Search Results

In the virtual development process validated simulation models are requested to accurately predict power train vibration and comfort phenomena. Conclusions from refined parameter studies enable to avoid costly tests on rigs and on the road. Thereby, an appropriate modeling approach for specific phenomena has to be chosen to ensure high quality results. But then, parameters for characterizing the dynamic properties of components are often insufficient and have to be roughly estimated in this development stage. This results in a imprecise prediction of power train resonances and in a less conclusive understanding of the considered phenomena. Conclusions for improvements remain uncertain. This paper deals with the two different aspects of model refinement and parameter updating. First an existing power train model (predecessor power train) is analyzed whether the underlying modeling approach can reproduce the physical behavior of the power train dynamics adequately.

When employing in-car active sound generation (ASG) and active noise cancellation (ANC), the accurate knowledge of the vehicle interior sound pressure distribution in magnitude as well as phase is paramount. Revisiting the ANC concept, relevant boundary conditions in spatial sound fields will be addressed. Moreover, within this study the controllability and observability requirements in case of ASG and ANC were examined in detail. This investigation focuses on sound pressure measurements using a 24 channel microphone array at different heights near the head of the driver. A shaker at the firewall and four loudspeakers of an ordinary in-car sound system have been investigated in order to compare their sound fields. Measurements have been done for different numbers of passengers, with and without a dummy head and real person on the driver seat. Transfer functions have been determined with a log-swept sine technique.

Car components are exposed to the random/harmonic/impact excitation which can result in component failure due to vibration fatigue. The stress and strain loads do depend on local stress concentration effects and also on the global structural dynamics properties. Standardized fatigue testing is long-lasting, while the dynamic fatigue testing can be much faster; however, the dynamical changes due to fatigue are usually not taken into account and therefore the identified fatigue and structural parameters can be biased. In detail: damage accumulation results in structural changes (stiffness, damping) which are hard to measure in real time; further, structural changes change the dynamics of the loaded system and without taking this changes into account the fatigue load in the stress concentration zone can change significantly (even if the excitation remains the same). This research presents a new approach for accelerated vibration testing of real structures.

Image-based methods in vibration measurements typically require the use of complex high-speed camera systems. By using the recently introduced Spectral Optical Flow Imaging method, full-field high-frequency vibration data can be measured using a cost-effective still-frame camera. Using a single camera, only the motion perpendicular to the optical axis can typically be identified. Depth information, lost in the 2D imaging process, can be obtained by employing multi-camera imaging systems. Alternatively, the recently introduced frequency domain triangulation method offers a way of measuring full-field 3D deflection shapes using a single, moving camera. This research presents the required theoretical background to combine the Spectral Optical Flow Imaging and frequency-domain triangulation methods in an experimental modal analysis experiment using a single, moving still-frame camera.

Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

Today’s automotive industry is changing rapidly towards environmentally friendly vehicle propulsion systems. All over the globe, legislative CO2 consumption targets are under discussion and partly already in force. Hybrid powertrain configurations are capable to lower fuel consumption and limit pollutant emissions compared to pure IC-Engine driven powertrains. Depending on boundary conditions a numerous of different hybrid topologies- and its control strategies are thinkable. Typical approach is to find the optimum hybrid layout and strategy, by performing certain technical design tasks in office simulation directly followed by vehicle prototype tests on the chassis dyno and road. This leads to a high number of prototype vehicles, overload on chassis dynos, time consuming road test and finally to tremendous costs. Our developed approach is using the engine testbed with simulation capabilities as bridging element between office and vehicle development environment.

Within the aerospace industry there is a growing interest in evaluating and reducing the environmental impacts of products and related risks to business. Consequently, requests from governments, customers, manufacturers, and other interested stakeholders, for environmental information about aerospace products are becoming widespread. Presently, requests are inconsistent and this limits the ability of the aerospace industry to meet the informational needs of various stakeholders and reduce the environmental impacts of their products in a cost-effective manner. Energy consumption is a significant business cost, risk, and a simple proxy value for overall environmental impact. This paper presents the initial research carried out by an academic and industry consortium to develop standardised methods for calculating and reporting the embodied manufacturing energy content of aerospace products.

Today's powertrains are becoming more and more complex due to the increasing number of gear box types requiring gearshift patterns like conventional (equipped with GSI) and automatic-manual transmissions (AT, AMT), double clutch and continuous variable transmissions (DCT, CVT). This increasing variety of gear boxes requires a higher effort for the overall optimization of the powertrain. At the same time, it is necessary to assess the impact of different powertrains and control strategies on CO₂ emissions very early in the development process. The optimization of Gear Shift Patterns (G.S.P.) has to fulfill multiple constraints in terms of objective customers' requirements, like driveability, NVH, performance, emissions and fuel consumption. For these reasons, RENAULT and AVL entered an engineering collaboration in order to develop a dedicated simulation tool: CRUISE GSP.

The presented paper deals with a methodology to model cycle-to-cycle variations (CCV) in 0-D/1-D simulation tools. This is achieved by introducing perturbations of combustion model parameters. To enable that, crank angle resolved data of individual cycles (pressure traces) have to be available for a reasonable number of engine cycles. Either experimental data or 3-D CFD results can be applied. In the presented work, experimental data of a single-cylinder research engine were considered while predicted LES 3-D CFD results will be tested in the future. Different engine operating points were selected - both stable ones (low CCV) and unstable ones (high CCV). The proposed methodology consists of two major steps. First, individual cycle data have to be matched with the 0-D/1-D model, i.e., combustion model parameters are varied to achieve the best possible match of pressure traces - an automated optimization approach is applied to achieve that.

The rate in the electrification of vehicles has risen in recent years. With intensified development more and more attention is paid to the noise and vibration in such vehicles especially from the EDU (Electric Drive Unit). In this paper the main NVH simulation process of a high-speed E-axle up to 30,000 rpm for premium class vehicle application is presented. The high speed, high-power density and lightweight design introduces new challenges. Benchmarking of different EDUs and vehicles leads to targets which can be used at the early stage of development as subsystem targets. This paper shows the CAE methodology which can be used to verify the design and guarantee the target achievement. Using CAE both source and structure can be optimized to improve the NVH behavior.

Fused filament fabrication (FFF) 3D printing technology, one of the most accessible additive manufacturing technologies, can be used to create sensors based on different sensing principles, e.g.: capacitance, inductance, piezoelectricity, piezoresistivity. Piezoresistivity (strain-dependent electrical resistivity) has been predominantly used for the creation of static/quasistatic 3d printed sensors with relatively low sensitivity. This study researches the possibilities of a single-process 3d printing of a piezoresistive accelerometer. Initially, the methods for the axial and cross-axial identification of the piezoresistive properties are discussed. It is shown that the sensitivity is highly dependent on the printing parameters, especially the printing track orientation vs the mechanical load orientation. The research on the sensitivity of a 3D printed piezoresistive structure is extended with an inertial mass-based accelerometer design.

The new generation of automatic transmissions is characterized by a compact and highly efficient design. By the use of a higher overall gear ratio and lightweight components combined with optimal gear set concepts it is possible to improve significantly fuel consumption and driving dynamics. Precise and efficient real time models of the whole power train including models for complex subsystems like the automatic transmission are needed to combine real hardware with virtual models on XiL test rigs. Thereby it's possible to achieve a more efficient product development process optimized towards low development costs by less needed prototypes and shorter development times by pushing front loading in the process. In this paper a new real time model for automatic transmissions including approved models for the torque converter, the lock-up clutch and the torsional damper are introduced. At the current development stage the model can be used for comfort analysis and drivability assessment.

This paper deals with the development of a Lap Time Simulator in order to carry out a first approximate evaluation of the potential benefits related to the adoption of the Kinetic Energy Recovery System (KERS). KERS will be introduced in the 2009 Formula 1 Season. This system will be able to store energy during braking and then use it in order to supply an extra acceleration during traction. Different technologies (e.g. electrical, hydraulic and mechanical) could be applied in order to achieve this target. The lap time simulator developed by the authors permits to investigate the advantages both in terms of fuel consumption reduction and the improvement of the lap time.

The present work introduces a fully integrated real-time (RT) capable engine and vehicle model. The gas path and drive line are described in the time domain of seconds whereas the reciprocating characteristics of an IC engine are reflected by a crank angle resolved cylinder model. The RT engine model is derived from a high fidelity 1D cycle simulation and gas exchange model to support an efficient and consistent transfer of model data like geometries, heat transfer or combustion. The workflow of model calibration and application is outlined and base ECU functionalities for boost pressure, EGR, smoke and idle speed control are applied for transient engine operation. Steady state results of the RT engine model are compared to experimental data and 1D high fidelity simulations for 19 different engine load points. In addition an NEDC (New European Drive Cycle) is simulated and results are evaluated with data from chassis dynamometer measurements.

Gear trains applied to automotive transmissions and combustion engines are potential excitation sources of undesired whine noise. Consequently, the prediction of gear whine issues in an early stage of the product development process is strongly requested. Beside the actual excitation mechanism which is closely related to the gear's transmission error, the vibratory behavior (e.g. resonances) of other affected components like shafts, bearings and housing plays an important role in terms of structure borne noise transfer. The paper deals with gear contact models of different degree of detail, which are embedded in a multi-body dynamics (MBD) environment. Since gear meshing frequency and their harmonics may easily reach up to 5 kHz or even 10 kHz, applied gear contact models must be highly efficient with respect to calculation performance. Otherwise, major requirements of the development process in terms of process time can not be satisfied as is the case with FEA-based contact models.

At the moment the documentation of failure inhibition matrices and the fault path management for different controller types and different vehicle projects are mainly maintained manually in individual Excel tables. This is not only time consuming but also gives a high potential for fault liability. In addition there is also no guarantee that the calibration of these failure inhibition matrices and its fault path really works. Conflicting aims between costs, time and fault liability require a new approach for the calibration, documentation and testing of failure inhibition matrices and the complete Diagnostic System Management (DSM) calibration. The standardization and harmonization of the Diagnostic System Management calibration for different calibration projects and derivates is the first step to reduce time and costs. Creating a master calibration for the conjoint fault paths and labels provides a significant reduction of efforts.

For noise quality and brand sound design of passenger cars a unique software tool is currently used by our clients world-wide to evaluate and optimise the interior noise quality and brand sound aspects of passenger cars on an objective basis. The software tools AVL-VOICE and AVL-COMFORT are designed for the objective analysis of interior noise quality, for benchmarking, for the definition of noise quality targets and most important for effective vehicle sound engineering. With this tool, the target orientated implementation of the required interior noise quality or brand sound by predictable hardware modifications into passenger cars - for tailor made joy of driving - becomes feasible. The use of this tools is drastically reducing vehicle evaluation time and sound engineering effort when compared with traditional jury subjective evaluation methods and standard acoustic NVH optimisation procedures.

Light duty diesel vehicles continue to win recognition and market shares in Europe due to their convincing economy, reliability and driveability features. The diesel boom finds a fresh rationale in the CO2 emission legislation to come, however, the competitiveness of diesel cars may be impaired in future in consequence of the progression of the exhaust emission legislation and its impact on vehicle cost. This paper reviews the technologies currently pursued on the side of the engine and its subsystems, as well as the exhaust gas aftertreatment concepts required to satisfy the European legislation. An integral system approach is suggested, aiming at an optimum match of vehicle design parameters, transmission gear and the engine including aftertreatment elements and control.

Future demands regarding emissions, fuel consumption and driveability lead to complex engine and power train control systems. The calibration of the increasing number of free parameters in the ECU's contradicts the demand for reduced time in the power train development cycle. This paper will focus on the automatic, unmanned closed loop optimization of driveability quality on a high dynamic engine test bed. The collaboration of three advanced methods will be presented: Objective real time driveability assessment, to predict the expected feelings of the buyers of the car Automatic computer assisted variation of ECU parameters on the basis of statistical methods like design of experiments (DoE). Thus data are measured in an automated process allowing an optimization based on models (e.g. neural networks).

Modelling of conflicts between cars and pedestrians is presented in the paper. The model looks at how the velocities and distances change over the time between the pedestrian when first sensed and a potential impact, taking account of how the vehicle speed may be changing due to braking, wheel slip etc. Further work is outlined looking at the probability of conflict resolution behaviour by drivers and pedestrians. The paper also reviews current sensor technology appropriate for detecting pedestrians in front of a moving vehicle. A sensor system is required that responds to the road environment in real-time, and intelligently analyses the data so as to predict potential collisions and determine the nature of such collisions. A detection system combining radar detection with passive infrared detection and classification is proposed as a possible solution, meeting the requirements determined by conflict modelling and a review of the operating environment.