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Technical Paper

A Combined Physical / Neural Approach for Real-Time Models of Losses in Combustion Engines

2007-04-16
2007-01-1345
Reliable estimation of pumping and friction losses in modern combustion engines allows better control strategies aiming at optimal fuel consumption and emissions. Sophisticated simulation tools enable detailed simulation of losses based as well on physical and thermodynamic laws as well as on design data. Models embedded in these tools however are not real-time capable and cannot be implemented into the programs of the electronic control units (ECU's). In this paper an approach is presented that estimates the pumping and friction losses of a combustion engine with variable valve train (VVT). Particularly the pumping losses strongly depend on the control of variable valve train by ECU. The model is based on a combination of a globally physical structure embedding data driven sub models based on test bed measurements. Losses are separated concerning different component groups (bearings, pistons, etc.).
Technical Paper

Tailor-Made Fuels for Future Advanced Diesel Combustion Engines

2009-06-15
2009-01-1811
The finite nature and instability of fossil fuel supply has led to an increasing and enduring investigation demand of alternative and regenerative fuels. The Institute for Combustion Engines at the RWTH Aachen University carried out an investigation program to explore the potential of tailor made fuels to reduce engine-out emissions while maintaining engine efficiency and an acceptable noise level. To enable optimum engine performance a range of different hydrocarbons having different fuel properties like cetane number, boiling temperature and different molecular compositions have been investigated. Paraffines and naphthenes were selected in order to better understand the effects of molecular composition and chain length on emissions and performance of an engine that was already optimized for advanced combustion performance. The diesel single-cylinder research engine used in this study will be used to meet Euro 6 emissions limits and beyond.
Technical Paper

Catalyst Aging Method for Future Emissions Standard Requirements

2010-04-12
2010-01-1272
This paper describes an alternative catalyst aging process using a hot gas test stand for thermal aging. The solution presented is characterized by a burner technology that is combined with a combustion enhancement, which allows stoichiometric and rich operating conditions to simulate engine exhaust gases. The resulting efficiency was increased and the operation limits were broadened, compared to combustion engines that are typically used for catalyst aging. The primary modification that enabled this achievement was the recirculation of exhaust gas downstream from catalyst back to the burner. The burner allows the running simplified dynamic durability cycles, which are the standard bench cycle that is defined by the legislation as alternative aging procedure and the fuel shut-off simulation cycle ZDAKW. The hot gas test stand approach has been compared to the conventional engine test bench method.
Technical Paper

Acoustics of Hybrid Vehicles

2010-06-09
2010-01-1402
The technology used in hybrid vehicle concepts is significantly different from conventional vehicle technology with consequences also for the noise and vibration behavior. In conventional vehicles, certain noise phenomena are masked by the engine noise. In situations where the combustion engine is turned off in hybrid vehicle concepts, these noise components can become dominant and annoying. In hybrid concepts, the driving condition is often decoupled from the operation state of the combustion engine, which leads to unusual and unexpected acoustical behavior. New acoustic phenomena such as magnetic noise due to recuperation occur, caused by new components and driving conditions. The analysis of this recuperation noise by means of interior noise simulation shows, that it is not only induced by the powertrain radiation but also by the noise path via the powertrain mounts. The additional degrees of freedom of the hybrid drive train can also be used to improve the vibrational behavior.
Technical Paper

Investigation of Predictive Models for Application in Engine Cold-Start Behavior

2004-03-08
2004-01-0994
The modern engine development process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust after-treatment and emission testing is becoming increasingly more sophisticated. It is expected that predictive simulation tools that encompass the entire powertrain can potentially improve the efficiency of the calibration process. The testing of an ECU using a HiL system requires a real-time model. Additionally, if the initial parameters of the ECU are to be defined and tested, the model has to be more accurate than is typical for ECU functional testing. It is possible to enhance the generalization capability of the simulation, with neuronal network sub-models embedded into the architecture of a physical model, while still maintaining real-time execution. This paper emphasizes the experimental investigation and physical modeling of the port fuel injected SI engine.
Technical Paper

The Impact of new Technologies and Tools on the Vehicle and Engine Development Process

2001-03-05
2001-01-0771
Technological progress opens the door for the development of new tools to be used for the development of vehicles and engines. This offers the opportunity for an optimization of the entire workflow on one hand, and an improvement of single tasks on the other hand. This paper describes the actual status of the development process, describes new directions of tool evolvement and finally gives an outlook into the future. Redline ADAPT-SIM is a tool for driver- and vehicle simulation, which was developed primarily for ECU application, but can also be used for other dynamic testing tasks. The introduction of this tool leads to better controllability and therefore also repeatability of tests.
Technical Paper

A New Approach to Boost Pressure and EGR Rate Control Development for HD Truck Engines with VGT

2002-03-04
2002-01-0964
Future HD Diesel engine technology is facing a combination of both extremely low exhaust emission standards (US 2002/2004, EURO IV and later US 2007, EURO V) and new engine test procedures such as the European Transient Cycle (ETC) in Europe and the Not-to-Exceed Area (NTE) in the US). Customers furthermore require increased engine performance, improved efficiency, and long-term durability. In order to achieve all targets simultaneously, future HD Diesel engines must have improved fuel injection and combustion systems and utilize suitable technologies such as exhaust gas recirculation (EGR), variable geometry turbine turbocharger systems (VGT) and exhaust gas after-treatment systems. Future systems require precision controlled EGR in combination with a VGT-turbocharger during transient operation. This will require new strategies and calibration for the Electronic Engine Control Unit (ECU).
Technical Paper

SI Engine Emissions Model Based on Dynamic Neural Networks and D-Optimality

2005-04-11
2005-01-0019
In the last two decades the abilities of neural networks as universal approximation tools of non linear functional relationships as well as identification tools for nonlinear dynamic systems have been recognized and used successfully in many applications areas like modelling, control and diagnosis of technical systems. At the same time an increasing interest in optimal design methods is observed. Design of experiment is used to cope with the growing amount of measurements needed for the calibration of engines due to the rising number of control variables to be considered and the need for more accuracy in the description of engine behaviour to derive the best control strategies. In this paper a strategy for the integration of the concept of D-optimality in the learning process of neural networks is proposed. This leads to an optimal selection of data to be presented to the training procedure of the neural network aiming to a generation of robust neural models using fewer training data.
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