Crank-Angle Resolved Real-Time Capable Engine and Vehicle Simulation - Fuel Consumption and Driving Performance

Wurzenberger, Johann C.; Bartsch, P.; Katrašnik, Tomaž

doi:10.4271/2010-01-0784

Cited by 35 publications

(20 citation statements)

References 11 publications

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“…The combustion is modelled using rate-ofheat-release curves derived from experimental incylinder pressure traces. This ensures a consistent comparison of numerical and experimental cylinder pressure traces [4]. Fig.…”

Section: Comparison Of Numerical and Experimental Resultsmentioning

confidence: 99%

“…Therefore, the crank angle resolved cylinder model presented here is embedded into a mean value based gas path model of the engine manifolds [4]. As presented in [4], the overall model is applied to a turbocharged, intercooled 4-cylinder diesel engine with a cooled external EGR and variable geometry turbine. The combustion is modelled using rate-ofheat-release curves derived from experimental incylinder pressure traces.…”

Section: Comparison Of Numerical and Experimental Resultsmentioning

confidence: 99%

“…[1] to [4], have emerged as a promising approach for real-time engine simulations of internal combustion engines (ICE) and hybrid powertrain of heavy-duty engines [5]. Unlike higher resolution 1-D, e.g.…”

mentioning

confidence: 99%

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On the Convergence, Stability, and Computational Speed of Numerical Schemes for 0-D IC Engine Cylinder Modelling

Katrašnik¹,

Schuemie²,

Wurzenberger³

2013

SV-JME

Self Cite

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The steadily increasing demands on vehicle fuel economy, emissions, and performance are a major driving force in developing and optimising future powertrains. In order to meet customers' and legislative requirements it is of particular importance not only to simulate and optimise different powertrain elements, but also to develop simulation models capable of modeling the performance of the powertrain system as a whole. The latter is of particular importance for developing and testing components in a virtual environment, as well as for accompanying the conventional development steps from design phases in the office to the application and validation phases on the test bed. Test bed validation, development and calibration of components in the hardware-in-the-loop (HiL) environment and modelbased engine controlling require real-time capable simulation models. Moreover, computational speed is also of considerable importance when simulating complete emission test cycles where engine and vehicle dynamics are simulated on time scales of 10 3 s.Recently, 0-dimensional (0-D) crank-angle (CA) resolved engine simulation models, e.g. [1] to [4], have emerged as a promising approach for real-time engine simulations of internal combustion engines (ICE) and hybrid powertrain of heavy-duty engines [5]. Unlike higher resolution 1-D, e.g.[6] to [9], and 3-D models, e.g.[10] and [11], 0-D models can comply with realtime constraints and provide a higher level of detail compared to mean-value engine models, e.g. [12] and [13]. The latter models reach their limits when future control functions need to be taken into account, which incorporate CA resolved events such as cylinder pressure based control functions, electronic control unit controlled fuel injections, and variable valve timing. Mean-value engine models are not able to model these phenomena predictably since they rely on experimental data that are used to tune or train the model as presented in [14] for camshaft variability.Besides computational speed, the convergence and stability of numerical solution algorithms are the prerequisites for the successful application of 0-D CA resolved engine simulation models. This topic has not yet been systematically analysed in the literature and therefore the presented paper aims to provide a study of the convergence, stability, and computational speed of different explicit and implicit integration schemes.The cylinder model represents the crucial element to attaining high computational speed and accuracy of results, since the time variation of the thermodynamic variables is most pronounced in the cylinder due to piston kinematics and combustion. It is common practice to validate the accuracy of simulation models by comparing numerical and experimental results. This indeed gives an indication of the consistency On the Convergence, Stability, and Computational Speed of Numerical Schemes for 0-D IC Engine Cylinder Modelling

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Section: Comparison Of Numerical and Experimental Resultsmentioning

confidence: 99%

Section: Comparison Of Numerical and Experimental Resultsmentioning

confidence: 99%

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On the Convergence, Stability, and Computational Speed of Numerical Schemes for 0-D IC Engine Cylinder Modelling

Katrašnik¹,

Schuemie²,

Wurzenberger³

2013

SV-JME

Self Cite

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“…Such models might have significant limitations when applied to transient conditions that are far from steady-state [1,5,6]. However, also more sophisticated methodologies for estimating transient engine performance from steady-state maps [1], might not be sufficiently accurate, since during transient operation performance and particularly emissions of the engines significantly differ from the corresponding steady-state values as presented in [7][8][9]. This is even more pronounced for turbocharged engines with Exhaust Gas Recirculation (EGR).…”

Section: Introductionmentioning

confidence: 93%

“…As discernable from Figure 3, the interaction between the gas path and the turbocharger dynamics as well as the EGR flow are modeled on a mechanistic basis in the mean value gas path approach. This is crucial for simulating transient engine operation [8].…”

Section: Internal Combustion Enginementioning

confidence: 99%

Optimization of Hybrid Power Trains by Mechanistic System Simulations

Katrašnik

Wurzenberger

2013

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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Re´sume´-Optimisation de groupes motopropulseurs e´lectriques hybrides par simulation du syste`me me´canique -L'article pre´sente un mode`le de simulation au niveau me´canique destine´a`la mode´lisation de topologies de ve´hicules hydrides et conventionnels. L'article de´crit l'interaction dynamique entre diffe´rents domaines : moteur a`combustion interne, dispositifs de post-traitement d'e´chappement, composants e´lectriques, chaıˆne cine´matique me´canique, circuit de refroidissement et les unite´s de controˆle correspondantes. Afin d'obtenir un rapport correct entre pre´cision, pre´visibilite´et vitesse de calculs du mode`le, un de´couplage innovant du domaine temporel est pre´sente´, lequel est base´sur l'application a`diffe´rents domaines, d'e´tapes d'inte´gration spe´cifiques au domaine et sur un couplage inter-domaines cohe´rent ulte´rieur des flux. En outre, une structure de calculs efficace permettant la simulation du transport d'espe`ces gazeuses actives et passives est introduite de manie`re a`combiner l'efficacite´des calculs a`la ne´cessite´d'une mode´lisation du transport des polluants dans le circuit des gaz. L'applicabilite´et la versatilite´du mode`le de simulation au niveau me´canique sont pre´sente´es au moyen d'analyses des phe´nome`nes transitoires provoque´s par l'interde´pendance e´leve´e des sous-syste`mes, c'est-a`-dire les domaines. Les re´sultats obtenus pour les ve´hicules hybrides sont compare´s à ceux obtenus pour les ve´hicules conventionnels afin de mettre l'accent sur les diffe´rences des re´gimes ope´ratoires de composants particuliers inhe´rents a`une topologie particulie`re du groupe motopropulseur.Abstract -Optimization of Hybrid Power Trains by Mechanistic System Simulations -The paper presents a mechanistic system level simulation model for modeling hybrid and conventional vehicle topologies. The paper addresses the dynamic interaction between different domains: internal combustion engine, exhaust after treatment devices, electric components, mechanical drive train, cooling circuit system and corresponding control units. To achieve a good ratio between accuracy, predictability and computational speed of the model an innovative time domain decoupling is presented, which is based on applying domain specific integration steps to different domains and subsequent consistent cross-domain coupling of the fluxes. In addition, a computationally efficient framework for transporting active and passive gaseous species is introduced to combine computational efficiency with the need for modeling pollutant transport in the gas path. The applicability and versatility of the mechanistic system level simulations model is presented through analyses of transient phenomena caused by the high interdependency of the sub-systems, i.e. domains. Results of a hybrid vehicle are compared to results of a conventional vehicle to highlight differences in operating regimes of particular components that are inherent to particular power train topology.

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System Simulation in Automotive Industry

Knaus¹,

Wurzenberger²

2020

Systems Engineering for Automotive Powertrain Development

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System simulation is a part of the overall field of systems engineering and provides quantitative results to verify and validate the architecture and parameters of a system under development. In the meantime, system simulation is a wellestablished activity in the automotive development area and covers a broad range of applications over the whole development process from system architecture definition, component dimensioning up to virtual testing and calibration. In all of these steps, simulation helps the systems engineer find the best choice of system architectures, evaluate the component target characteristics, define the control logic and parameters, and support the individual tests. Thanks to system simulation, proper system function can be confirmed in early phases of development, which minimizes the number of cost-intensive development loops. In addition, verification and validation and calibration tasks can be frontloaded to reduce overall development time. This chapter focuses on the setup of different physical domain models and how they are linked together. The modeling approaches of the individual domains and simulation management are discussed.

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Crank-Angle Resolved Real-Time Capable Engine and Vehicle Simulation - Fuel Consumption and Driving Performance

Cited by 35 publications

References 11 publications

On the Convergence, Stability, and Computational Speed of Numerical Schemes for 0-D IC Engine Cylinder Modelling

On the Convergence, Stability, and Computational Speed of Numerical Schemes for 0-D IC Engine Cylinder Modelling

Optimization of Hybrid Power Trains by Mechanistic System Simulations

System Simulation in Automotive Industry

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