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The electric range of plug-in hybrids as well as the installed electric power has steadily increased. With an electric power share of more than half of the overall system power, concepts of hybrid electric vehicles with at least two electric machines come into focus. Especially the concept of adding an individual electric axle to a state-of-the-art parallel hybrid, such as a P2-hybrid, is promising. However, the system complexity of a so-called P24-hybird increases significantly because the number of possible system states rises. This leads to an increased development and calibration effort for an online energy management. Especially a transfer from an optimized operating strategy to a rule-based energy management is challenging. Thus, a development framework for the calibration of an online energy management system (EMS) which is as fuel efficient as possible is needed.

Increasing combustion pressure, low viscosity oils, less oil supply and the increasing stress due to downsizing of internal combustion engines (ICE) lead to higher loads within the bearing. As the mechanical and tribological loads on the piston pin bearings have a direct impact on the service life and function of the overall engine system, it is necessary to develop a robust tribological design approach. Regarding the piston pin bearing of a diesel engine, this study aims to describe the effects of different parameters on a DLC-coated piston pin within the bearing. Therefore, an external engine part test rig, which applies various forces to the connecting rod and measures the torque on a driven pin, is used to carry out validation measurements. The special feature of the test bench is the way the piston is beared. For the first experiments, the piston crown is placed against a plate (plate-bearing); later, this plate-bearing is replaced by a hydrostatic bearing.

It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.

During the last decades, big steps have been taken towards a realistic simulation of NVH (Noise Vibration Harshness) behavior of vehicles using the Finite Element (FE) method. The quality of these computation models has been substantially increased and the accessible frequency range has been widened. Nevertheless, to perform a reliable prediction of the vehicle vibroacoustic behavior, the consideration of uncertainties is crucial. With this approach there are many challenges on the way to valid and useful simulation models and they can be divided into three areas: the input uncertainties, the propagation of uncertainties through the FE model and finally the statistical output quantities. Each of them must be investigated to choose sufficient methods for a valid and fast prediction of vehicle body vibroacoustics. It can be shown by rough estimation that dimensionality of the corresponding random space for different types of uncertainty is tremendously high.

Due to the continuous electrification of vehicles, the variety of different hybrid topologies is expected to increase in the future. As the calibration of real-time capable energy management systems (EMS) is still challenging, a development framework for the EMS that is independent of the hybrid topology would simplify the overall development process of hybrid vehicles. In this paper an analytical methodology, which is used to derive a fuel-optimal, rule-based EMS for parallel hybrids, is transferred to a series topology. It is shown that the fundamental correlations can be applied universally to both parallel and series configurations. This enables the possibility to develop a real-time capable, rule-based controller for a series HEV based on maps that ensures a fuel-optimal operation. These maps provide the optimal power threshold for the activation of the auxiliary power unit and the optimal power output dependent on the driver’s power request.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

As a result of the R&D focus being shifted from internal combustion engines to electrified powertrains, resources for the development of internal combustion engines are restricted more and more. With that, the importance of highly efficient engine development tools is increased. In this context, 0D/1D engine simulation offers the advantage of low computational effort and fast engine model set-up. To ensure a high predictive ability of the engine simulation, a reliable burn rate model is needed. Considering the increasing interest in alternative fuels, the aspect of predicting the fuel influence on combustion is of special importance. To reach these targets, the change of engine combustion characteristics with changing fuels and changing air-fuel-ratios were investigated systematically in a first step. For this purpose, engine test bed data were compared with expected fuel-dependent flame wrinkling trends based on Markstein/Lewis number theory.

The current automotive market is dynamic, leading to complex functionalities being incorporated into the control software of various components like engine, gearbox, battery, E-motor etc. This results in utilization of virtual environments for software testing to reduce the development time. The virtual platforms under the category X-in-the-Loop (XiL) e.g. Software-in-the-Loop (SiL) and Hardware-in-the-Loop (HiL) use simulated models to achieve a desired test goal. These component models must be rigorously validated to ensure the quality of XiL-Testing. Thus, it is essential to define a model release process that maintains model quality irrespective of the modeling approach used and the user. One of the challenges is to choose an appropriate Error Metric (EM) that sets criteria for model release. This paper proposes a combination of Theil’s Inequality Coefficient (TIC) and Unscaled Mean Bounded Relative Absolute Error (UMBRAE) as the EM.

Computational models directly derived from data gained increased interest in recent years. Data-driven approaches have brought breakthroughs in different research areas such as image-, video- and audio-processing. Often denoted as Machine Learning (ML), today these approaches are not widely applied in the field of vehicle Noise, Vibration and Harshness (NVH). Works combining ML and NVH mainly discuss the topic with respect to psychoacoustics, traffic noise, structural health monitoring and as improvement to existing numerical simulation methods. Vehicle interior noise is a major quality criterion for today’s automotive customers. To estimate noise levels early in the development process, deterministic system descriptions are created by utilizing time-consuming measurement techniques. This paper examines whether pattern-recognizing algorithms are suitable to conduct the prediction process for a steering system.

The reduction of vehicle exhaust particle emissions is a success story of European legislation. Various particle number (PN) counters and calibration procedures serve as tools to enforce PN emission limits during vehicle type approval (VTA) or periodical technical inspection (PTI) of in-use vehicles. Although all devices and procedures apply to the same PN-metric, they were developed for different purposes, by different stakeholder groups and for different target costs and technical scopes. Furthermore, their calibration procedures were independently defined by different stakeholder communities. This frequently leads to comparability and interpretation issues. Systematic differences of stationary and mobile PN counters (PN-PEMS) are well-documented. New, low-cost PTI PN counters will aggravate this problem. Today, tools to directly compare different instruments are scarce.

Wheel slip control system have found a remarkable penetration in all car segments. The information on the wheel behavior has lead to further developments which control the brake performance as well as the driving of the car in general. Latest systems introduced especially on luxury cars use wheel individual brake intervention to ensure vehicle stability under various driving maneuvers within the physical limits. Such systems use vehicle dynamic sensors and special hydraulics which serve as energy source for the automatic brake application. The technical effort of such systems like the Dynamic Stability Control DSC has limited the installation to upper class cars so far. New approaches are required to allow for a more wide spread penetration. Optimized hydraulics together with a rational design of the electronics seems to offer a basis for a more cost effective design.

To meet LEV and EU Stage III emission requirements, it is necessary for new catalytic converters to be designed which exceed light-off temperature as quickly as possible. The technical solutions are secondary air injection, active heating systems such as the electrically heated catalytic converter, and the close coupled catalytic converter. Engine control functions are extensively used to heat the converter and will to play a significant role in the future. The concept of relocating the converter to a position close to the engine in an existing vehicle involves new conflicts. Examples include the space requirements, the thermal resistance of the catalytic coating and high temperature loads in the engine compartment.

Since the introduction of the 4-speed automatic transmissions W4A040 in 1979 and W4A020 in 1981, more than 50% of Mercedes-Benz cars have been equipped with automatic transmissions. These transmissions have undergone continuous development since their introduction. Due to engine/transmission management, the kick-down shift points are electronically influenced, the shift comfort is improved partially by ignition timing manipulation. During the warm-up phase the shift points are raised via output signals from the electronic engine system to improve exhaust gas emissions. In this paper considerations are explained which resulted in supplementing the proven four-speed transmission with a five-speed transmission.

The new SL from Mercedes-Benz was conceived as a pure-bred roadster, i.e. without a fixed roll-over bar which would mar the looks of this open sports car and moreover emphasize the added risk of injury in the event of a roll-over accident. At the same time, the aim was to further enhance occupant safety in the event of such a roll-over. These aims led to the designing of a completely new kind of passive protection system which comes into operation automatically if a roll-over is imminent. Between the rear seats and the soft-top recess, a roll-over bar was therefore integrated; this is mounted on a pivot system and does not affect the apearance of the car when lowered. A sensor system, which is also new, registers driving situations which could result in a roll-over. As a consequence of this, the roll-over bar is raised via a spring/damper mechanism and locked into position.

In the present work we investigated experimentally and computationally the unsteady flow around a BMW car model including wheels*. This simulation yields mean flow and turbulence fields, enabling the study aerodynamic coefficients (drag and lift coefficients, three-dimensional/spatial wall-pressure distribution) as well as some unsteady flow phenomena in the car wake (analysis of the vortex shedding frequency). Comparisons with experimental findings are presented. The computational approach used is based on solving the complete transient Reynolds-Averaged Navier-Stokes (TRANS) equations. Special attention is devoted to turbulence modelling and the near-wall treatment of turbulence. The flow calculations were performed using a robust, eddy-viscosity-based ζ - ƒ turbulence model in the framework of the elliptic relaxation concept and in conjunction with the universal wall treatment, combining integration up to the wall and wall functions.

Although hydrogen ICE engines have existed in one sort or another for many years, the testing of fuel consumption by way of exhaust emissions is not yet a proven method. The current consumption method for gasoline- and diesel-fueled vehicles is called the Carbon-Balance method, and it works by testing the vehicle exhaust for all carbon-containing components. Through conservation of mass, the carbon that comes out as exhaust must have gone in as fuel. Just like the Carbon-Balance method for gas and diesel engines, the new Hydrogen-Balance equation works on the principle that what goes into the engine must come out as exhaust components. This allows for fuel consumption measurements without direct contact with the fuel. This means increased accuracy and simplicity. This new method requires some modifications to the testing procedures and CVS (Constant Volume Sampling) system.

The study of oil emission is of essential interest for the engine development of modern cars, as well as for the understanding of hydrocarbon emissions especially during cold start conditions. A laser mass spectrometer has been used to measure single aromatic hydrocarbons in unconditioned exhaust gas of a H2-fueled engine at stationary and transient motor operation. These compounds represent unburned oil constituents. The measurements were accompanied by FID and GC-FID measurements of hydrocarbons which represent the burned oil constituents. The total oil consumption has been determined by measuring the oil sampled by freezing and weighing. It has been concluded that only 10 % of the oil consumption via exhaust gas has burned in the cylinders. A correlation of the emission of single oil-based components at ppb level detected with the laser mass spectrometer to the total motor oil emission has been found.

This paper describes a practical approach to extract the global static stiffness of a body in white (BIW) from dynamic measurements in free-free conditions. Based on a limited set of measured frequency response functions (FRF), the torsional and bending stiffness values are calculated using an FRF based substructuring approach in combination with inverse force identification. A second approach consists of a modal approach whereby the static car body stiffness is deduced from a full free-free modal identification including residual stiffness estimation at the clamping and load positions. As an extra important result this approach allows for evaluating the modal contribution of the flexible car body modes to the global static stiffness values. The methods have been extensively investigated using finite element modeling data and verified on a series of body in white measurements.

The aim of the project is to reliably identify the set of constructive features responsible for the highest noise levels in the interior of motor vehicles. A simulation environment based on artificial intelligence techniques such as neural networks and genetic algorithms has been implemented. We used a system identification approach in order to approximate the functional relationship between the target noise series and the sets of constructive parameters corresponding to the cars. The noise levels were measured with a microphone positioned on the driver''s chair, and corresponded to a variation of the engine rotation of 600-900 rot/min. The database includes 45 different cars, each described by vectors of 67 constructive features.