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Measurements of ultrafine particles (diameter < 300 nm) and total suspended particulates (TSP) were performed in 2 tunnels (Lundby, Gothenborg, S, and Plabutsch, Graz, A). The measurements in the Lundby tunnel were performed directly in the tunnel tube at the roadside whereas the measurements at the Plabutsch tunnel took place at the top of a 90 m high ventilation shaft. There was good correlation for all diameters (7.91 nm - 300 nm) between ultrafine particles and TSP for the measurements at the Lundby tunnel. At the Plabutsch site a correlation between ultrafine particles and TSP was detected only for particles > 35 nm. The maximum of the particle size distribution function for Lundby was at 30 nm and for the Plabutsch tunnel at 80 nm.

Small engines for non-automotive applications include 2-stroke and 4-stroke gasoline engine concepts which have a reduced number of sensors due to cost and packaging constraints. In order to cope with future emission regulations, more sophisticated engine control and monitoring becomes mandatory. Therefore, a cost-effective way has to be found to gain maximum information from the existing sensors and actuators. Due to an increasing bio-fuel share in the market, the detection of bio-fuel content is necessary to guarantee a stable combustion by adapting the injection and ignition control strategy. Meaningful information about the combustion can be retrieved from combustion chamber ion current measurements. This paper proposes a general overview of combustion process monitoring in different engine concepts by measuring the ion current during combustion.

As the number of different engine and vehicle concepts for powered-two wheelers is very high and will even rise with hybridization, the simulation of emissions and fuel consumption is indispensable for further development towards more environmentally friendly mobility. In this work, an adaptive artificial neural network based predictive model for emission and fuel consumption simulation of motorcycles operated in real world conditions is presented. The model is developed in Matlab and Simulink and is integrated into a longitudinal vehicle dynamic simulation whereby it is possible to simulate various and not yet measured test cycles. Subsequently, it is possible to predict real drive emissions RDE and on-road fuel consumption by a minimum of previous measurement effort.

In the research and development of internal combustion engines, there are several drivers for developing an accurate online lube oil consumption (LOC) measurement system. Lube oil consumption is considered to be a root cause of hydrocarbon and particle emissions and lubricating oil autoignition. It also negatively influences the life cycle cost for engine operators. Highly accurate measurement of lube oil consumption must be possible before it can be reduced - or rather optimized - to levels stakeholders will require in the future. State-of-the-art methods such as gravimetric and volumetric measurements are not fully satisfactory for several reasons. Generally, offline LOC measurement is no longer suitable for fast and accurate measuring cycles, oil condition monitoring and wear monitoring. At present, tracer methods are considered to be the most promising approach. However, current tracer methods have their downsides as well.

Measuring emissions of internal combustion engines-not only at steady-state conditions, but also with highly dynamic test cycles-is an important issue in modern engine development. Due to the fact that ambient conditions have an essential influence on power and emissions of internal combustion engines, test beds used for such measurements typically incorporate intake air and exhaust back pressure control for reasons of repeatability, accuracy and comparability. As test cycle dynamics get faster and legal pressure tolerances get narrower, pressure control becomes more demanding and simple PI control schemes are pushed to their limits; therefore, more sophisticated control schemes are necessary. In this paper, a linearised model is first derived and then used to both simplify and optimise PI controller tuning. This is done by means of frequency domain methods. Limitations to such controllers and possible approaches to overcome them are discussed.

Automated, conductive charging systems enable both, the transmission of high charging power for long electric driving distances as well as comfortable and safe charging processes. Especially by the use of heavy and unhandy cables for fast charging, these systems offer user friendly vehicle charging - in particularly in combination with autonomously driving and parking vehicles. This paper deals with the definition of requirements for automated conductive charging stations with standard charging connectors and vehicle inlets and the development of a fully-automated charging robot for electric and plug-in hybrid vehicles. In cooperation with the project partners BMW AG, MAGNA Steyr Engineering, KEBA AG and the Institute of Automotive Engineering at Graz University of Technology, the development and implementation of the prototype took place in the course of a governmental funded research project titled “Comfortable Mobility by Technology Integration (KoMoT)”.

Car driver’s behavior and its influence on driving characteristics play an increasing role in the development of modern vehicles, e.g. in view of efficient powertrain control and implementation of driving assistance functions. In addition, knowledge about actual driving style can provide feedback to the driver and support efficient driving or even safety-related measures. Driving patterns are caused not only by the driver, but also influenced by road characteristics, environmental boundary conditions and other traffic participants. Thus, it is necessary to take the driving circumstances into account, when driving patterns are studied. This work proposes a methodology to cluster and evaluate driving patterns under consideration of vehicle-related parameters (e.g. acceleration and jerk) in combination with additional influencing factors, e.g. road style and inclination. Firstly, segmentation of the trip in distance series is performed to generate micro cycles.

The paper focuses on an optimization methodology, which uses Design of Experiments (DoE) methods to define component parameters of parallel hybrid powertrains such as number of gears, transmission spread, gear ratios, progression factor, electric motor power, electric motor nominal speed, battery voltage and cell capacity. Target is to find the optimal configuration based on specific customer targets (e.g. fuel consumption, performance targets). In the method developed here, the hybrid drive train configuration and the combustion engine are considered as fixed components. The introduced methodology is able to reduce development time and to increase output quality of the early system definition phase. The output parameters are used as a first hint for subsequently performed detailed component development. The methodology integrates existing software tools like AVL CRUISE [5] and AVL CAMEO [1].

CFD has been widely used to predict the flow behavior inside 2-stroke engines over the past twenty years. Usually a mass flow profile or a simple 0D model is used for the inlet boundary condition, which replaces the complete intake geometry, such as reed valve, throttle, and air box geometries. For a CFD simulation which takes into account the exact reed valve geometry, a simulation of all above mentioned domains is required, as these domains are coupled together and thus interact. As the high speed of the engine affects the opening dynamic and closure of the reed valve, the transient data from the crank case volume and the section upstream the reed valve have an important influence on the reed petal dynamic and therewith on the sucked fresh air mass of the engine. This paper covers a methodology for the transient CFD simulation of the reed petals of a 2-stroke engine by using a 2D model.

Discussions about the optimal technology of propulsion systems for future ground vehicles have been raising over the last few years. Several options include different types of technologies. However, those who are advocating conventional internal combustion engines are faced with the fact that fossil fuels are limited. Others favor hydrogen fuel as the solution for the future, either in combination with combustion engines or as an energy carrier for fuel cells. In any case, the production and storage of hydrogen is an ongoing challenge of numerous research works. Finally, there are battery-electric or hybrid propulsion systems in use, gaining more and more popularity worldwide. Ongoing advances in power electronics help to improve control systems within automotive applications. New developed or designed components enable more efficient system architectures and control.

Automotive embedded systems have become very complex, are strongly integrated, and the safety-criticality and real-time constraints of these systems raise new challenges. The OSEK/VDX standard provides an open-ended architecture for distributed real-time capable units in vehicles. This is supported by the OSEK Implementation Language (OIL), a language aiming at specifying the configuration of these real-time operating systems. The challenge, however, is to ensure consistency of the concept constraints and configurations along the entire product development. The contribution of this paper is to bridge the existing gap between model-driven systems engineering and software engineering for automotive real-time operating systems (RTOS). For this purpose a bidirectional tool bridge has been established based on OSEK OIL exchange format files.

Looking at upcoming emission legislations for two-wheelers, it is quite obvious that the fulfilment of these targets will become one of the biggest challenges within the engine development process. The gradual harmonization of emission limits for two-wheelers with existing automotive standards will subsequently lead to new approaches regarding mixture preparation and exhaust gas aftertreatment. Referring to these future scenarios, a state-of-the-art in development of catalytic converters for two- or three-wheeler applications should be presented. After choosing a suitable test carrier, which has already been equipped with EFI components including an oxygen sensor for λ=1 operation mode, a basic injection system calibration was used to optimize the combustion process. Based on this setup, a variable exhaust system was manufactured to be able to integrate different catalyst configurations.

Increasing demands for safety, security, and certifiability of embedded automotive systems require additional development effort to generate the required evidences that the developed system can be trusted for the application and environment it is intended for. Safety standards such as ISO 26262 for road vehicles have been established to provide guidance during the development of safety-critical systems. The challenge in this context is to provide evidence of consistency, correctness, and completeness of system specifications over different work-products. One of these required work-products is the hardware-software interface (HSI) definition. This work-product is especially important since it defines the interfaces between different technologies. Model-based development (MBD) is a promising approach to support the description of the system under development in a more structured way, thus improving resulting consistency.

These days a new generation of hybrid electric vehicles (HEV) are penetrating the global vehicle market - the plug-in hybrid electric vehicles (PHEVs). Compared to conventional HEVs, PHEVs have additional significant potential. They are able to improve fuel efficiency and reduce local emissions due to higher battery capacities, and they can be recharged from external outlets. Energy management has a major impact on the PHEVs performance. In this publication, an innovative operation strategy for PHEVs is presented. This is due to the fact that both increasing fuel efficiency and enhancing the vehicle's longitudinal performance requires a fine balance between the consumption of fossil and electric energy. The new operation strategy combines advanced predictive and adaptive algorithms. In contrast to the charge-sustaining strategy of HEVs, the charge-depleting mode for PHEVs is more appropriate.

Precise three-dimensional dummy head trajectories during crash tests are very important for vehicle safety development. To determine precise trajectories with a standard deviation of approximately 5 millimeters, three-dimensional video analysis is an approved method. Therefore the tracked body is to be seen on at least two cameras during the whole crash term, which is often not given (e.g. head dips into the airbag). This non-continuity problem of video analysis is surmounted by numerical integration of differential un-interrupted electrical rotation and acceleration sensor signals mounted into the tracked body. Problems of this approach are unknown sensor calibration errors and unknown initial conditions, which result in trajectory deviations above 10 centimeters.

This work presents a physical model that calculates the efficiency maps of the inverter-fed Permanent Magnet Synchronous Machine (PMSM) drive. The corresponding electrical machine and its controller are implemented based on the two-phase (d-q) equivalent circuits that take into account the copper loss as well as the iron loss of the PMSM. A control strategy that optimizes the machine efficiency is applied in the controller to maximize the possible output torque. In addition, the model applies an analytical method to predict the losses of the voltage source inverter. Consequently, the efficiency maps within the entire operating region of the PMSM drive can be derived from the simulation results, and they are used to represent electric drives in the system simulation model of electric vehicles (EVs).

Hybrid electric vehicles (HEVs) with a power-split system offer a variety of possibilities in reduction of CO2 emissions and fuel consumption. Power-split systems use a planetary gear sets to create a strong mechanical coupling between the internal combustion engine, the generator and the electric motor. This concept offers rather low oscillations and therefore passive damping components are not needed. Nevertheless, during acceleration or because of external disturbances, oscillations which are mostly influenced by the ICE, can still occur which leads to a drivability and performance downgrade. This paper proposes a design of an active damping control system which uses the electric motor to suppress those oscillations instead of handling them within the ICE control unit. The control algorithm is implemented as part of an existing hybrid controller without any additional hardware introduced.

The enhancement of efficiency will play a more and more important role in the development of future (small) internal combustion engines. In recent years, the Atkinson cycle, realized over the crank drive, has attracted increasing attention. Several OEMs have been doing investigations on this efficiency-increasing principle with in the whole range from small engines up to automotive ones. In previous publications, the authors stated that an indicated efficiency of up to 48% could be reached with an Atkinson cycle-based engine. However, these studies are based on 1D-CFD simulation. To verify the promising simulation results, a prototype engine, based on the Atkinson principle, was designed and experimentally tested. The aim of the present study is to evaluate and validate the (indicated) engine efficiency gained by experimental tests compared to the predicted simulation results. In order to investigate part load behavior, several valve timing strategies were also developed and tested.

In the next 20 years the share of small electric vehicles (SEVs) will increase especially in urban areas. SEVs show distinctive design differences compared to traditional vehicles. Thus the consequences of impacts of SEVs with vulnerable road users (VRUs) and other vehicles will be different from traditional collisions. No assessment concerning vehicle safety is defined for vehicles within European L7e category currently. Focus of the elaborated methodology is to define appropriate test scenarios for this vehicle category to be used within a virtual tool chain. A virtual tool chain has to be defined for the realization of a guideline of virtual certification. The derivation and development of new test conditions for SEVs are described and are the main focus of this work. As key methodology a prospective methodical analysis under consideration of future aspects like pre-crash safety systems is applied.

Advanced Driver Assistance Systems (ADAS) for collision avoidance/mitigation have already demonstrated their benefit on vehicle safety. Often those systems have an additional functionality for comfort to assist the driver in non-critical driving. The verification of ADAS functionality using different test scenarios is currently investigated in many different projects worldwide. A harmonization of test scenarios and evaluation criteria is not yet accomplished. Often, these test scenarios focus on objective collision avoidance and not on the subjective interaction between driver and vehicle. The present study deals with the development of an experimental validation plan for the systems Automatic Cruise Control (ACC), Lane Departure Warning (LDW) and Lane Keeping Assist (LKA). Standardized driving maneuvers with two or more vehicles equipped with synchronized measurement are performed by professional test drivers.