Documents disponibles écrits par cet auteur

Engine emission modeling using a mixed physics and regression approach / Michael Benz in Transactions of the ASME . Journal of engineering for gas turbines and power, Vol. 132 N° 4 (Avril 2010) 

Public ISBD [article]  in Transactions of the ASME . Journal of engineering for gas turbines and power > Vol. 132 N° 4 (Avril 2010) . - 11 p. Titre : Engine emission modeling using a mixed physics and regression approach Type de document : texte imprimé Auteurs : Michael Benz, Auteur ; Christopher H. Onder, Auteur ; Lino Guzzella, Auteur Année de publication : 2010 Article en page(s) : 11 p. Note générale : Génie Mécanique Langues : Anglais (eng) Mots-clés : Air  pollution  control  Artificial  intelligence  Diesel  engines  Engine  cylinders  Fuel  economy  Genetic  algorithms  Neurocontrollers  Regression  analysis Index. décimale : 620.1 Essais des matériaux. Défauts des matériaux. Protection des matériaux Résumé : This paper presents a novel control-oriented model of the raw emissions of diesel engines. An extended quasistationary approach is developed where some engine process variables, such as combustion or cylinder charge characteristics, are used as inputs. These inputs are chosen by a selection algorithm that is based on genetic-programming techniques. Based on the selected inputs, a hybrid symbolic regression algorithm generates the adequate nonlinear structure of the emission model. With this approach, the model identification efforts can be reduced significantly. Although this symbolic regression model requires fewer than eight parameters to be identified, it provides results comparable to those obtained with artificial neural networks. The symbolic regression model is capable of predicting the behavior of the engine in operating points not used for the model parametrization, and it can be adapted easily to other engine classes. Results from experiments under steady-state and transient operating conditions are used to show the accuracy of the presented model. Possible applications of this model are the optimization of the engine system operation strategy and the derivation of virtual sensor designs. DEWEY : 620.1 ISSN : 0742-4795 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JETPEZ000132000004 [...] [article] Engine emission modeling using a mixed physics and regression approach [texte imprimé] / Michael Benz, Auteur ; Christopher H. Onder, Auteur ; Lino Guzzella, Auteur . - 2010 . - 11 p. Génie Mécanique Langues : Anglais (eng) in Transactions of the ASME . Journal of engineering for gas turbines and power > Vol. 132 N° 4 (Avril 2010) . - 11 p. Mots-clés : Air  pollution  control  Artificial  intelligence  Diesel  engines  Engine  cylinders  Fuel  economy  Genetic  algorithms  Neurocontrollers  Regression  analysis Index. décimale : 620.1 Essais des matériaux. Défauts des matériaux. Protection des matériaux Résumé : This paper presents a novel control-oriented model of the raw emissions of diesel engines. An extended quasistationary approach is developed where some engine process variables, such as combustion or cylinder charge characteristics, are used as inputs. These inputs are chosen by a selection algorithm that is based on genetic-programming techniques. Based on the selected inputs, a hybrid symbolic regression algorithm generates the adequate nonlinear structure of the emission model. With this approach, the model identification efforts can be reduced significantly. Although this symbolic regression model requires fewer than eight parameters to be identified, it provides results comparable to those obtained with artificial neural networks. The symbolic regression model is capable of predicting the behavior of the engine in operating points not used for the model parametrization, and it can be adapted easily to other engine classes. Results from experiments under steady-state and transient operating conditions are used to show the accuracy of the presented model. Possible applications of this model are the optimization of the engine system operation strategy and the derivation of virtual sensor designs. DEWEY : 620.1 ISSN : 0742-4795 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JETPEZ000132000004 [...]

Iterative tuning of internal model controllers with application to air/fuel ratio control / Daniel Rupp in IEEE Transactions on control systems technology, Vol. 18 N° 1 (Janvier 2010) 

Public ISBD [article]  in IEEE Transactions on control systems technology > Vol. 18 N° 1 (Janvier 2010) . - pp. 177-184 Titre : Iterative tuning of internal model controllers with application to air/fuel ratio control Type de document : texte imprimé Auteurs : Daniel Rupp, Auteur ; Lino Guzzella, Auteur Année de publication : 2011 Article en page(s) : pp. 177-184 Note générale : Génie Aérospatial Langues : Anglais (eng) Mots-clés : Air/fuel  ratio  (AFR)  Identification  for  control  Internal  model  control  Iterative  feedbak  tuning  (IFT)  Oxygen  sensor Index. décimale : 629.1 Résumé : A new tuning method for internal model controllers (IMCs) is presented. The parameters of an IMC can be structurally assigned to two groups: 1) parameters of the internal model and 2) parameters of the controller. The method described in this brief suggests a sequential tuning of the two parameter groups. For both groups, the parameter values are found by minimizing a predefined cost function. The optimization is run with a gradient-based minimization procedure where, analogously to the well-known iterative feedback tuning (IFT) scheme, the gradients are computed from signals obtained from closed-loop experiments. Thus, for the calculation of the gradient, the unknown plant is utilized, whereas other ??local?? tuning methods suggest the replacement of the real plant by its model to calculate the gradient. The main advantages of the suggested algorithm are its inherent operation in the closed control loop and the fact that, for the tuning of the internal model, no information about the disturbance model is required. The method can be used either for an initial tuning of the controller or for autotuning during operation. DEWEY : 629.1 ISSN : 1063-6536 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5075514 [article] Iterative tuning of internal model controllers with application to air/fuel ratio control [texte imprimé] / Daniel Rupp, Auteur ; Lino Guzzella, Auteur . - 2011 . - pp. 177-184. Génie Aérospatial Langues : Anglais (eng) in IEEE Transactions on control systems technology > Vol. 18 N° 1 (Janvier 2010) . - pp. 177-184 Mots-clés : Air/fuel  ratio  (AFR)  Identification  for  control  Internal  model  control  Iterative  feedbak  tuning  (IFT)  Oxygen  sensor Index. décimale : 629.1 Résumé : A new tuning method for internal model controllers (IMCs) is presented. The parameters of an IMC can be structurally assigned to two groups: 1) parameters of the internal model and 2) parameters of the controller. The method described in this brief suggests a sequential tuning of the two parameter groups. For both groups, the parameter values are found by minimizing a predefined cost function. The optimization is run with a gradient-based minimization procedure where, analogously to the well-known iterative feedback tuning (IFT) scheme, the gradients are computed from signals obtained from closed-loop experiments. Thus, for the calculation of the gradient, the unknown plant is utilized, whereas other ??local?? tuning methods suggest the replacement of the real plant by its model to calculate the gradient. The main advantages of the suggested algorithm are its inherent operation in the closed control loop and the fact that, for the tuning of the internal model, no information about the disturbance model is required. The method can be used either for an initial tuning of the controller or for autotuning during operation. DEWEY : 629.1 ISSN : 1063-6536 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5075514

Torque-assist hybrid electric powertrain sizing: from optimal control towards a sizing law / Olle Sundstrom in IEEE Transactions on control systems technology, Vol. 18 N° 4 (Juillet 2010) 

Public ISBD [article]  in IEEE Transactions on control systems technology > Vol. 18 N° 4 (Juillet 2010) . - pp. 837-849 Titre : Torque-assist hybrid electric powertrain sizing: from optimal control towards a sizing law Type de document : texte imprimé Auteurs : Olle Sundstrom, Auteur ; Lino Guzzella, Auteur ; Patrik Soltic, Auteur Année de publication : 2011 Article en page(s) : pp. 837-849 Note générale : Génie Aérospatial Langues : Anglais (eng) Mots-clés : Fuel  optimal  Optimization  methods  Road  vehicle  propulsion Index. décimale : 629.1 Résumé : In this study a novel method is proposed with which the optimal hybridization ratio of a torque-assist hybrid electric powertrain can be found with very little computational effort. The objective is to minimize the total CO2 emissions of the vehicle, while maintaining its drivability at a constant level. The starting point is an analysis in which the optimal driving strategy is found for eight typical driving cycles using dynamic programming. Analyzing these results, a simple yet powerful rule-based method is proposed that allows to choose the sizes of the combustion engine and of the electric motor such that the CO2 emissions are very close to the minimum value, i.e., with a deviation of less than 1% for most driving cycles. DEWEY : 629.1 ISSN : 1063-6536 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5282521 [article] Torque-assist hybrid electric powertrain sizing: from optimal control towards a sizing law [texte imprimé] / Olle Sundstrom, Auteur ; Lino Guzzella, Auteur ; Patrik Soltic, Auteur . - 2011 . - pp. 837-849. Génie Aérospatial Langues : Anglais (eng) in IEEE Transactions on control systems technology > Vol. 18 N° 4 (Juillet 2010) . - pp. 837-849 Mots-clés : Fuel  optimal  Optimization  methods  Road  vehicle  propulsion Index. décimale : 629.1 Résumé : In this study a novel method is proposed with which the optimal hybridization ratio of a torque-assist hybrid electric powertrain can be found with very little computational effort. The objective is to minimize the total CO2 emissions of the vehicle, while maintaining its drivability at a constant level. The starting point is an analysis in which the optimal driving strategy is found for eight typical driving cycles using dynamic programming. Analyzing these results, a simple yet powerful rule-based method is proposed that allows to choose the sizes of the combustion engine and of the electric motor such that the CO2 emissions are very close to the minimum value, i.e., with a deviation of less than 1% for most driving cycles. DEWEY : 629.1 ISSN : 1063-6536 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5282521