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Finite element simulation (FE) makes it possible to analyze the structural dynamic behavior of vehicle seat structures in early design phases to meet Noise-Vibration-Harshness (NVH) requirements. For this purpose, linear simulations are usually used, which neglect many nonlinear mechanical properties of the real structure. These models are trimmed to fit global vibration behavior based on the complex description of contact or jointed definitions. Targeted design is therefore only possible to a limited extent. The aim of this work is to characterize the entire seat structure and its sub-components in order to identify the main contributors using experimental and simulative data. The Lagrange Multiplier Frequency Based Substructuring (LM-FBS) method is used for this purpose. Therefore, the individual subsystems of seat frame, seat backrest and headrest are characterized under different conditions.

Raising demands towards lightweight design paired with a loss of originally predominant engine noise pose significant challenges for NVH engineers in the automotive industry. From an aeroacoustic point of view, low frequency buffeting ranks among the most frequently encountered issues. The phenomenon typically arises due to structural transmission of aerodynamic wall pressure fluctuations and/or, as indicated in this work, through rear vent excitation. A possible workflow to simulate structure-excited buffeting contains a strongly coupled vibro-acoustic model for structure and interior cavity excited by a spatial pressure distribution obtained from a CFD simulation. In the case of rear vent buffeting no validated workflow has been published yet. While approaches have been made to simulate the problem for a real-car geometry such attempts suffer from tremendous computation costs, meshing effort and lack of flexibility.

The Noise Vibration and Harshness (NVH) characteristics and requirements of vehicles are changing as the automotive manufacturers turn their focus from developing and producing cars propelled by internal combustion engines (ICE) to electrified vehicles. This new strategic orientation enables them to offer products that are more efficient and environmentally friendly. Although electric powertrains have many advantages compared to their established predecessors they also bring new challenges that increase the difficulty of matching the high quality requirements of premium car producers especially regarding NVH. Electric motors are one of the most important sources of vibrations in electric vehicles.

Driving cycles are valuable tools for emissions calibration at engine and powertrain test beds. While generic velocity profiles were sufficient in the past, legislative changes and increasing complexity of powertrain and exhaust aftertreatment systems require a new approach: Realistically transient cycles - which include critical driving maneuvers and can be tailored to a specific powertrain configuration - are needed to optimize the emission behavior of the said powertrain. For the generation of realistic velocity profiles, the Markov chain approach has been widely used and described in literature. However, this approach, so far, has only been used to generate cycles that are statistically representative of a large database of real driving trips, which is typically not available during the early stages of development of a new powertrain.

Classical decentralized architectures based on large networks of microprocessor-based Electronic Control Units (ECU), namely those used in self-driving cars and other highly-automated applications used in the automotive industry, are becoming more and more complex. These new, high computational power demand applications are constrained by limits on energy consumption, weight, and size of the embedded components. The adoption of new embedded centralized electrical/electronic (E/E) architectures based on dynamically reconfigurable hardware represents a new possibility to tackle these challenges. However, they also raise concerns and questions about their safety. Hence, an appropriate evaluation must be performed to guarantee that safety requirements resulting from an Automotive Safety Integrity Level (ASIL) according to the standard ISO 26262 are met. In this paper, a methodology for the evaluation of dynamically reconfigurable systems based on centralized architectures is presented.

Model Order Reduction (MOR) methods such as Component Mode Synthesis (CMS) have been used in order to simulate large linear dynamic systems for many years and have reached a considerable level of saturation. These reduction methods have many advantages such as minimizing computational costs but also have restrictions. One of their disadvantages is that material damping characteristics can only be defined in form of Rayleigh damping. Another disadvantage is that the reduced order model can only represent one state of the structure determined in the generation process of the reduced matrices. In this paper we present a way to consider material damping in reduced matrices that contain one or more materials having different damping characteristics without the disadvantages of using Rayleigh damping.

The Deep Orange program immerses automotive engineering students into the world of an OEM as part of their 2-year graduate education. In support of developing the program’s seventh vehicle concept, the students studied the sponsoring brand essence, conducted market research, and made a heuristic assessment of competitor vehicles. The upfront research lead to the definition of target customers and setting vehicle level targets that were broken down into requirements to develop various vehicle sub-systems. The powertrain team was challenged to develop a scalable propulsion concept enabled by a common vehicle architecture that allowed future customers to select (at the point of purchase) among various levels of electrification best suiting their needs and personal desires. Four different configurations were identified and developed: all-electric, two plug-in hybrid electric configurations, and an internal combustion engine only.

The quiet nature of hybrid and electric vehicles has triggered developments in research, vehicle manufacturing and legal requirements. Currently, three countries require fitting an Approaching Vehicle Alerting System (AVAS) to every new car capable of driving without a combustion engine. Various other geographical areas and groups are in the process of specifying new legal requirements. In this paper, the design challenges in the on-going process of designing the sound for quiet cars are discussed. A proposal is issued on how to achieve the optimum combination of safety, environmental noise, subjective sound character and technical realisation in an iterative sound design process. The proposed sound consists of two layers: the first layer contains tonal components with their pitch rising along with vehicle speed in order to ensure recognisability and an indication of speed.

The requirement of the start of the internal combustion engine (ICE) not only at vehicle standstill is new for full hybrid electric vehicles in comparison to conventional vehicles. However, the customer will not accept any deterioration with respect to dynamics and comfort. ICE-starting-systems and -strategies have to be designed to meet those demands. Within this research, a method was developed which allows a reproducible maneuver-based analysis of ICE-starts. In the first step, a maneuver catalogue including a customer-oriented maneuver program with appropriate analysis criteria was defined. Afterwards, the maneuvers were implemented and verified in a special test bench environment. Based on the method, two sample hybrid vehicles were benchmarked according to the maneuver catalogue. The benchmarking results demonstrate important dependencies between the criteria-based assessment of ICE-starts and the embedded ICE-starting-system and -strategy.

Modern exhaust systems contain not only a piping network to transport hot gas from the engine to the atmosphere, but also functional components such as the catalytic converter and turbocharger. The turbocharger is common place in the automotive industry due to their capability to increase the specific power output of reciprocating engines. As the exhaust system is a main heat source for the under body of the vehicle and the turbocharger is located within the engine bay, it is imperative that accurate surface temperatures are achieved. A study by K. Haehndel [1] implemented a 1D fluid stream as a replacement to solving 3D fluid dynamics of the internal exhaust flow. To incorporate the 3D effects of internal fluid flow, augmented Nusselt correlations were used to produce heat transfer coefficients. It was found that the developed correlations for the exhaust system did not adequately represent the heat transfer of the turbocharger.

Wind noise is a significant source of interior noise in automobiles at cruising conditions, potentially creating dissatisfaction with vehicle quality. While wind noise contributions at higher frequencies usually originate with transmission through greenhouse panels and sealing, the contribution coming from the underbody area often dominates the interior noise spectrum at lower frequencies. Continued pressure to reduce fuel consumption in new designs is causing more emphasis on aerodynamic performance, to reduce drag by careful management of underbody airflow at cruise. Simulation of this airflow by Computational Fluid Dynamics (CFD) tools allows early optimization of underbody shapes before expensive hardware prototypes are feasible. By combining unsteady CFD-predicted loads on the underbody panels with a structural acoustic model of the vehicle, underbody wind noise transmission could be considered in the early design phases.

The thermal prediction of a vehicle under-body environment is of high importance in the design, optimization and management of vehicle power systems. Within the pre-development phase of a vehicle's production process, it is important to understand and determine regions of high thermally induced stress within critical under-body components. Therefore allowing engineers to modify the design or alter component material characteristics before the manufacture of hardware. As the exhaust system is one of the primary heat sources in a vehicle's under-body environment, it is vital to predict the thermal fluctuation of surface temperatures along corresponding exhaust components in order to achieve the correct thermal representation of the overall under-body heat transfer. This paper explores a new method for achieving higher accuracy exhaust surface temperature predictions.

Aerodynamic performance assessment of automotive shapes is typically performed in wind tunnels. However, with the rapid progress in computer hardware technology and the maturity and accuracy of Computational Fluid Dynamics (CFD) software packages, evaluation of the production-level automotive shapes using a digital process has become a reality. As the time to market shrinks, automakers are adopting a digital design process for vehicle development. This has elevated the accuracy requirements on the flow simulation software, so that it can be used effectively in the production environment. Evaluation of aerodynamic performance covers prediction of the aerodynamic coefficients such as drag, lift, side force and also lift balance between the front and rear axle. Drag prediction accuracy is important for meeting fuel efficiency targets, prediction of front and rear lifts as well as side force and yawing moment are crucial for high speed handling.

What are the requirements of customers in an urban environment? What will sustainable mobility look like in the future? This presentation gives an overview of the integrated approach used by BMW to develop the BMW i3 - a purpose-built battery electric vehicle. Very low driving resistances for such a vehicle concept enable the delivery of both impressive range and driving excitement. A small optional auxiliary power unit offers range security for unexpected situations and opens up BEVs to customers who are willing to buy a BEV but are still hesitant due to range anxiety. Additional electric vehicles sold to the formerly range anxious will create additional electric miles. Presenter Franz Storkenmaier, BMW Group

In the environmentally conscious world we live in, auto manufacturers are under extreme pressure to reduce tailpipe emissions from cars and trucks. The manufacturers have responded by creating clean-burning engines and exhaust treatments that mainly produce CO2 and water vapor along with trace emissions of pollutants such as CO, THC, NOx, and CH4. The trace emissions are regulated by law, and testing must be performed to show that they are below a certain level for the vehicle to be classified as road legal. Modern engine and pollution control technology has moved so quickly toward zero pollutant emissions that the testing technology is no longer able to accurately measure the trace levels of pollutants. Negative emission values are often measured for some pollutants, as shown by results from eight laboratories independently testing the same SULEV automobile.

The G-equation model was implemented in the commercial code ANSYS CFX and validated against experimental data in order to successfully simulate turbulent premixed combustion in internal combustion engines. The model is based on the level-set approach. Two transport equations are solved respectively for the G-scalar mean value, representing the local distance function from the time-averaged mean flame front, and its variance, correlated to the turbulent flame brush thickness. The model closure for tracking the flame front is based on an algebraic expression for the turbulent burning velocity. The composition of the reacted mixture is evaluated by coupling the code with flamelet libraries generated with the ANSYS CFX-RIF package by means of a reaction progress variable computed as a function of the G-related quantities.

While hybrid-electric powertrain features such as regenerative braking and electric driving can improve the fuel economy of a vehicle significantly, these features may also have a considerable impact on driving dynamics. That is why extra effort is necessary to ensure safety and comfort that customers usually expect from a conventional vehicle. The purpose of this paper is to initiate a discussion regarding different drivetrain concepts, necessary changes in chassis systems, and the impact on vehicle dynamics. To provide input to this essential discussion, braking and steering systems, as well as suspension design, are analyzed regarding their fit with hybrid systems. It is shown how an integration of hybrid technology and chassis systems benefits vehicle dynamics and why “by-wire” technology is a key enabler for safe and comfortable hybrid-electric vehicles.

AM-SC1™ is a high temperature Mg alloy that was originally developed as a sand casting alloy for automotive powertrain applications. The alloy has been selected as the engine block material for both the AVL Genios LE and the USCAR lightweight magnesium engine projects. The present work assesses the potential of this alloy for permanent-mould die cast applications. Thermo-physical and mechanical properties of AM-SC1 were determined for material derived from a permanent-mould die casting process. The mechanical properties determined included: tensile, creep, bolt load retention/relaxation and both low and high cycle fatigue. To better assess the creep performance, a comparative analysis of the normalized creep properties was carried out using the Mukherjee-Dorn parameter, which confirmed the high viscoplastic performance of AM-SC1 compared with common creep resistant high pressure die cast (HPDC) Mg-alloys.

In large-scale industrial simulations the numerical prediction of fracture in sheet metal forming operations as well as in crash events is still a challenging task of high social and economic relevance. Among several approaches presented in literature, the authors and their colleagues developed a model which accounts each for three different mechanisms leading finally to fracture in thin sheet metals: the local instability (necking), ductile normal fracture and ductile shear fracture. The focus of this paper is to develop and validate a new approach to improve the predictive capabilities for fracture triggered by localized necking for a wide variety of steel grades. It is well known that after the onset of a local instability additional strain is still necessary to induce fracture. In a numerical simulation using shell elements this post instability strain becomes of increasing importance when the ratio of the characteristic shell element edge length to its thickness decreases.

Underbody aerodynamics has become increasingly important over the last three decades because of its vital contribution to improving a vehicle's overall performance. This was the motivation for the research conducted by BMW Aerodynamics, concerning the determination of the overall pressure distribution on the underbody of a series-production vehicle. Static pressure measurements have been taken under various test conditions. Real on-road tests were carried out as well as wind tunnel experiments under application of different road simulation techniques. The analyzed vehicle configurations include wheel rim-tire and body modifications. The results presented include surface pressure data, drag and lift coefficients, ride heights, pitch and roll angles. The acquired data is used to examine the underbody flow topology and determine how the diverse attempts to represent the real on-road conditions affect its pressure distribution.