Relevant bibliographies by topics / Automated Engine Calibration

Academic literature on the topic 'Automated Engine Calibration'

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Published: 14 March 2023

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Journal articles on the topic "Automated Engine Calibration"

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Murgovski, Nikolce, Markus Grahn, Lars Mardh Johannesson, and Tomas McKelvey. "Automated Engine Calibration of Hybrid Electric Vehicles." IEEE Transactions on Control Systems Technology 23, no. 3 (May 2015): 1063–74. http://dx.doi.org/10.1109/tcst.2014.2360920.

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Ma, He, Ziyang Li, Mohamad Tayarani, Guoxiang Lu, Hongming Xu, and Xin Yao. "Model-based computational intelligence multi-objective optimization for gasoline direct injection engine calibration." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 6 (June 4, 2018): 1391–402. http://dx.doi.org/10.1177/0954407018776743.

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For modern engines, the number of adjustable variables is increasing considerably. With an increase in the number of degrees of freedom and the consequent increase in the complexity of the calibration process, traditional design of experiments–based engine calibration methods are reaching their limits. As a result, an automated engine calibration approach is desired. In this paper, a model-based computational intelligence multi-objective optimization approach for gasoline direct injection engine calibration is developed, which can optimize the engine’s indicated specific fuel consumption, indicated specific particulate matter by mass, and indicated specific particulate matter by number simultaneously, by intelligently adjusting the engine actuators’ settings through Strength Pareto Evolutionary Algorithm 2. A mean-value model of gasoline direct injection engine is developed in the author’s earlier work and used to predict the performance of indicated specific fuel consumption, indicated specific particulate matter by mass, and indicated specific particulate matter by number with given value of intake valves opening timing, exhaust valves closing timing, spark timing, injection timing, and rail pressure. Then a co-simulation platform is established for the introduced intelligence engine calibration approach in the given engine operating condition. The co-simulation study and experimental validation results suggest that the developed intelligence calibration approach can find the optimal gasoline direct injection engine actuators’ settings with acceptable accuracy in much less time, compared to the traditional approach.
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Ebrahimi, Kambiz, Antonios Pezouvanis, Mark Cary, Bob Lygoe, Nikolaos Kalantzis, and Tom Fletcher. "Automated engine calibration validation for real world driving conditions." International Journal of Powertrains 9, no. 4 (2020): 345. http://dx.doi.org/10.1504/ijpt.2020.10033157.

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Fletcher, Tom, Nikolaos Kalantzis, Mark Cary, Bob Lygoe, Antonios Pezouvanis, and Kambiz Ebrahimi. "Automated engine calibration validation for real world driving conditions." International Journal of Powertrains 9, no. 4 (2020): 345. http://dx.doi.org/10.1504/ijpt.2020.111251.

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Millo, Federico, Andrea Piano, Benedetta Peiretti Paradisi, Mario Rocco Marzano, Andrea Bianco, and Francesco C. Pesce. "Development and Assessment of an Integrated 1D-3D CFD Codes Coupling Methodology for Diesel Engine Combustion Simulation and Optimization." Energies 13, no. 7 (April 1, 2020): 1612. http://dx.doi.org/10.3390/en13071612.

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In this paper, an integrated and automated methodology for the coupling between 1D- and 3D-CFD simulation codes is presented, which has been developed to support the design and calibration of new diesel engines. The aim of the proposed methodology is to couple 1D engine models, which may be available in the early stage engine development phases, with 3D predictive combustion simulations, in order to obtain reliable estimates of engine performance and emissions for newly designed automotive diesel engines. The coupling procedure features simulations performed in 1D-CFD by means of GT-SUITE and in 3D-CFD by means of Converge, executed within a specifically designed calculation methodology. An assessment of the coupling procedure has been performed by comparing its results with experimental data acquired on an automotive diesel engine, considering different working points, including both part load and full load conditions. Different multiple injection schedules have been evaluated for part-load operation, including pre and post injections. The proposed methodology, featuring detailed 3D chemistry modeling, was proven to be capable assessing pollutant formation properly, specifically to estimate NOx concentrations. Soot formation trends were also well-matched for most of the explored working points. The proposed procedure can therefore be considered as a suitable methodology to support the design and calibration of new diesel engines, due to its ability to provide reliable engine performance and emissions estimations from the early stage of a new engine development.
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Sadykov, M. F. "AUTOMATED MULTIFUNCTIONAL INSTALLATION FOR THE RESEARCH, DEVELOPMENT AND TESTING OF INTERNAL COMBUSTION ENGIN." Proceedings of the higher educational institutions. ENERGY SECTOR PROBLEMS 20, no. 9-10 (January 24, 2019): 138–45. http://dx.doi.org/10.30724/1998-9903-2018-20-9-10-138-145.

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At present, testing and tuning of electronic engine control systems is a long and laborious process, since it is necessary to fulfill all safety requirements, ensure power and environmental parameters and fuel efficiency of the engine being developed. The article describes a multifunctional automated installation for tuning up an electronic control system, speeding up the calibration and modification of algorithms for electronic control systems of an internal combustion engine, and to work off reactions to occurring malfunctions.
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Asprion, Jonas, Oscar Chinellato, and Lino Guzzella. "Optimal Control of Diesel Engines: Numerical Methods, Applications, and Experimental Validation." Mathematical Problems in Engineering 2014 (2014): 1–21. http://dx.doi.org/10.1155/2014/286538.

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In response to the increasingly stringent emission regulations and a demand for ever lower fuel consumption, diesel engines have become complex systems. The exploitation of any leftover potential during transient operation is crucial. However, even an experienced calibration engineer cannot conceive all the dynamic cross couplings between the many actuators. Therefore, a highly iterative procedure is required to obtain a single engine calibration, which in turn causes a high demand for test-bench time. Physics-based mathematical models and a dynamic optimisation are the tools to alleviate this dilemma. This paper presents the methods required to implement such an approach. The optimisation-oriented modelling of diesel engines is summarised, and the numerical methods required to solve the corresponding large-scale optimal control problems are presented. The resulting optimal control input trajectories over long driving profiles are shown to provide enough information to allow conclusions to be drawn for causal control strategies. Ways of utilising this data are illustrated, which indicate that a fully automated dynamic calibration of the engine control unit is conceivable. An experimental validation demonstrates the meaningfulness of these results. The measurement results show that the optimisation predicts the reduction of the fuel consumption and the cumulative pollutant emissions with a relative error of around 10% on highly transient driving cycles.
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Yahagi, Shuichi, Itsuro Kajiwara, and Tomoaki Shimozawa. "Slip control during inertia phase of clutch-to-clutch shift using model-free self-tuning proportional-integral-derivative control." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, no. 9 (April 8, 2020): 2279–90. http://dx.doi.org/10.1177/0954407020907257.

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Transmissions require a good shift feeling and improved fuel efficiency. In state-of-the-art stepped automated transmissions, the number of gear stages increases, and the lock-up area is expanded to improve fuel efficiency. However, this makes it difficult to obtain a good shift feeling and it takes a large number of calibration man-hours. Therefore, to reduce the number of calibration man-hours and improve the shift feeling, we propose a slip control law between the engine and the clutch, which is composed of a proportional-integral-derivative (PID) controller and a disturbance observer. Moreover, PID gain is adjusted online by installing an automatic tuning method, which does not require a controlled object model. The effects of the proposed method are verified via an experiment using an actual vehicle. The experimental results show that the proposed method is effective for automatically adjusting PID gain and improving the shift feeling of the stepped automated transmission.
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Evdonin, E. S., P. V. Dushkin, A. I. Kuzmin, S. S. Khovrenok, and V. V. Kremnev. "Automation of an automobile internal combustion engine bench calibration tests." Trudy NAMI, no. 4 (January 4, 2022): 12–21. http://dx.doi.org/10.51187/0135-3152-2021-4-12-21.

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Introduction (problem statement and relevance). The article presents the work on the automation of an internal combustion engine (ICE) calibration tests results on a motor stand. The relevance of the article is due to the high labor intensity of such tests, the complexity of documentation and decisionmaking based on the results of the work.Purpose of the study. This work is part of a comprehensive methodology, the purpose of which is to reduce the duration of tests and improve the calibration results quality of the vehicle’s power plant. The entire methodology description as a whole is also given in the publication.Methodology and research methods. The achievement of this goal is ensured with the help of special systems – INCA-FLOW (test automation) and ASCMO (processing results and optimization), produced by Bosch/ETAS. The approbation of the technique was carried out on a motor stand in the MADI training box in relation to the problem of forming an ignition timing map.Scientific novelty and results. As a result of the methodology application, a 4.8 times reduction in the motor tests duration takes place if 2 people work in manual mode at the test bench without interruption.At the same time, the variance of the adequacy of Sad of the torque empirical model Mk turned out to be, on average, 1.5 times less if the model was built according to the automated tests results. The obtained data indicated an improvement in the quality of measurements in the transition to automated test methods.From a scientific point of view, the most original part of the work is the application of the “Gaussian process” method to build empirical models. This method provides more accurate results than, for example, the traditional method of least squares.The practical significance of the work lies in the ability to considerably reduce routine actions on a motor stand, and the additional time spent on developing and testing a test scenario (program) is compensated for by the fact that scenario models can be used in the future for other similar tests. The proposed methodology makes it possible to cover a significant part of the internal combustion engine calibration tests. For example, you can apply it if you possess the preliminary information about the test object (basing on which you can draw up an experiment plan) and the engine is to be prepared either for a car road tests or tests under special conditions.
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Pasternak, Michal, Fabian Mauss, Christian Klauer, and Andrea Matrisciano. "Diesel engine performance mapping using a parametrized mixing time model." International Journal of Engine Research 19, no. 2 (July 17, 2017): 202–13. http://dx.doi.org/10.1177/1468087417718115.

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A numerical platform is presented for diesel engine performance mapping. The platform employs a zero-dimensional stochastic reactor model for the simulation of engine in-cylinder processes. n-Heptane is used as diesel surrogate for the modeling of fuel oxidation and emission formation. The overall simulation process is carried out in an automated manner using a genetic algorithm. The probability density function formulation of the stochastic reactor model enables an insight into the locality of turbulence–chemistry interactions that characterize the combustion process in diesel engines. The interactions are accounted for by the modeling of representative mixing time. The mixing time is parametrized with known engine operating parameters such as load, speed and fuel injection strategy. The detailed chemistry consideration and mixing time parametrization enable the extrapolation of engine performance parameters beyond the operating points used for model training. The results show that the model responds correctly to the changes of engine control parameters such as fuel injection timing and exhaust gas recirculation rate. It is demonstrated that the method developed can be applied to the prediction of engine load–speed maps for exhaust NOx, indicated mean effective pressure and fuel consumption. The maps can be derived from the limited experimental data available for model calibration. Significant speedup of the simulations process can be achieved using tabulated chemistry. Overall, the method presented can be considered as a bridge between the experimental works and the development of mean value engine models for engine control applications.
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Dissertations / Theses on the topic "Automated Engine Calibration"

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Ward, Matthew. "Automatic-calibration methods for internal combustion engines." Thesis, University of Bath, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.418598.

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Flärdh, Oscar, and Manne Gustafson. "Mean Value Modelling of a Diesel Engine with Turbo Compound." Thesis, Linköping University, Department of Electrical Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1777.

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Over the last years, the emission and on board diagnostics legislations for heavy duty trucks are getting more and more strict. An accurate engine model that is possible to execute in the engine control system enables both better diagnosis and lowered emissions by better control strategies.

The objective of this thesis is to extend an existing mean value diesel engine model, to include turbo compound. The model should be physical, accurate, modular and it should be possible to execute in real time. The calibration procedure should be systematic, with some degree of automatization.

Four different turbo compound models have been evaluated and two models were selected for further evaluation by integration with the existing model. The extended model showed to be quite insensitive to small errors in the compound turbine speed and hence, the small difference in accuracy of the tested models did not affect the other output signals significantly. The extended models had better accuracy and could be executed with longer step length than the existing model, despite that more complexity were added to the model. For example, the mean error of the intake manifold pressure at mixed driving was approximately 3.0%, compared to 5.8% for the existing model. The reasons for the improvements are probably the good performance of the added submodels and the systematic and partly automatized calibration procedure including optimization.

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Burggraf, Timo [Verfasser], Stefan [Akademischer Betreuer] Ulbrich, and Christian [Akademischer Betreuer] Beidl. "Development of an automatic, multidimensional, multicriterial optimization algorithm for the calibration of internal combustion engines / Timo Burggraf. Betreuer: Stefan Ulbrich ; Christian Beidl." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2015. http://nbn-resolving.de/urn:nbn:de:tuda-tuprints-43987.

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Burggraf, Timo Verfasser], Stefan [Akademischer Betreuer] [Ulbrich, and Christian [Akademischer Betreuer] Beidl. "Development of an automatic, multidimensional, multicriterial optimization algorithm for the calibration of internal combustion engines / Timo Burggraf. Betreuer: Stefan Ulbrich ; Christian Beidl." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2015. http://d-nb.info/1111112231/34.

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Bashtova, Kateryna. "Modélisation et identification de paramètres pour les empreintes des faisceaux de haute énergie." Thesis, Université Côte d'Azur (ComUE), 2016. http://www.theses.fr/2016AZUR4112/document.

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Le progrès technologique nécessite des techniques de plus en plus sophistiquées et précises de traitement de matériaux. Nous étudions le traitement de matériaux par faisceaux de haute énergie : un jet d’eau abrasif, une sonde ionique focalisée, un laser. L’évolution de la surface du matériau sous l’action du faisceau de haute énergie est modélisée par une EDP. Cette équation contient l’ensemble des coefficients inconnus - les paramètres de calibration de mo- dèle. Les paramètres inconnus peuvent être calibrés par minimisation de la fonction coût, c’est-à-dire, la fonction qui décrit la différence entre le résultat de la modélisation et les données expérimentales. Comme la surface modélisée est une solution du problème d’EDP, cela rentre dans le cadre de l’optimisation sous contrainte d’EDP. L’identification a été rendue bien posée par la régularisation du type Tikhonov. Le gradient de la fonction coût a été obtenu en utilisant les deux méthodes : l’approche adjointe et la différen- ciation automatique. Une fois la fonction coût et son gradient obtenus, nous avons utilisé un minimiseur L-BFGS pour réaliser la minimisation.Le problème de la non-unicité de la solution a été résolu pour le problème de traitement par le jet d’eau abrasif. Des effets secondaires ne sont pas inclus dans le modèle. Leur impact sur le procédé de calibration a été évité. Ensuite, le procédé de calibration a été validé pour les données synthétiques et expérimentales. Enfin, nous avons proposé un critère pour distinguer facilement entre le régime thermique et non- thermique d’ablation par laser
The technological progress demands more and more sophisticated and precise techniques of the treatment of materials. We study the machining of the material with the high energy beams: the abrasive waterjet, the focused ion beam and the laser. Although the physics governing the energy beam interaction with material is very different for different application, we can use the same approach to the mathematical modeling of these processes.The evolution of the material surface under the energy beam impact is modeled by PDE equation. This equation contains a set of unknown parameters - the calibration parameters of the model. The unknown parameters can be identified by minimization of the cost function, i.e., function that describes the differ- ence between the result of modeling and the corresponding experimental data. As the modeled surface is a solution of the PDE problem, this minimization is an example of PDE-constrained optimization problem. The identification problem was regularized using Tikhonov regularization. The gradient of the cost function was obtained both by using the variational approach and by means of the automatic differentiation. Once the cost function and its gradient calculated, the minimization was performed using L-BFGS minimizer.For the abrasive waterjet application the problem of non-uniqueness of numerical solution is solved. The impact of the secondary effects non included into the model is avoided as well. The calibration procedure is validated on both synthetic and experimental data.For the laser application, we presented a simple criterion that allows to distinguish between the thermal and non-thermal laser ablation regimes
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Burggraf, Timo. "Development of an automatic, multidimensional, multicriterial optimization algorithm for the calibration of internal combustion engines." Phd thesis, 2015. https://tuprints.ulb.tu-darmstadt.de/4398/1/Doktorarbeit_Burggraf_Public.pdf.

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The process of engine application is crucial for the fulfillment of exhaust emission limits and for the reduction of fossil fuel consumption. During the past decade, this process became more and more complex, consequently the test bench measurement times become longer and even more expensive. Commercial software tools try to deliver good application methods, that reduce the total application time and application costs. In this work an alternative holistic optimization approach based on integer optimization is presented. Furthermore, we validate the algorithm by testing the approach with test bench data, which have been compressed to a polynomial data model. Finally, we present current results based on the new real world emissions cycle. The numerical results show that this new approach reduces measurement and optimization time in comparison to State-of-the-Art methods, noticeably. Additionally, the results show that one does not need data modeling, in order to solve the multi-criteria optimization problem.
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Book chapters on the topic "Automated Engine Calibration"

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Tietze, Nils, U. Konigorski, C. Fleck, and D. Nguyen-Tuong. "Model-based calibration of engine controller using automated transient design of experiment." In Proceedings, 1587–605. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-05130-3_111.

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Meyer, Sven. "Intelligent control of the automated calibration of engine management systems by using a new calibration process scheduler." In Proceedings, 1473–94. Wiesbaden: Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-658-08844-6_103.

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Babovic, V., and A. W. Minns. "Hydroinformatics opening new horizons: union of computational hydraulics and artificial intelligence." In Michael Abbott's Hydroinformatics, 33–44. IWA Publishing, 2022. http://dx.doi.org/10.2166/9781789062656_0033.

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Abstract The strengthening dominance of electronics over past several decades has resulted in an almost total dominance of digital representation of the hydro-environment. Recognizing these developments, Mike Abbott introduced the notion of electronic encapsulation of information and knowledge. The act of encapsulating information and knowledge changes the very nature of the information and knowledge involved. Suffice to say that electronic encapsulation must also change the way in which an engineer accesses and uses the available information and knowledge. There is a shift in paradigm away from a model-based approach to a more data-based approach. Adopting such foundational considerations as its core, hydroinformatics opened research to the latest IT developments in the fields of artificial intelligence (including machine learning, evolutionary algorithms and artificial neural networks), artificial life, cellular or finite-state automata and other, previously unrelated sciences and technologies. Through studying and exploiting elements of these, at first sight unrelated, sciences, hydroinformatics produced new and innovative solutions to hydraulic and hydrological problems, as represented by real-time control and diagnosis, real-time forecasting, calibration of numerical models, data analysis and parameter estimation. In particular, the new approaches are able to generate important components of physically based, modelling systems by inducing models or sub-models of individual physical processes based only upon measured data. These (sub)models may then replace whole systems of complex, non-linear, differential equations that would otherwise require great skills from the modeller to calibrate, and powerful computing devices to solve. This chapter captures evolution of data science and AI within the field of hydroinformatics and provides an outline of the present state-of-affairs together with some ideas for future directions. The chapter outlines tangible solutions that have been applied by the hydroinformatics community to address specific challenges in hydro-environmental systems.
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Conference papers on the topic "Automated Engine Calibration"

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GREENE, WILLIAM. "SSME Automated Engine Calibration System (AECS)." In 28th Joint Propulsion Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-3453.

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Singh, Ripudaman, Andrew Mansfield, and Margaret Wooldridge. "Automated Engine Calibration Optimization Using Online Extremum Seeking." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-87911.

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Emissions compliance during engine start-up conditions is a major obstacle for current automotive manufacturers across global markets. The challenges to meeting emissions targets are both due to increasingly stringent regulations and the difficulty in developing control strategies for a high degree-of-freedom and highly non-linear system. Online extremum-seeking (ES) methods offer a promising alternative to traditional optimization based on design-of-experiment based automotive calibration. With extremum-seeking methods, results from all prior experiments are used to intelligently and efficiently generate the next iteration of the control parameter(s). In this work, the applicability of the online extremum-seeking method is explored to optimize five performance variables (injection timing for two injection events, the injection fuel mass divided between the first and second injection events, air-fuel equivalence ratio and exhaust cam timing) to minimize brake specific fuel consumption while imposing different constraints on NOx emissions. The experiments were conducted using a production turbocharged four-cylinder gasoline engine with an advanced fuel injection system. The results show the utility of the ES strategy to quickly identify optimal control parameter combinations and the emissions and engine performance improvements during the calibration process. The results also demonstrate the dramatic benefit of the ES calibration strategy in terms of test time required.
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Schmitz, G., U. Oligschläger, G. Eifler, and H. Lechner. "Automated System for Optimized Calibration of Engine Management Systems." In International Congress & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1994. http://dx.doi.org/10.4271/940151.

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Stuhler, Harald, Thomas Kruse, Axel Stuber, Kurt Gschweitl, Walter Piock, Horst Pfluegl, and Peter Lick. "Automated Model-Based GDI Engine Calibration Adaptive Online DoE Approach." In SAE 2002 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2002. http://dx.doi.org/10.4271/2002-01-0708.

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Barasa, Patrick, Ye Tian, Stefan Hardes, Shahaboddin Owlia, Purvi Limaye, Derek Bailey, and Tarun Sehgal. "Virtual Engine, Controls, and Calibration Development in Automated Co-Simulation Environment." In SAE 2016 World Congress and Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2016. http://dx.doi.org/10.4271/2016-01-0090.

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Damji, Nilufar, Daniel Dresser, Jerome Bellavoine, and Mohan Swaminathan. "Automated Model-Based Calibration for Drivability Using a Virtual Engine Test Cell." In SAE 2015 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2015. http://dx.doi.org/10.4271/2015-01-1628.

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Esteves, Alexandre Tadeu Mencacci, Alexandre Massayuki Kawamoto, André Pelisser, and David Gazitto Carmelutti. "Automated engine calibration in vehicle to optimize emissions levels using machine learning." In XXVIII SIMPÓSIO INTERNACIONAL DE ENGENHARIA AUTOMOTIVA. São Paulo: Editora Blucher, 2021. http://dx.doi.org/10.5151/simea2021-pap32.

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Yoo, Jaegon, Heungseok Lee, JungWoong Jang, Ohcheol Hwang, and Chang-Kook Chae. "Automated Optimizing Calibration of Engine Driveability on the Dynamic Powertrain Test Bed." In SAE/KSAE 2013 International Powertrains, Fuels & Lubricants Meeting. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2013. http://dx.doi.org/10.4271/2013-01-2588.

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Monaco, Jeffrey F., David S. Kidman, Donald J. Malloy, David G. Ward, and James F. Gist. "Automated Methods to Calibrate a High-Fidelity Thrust Deck to Aid Aeropropulsion Test and Evaluation." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-50213.

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Modeling and simulation is regularly used to support test and evaluation at the U.S. Air Force aeropropulsion ground and flight test centers. Advanced modeling and simulation tools used to calibrate a high-fidelity thrust program that predicts steady-state and transient operation of a fighter aircraft turbofan engine are discussed in this paper. Maximum likelihood parameter estimation is used to estimate engine-model calibration factors. Empirical modeling techniques are then used to obtain closed-form polynomials characterizing the variations in the calibration factors as functions of engine operating condition. The inferred polynomial relationships are used to constrain the functional form of the calibration factors as part of a final maximum likelihood parameter estimation step. The coefficients of the polynomials are estimated over all ground-test cases simultaneously to minimize the weighted error between ground-test output measurements and thrust-deck predictions. An overview of the modeling and simulation framework is given with examples illustrating how the framework can readily be applied to a diverse range of aeropropulsion test and evaluation tasks. Details of the thrust deck, key variables, and the calibration factors are presented. Calibrated thrust deck predictions are compared with steady-state ground test data; and it is shown how the approach advances the state-of-the-art through methods that are more highly automated and intuitive to the engine analyst. The enhancements that automate the steps to set up a modeling task provide tangible benefits for a variety of test and evaluation applications.
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Malloy, Donald J., Mark A. Chappell, and Csaba Biegl. "Real-Time Fault Identification for Developmental Turbine Engine Testing." In ASME 1997 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/97-gt-141.

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Hundreds of individual sensors produce an enormous amount of data during developmental turbine engine testing. The challenge is to ensure the validity of the data and to identify data and engine anomalies in a timely manner. An automated data validation, engine condition monitoring, and fault identification process that emulates typical engineering techniques has been developed for developmental engine testing. An automated data validation and fault identification approach employing engine cycle-matching principles is described. Engine cycle-matching is automated by using an adaptive nonlinear component-level computer model capable of simulating both steady-state and transient engine operation. An automated model calibration process is also described. The model enables automation of traditional data validation, engine condition monitoring, and fault identification procedures. A distributed parallel computing approach enables the entire process to operate in realtime. The result is a capability to detect data and engine anomalies in realtime during developmental engine testing. The approach is shown to be successful in detecting and identifying sensor anomalies as they occur and distinguishing these anomalies from variations in component and overall engine aerothermodynamic performance.
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Reports on the topic "Automated Engine Calibration"

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Berney, Ernest, Jami Lynn Daugherty, and Lulu Edwards. Validation of the automatic dynamic cone penetrometer. Engineer Research and Development Center (U.S.), July 2022. http://dx.doi.org/10.21079/11681/44704.

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The U.S. military requires a rapid means of measuring subsurface soil strength for construction and repair of expeditionary pavement surfaces. Traditionally, a dynamic cone penetrometer (DCP) has served this purpose, providing strength with depth profiles in natural and prepared pavement surfaces. To improve upon this device, the Engineer Research and Development Center (ERDC) validated a new battery-powered automatic dynamic cone penetrometer (A-DCP) apparatus that automates the driving process by using a motor-driven hammering cap placed on top of a traditional DCP rod. The device improves upon a traditional DCP by applying three to four blows per second while digitally recording depth, blow count, and California Bearing Ratio (CBR). An integrated Global Positioning Sensor (GPS) and Bluetooth® connection allow for real-time data capture and stationing. Similarities were illustrated between the DCP and the A-DCP by generation of a new A-DCP calibration curve. This curve relates penetration rate to field CBR that nearly follows the DCP calibration with the exception of a slight offset. Field testing of the A-DCP showed less variability and more consistent strength measurement with depth at a speed five times greater than that of the DCP with minimal physical exertion by the operator.
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