22. Internationales Stuttgarter Symposium

The emission-free drive type for small commercial vehicles for inner-city supply must remain individualized and technically combined in the overall vehicle and infrastructure concept.

As an important extension and modern methodology to fully digitize test management in full vehicle testing, we present the possible advantages of using modern blockchain technology and contrast classical methods. In doing so, we present some of the various requirements for the stakeholders and how these challenges can be met with the help of the new properties of distributed ledgers. This technology has all the properties of a decentralized database and can thus be used as a neutral storage medium, which would ensure the highest level of manipulation resistance and access security. The integration of such a solution requires a fully digitized, modern test environment that can be developed through consistent process digitization. The following four core characteristics of such a system would be: Machine and human readable, standardized tests and assignment to specifications Objective and subjective evaluation measures Storage of results in databases (e.g. the blockchain), comprehensive reporting, traceability of measurements Communication of final results and testing metadata in the blockchain

The driverless and electrically powered vehicle concept U-Shift enables a new type of flexibility and efficiency for the mobility of tomorrow by separating the drive unit (driveboard) and transport capsule. In combination with various capsule types, the driveboard is used to transport both people and goods. In a first step, a rollable Mock-up was built (U-Shift I project). The development of another prototype with extended functions for driverless driving (U-Shift II project) is described in this article. Automation – implementation of driverless operation based on sensor modules in the driveboard, supported by sensors in capsules and infrastructure. Chassis – integration of a lifting unit for flexible and quick capsule changes as well as a compact design of the wheel suspension. Drive train – design and implementation of a compact drive concept with wheel hub motors and a modular traction battery in connection with holistic energy and thermal management. Electrics/Electronics Architecture – Conception of a service-oriented architecture with distributed services in the driveboard, capsule and infrastructure. Vehicle structure – optimization of the load distribution in the driveboard and the capsules, as well as secure locking of the capsules on the vehicle. Citizen Participation – Dialogue on the Concept.

As an effective measure against global climate change, the electrification of automotive become an irreversible tendency. But because of limited power bettery capacity, how to reduce the power consumption of vehicle thermal management system (TMS) is an important issue for the car developers. The introducing heat pump into vehicle thermal management system shows a big benefit compared with other systems. In this artilcle the archietecture of some kinds heat pump based TMS are presented and the concept of a pilot TMS project for EV is introduced.

Well-to-Wheel Betrachtung konventioneller und alternativer Fahrzeugantriebe für kommunale MüllentsorgungsfahrzeugeKommunale Entsorgungsbetriebe und ähnliche Dienstleister sind insbesondere aufgrund des öffentlichen Drucks bemüht, ihren ökologischen Fußabdruck zu reduzieren, um lokale Aspekte der Luftreinhaltung und das globale Problem des Klimawandels gezielt anzugehen. Insbesondere die kommunale Müllentsorgung weist dabei hochgradig spezifische Einsatzprofile sowie stark eingeschränkte Randbedingungen auf, die einen systemischen Vergleich verschiedener Antriebskonzepte ermöglicht. Bspw. fährt jedes Müllfahrzeug auf spezifischen Routen, die täglich zu gleichen Zeiten abgefahren werden. Anhand der Fahrprofile kann daher jedes Fahrzeug individuell betrachtet und jeweils ein Optimum bzgl. des ökologischen Fußabdrucks gefunden werden.Zunächst werden die typischen Einsatzprofile näher analysiert und in eine virtuelle Testumgebung überführt. Gleiche Basisfahrzeuge mit unterschiedlichen Antriebssträngen und Energiespeichern/Kraftstoffen können somit unter konstanten Bedingungen verglichen werden. Dabei ist die Well-to-Wheel Betrachtung der CO2-Emissionen das einzige Vergleichskriterium. Es wird sich anhand realer Fahrzeugdaten hinsichtlich der Dimensionierungen orientiert.Das Ergebnis dieses Vergleichs ist neben der variierbaren Simulation durch veränderte Randbedingungen oder Streckenprofile auch die Beantwortung der für Entsorgungsbetriebe relevanten Frage des ökologischen Optimums. Sie dient im hierbei spezifischen Fall als Orientierungshilfe, um bei einer möglichen Flottenanpassung den ökologischen Aspekt stärker zu berücksichtigen.

The electrification of the powertrain results in complex functions, such as the engine restart in hybrid vehicles. At the same time, large amounts of data are generated in the development process that are only used to a limited extent. An experience-based and less systematic procedure for the manual evaluation of individual measurements or an elaborate statistical evaluation of data often produce little knowledge in the development process of transmission functions. However, in the course of digitalization data must be used efficiently and intelligently.The authors present a method that uses artificial intelligence to analyze large amounts of data automatically and efficiently to identify similarities and differences. The DBSCAN cluster algorithm is an important part of this method.The method analyzes vehicle data of a hybrid vehicle engine restart. About 300 engine restarts are detected from vehicle measurements, twelve key performance indicators per start are evaluated and commonalities are identified with the help of the cluster algorithm. The evaluation results can be used to define important operating points for an engine restart and evaluate the engine restart strategy. This method supports the development engineer to get a better understanding of the system and gain new knowledge about the transmission functions from data.

This paper presents a novel approach for dead reckoning. The described localization system consists of an inertial navigation system (INS), a magnetic, angular rate, gravity sensor (MARG sensor) and an odometry an odometry model. In contrast to conventional odometry models, a kinematic two-track model is implemented. The odometry model uses wheel-individual steering angles. It can therefore be applied for vehicles with all-wheel steering and steering geometries that allow opposite steering angle directions at one axle. An error-state Kalman filter is used to merge the individual submodels. While conventional odometry based localization systems only consider the vehicle longitudinal and lateral speed and position change, the proposed localization system is also able to correctly represent movements along the vehicles vertical axis. Furthermore, the algorithm uses the vehicle acceleration calculated from the odometry model to increase the robustness of the orientation estimation. The aim of the localization method is a high positioning accuracy in the low speed range, e.g. during precise maneuvering or parking. For this reason, the accuracy of the localization system is demonstrated by driving tests on a parking lot. The all-electric vehicle platform flexCAR is used as a test vehicle. Through its symmetrical design, this vehicle is able to realize wheel steering angles of up to 30° on the front and rear axles. Due to its maneuverability it is particularly suitable for the investigation of parking and (maneuvering).

The mobility of the future is not only relevant for passenger and goods traffic in large cities and on the highway. For an attractive and vital campus with intelligent infrastructure modern mobility is also an important precondition for achieveing excellent results in studies, research and teaching. This manuscript gives insights in current results of the Mobility Living Lab of the University of Stuttgart where the campus is going to be redesigned by an innovative mobility concept. One inherent big challenge is the development and validation of automated driving functions for the future campus shuttle and the autonomous e-scotters which can be supported by modern simulation environments like Tronis®. Especially the connectivity between the different protagonists in the campus mobility is essential e.g. for traffic safety and infotainment. Herein we present results and plans from the corresponding research projects SMART (BMBF) and AINET-ANTILLAS (BMBF/CELTIC-NEXT). We focus on the topics connectivity, automation and simulation which have been realised in collaboration between the University of Stuttgart and TWT in teaching courses. In these courses driver assistance systems are concepted, implemented and virtually validated to become employed in real scenarios in the further course of the project Mobility Living Lab.

The market launch of series-produced vehicles with the first functions of conditional automation according to SAE Level 3 by automobile manufacturers is imminent. For years, research has been conducted worldwide into the requirements placed on drivers when they are called upon by the vehicle to take over the driving task from the vehicle again (Take Over Request, TOR). In the next higher Level of automation, Level 4, the human driver will no longer be permanently required as a fallback Level, which represents a major step toward the fully autonomous mobility of the day after tomorrow. Accordingly, the vehicle's occupants will be able to devote themselves to other activities (non-driving-related activities, NDRA) during the automated journey, leaving the driver’s seat unoccupied. Over a longer introductory phase, the use of Level 4 functions will remain restricted to routes of manageable complexity, i.e. highways and their feeder routes. If a TOR to Level 2 is made in Level 4, for example to be able to drive manually on a detour route beyond the freeway, a significantly more extensive transfer procedure will be required than in Level 3. At the end of a more elaborate takeover process, there is the question of the required situational awareness of the human driver. A novel software function to increase and verify this situation awareness is presented in this paper.

The automation of vehicles, the electrification of the powertrain, as well as vehicle connectivity, and new usage concepts, are considered to be some of the major mobility trends in the future of automotive development. [1] With an increasing degree of automation, human drivers increasingly hand over the tasks for longitudinal and lateral control of the vehicle and in the long term become pure users without driving task responsibilities. Accordingly the interaction with the vehicle will change, whereby the interior represents the direct interface between humans and cars, so that the “Experiencing of the interior” is becoming much more important than before. In response to these changes, new tools are necessary to integrate users more clearly into the solution finding process for innovative upcoming products. Immersive visualization tools (e.g. based on augmented or virtual reality technology) offer a key to user-oriented product development. Using the example of a dynamically configurable autonomous vehicle, this article demonstrates the conception and application of a visualization tool. In this study, a mixed reality mock-up is develop which offers unique possibilities in the validation of new prototypes. Finally, the added value for vehicle concept development can be recognized by means of user integration during the early development stage, which is validated via subject tests in the Virtual Reality Laboratory at the Automotive Research Centre Niedersachsen (NFF).

Beside magnetic materials also completely non-magnetic materials make a significant contribution for the efficiency of electrical engineering components in automotive applications. Thereby, fully austenitic stainless steels offer a stable, one-phase, non-magnetic and non-magnetizable microstructure which minimizes the influence on the magnetic field. But only the holistic material design approach with high strength values, its complete recyclability, the high temperature resistance and low volatility in material costs leads into new design possibilities for electric engines, sensor covers or housings of electrical components. The present article explains the individual properties and their importance for component design in electrical engineering.

The update of the Mercedes-Benz strategy from “Electric first” to “Electric only” is accelerating the transformation towards an emission-free future, placing the focus on fully electric drives [1]. In addition to radial flux motors, which have been very common to date, axial flux motors offer new possibilities for drive topologies due to their comparatively small axial installation space, serve as enabler for compact dual drive units, for example.The special potential of axial flux motors lies in their combination of an extraordinary power-to-size, power-to-weight ratio with the highest level of efficiency [2, 3].Taking the general requirements for the electric motor as a basis, the aim is to derive the mechanical requirements and determine the properties of the component parts. The standards for laminated sheet packages of radial flux motors that specify the electromagnetic and mechanical properties have been defined. So far, laminated sheet packages in the form of laminated back iron for rotors of axial flux motors have been specified in terms of their electromagnetic properties exclusively. The relevant standards therefore do not take into account any requirements relating to the axial strength and stiffness of laminated back iron. In this paper the author focuses on simulation and experimental validation of these mechanical properties of axial flux rotor back iron.

Thermal security is a key concern for the design of components in electric powertrains. For electric motors this often means to define and test suitable cooling concepts that guarantee a maximum end winding temperature under time varying peak and continuous electrical loads. As a result, it is desired to have digital twins for real-time prediction of component dynamics. In this paper a 1D–3D synergetic modeling approach is presented for early design discovery and faster design iteration of electric motors in a virtual development cycle, where flow through the cooling channels is based on 1D Navier–Stokes equation and thermal conduction through the motor structure is based on 3D heat transport. Moreover, for real-time drive cycle prognoses, a simplified physics based reduced order modeling approach is presented. The permanent magnet synchronous motor investigated in this paper is based on a hybrid cooling concept to include direct winding spray cooling and indirect housing channel cooling. Four different designs of cooling channels are investigated in terms of design criteria such as maximum temperature and heat rejection. The final model with chosen design is implemented to test the entire operational range of electric motor in case of transient drive cycles. In conclusion, this paper successfully demonstrates how to overcome the limitations of computationally expensive 3D CFD simulation for e-motor design and integrated system transient analysis.

The range of battery electric vehicles (BEVs) is a very important factor for a customer’s choice and utilization behavior. One use case is towing a trailer on long distance drives, where the aerodynamic drag is the dominating factor regarding the possible range. Therefore, it is important to know the influence of a towed trailer behind a passenger car.Wind tunnel investigations of two exemplary passenger cars, one sedan and one sport utility vehicle (SUV), with several trailers are presented. As expected, the aerodynamic drag of a car/trailer unit rises massively compared to the stand-alone car. Compared to the sedan, the SUV builds a more effective ramp-up body for the trailers which results in lower drag values.Accompanying computational fluid dynamics (CFD) simulations were performed, allowing a detailed aerodynamic analysis of the car/trailer interaction. A very good agreement between the CFD simulations and the wind tunnel measurements is found. This gives confidence in predicting the aerodynamic drag of new car/trailer combinations with numerical methods.

Since the introduction of the first ABS control systems in 1978 by Daimler-Benz and Robert Bosch GmbH, one thing has always remained the same: The wheel speed sensors. However, the exact forces on a wheel cannot be calculated from the pure speed signals. This was not necessary at the time these systems were introduced as they were just anti-lock braking systems and nothing more. The sensatorq UG has developed a measurement method to make the “force on the wheel” measured value available for future driving dynamics controls. This brings more safety through shorter braking distances, fewer emissions through friction-optimized tires and the possibility to measure the rolling resistance during the entire journey and gives the system a sense for the road.

On long-distance trips, factors relevant to consumption such as traffic conditions, road slope, rolling resistance, auxiliary consumers and ambient temperature are known or can be easily predicted. Long-distance trips, however, typically take place on freeways and expressways at high speeds, making air drag the main driving resistance. Changes in drag caused by atmospheric winds influences the air resistance and can lead to significant changes in required power and to uncertainties in the range forecast. The near-surface wind forecast is highly dependent on local phenomena such as topography, vegetation and buildings. At best, conventional weather forecast models have a spatial resolution of several kilometers and therefore cannot take such local and small-scale phenomena into account. Our forecasting system Wind on Highways uses a high spatial resolution of 30 m, which significantly improves the near-surface wind forecasts. These forecasts can be integrated into existing route planning and range estimation services in order to provide more precise and reliable range estimates to the end customer.

The Eaton Breaktor™ is the next generation of electric vehicle power switch and circuit protection, protecting vehicle operators, first responders, and service technicians by covering the full range of over current and short circuit fault conditions from high voltage battery packs. The Breaktor™ actively senses and quickly interrupts high voltage power system faults, while improving electric vehicle service convenience with the ability to reset. The Breaktor™ has the functionality of both a switching and a protection device which gives it the added benefit of reducing system complexity and costs in an electric vehicle power distribution architecture.

Safety is a crucial part of autonomous driving functions. To ensure a safe operation within the defined Operational Design Domain (ODD), extensive tests and validation procedures must take place. Vehicles must drive millions of kilometers to find various corner cases, which only occur seldom. Simulation can accelerate this process by supporting real-world driving with unique, dangerous and seldom occurring sequences. Although many different, well-established simulation software tools already exist, they are still limited to specific use cases. To benefit from their individual strengths, we built a modular co-simulation framework. In this paper, we introduce the structure and functionality of this toolchain, fundamentally existing of Open Source Software and automotive simulation standards, such as OpenDRIVE, OpenSCENARIO, Measurement Data Format (MDF) and Open Simulation Interface (OSI).

In the development process of complex systems, as in modern systems and products of e-mobility in automotive industry, interdisciplinary interaction of the system elements involved is facilitated by the principle of systems engineering. The sub-process of testing, too, reflects the division of the overall system's complexity and has intense dependencies on the overarching process. The use of modern IT architectures, such as platform-based test process management systems bringing along open interfaces in modern technologies, can help meet these challenges in the best possible way. Digitalized use cases requiring data from different tools and processes become possible and interoperability between the different processes is achieved. This article describes how a sophisticated test data and test process management system can adopt to existing and new processes or tools and how it can add considerable value to the overall development process while increasing the product quality at the same time.

In vehicle development, more and more test sequences (diagnostic scripts) are established for function testing of individual components, systems and cross-functional methods. Due to decentralization and the modular approach, modern development vehicles consist of different numbers of electronic control units (ECU). The high number of ECUs in purpose and number poses a challenge for test creation and updating.The ECU software is also developed in cycles within the vehicle cycle. This results in a high software variance. This variance leads to the fact that in the vehicle development with global test conditions works. The vehicle structure (ECU and their software status) is uncertain, so errors and a longer script runtime must be expected during test execution.Due to this initial situation a concept was developed, which excludes the individual vehicle structure (global pattern) and verifies and stores this supported by an Artificial Intelligence (AI) database. This always ensures traceability of the vehicle condition. In addition, it is possible to create individualized test sequences for each vehicle and to keep them up to date. Furthermore, the AI can identify the user and to generate user-specific test sequences. Finally, the AI evaluates the quality of the measured values in order to provide the ECU developer with a tool to detect discrepancies.

Modern driver assistance systems are taking over more and more of the driver’s tasks. The development is moving from highly automated to autonomous driving. One major goal is to minimize the risk of accidents. This means that vehicle manufacturers and suppliers have great responsibilities, which results in an enormous testing effort for software and hardware. Mapping all the possible situations to driving scenarios requires millions of kilometers of driving and cannot be done with real-world testing alone. Therefore, virtual validation plays a greater role than ever.Testing in a virtual environment makes it possible to detect errors in an early stage of development when real-world testing is not possible yet.Virtual test scenarios can mimic any environmental conditions and locations at any time. Also, critical situations can be created and reproduced as often as needed without the risk of damage or injuries.Automated test runs allow the generation of test kilometers around the clock and with higher reproducibility. This paper provides an overview of executing scenarios for testing complex driver assistance functions in simulation and on the automated test track. Special attention is paid to the virtual world.This is done by combining the strength of both test instances (virtual world and reality) and overcoming the imposed challenges by the means of a standardized description language and the introduction of abstraction levels.

Sustaining the light-off temperatures of the catalytic converter can no longer be guaranteed at all times due to progressive hybridization of the powertrain. External electrical heating allows to obtain the light-off temperatures in a targeted manner and thus to minimize emissions, even under more difficult conditions. For helping to decide when this external energy supply is required, a real-time temperature model is needed. In the presented approach, the temperature is calculated by using different exponential growth functions for different loads. For these mathematical functions two parameters, the maximum temperature and the growth gradient, need to be identified. These parameters are determined empirically on a test bench. Results of different WLTC observations show a high conformity between the predicted temperature curves and the temperature actually measured.

The present work aims in analyzing the dispersion of pollutants in the vehicle wake in order to assess general capabilities of Remote Emission Sensing (RES) systems. Therefore, the Reynolds-Averaged Navier-Stokes Equations (RANS) are used in order to represent the instationary, turbulent flow of a multicomponent mixture. The most crucial volume that RES has to capture is the core exhaust plume, which lays within the first 1.5 m behind the vehicle. The location of the pollutant concentration peak as well as the core exhaust plume shape are mainly influenced by the pipe position. The vehicle acceleration acts as an additional momentum on the flow, causing the pollutant concentration peak (PCP) to shift towards the vehicle. Additionally, the simulations show that wind has no significant influence on the core exhaust plume. With regard to RES, an independence of the width of the street is found.

Wall-flow filters are used as particle filters in the exhaust gas after treatment of combustion engines. Soot is deposited in the filter and removed from it by regeneration through oxidation. However, an inert portion (ash) remains in the filter and forms different deposition patterns. Those patterns affect the separation efficiency as well as the overall pressure drop. The formation of deposition patterns is caused by rearrangement processes during regeneration, which result from the break-up of the particle layer as well as the resuspension and transport of individual agglomerates.With the help of the Homogenized Lattice Boltzmann Method (HLBM), resolved particle simulations are carried out within the framework of the open source software OpenLB. This allows the forces acting on the agglomerates to be determined and detachment and transport processes to be modelled. The focus of the present work is on a detailed investigation of the flow-induced transport of individual particle-agglomerates.

Stricter pollutant emission regulations and CO2 reduction requirements for internal combustion engines make further development of gasoline engine combustion processes essential. Homogeneous lean-burn processes, also in combination with high powertrain hybridization, offer great potential for increasing efficiency. However, nitric oxide (NO) emissions increase due to excess air and the use of a conventional three-way catalytic converter is not effective because the excess air prevents the complete reduction of the produced NO. In stoichiometric operation, nitric oxide and carbon monoxide (CO) emissions are also expected to increase in importance with higher degrees of hybridization since engine starts with potentially cooled down exhaust gas after-treatment systems are expected to occur more frequently. Therefore, reliable prediction of NO and CO raw emissions is of crucial importance in engine design and calibration. The formation of NO and CO depends significantly on the air-fuel ratio and the temperatures in the burnt mixture. Accordingly, existing mixture inhomogeneities have a major influence on NO and CO formation, with research showing different behavior in stoichiometric and homogeneous-lean operation. Currently used 0D/1D emission models for NO and CO show large deviations from the measurement, especially in lean operation. Within an FVV project, a quasi-dimensional model based on a distribution function is developed to reproduce the influence of mixture inhomogeneities on emission formation.

Various exhaust gas aftertreatment systems are used in the internal combustion engine to comply with the current exhaust gas standards. The diesel oxidation catalyst (DOC) is used in the diesel engine to oxidize carbon monoxide and hydrocarbons outside the engine. In order to ensure optimal operation and thus a high conversion rate, the light-off temperature must be reached at all times. The temperature modelling of the exhaust gas temperature after the catalytic converter represents a high degree of complexity due to the chemical energy release in the catalytic converter. In the model presented here, the chemical energy release is calculated on the basis of the reaction enthalpies of a one-step chemistry. In addition, the agglomeration of the hydrocarbons in the catalyst and their rapid burn-off when the light-off temperature is reached are taken into account. By combining both processes, an accurate modelling of the exhaust gas temperature in the catalyst is possible, which additionally takes into account strong temperature increases due to rapid conversion of stored hydrocarbons.

The study deals with the actuation sounds of mechanical control elements (stimulus) and the hearing sensations elicited by these stimuli. The singular impulsive sound signals are described with the help of technical and psychoacoustic magnitudes. In addition, 133 participants assessed the auditory perceived quality of the very same control elements in four different passenger cars. The relation between stimuli and user judgement clarifies which parameters have an influence on high perceived quality. Based on the participants’ preferences, favorable value ranges for actuation acoustics can be reported. When developing control elements as a central component of the human-machine interface, OEMs are increasingly striving to ensure customer-relevant value impression.

Modern drivetrain architectures that include e-Axles and hybrid transmissions require filtration solutions with higher demands to protect all system components and to reduce the energy consumption. MANN+HUMMEL has developed a new generation of filters that are covering these demands. In this contribution it will be presented how these filters increase the degrees of freedom for the development of lubrication circuits of modern drivetrains significantly by offering an ultra-compact and flexible installation space, lowest differential pressure or highest filtration efficiencies. The new MANN+HUMMEL filter media portfolio MULTIGRADE O-eM provides a high system security with long lifetimes at low energy dissipations, which contributes to enlarge the range of e-drives and also to lower the CO2 emission. With MANN+HUMMEL’s numerical development tools filter media as well as filters can be adapted digitally to fast changing demands and challenging installation spaces. To multiply these advantages a new generation of pleated suction-side filters has been developed. With up to 60 percent more filter area the new concept uses the given installation space to a maximum. A drainage grid keeps the energy efficiency as large as possible and media performance at a maximum level over the whole filter life. Based on that, a MANN+HUMMEL oil management system with highest filtration capabilities will be presented that can deal with air bubbles, intelligent cooling function and integrated oil drying.

Drive shafts are safety–critical components whose failure can result in situations ranging from a simple breakdown due to loss of tractive force to danger to life and limb. In addition, economic damage is caused by downtime, particularly in the commercial vehicle sector.In almost all cases, cardan shaft damage on commercial vehicles is caused by the rolling bearings used in the universal joints. Bearing damage is often indicated at an early stage by measurable vibrations. This allows damage to be detected even before the driver can notice it. Current diagnostic systems for rolling bearing damage are unsuitable for application in vehicle cardan shafts. At present, the authors are not aware of any system that can detect faults while the vehicle is in operation and inform the driver accordingly.This paper shows a way on how to identify damaged bearings of drive shafts of commercial vehicles reliably at an early stage and on how the driver can be informed about the failure.In the first step, a low-cost measuring system was developed whose package space requirements allow it to be installed in the drive shaft. Subsequently, measurements were carried out on a test rig for cardan shafts. Based on the collected vibration measurement data, an algorithm was developed whose output is an indicator value for the cardan shaft condition. The value is transmitted to a driver information system via a wireless connection. This enables the driver to react accordingly in order to exclude hazards due to consequential damage.

The European Environmental Agency (EEA) considers fine dust as one of the biggest environmental threats on human health (EEA, Healthy Environment, Healthy Lives: How the Environment Influences Health and Well-Being in Europe, 2020). While the current legislation focuses mainly on the exhaust emission of vehicles, 85% of the overall fine dust emissions originating from brakes, tires and road abrasion are not yet regulated (Barlow et al., Non-exhaust particulate matter emissions from road traffic: summary report. Published project report PPR231, 2007).Although the emission reduction at component level will reduce the emission footprint of the vehicle, it will not be sufficient to achieve emission-neutral vehicles. Therefore, a holistic approach has been developed to reach this target. It results in an integrated fine dust particle filter which can be fitted into previously unused installation spaces in frontends. The proposed solution is an effective and sustainable way to improve the emission balance of vehicles and thus contributes to an improved air quality, regardless of the drive system.The implementation in vehicles requires to develop specific, high efficient filter elements with low pressure loss level to guarantee the function of the thermal management system. A high dust holding capacity of the filter leads to customer friendly service intervals. In order to withstand the harsh operating conditions a filter element reinforcement has been implemented to enhance the mechanical stability.With the integrated fine dust particle filter system, it is possible that all types of vehicles can be PM10 emission-neutral for a central Europe representative use case.

The European Green Deal requires industry to invest in more climate-friendly and efficient production processes and products. This calls for new technologies to optimize sustainability in the manufacture, use and disposal of products. The most important contribution to almost all areas of life and technology is made by further developments in materials technology.New manufacturing technologies modify the physical, chemical, technological and ecological properties of light metals and offer new solutions for multidisciplinary applications with conflicting demands on material properties. They expand the design and functional properties of light metals and light metal-based material hybrids at the nano, micro and macro levels and generate many previously unknown technical, economic, and environmental potentials.

Design concepts of future passenger cars are changing due to new driving technologies such as hybrid or pure-electric concepts, so, one may assume that strived standardization of platforms in the automotive sector in future may play an important role. In this paper it is found that those changes do not have a strong impact on the production volumes of components being needed for future car platforms as well as car bodies compared to last two years. Considering published annual business reports of entire VWGroup containing produced numbers of existing models since 2000 as well as announced new model series volumes up to 2025 for the brands Audi, Seat, Škoda, Porsche and Volkswagen a slight increase of expected market volume was identified. A computer tool was developed and is presented in this paper to predict production volumes of mentioned brands until 2030. With this required sheet metal and forged components being used for different kinds of future vehicle platforms were forecasted.

The development of new vehicles is characterized by a high number of variants and shortened development times. Consequently, an efficiency enhancement of the development process is required particularly in the field of driving dynamics which is strongly based on expert drivers and prototype vehicles. Concerning the development of driving dynamics, efficiency improvements can be carried out by an objective evaluation of vehicle dynamics in simulations. For this purpose, adequate objective evaluation criteria are essential. This paper presents a generic process for the identification of appropriate criteria and demonstrates its usability on the example of the acceleration out of steady-state circular maneuver. Starting point are separate driving tests for vehicle dynamic measurements and subjective evaluation. Based on the measurement data a large set of characteristic values is defined in a generic process. By using statistical methods suitable characteristic values are identified and a dimension reduction of the subjective rating data is achieved. Afterwards, linear relationships between characteristic values and subjective ratings are analyzed to find the appropriate objective evaluation criteria. The application example shows that the generic process is capable to identify new objective evaluation criteria apart from the existing ones for the acceleration out of steady-state circular maneuver. Objective criteria are identified for the subjective rating criteria course guidance, self-steering behavior and stability.

Steering feel has a high importance for the driver, as it gives feedback regarding the current vehicle state and the drivers steering input, which is necessary for a good controllability of the vehicle. Therefore, a large effort is made during the steering system application to achieve a desired steering feel, mainly based on subjective driving tests.To minimize this effort, to get a consistent OEM specific steering feel for all vehicle models, objective parameters with defined values are required, describing the desired subjective steering feel. Furthermore, objective parameters are indispensable for the virtual phases of the vehicle development process.In this paper objective parameters are allocated to subjective steering feel characteristics, using literature and expert knowledge as basis. The validity of this allocation is tested with a new method, which gives reliable results for a low number of test participants. A possible redundancy of objective parameters is ruled out by correlation analysis of 250 measured vehicles from many different OEMs. The robustness of the parameters is examined with repeated measurements of two test vehicles.Final validation of the objective steering feel parameter set is done by using it for a virtual application of a steering system. The corresponding subjective driving tests show very promising results.