No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Individual concepts for electric vehicles: Interaction between battery package and vehicle concept
Abstract
Wenn in der Vergangenheit technische Innovationen auftraten, gab es zu Beginn die-
ser Phasen stets eine Vielfalt von miteinander im Wettbewerb stehenden Ideen. Nach
dieser Phase der Diversifikation setzte sich jedoch meist ein sog. Dominant-Design
durch, welches die übrigen Konzepte vom Markt verdrängte (vgl. [1]). Beispiele dafür
sind die frühen Phasen der Flugzeuge, die sich von Doppeldeckern mit Propellern zu
den heutigen Jets entwickelten, aber auch technische Systeme wie Fahrwerke, in de-
nen sich z.B. die McPherson-Achse durchgesetzt hat.
Ein solcher Umschwung kann auch in bereits etablierten Technologien erfolgen, wie
z.B. der Erfolg von Smartphones in der jüngeren Vergangenheit zeigt. Murmann sieht
den Auslöser für derartige Veränderungen immer dann gekommen, wenn ein Kern-
Subsystem eines technischen Produktes eine gravierende Änderung erfährt [1]. Ein
derartiger Auslöser für ein neues Dominant-Design könnte somit auch die sich mo-
mentan vollziehende Anwendung des E-Motors als PKW-Antrieb sein.
Aktuelle E-Fahrzeug Konzepte werden noch nach dem bislang vorherrschenden Do-
minant-Design verbrennungsmotorischer Fahrzeuge konzipiert. Langfristig, so die
einhellige Expertenmeinung, müssen die Änderungen über eine reine Elektrifizierung
bisheriger Fahrzeugkonzepte („Conversion-Design“) hinausgehen und ein verstärkter
Fokus auf die ganzheitliche Entwicklung von Fahrzeugkonzept und Antrieb gelegt
werden (vgl. [2]).
Das Ziel sollte es folglich sein, möglichst früh Aussagen über ein zukünftiges Domi-
nant-Design treffen zu können. Henderson beschreibt den Weg dorthin als eine Ab-
folge von Variations- und Auswahlprozessen (vgl. [3]). Um sich gegen bestehende
Konzepte zu behaupten muss ein neues Fahrzeugkonzept dabei die Defizite aktueller
Wettbewerber adressieren. Dies sind die derzeit noch sehr geringen Reichweiten so-
wie die durch die Batterie entstehenden hohen Kosten.
... Sources Vehicle length, overhangs, and wheelbase in mm Angerer [13][14][15], Bhise [37,38], Felgenhauer [16][17][18], J. Fuchs [19,20], S. Fuchs [50,51], Hahn [39], Hogt [52,53], Matz [27,28], Pesce [55,56], Prinz [44], Raabe [1,29], Sethuraman [32], Stefaniak [33,34], Wiedemann [35,36] Vehicle width and track width in mm Angerer [13][14][15], Bhise [37,38], Felgenhauer [16][17][18], J. Fuchs [19,20] [37,38], Felgenhauer [16][17][18], J. Fuchs [19,20], Hahn [39], Matz [27,28], Prinz [44], Raabe [1,29], Ried [30,31], Stefaniak [33,34] Vehicle height in mm Angerer [13][14][15], Bhise [37,38], J. Fuchs [19,20], S. Fuchs [50,51], Hahn [39], Matz [27,28], Raabe [1,29], Sethuraman [32], Wiedemann [35,36] Ground clearance in mm J. Fuchs [19,20], Hahn [39], Kuchenbuch [24][25][26],Raabe [1,29], Ried [30,31], Sethuraman [32], Stefaniak [33,34] Number of seats S. Fuchs [50,51], Hahn [39], Matz [27,28], Prinz [44], Sethuraman [32], Wiedemann [35,36] Headroom in mm Bhise [37,38], Hahn [39], Kuchenbuch [24][25][26], Prinz [44], Raabe [1,29], Wiedemann [35,36] ...
... Sources Vehicle length, overhangs, and wheelbase in mm Angerer [13][14][15], Bhise [37,38], Felgenhauer [16][17][18], J. Fuchs [19,20], S. Fuchs [50,51], Hahn [39], Hogt [52,53], Matz [27,28], Pesce [55,56], Prinz [44], Raabe [1,29], Sethuraman [32], Stefaniak [33,34], Wiedemann [35,36] Vehicle width and track width in mm Angerer [13][14][15], Bhise [37,38], Felgenhauer [16][17][18], J. Fuchs [19,20] [37,38], Felgenhauer [16][17][18], J. Fuchs [19,20], Hahn [39], Matz [27,28], Prinz [44], Raabe [1,29], Ried [30,31], Stefaniak [33,34] Vehicle height in mm Angerer [13][14][15], Bhise [37,38], J. Fuchs [19,20], S. Fuchs [50,51], Hahn [39], Matz [27,28], Raabe [1,29], Sethuraman [32], Wiedemann [35,36] Ground clearance in mm J. Fuchs [19,20], Hahn [39], Kuchenbuch [24][25][26],Raabe [1,29], Ried [30,31], Sethuraman [32], Stefaniak [33,34] Number of seats S. Fuchs [50,51], Hahn [39], Matz [27,28], Prinz [44], Sethuraman [32], Wiedemann [35,36] Headroom in mm Bhise [37,38], Hahn [39], Kuchenbuch [24][25][26], Prinz [44], Raabe [1,29], Wiedemann [35,36] ...
... Hahn [39], Prinz [44], Raabe [1,29], Sethuraman [32], Wiedemann [35] Front area in m 2 J. Fuchs [19,20], Hahn [39], Nemeth [29], Pesce [55,56], Prinz [44] Acceleration heel point (AHP) position in mm Bhise [37,38], Hahn [39], Raabe [1,29], Stefaniak [33,34] Length of crash in mm Kuchenbuch [24][25][26], Prinz [44], Raabe [1,29] The vehicle height defines, in combination with the vehicle width, the vehicle's front area. Furthermore, given the vehicle height, the available vertical space for the battery can be derived [5]. ...
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.
... As already Kuchenbuch showed in [10], the disadvantages of this method are whenever there are changes, caused of interrelation between exterior and interior, it can only be solved by difficult iteration loops alternatively decisions by the developer. [Braess] and [Seiffert] [3] subdivide the overall vehicle in their vehicle conception extension into singular system groups. ...
... Therefore in order to bring these into a direct connection with all components influencing themselves mutually a mathematical formulation of the degrees of freedom is to be striven for (Fig. 4). Similar as shown in [10], a connection between the characterization of the freedoms, the influences and the geometrical properties is also in this extension expedient. Additional to the interior passenger restrictions, there are further requirements coming from the exterior. ...
... New innovations increase the complexity and the possible design freedoms from future vehicle concepts. In order to evaluate new solutions out of the huge solution space, already in the early phase of the development process, a developer needs suitable auxiliary tools, as they were imagined in primary sources like [6], [10], [11], [21] and further. The practice shows that in increasingly shorter development times and at simultaneously increasing requirements, the processes of development must expire parallel, so-called simultaneously [3] [5]. ...
New innovations increase the complexity and the possible design freedoms from future vehicle concepts. In order to evaluate new solutions out of the huge solution space, already in the early phase of the development process, a developer needs suitable auxiliary tools. The practice shows that in increasingly shorter development times and at simultaneously increasing requirements, the processes of development must expire parallel, so-called simultaneously [3] [5]. With regard to the front-loading process it is an essential importance to realize as early as possibly the technological properties and potentials. Therefore an early simulation and analysis in the early concept and design phase is absolutely necessary. The presented method enables the design engineer to figure out which freedom has an optimal advantage for packaging. The major effort, next to the passenger positions also the possible new arrangement of interior modules that must be considered in the future more strongly. The featured tool will be enlarged with supplementary new parameters and modules in order to transmit the advantages of freedoms to if possible many components. In the end, the model is supposed to have more interfaces to already existing layout tools, like ConceptCar [6] or EVA_OS [11], in order to improve the individual strengths of each together in one.
... Nevertheless, these models do not consider the presence of a traction battery. Kuchenbuch et al. study the interdependencies between driver's seat configuration and battery installation space for BEVs [9] (p. 82). ...
... Finally, combining the previously presented dimensional chains, we derive an estimation model for the passenger compartment volume (Figure 7). In this case, a 2D-representation is sufficient because the dimension in the Y-direction is kept constant at the W3-1 value described in Equation (9). ...
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.
... The system design methodology can also be applied to further vehicle topologies such as Hybrid Electric Vehicles (HEV) or BEVs with 2 or more electric machines (Kuchenbuch et al. (2011), Appel et al. (2014), Buerger et al. (2010), Buerger et al. (2012, Schulte-Cörne (2015)). Typical optimization targets for HEVs are CO 2 emissions evaluated with regards to the target certification procedure, e.g. ...
In this paper a complete vehicle system simulation tool chain which applies a Multi Objective Optimization (MOO) methodology for designing the Electric Powertrain (ePT) of Battery Electric Vehicles (BEV) is presented. Optimization scope includes all relevant electric powertrain components from battery, inverter, electric machine to gear box. In addition to cost, vehicle dynamics, energy consumption and range are further optimization targets. For an overall minimal system cost design a multiplicity of interactions between all powertrain components has to be taken into account. High system complexity prevents an expert to consider all relevant correlations without the support of numeric simulation tools. The presented simulation tool chain enables fast identification of the best cost/benefit trade off regarding system cost while considering all defined system performance requirements. The approach enables experts to find unconventional solutions which would have been overlooked applying a classical straight forward approach and, thus, helps to sharpen the expert's knowledge in cause-effect relationships on the system level. Typical use cases are given and illustrated by several practical examples.
... The methodology of linking parameters of the vehicle with those of individual concept variables using mathematical relationships has been previously described in [8] and [9]. Newer approaches are presented for example in [10] and [11], where the variation of selected concept variables is pursued to optimise characteristics of rough concepts for battery electric vehicles. The extent of analyses which are necessary in accordance with the details given in Chapter 1 and in Section 3.1 create further functional requirements on the configuration tool: High-voltage supply as well as the performance of calculation and simulation operations on the complete vehicle level to determine the variables listed inTable 2. As additional components of the high-voltage system, power inverters, high-voltage distributors, DC/DC converters, recharging devices, high-voltage wiring as well as PTC heating and air conditioning compressor are taken into account to describe their influence on the complete vehicle, and especially on the topology of the high-voltage system. ...
The design of electric car concepts requires the development and integration of new components that have not been relevant in the design of conventional combustion-driven cars. High-voltage battery systems, electric powertrains, fuel cell systems and hydrogen storage systems for instance, are challenging with regard to an efficient package and design of constructed space. In addition, compromises between the functional and geometrical layout of these components, which determine the overall vehicle concept, are necessary. In respect of development of future electric vehicle concepts it is essential to know the interdependencies between the entire vehicle, its determining components and not least their underlying technologies. The first part of this paper presents the key components that determine the concepts for battery electric vehicles (BEV) and fuel cell electric vehicles (FCEV). Using the example of the BEV traction battery system, an approach for design and analysis of electric key components for a basic vehicle concept is introduced afterwards. In this context, a process model as well as dimensioning and construction tools based on MATLAB/Simulink and CATIA V5 have been developed and are to be explained in this paper.
Es wird eine Methode vorgestellt, die den Konstrukteur beziehungsweise Konzeptentwickler in die Lage versetzt, bereits in der fruehen Entwicklungsphase von Fahrzeugen mit elektrischem Antrieb eine hohe Vielfalt an grundlegend unterschiedlichen Fahrzeugkonzepten sowohl qualitativ miteinander zu vergleichen als auch erste quantitative Einordnungen bezueglich zu erwartender Eigenschaften vornehmen zu koennen. Sie ermoeglicht die schnelle und zielgerichtete Identifikation innovativer Fahrzeugkonzepte, die ueber den bekannten Erfahrungsraum des Anwenders hinausgehen. Die Methode ist um neue Parameter beziehungsweise detailliertere Rechenmodelle erweiterbar und wird in Zukunft dazu genutzt, ein tiefgreifendes Verstaendnis fuer die Moeglichkeiten alternativer E-Fahrzeug-Architekturen zu entwickeln. Das Auslegungswerkzeug erlaubt es, das bekannte Problem konfliktbehafteter Anforderungen sowie mangelnder Transparenz in der fruehen Konzeptphase von E-Fahrzeugen zu adressieren. Den Kern der Methode bildet die gemeinsame Darstellung der Wechselwirkungen zwischen Package und Fahrzeugeigenschaften F(x) in einem gemeinsamen mathematischen Modell. Die mathematischen Zusammenhaenge basieren auf Formeln wie zum Beispiel der Fahrwiderstandsgleichung sowie empirisch hergeleiteten Modellen und sind nicht auf ein Referenzfahrzeug normiert. Sie sind daher in weiteren Grenzen veraenderbar, ohne ihre Gueltigkeit zu verlieren. Da die Batterie in kuenftigen Elektrofahrzeugen die zweitgroesste Package-Komponente neben den Insassen darstellen wird, ist insbesondere die Wechselwirkung zwischen Insassen, Raum und Batteriebauraum relevant. Der Beitrag erlaeutert die Modellierung der zugrundeliegenden Abhaengigkeiten und ihre Integration in einem anwenderorientierten Tool stellvertretend fuer die Gesamtfahrzeug-Wechselwirkungen.
ResearchGate has not been able to resolve any references for this publication.