While a universal application cannot be guaranteed, the adaptive design was proven for a variety of complex geometries. Using automotive trim parts as an example, the usability, benefits, and novelty of the design method is presented. The method itself shows a high potential to overcome the build volume limitation for thin-walled parts in an economic manner.

The megatrends of individualization and sharing will dramatically change our consumer behavior. The needs of a product’s users will be central input for its development. Current development processes are not suitable for this product development; thus, we propose a combination of a genetic algorithm and a fuzzy system for user-centered development. We execute our new methodological approach on the example of autonomous vehicle concepts to demonstrate its implementation and functionality. The genetic algorithm minimizes the required number of vehicle concepts to satisfy the mobility needs of a user group, and the fuzzy system transfers user needs into vehicle-related properties, which are currently input for vehicle concept development. To present this method, we use a typical family and their potential mobility behavior. Our method optimizes their minimal number of vehicle concepts to satisfy all mobility needs and derives the properties of the vehicle concepts. By integrating our method into the entire vehicle concept development process, autonomous vehicles can be designed user-centered in the context of the megatrends of individualization and sharing. In summary, our method enables us to derive an optimized number of products for qualitatively described, heterogeneous user needs and determine their product-related properties.