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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.

To get an overview of the emission situation in the field of small non-road mobile machinery powered by various types of SI engines, the Association for Emissions Control by Catalyst (AECC), together with the Institute for Internal Combustion Engines and Thermodynamics (IVT) of Graz University of Technology, conducted a customized test program. The main goal for this campaign was to derive information regarding the emissions of regulated gaseous components (following European Directive 97/68/EC) as well as particulate matter. With regard to the big variety of different engines that are available on the European and North-American market, the most representative ones had to be chosen. This resulted in a pool of test devices to cover different engine working principles (2-Stroke and 4-Stroke), technological standards (low-cost and professional tools) and different emissions control strategies (advanced combustion and exhaust gas aftertreatment).

The European emission legislation for two-wheeler vehicles driven by engines of ≤ 50 cm₃ is continuously developing. One of the most important issues in the near future will be the finalization of the European Commission's proposals for future steps in the emissions regulations as well as the verification of the impacts of current standards on the market. To have a basis for the discussion about these topics, the Association for Emissions Control by Catalyst (AECC) with the Institute for Internal Combustion Engines and Thermodynamics of Graz University of Technology (IVT) carried out an extensive test program to show the actual emission situation of state-of-the-art mopeds including mass and number of particulate matter as well as unregulated gaseous components. One of the main goals of these tests was to measure exhaust emissions without any modifications to the engines of standard production vehicles available on the European market.

In hybrid electric vehicles (HEV), the operation strategy strongly influences the available system power, as well as local exhaust emissions. Predictive operation strategies rely on knowledge of future traction-force demands. This predicted information can be used to balance the battery’s state of charge or the engine’s thermal system in their legal operation limits and can reduce peak loads. Assuming the air and rolling drag-coefficient to be constant, the desired vehicle velocity, vehicle-mass and longitudinal driving resistances determine the vehicle’s traction-force demand. In this paper, a novel methodology, combining a history-based prediction algorithm for estimating future traction-force demands with the parameter identification of road grade angle and vehicle mass, is proposed. It is solely based on a route-history database and internal vehicle data, available on its on-board communication and measuring systems.

Trends towards lower vehicle fuel consumption and smaller environmental impact will increase the share of Diesel hybrids and Diesel Range Extended Vehicles (REV). Because of the Diesel engine presence and the ever tightening soot particle emissions, these vehicles will still require soot particle emissions control systems. Ceramic wall-flow monoliths are currently the key players in the Diesel Particulate Filter (DPF) market, offering certain advantages compared to other DPF technologies such as the metal based DPFs. The latter had, in the past, issues with respect to filtration efficiency, available filtration area and, sometimes, their manufacturing cost, the latter factor making them less attractive for most of the conventional Diesel engine powered vehicles. Nevertheless, metal substrate DPFs may find a better position in vehicles like Diesel hybrids and REVs in which high instant power consumption is readily offered enabling electrical filter regeneration.

During recent years the accident simulation program PC-Crash was developed. This software simulates vehicle movement before, during and after the impact, using 3D vehicle and scene models. When reconstructing car accidents, quite often questions arise regarding occupant movement and loading. Especially important is the influence of different types of restraint systems on the occupant. MADYMO® is a software tool which was developed by TNO in the Netherlands and which is well known in the automotive industry for the simulation of occupant movement. It allows the simulation of all kinds of modern restraint systems such as airbags and seatbelts with and without pretensioners. As the software is used in the automotive industry quite extensively, a huge validated database of dummy and human models is available. Since MADYMO® demands the setup of quite complicated input files, its use normally requires a high level of expertise.

Future legislation, like EURO IV and EURO V or the US 2007 HD regulation will have massive reduction of particulate emission limits. For this beside improvement of engine combustion also exhaust aftertreatment systems are under investigation, like Diesel Particulate Filters (DPF), or Selective Catalytic Reduction (SCR) of Nitrogen Oxides. For all those tasks transient soot emission monitoring is one of the key features. To meet this demand a new device for the on-line measurement of soot emitted by combustion engines has been developed. Based on the photoacoustic principle, which has been optimized for automotive applications and easy use in test cells, the instrument shows a sensitivity of 5μg/m3, which is lower than current particulate immission standards in ambient air, and a time resolution of 1 sec. In the paper first the principles of measurement are shown, and then the specifications and results from measurements of very low soot concentration in the exhaust gas are presented.

Particulates are among the most harmful emission components of internal combustion engines (ICE)). Thus, emission limits have been widely introduced, e.g., for light- and heavy-duty vehicles. Although there are still engine applications without particulate limitations, the measurement of particulate mass (PM) and particulate number (PN) emissions is therefore of special interest for the development and operation of ICE. For this purpose, a measurement system for PN consisting of a custom-built sample conditioning and dilution system, and a TSI 3790-A10 [1] condensation particle counter (CPC) as particle number counter (PNC) was designed and built. In this work, we present the conditioning and dilution system, the operational parameters, and results from the particle concentration reduction factor (PCRF) calibration.

The reduction of particulate emissions limits requires new tools for the tuning of engines and exhaust aftertreatment systems. Time-resolved monitoring of low soot emissions is a key feature for such developments. The paper describes an improved photoacoustic soot sensor, and presents its applications for the characterization of transient exhaust soot emissions before and after Diesel emission after-treatment systems. The detection limit of the unit is around 5 μg/m3 soot, which is two orders of magnitude better than conventional time-resolved transmission measurement. Additionally, a wide dynamic range of four orders of magnitude can be achieved without range switching. The photoacoustic signal is proportional to the soot mass, no significant cross-sensitivities to gaseous absorbers were detected.

The measurement of the particle number (PN) concentration of non-volatile particles ≻23 nm was introduced in the light-duty vehicles regulation; the heavy-duty regulation followed. Based on the findings of the Particle Measurement Program (PMP), heavy-duty inter-laboratory exercise, the PN concentration measurement can be conducted either from the full dilution tunnel with constant volume sampling (CVS) or from the partial flow dilution system (PFDS). However, there are no other studies that investigate whether the PN results from the two systems are equivalent. In addition, even the PMP study never investigated the uncertainty that is introduced at the final result from the extraction of a flow by a PN system from the PFDS. In this work we investigate the uncertainty for the three possible cases, i.e., considering a constant extracted flow from the PFDS, sending a signal with 1 Hz frequency to the PFDS, or feeding back the extracted flow to the PFDS.

Eliminating toxic exhaust emissions, amongst them particulate matter (PM), is one of the driving factors behind the increasing use of electrified vehicles. However, it is frequently overseen that PM arise not only from combustion, but from non-exhaust traffic related causes as well; in particular from the vehicle brakes, tires and the road surface. Furthermore, as electrified vehicles weigh more and typically exhibit higher torques at low speeds, their non-exhaust emissions tend to be higher than for comparable conventional vehicles, especially those generated by tires. Fortunately, tire related emissions are directly related to tire wear, so that limiting tire wear can reduce these emissions as well. This can be accomplished by intelligently modulating the vehicle torque profile in real time, to limit the operation in conditions of higher tire wear.

A calibration and validation workflow will be presented in this paper, which utilizes common static global models for fuel consumption, NOx and soot. Due to the applicability for warm-up tests, e.g. New European Driving Cycle (NEDC), the models need to predict the temperature influence and will be fitted with measuring data from a conditioned engine test bed. The applied model structure consisting of a number of global data-based sub-models is configured especially for the requirements of multi-injection strategies of common rail systems. Additionally common global models for several constant coolant water temperature levels are generated and the workflow tool supports the combination and segmentation of global nominal map with temperature correction maps for seamless and direct ECU setting.

One of the most significant current discussions worldwide is the anthropogenic climate change accompanying fossil fuel consumption. Sustainable development in all fields of combustion engines is required with the principal objective to enhance efficiency. This certainly concerns the field of hand-held power tools as well. Today, two-stroke SI engines equipped with a carburetor are the most widely used propulsion technology in hand-held power tools like chain saws and grass trimmers. To date, research tended to focus on two-stroke engines with rich mixture setting. In this paper the advantages and challenges of leaner and/or lean operation are discussed. Experimental investigations regarding the influence of equivalence ratio on emissions, fuel consumption and power have been performed. Accompanying 3D-CFD simulations support the experiments in order to gain insight into these complex processes. The investigations concentrate on two different mixture formation processes, i.e.

As emission regulations become tighter and tighter, equipment must evolve to be able to achieve the new standards. Also additional test requirements demand a system that is flexible and can accommodate differences both in the tests and the test facility. By that test cell equipment for chassis dynamometer as well as engine dynamometer applications is getting increasingly complex. That also will require new concepts for the design of such systems. In the past emission system design was more likely a collection and packaging process, which has interfaced various independent components. Now, the development of modern analytical emission systems requires a true holistic design process. This paper will describe the demands and the realization of a modern emission system. It can be shown that an extended effort during the design process will result in a high performance system, which still remains simple and robust.

Based on the fundamental analysis of the two-stroke process (SETC 2005-32-0098) and the development of a stratified scavenged small capacity two-stroke engine (SETC 2006-32-0065), a further approach to achieve low emissions in this engine category is the main subject of this publication. The principles of the system are described by design activities, results of the 3D-CFD simulation and the visualization of the spray in the cylinder. The benefit of this system on exhaust emissions is demonstrated by engine test bench as well as chassis dynamometer results. The achievable reduction of exhaust emissions, especially with an applied oxidation catalytic converter, is remarkable and the potential to fulfill future emission limits has already been demonstrated.

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.

The paper describes a universally structured simulation platform which is used for the analysis and prediction of combustion in compression ignition (CI) engines. The models are on a zero-dimensional crank angle resolved basis as commonly used for engine cycle simulations. This platform represents a kind of thermodynamic framework which can be linked to single and multi zone combustion models. It is mainly used as work environment for the development and testing of new models which thereafter are implemented to other codes. One recent development task focused on a multi zone combustion model which corresponds to the approach of Hiroyasu. This model was taken from literature, extended with additional features described in this paper, and implemented into the thermodynamic simulation platform.

With the increased number of variants, the preservation of a brand-specific vehicle DNA becomes more and more important. Paired with growing customer expectations, brand DNA can be a crucial point in the decision-making process of buying a new vehicle. Whereas the customer will assess the DNA subjectively during driving by evaluating the vehicle drive quality (“driveability”), most manufacturers are not merely relying on subjective evaluations by having test drivers perform maneuvers with prototype vehicles. Nowadays, the assessment is performed objectively during the vehicle development process. As a supporting measure, the Anstalt für Verbrennungskraftmaschinen List (AVL) has made the objective assessment tool AVL-DRIVE commercially available. Up to now, the AVL-DRIVE ratings had to be manually analyzed and checked for outliers. Low ratings and high deviations to a priori specified target values are a good starting point for the search of outliers.

This publication covers investigations on different 3D CFD models for the description of the spray wall and droplet-fluid interaction and the influence of these models on the mixture formation calculation results. Basic experimental investigations in a spray chamber and a flow tunnel as well as the corresponding 3D CFD simulation were conducted in order to clarify the prediction quality of the physical phenomena of spray-wall and spray-fluid interaction by the simulation. Influencing parameters such as the piston top temperature, piston bowl geometry, soot deposits on the piston top as well as flow velocity are investigated. This paper provides a direct link between the underlying simulation models of the mixture formation and actual real world combustion system development processes - underlining the importance of a close interaction of the model calibration and the development process.

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.