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Analytical target cascading framework for engine calibration optimisationKianifar, Mohammed R., Campean, Felician January 2014 (has links)
Yes / This paper presents the development and implementation of an Analytical Target Cascading (ATC) Multi-disciplinary Design Optimisation (MDO) framework for the steady state engine calibration optimisation problem. The case is made that the MDO / ATC offers a convenient framework for the engine calibration optimisation problem based on steady state engine test data collected at specified engine speed / load points, which is naturally structured on 2 hierarchical levels: the “Global” level, associated with performance over a drive cycle, and “Local” level, relating to engine operation at each speed / load point. The case study of a gasoline engine equipped with variable camshaft timing (VCT) was considered to study the application of the ATC framework to a calibration optimisation problem. The paper describes the analysis and mathematical formulation of the VCT calibration optimisation as an ATC framework, and its Matlab implementation with gradient based and evolutionary optimisation algorithms. The results and performance of the ATC are discussed comparatively with the conventional two-stage approach to steady state calibration optimisation. The main conclusion from this research is that ATC offers a powerful and efficient approach for engine calibration optimisation, delivering better solutions at both “Global” and “Local” levels. Further advantages of the ATC framework is that it is flexible and scalable to the complexity of the calibration problem, and enables calibrator preference to be incorporated a priori in the optimisation problem formulation, delivering important time saving for the overall calibration development process. / The research work presented in this paper was funded by UK Technology Strategy Board (TSB) through the CREO (Carbon Reduction through Engine Optimisation) project.
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Application of analytical target cascading for engine calibration optimization problemKianifar, Mohammed R., Campean, Felician 08 1900 (has links)
No / This paper presents the development of an Analytical Target Cascading (ATC) Multidisciplinary Design Optimization (MDO) framework for a steady-state engine calibration optimization problem. The implementation novelty of this research is the use of the ATC framework to formulate the complex multi-objective engine calibration problem, delivering a considerable enhancement compared to the conventional 2-stage calibration optimization approach [1]. A case study of a steady-state calibration optimization of a Gasoline Direct Injection (GDI) engine was used for the calibration problem analysis as ATC. The case study results provided useful insight on the efficiency of the ATC approach in delivering superior calibration solutions, in terms of “global” system level objectives (e.g. improved fuel economy and reduced particulate emissions), while meeting “local” subsystem level requirements (such as combustion stability and exhaust gas temperature constraints). The ATC structure facilitated the articulation of engineering preference for smooth calibration maps via the ATC linking variables, with the potential to deliver important time saving for the overall calibration development process.
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Probabilistic Multidisciplinary Design Optimization on a high-pressure sandwich wall in a rocket engine applicationWahlström, Dennis January 2017 (has links)
A need to find better achievement has always been required in the space industrythrough time. Advanced technologies are provided to accomplish goals for humanityfor space explorer and space missions, to apprehend answers and widen knowledges. These are the goals of improvement, and in this thesis, is to strive and demandto understand and improve the mass of a space nozzle, utilized in an upperstage of space mission, with an expander cycle engine. The study is carried out by creating design of experiment using Latin HypercubeSampling (LHS) with a consideration to number of design and simulation expense.A surrogate model based optimization with Multidisciplinary Design Optimization(MDO) method for two different approaches, Analytical Target Cascading (ATC) and Multidisciplinary Feasible (MDF) are used for comparison and emend the conclusion. In the optimization, three different limitations are being investigated, designspace limit, industrial limit and industrial limit with tolerance. Optimized results have shown an incompatibility between two optimization approaches, ATC and MDF which are expected to be similar, but for the two limitations, design space limit and industrial limit appear to be less agreeable. The ATC formalist in this case dictates by the main objective, where the children/subproblems only focus to find a solution that satisfies the main objective and its constraint. For the MDF, the main objective function is described as a single function and solved subject to all the constraints. Furthermore, the problem is not divided into subproblems as in the ATC. Surrogate model based optimization, its solution influences by the accuracy ofthe model, and this is being investigated with another DoE. A DoE of the full factorial analysis is created and selected to study in a region near the optimal solution.In such region, the result has evidently shown to be quite accurate for almost allthe surrogate models, except for max temperature, damage and strain at the hottestregion, with the largest common impact on inner wall thickness of the space nozzle. Results of the new structure of the space nozzle have shown an improvement of mass by ≈ 50%, ≈ 15% and ≈ -4%, for the three different limitations, design spacelimit, industrial limit and industrial limit with tolerance, relative to a reference value,and ≈ 10%, ≈ 35% and ≈ 25% cheaper to manufacture accordingly to the defined producibility model.
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