PARTIAL NEEDLE LIFT AND INJECTION RATE SHAPE EFFECT ON THE FORMATION AND COMBUSTION OF THE DIESEL SPRAY

Fuel direct injection represents one of the key turning points in the development of the Diesel engines. The appeal of this solution has been growing thanks to the parallel advancement in the technology of the injection hardware and in the knowledge of the physics involved in the spray formation and combustion. In the present thesis, the effect of partial needle lift and injection rate shaping has been investigated experimentally using a multi-orifice Diesel injector. Injection rate shaping is one of the most attractive alternatives to multiple injection strategies but its implementation has been for long time impeded by technological limitations. A novel direct-acting injector prototype made it possible to carry out the present research: this injector features a mechanical coupling between the nozzle needle and the piezo-stack actuator, allowing a fully flexible control on the nozzle needle movement and enabling partial needle lift as well as the implementation of alternative injection rate shapes typologies. Different optical diagnostics were applied to study the spray development and combustion in a novel continuous flow test chamber that allows an accurate control on a wide range of thermodynamic conditions (up to 1000K and 15MPa). In addition, hydraulic characterization tests were carried out to analyze the fuel flow through the injector nozzle. Partial needle lift has been found to affect the injection event, reducing the mass flow rate (as expected) but also causing a reduction in the effective orifice area and an increase on the spreading angle. Moreover, at this condition, higher hole-to-hole dispersion and flow instabilities were detected. Needle vibrations caused by the needle interactions with fuel flow and by the onset of cavitation in the needle seat are likely the causes of this behavior. Injection rate shaping has a substantial impact on the premixed phase of the combustion and on the location where the ignition takes place. Furthermore, the results proved that the modifications in the internal flow caused by the partial needle lift are reflected on the ignition timing. On the other hand, the analysis of the experimental data through a 1D spray model revealed that an increasing mass flow rate (e.g. ramp or boot injection rate profiles) causes an increase in the fuelair equivalence ratio at the lift-off length and a consequent higher soot formation during the diffusive phase of the combustion. Finally, the wide range of boundary conditions tested in all the experiments served to draw general conclusions about the physics involved in the injection/combustion event and, in some cases, to obtain statistical correlations.Bardi, M. (2014). PARTIAL NEEDLE LIFT AND INJECTION RATE SHAPE EFFECT ON THE FORMATION AND COMBUSTION OF THE DIESEL SPRAY [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/37374TESI

Machine learning assisted optimization with applications to diesel engine optimization with the particle swarm optimization algorithm

A novel approach to incorporating Machine Learning into optimization routines is presented. An approach which combines the benefits of ML, optimization, and meta-model searching is developed and tested on a multi-modal test problem; a modified Rastragin\u27s function. An enhanced Particle Swarm Optimization method was derived from the initial testing. Optimization of a diesel engine was carried out using the modified algorithm demonstrating an improvement of 83% compared with the unmodified PSO algorithm. Additionally, an approach to enhancing the training of ML models by leveraging Virtual Sensing as an alternative to standard multi-layer neural networks is presented. Substantial gains were made in the prediction of Particulate matter, reducing the MMSE by 50% and improving the correlation R^2 from 0.84 to 0.98. Improvements were made in models of PM, NOx, HC, CO, and Fuel Consumption using the method, while training times and convergence reliability were simultaneously improved over the traditional approach

ME-EM 2018-19 Annual Report

Table of Contents Faculty Research Enrollment & Degrees Department News Graduates Faculty & Staff Alumni Donors Contracts & Grants Patents & Publicationshttps://digitalcommons.mtu.edu/mechanical-annualreports/1000/thumbnail.jp

Computer-aided engineering and design of internal combustion engines to support operation on non-traditional fuels

2020 Fall.Includes bibliographical references.Traditional fuels like gasoline and diesel make up ~37 % of the US energy production; because of that, they are rapidly depleting their finite resources. These traditional fuels are also primary contributors to greenhouse gases, global warming, and particulate matter, which are bad for the environment and human beings. For that reason, research in non-traditional fuels (e.g., Carbon neutral biofuels, low GHG emitting gaseous fuels including NG and hydrogen) that achieve greater if not similar efficiencies compared to traditional fuels is gaining traction. On top of that, emission requirements are becoming even more strenuous. Engineers must find new ways to investigate non-traditional fuels and their performance in internal combustion engines while permitting the engine-fuel system's low-cost design. This being the case, Computer-Aided Engineering (CAE) tools like Computational Fluid Dynamics (CFD) and chemical kinetics solvers are being taken advantage of to assist in the research of these non-traditional fuel applications. This thesis describes the use of CONVERGE CFD to investigate two different non-traditional fuel applications, namely, the retrofitting of a premixed gasoline two-stroke spark-ignited (SI) engine to function with multiple injections of JP-8 fuel and to retrofit a diesel compression-ignited engine into a premixed anode tail-gas SI engine. The first application described herein uses a solid oxide fuel cell "Anode Tail-gas," which has similar syngas characteristics in a spark-ignited engine. Anode Tail-gas is a byproduct from an underutilized Metal Supported Solid Oxide Fuel Cell (MS-SOFC) used in a high efficiency distributed power (~100 kWe) system. Gas turbines or reciprocating ICEs typically drive distributed power systems of this capacity because they can quickly react to change in demand but traditionally have lower thermal efficiencies than a large-scale Rankine cycle plant. However, with the MS-SOFC, it may be possible to design a 125 kWe system with 70 % efficiency while keeping the system cost-competitive (below $1000/kW). The system requires a ~14 kW engine that can operate at 35 % efficiency with the highly dilute (17.7% H2, 4.90 % CO, 0.40% CH4, 28.3 % CO2, 48.7 % H2O) Anode Tail-gas to meet these lofty targets. CAE approaches were developed and used to identify high-efficiency operation pathways with the highly diluted anode tail-gas fuel. The fuel was first tested and modeled in a Cooperative Fuel Research (CFR) engine to investigate the anode tail gas's combustibility within an IC engine and to provide validation data with highly specified boundary conditions (Compression Ratio (CR), fuel compositions, intake temperature/pressure, and spark timing). A chemical mechanism was selected through CAE tools to represent the highly diluted fuel combustion best based on the CFR data. Five experimental test points were used to validate the CFD model, which all were within a maximum relative error of less than 8 % for IMEP and less than 4 crank angle degrees for CA10 and CA50. The knowledge gained from the CFR engine experiments and associated model validation helped direct the design of a retrofitted Kohler diesel engine to operate as a spark-ignited engine on the anode tail gas fuel. CFD Investigations into spark plug and piston bowl designs were performed to identify combustion chamber design improvements to boost the Kohler engine's efficiency. Studies revealed that piston designs incorporating small clearance heights, large squish areas, and deep bowl depths could enhance efficiency by 5.41 pts with additional efficiency gain possible through piston rotation. The second fuel investigation was a jet propellant fuel called "JP-8," which was deemed non-tradition when used in a two-stroke UAV engine to satisfy the military's single fuel policy requirements. The JP-8 fuel proved challenging in this application due to its significantly lower octane number and volatility than gasoline and experienced knock when used as a homogeneous premixed mixture within the simulated UAV platform. Although with CFD modeling, it was possible to reduce the severity of knock by using eight rapid direct injections of JP-8 at 20 µm diameter droplets. With further investigation, it might be possible to reduce further the severity of knock using CFD through more advanced injection strategies

Development of a Simulation based Powertrain Design Framework for Evaluation of Transient Soot Emissions from Diesel Engine Vehicles.

This dissertation presents the development of a modeling and simulation framework for diesel engine vehicles to enable soot emissions as a constraint in powertrain design and control. To this end, numerically efficient models for predicting temporallyresolved transient soot emissions are identified in the form of a third-order dual-input single-output (DISO) Volterra series from transient soot data recorded by integrating real-time (RT) vehicle level models in Engine-in-the-loop (EIL) experiments. It is shown that the prediction accuracy of transient soot significantly improves over the steady-state maps, while the model remains computationally efficient for systemslevel work. The evaluation of powertrain design also requires a systematic procedure for dealing with the issue that drivers potentially adapt their driving styles to a given design. In order to evaluate the implications of different powertrain design changes on transient soot production it is essential to compare these design changes on a consistent basis. This problem is explored in the context of longitudinal motion of a vehicle following a standard drive-cycle repeatedly. This dissertation develops a proportional-derivative (PD) type iterative learning based algorithm to synthesize driver actuator inputs that seek to minimize soot emissions using the Volterra series based transient soot models. The solution is compared to the one obtained using linear programming. Results show that about 19% reduction in total soot can be achieved for the powertrain design considered in about 40 iterations. The two contributions of this dissertation: development of computationally efficient system level transient soot models and the synthesis of driver inputs via iterative learning for reducing soot, both contribute to improving the art of modeling and simulation for diesel powertrain design and control.Ph.D.Mechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86386/1/ahlawatr_1.pd

Model-Based Control of Gasoline Partially Premixed Combustion

Partially Premixed Combustion (PPC) is an internal combustion engine concept that aims to yield low NOx and soot emission levels together with high engine efficiency. PPC belongs to the class of low temperature combustion concepts where the ignition delay is prolonged in order to promote the air-fuel-mixture homogeneity in the combustion chamber at the start of combustion. A more homogeneous combustion process in combination with high exhaust-gas recirculation (EGR) ratios gives lower combustion temperatures and thus decreased NOx and soot formation. The ignition delay is mainly controlled by temperature, gas-mixture composition, fuel type and fuel-injection timing. It has been shown that PPC run on gasoline fuel can provide sufficient ignition delays in conventional compression-ignition engines. The PPC concept differs from conventional direct-injection diesel combustion because of its increased sensitivity to intake conditions, its decreased combustion-phasing controllability and its high pressure-rise rates related to premixed combustion, this puts higher demands on the engine control system. This thesis investigates model predictive control (MPC) of PPC with the use of in-cylinder pressure sensors. Online heat-release analysis is used for the detection of the combustion phasing and the ignition delay that function as combustion-feedback signals. It is shown that the heat-release analysis could be automatically calibrated using nonlinear estimation methods, the heat-release analysis is also a central part of a presented online pressure-prediction method which can be used for combustion-timing optimization. Low-order autoignition models are studied and compared for the purpose of model-based control of the ignition-delay, the results show that simple mathematical models are sufficient when anipulating the intake-manifold conditions. The results also show that the relation between the injection timing and the ignition delay is not completely captured by these types of models when the injection timing is close to top-dead-center. Simultaneous control of the ignition delay and the combustion phasing using a dual-path EGR system, thermal management and fuel injection timings is studied and a control design is presented and evaluated experimentally. Closed-loop control of the pressure-rise rate using a pilot fuel injection is also studied and the multiple fuel-injection properties are characterized experimentally. Experiments show that the main-fuel injection controls the combustion timing and that the pilot-injection fuel could be used to decrease the main fuel injection ignition delay and thus the pressure-rise rate. The controllability of the pressure-rise rate was shown to be higher when the pilot injection was located close to the main-fuel injection. A pressure-rise-rate controller is presented and evaluated experimentally. All experiments presented in this thesis were conducted on a Scania D13 production engine with a modified gas-exchange system, the fuel used was a mixture of 80 % gasoline and 20 % N-heptane (by volume)