Optimization of Heavy-duty Diesel Engine Operating Parameters at High Speed and Medium Load Using [mu]-genetic Algorithms PDF Download
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Author: Mike P. Liechty
Publisher:
ISBN:
Category :
Languages : en
Pages : 414
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Book Description
![Optimization of Heavy-duty Diesel Engine Operating Parameters at High Speed and Medium Load Using [mu]-genetic Algorithms PDF](https://books.google.com/books/content/images/frontcover/6L5bAAAAMAAJ?fife=w80-h100)
Author: Mike P. Liechty
Publisher:
ISBN:
Category :
Languages : en
Pages : 414
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Book Description
Author: P. V. Farrell
Publisher:
ISBN:
Category :
Languages : en
Pages : 4
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Book Description
A computational optimization study was performed for a heavy-duty direct-injection diesel engine using the recently developed KIVA-GA computer code. The effects of 11 engine input parameters on emissions and performance were studied. Start of injection (SOI), amount of EGR, boost pressure and eight parameters defining the fuel injection rate-shape were included in the search. The optimized configuration results in very low soot and NO(x) emissions together with relatively low fuel consumption.
Author: David T. Montgomery
Publisher:
ISBN:
Category : Mechanical engineering
Languages : en
Pages : 332
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Author: Justin Brett Pennington
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 286
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Book Description
A medium-duty diesel engine is equipped with a High Pressure EGR (Exhaust Gas Recirculation) and a VNT (Variable Nozzle Turbine) and coupled to an AC Dynamometer. The control of the HPEGR and VNT will be optimized during steady state and transient engine operation to lower nitric oxide and particulate matter production as well as fuel consumption. Brake specific particulate matter, nitric oxide, and fuel consumption will be recorded with fast measurement systems capable of capturing results of transient events. A steady state map of engine speed and load will be used to calibrate initial VNT and EGR control. The calibration will be optimized with a defined formula using emissions production and fuel consumption. After a steady state VNT and HPEGR map is created, the map will be used as a baseline in transient engine operation. The dissertation will contain three parts. Firstly, VNT and HPEGR control assigned via the steady state table will be used during transient events, which will then be increased in speed from a 10 second to a 2 second event. Secondly, the VNT and EGR control will be manually configured in attempt to improve engine performance throughout the transient. Finally, the VNT and EGR control will be applied before the transient event to inspect the effect on engine performance.
Author: P. A. Lakshminarayanan
Publisher: Springer Nature
ISBN: 9811509700
Category : Technology & Engineering
Languages : en
Pages : 914
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Book Description
This book is intended to serve as a comprehensive reference on the design and development of diesel engines. It talks about combustion and gas exchange processes with important references to emissions and fuel consumption and descriptions of the design of various parts of an engine, its coolants and lubricants, and emission control and optimization techniques. Some of the topics covered are turbocharging and supercharging, noise and vibrational control, emission and combustion control, and the future of heavy duty diesel engines. This volume will be of interest to researchers and professionals working in this area.
Author: William L. Hardy
Publisher:
ISBN:
Category :
Languages : en
Pages : 494
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Book Description
Author: María Teresa Abad Lozano
Publisher:
ISBN: 9783832512897
Category :
Languages : en
Pages : 154
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Book Description
Author: David D. Wickman
Publisher:
ISBN:
Category :
Languages : en
Pages : 240
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Book Description
Author: Jihad Badra
Publisher: Elsevier
ISBN: 0323884571
Category : Technology & Engineering
Languages : en
Pages : 260
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Book Description
Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines summarizes recent developments in Artificial Intelligence (AI)/Machine Learning (ML) and data driven optimization and calibration techniques for internal combustion engines. The book covers AI/ML and data driven methods to optimize fuel formulations and engine combustion systems, predict cycle to cycle variations, and optimize after-treatment systems and experimental engine calibration. It contains all the details of the latest optimization techniques along with their application to ICE, making it ideal for automotive engineers, mechanical engineers, OEMs and R&D centers involved in engine design. Provides AI/ML and data driven optimization techniques in combination with Computational Fluid Dynamics (CFD) to optimize engine combustion systems Features a comprehensive overview of how AI/ML techniques are used in conjunction with simulations and experiments Discusses data driven optimization techniques for fuel formulations and vehicle control calibration
Author: Jost Weber
Publisher: Cuvillier Verlag
ISBN: 373692724X
Category : Technology & Engineering
Languages : en
Pages : 266
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Book Description
The optimization of the combustion and mixture formation process in Diesel engines by CFD simulations requires a reliable model approach as a pre-requisite in order to predict combustion and emissions. A general and commonly used model for the liquid spray is the discrete droplet model. Sub-models for droplet breakup, collision and coalescence, and evaporation are available in the CFD code. With regard to combustion, the flamelet model approach is interactively coupled with the CFD code, known as RIF model. It benefits from a one-dimensional description of the thin reaction zone in the flame. By this approach, a detailed reaction mechanism for the model fuel can be used. Sub-mechanisms for NOx formation and a soot model are included. The reaction mechanism has been modified in this work to account for a correct ignition delay and heat-release at low-temperature conditions e.g. in the PCCI combustion. The modeling of the mixture formation in a spray contains uncertainties in the model constants and initial conditions. Spray data is required to calibrate the spray model. At least, the spray penetration has to be measured under engine like conditions as performed in a spray chamber. The spray penetration is interpreted as a criterion for the mass and momentum exchange between the spray and the surrounding gas on a macroscopic level. Finding a good agreement for the spray penetration between simulation and experiment defines an optimization problem. That agreement is expressed in an Euclidean norm as a merit function. The objective is to minimize this merit function. The search for an appropriate set of spray model parameters and initial conditions is denoted here as calibration of the spray model. Six parameters have been identified, spanning a six dimensional parameter space. A manual search is not feasible anymore but the implemented Genetic Algorithm is suitable to find a global optimum where a good agreement between measured and simulated spray penetration is obtained. If the same spray parameters are applied to a virtual engine case, a similar good agreement is achieved although the mesh resolution is much finer and the mesh topology is different than for the spray chamber simulation. From this result, spray data for engine simulations should be provided and be used for sake of calibration before the engine simulation is conducted. Additionally data is obtained by PDA measurements at discrete points in the spray. That measurement technique is, however, limited to less dense areas. Nevertheless, it shows that also local data is in agreement with the simulation data. Agreement with spray penetration is thus a relatively good choice and accounts also for the physics on a local or microscopic level. That hypothesis is well supported by the data from the ethanol spray calibration. The excellent agreement with regard to the global spray penetration is reflected by the 2D comparison of liquid and vapor fuel concentrations and temperature, respectively. Furthermore, a similar good agreement in spray penetration is obtained if the breakup and collision model is not used. In that case, the spray penetration is only controlled by the evaporation process. The Genetic Algorithm finds a point in the parameter space with an initial SMR that is of the order of size of the outcome of the secondary droplet breakup. However in engine simulations, spray data is not always available. In that case the spray parameters have to be adjusted. That adjustment is carried out following a methodology that is presented in this work. Mainly, SOI and EGR variations have to be used to calibrated the spray and combustion model. That approach has been investigated for three different engine data sets for conventional and PCCI combustion mode. On the Cummins QSX engine, a conventional combustion has been studied. Spray parameters are subject of adjustment. On the Duramax 6600 Diesel engine, a conventional and PCCI combustion mode are investigated. For the PCCI combustion mode, the reaction mechanism is modified in order to account for a correct ignition delay in the low temperature combustion regime. The comparison between engine data and results from the simulation indicates a good agreement for the combustion and engineout emissions. On the Duramax full load case, most uncertainties are addressed to the spray-wall interaction. Uncertainties from physical not well based models will always occur in the engine simulation. Therefore, calibration of these models is a mean to quantify its influence and minimize the discrepancies.
