Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

Aortic flow patterns resulting from right axillary artery cannulation

Right axillary artery (RAA) cannulation is increasingly used in cardiac surgery. Little is known about resulting flow patterns in the aorta. Therefore, flow was visualized and analyzed. A mock circulatory circuit was assembled based on a compliant transparent anatomical silicon aortic model. A RAA cannula was connected to a continuous flow rotary blood pump (RBP), pulsatile heart action was provided by a pneumatic ventricular assist device (PVAD). Peripheral vascular resistance, regional flow and vascular compliance were adjusted to obtain physiological flow and pressure waveforms. Colorants were injected automatically for flow visualization. Five flow distributions with a total flow of 4 l/min were tested (%PVAD:%RBP): 100:0, 75:25, 50:50, 25:75, 0:100. Colorant distribution was assessed using quantitative 2D image processing. Continuous flow from the RAA divided in a retrograde and an antegrade portion. Retro- to antegrade flow ratio increased with increasing RAA-flow. At full RBP support flow was stagnant in the ascending aorta. There were distinct flow patterns between the right- and left-sided supra-aortic branches. At full RBP support retrograde flow was demonstrated in the right carotid and right vertebral arteries. Further studies are needed to confirm and evaluate the described flow patterns.

Reduction of Transient Particulate Matter Spikes with Decision Tree Based Control

Decision trees have been proposed as a basis for modifying table based injection to reduce transient particulate spikes during the turbocharger lag period. It has been shown that decision trees can detect particulate spikes in real time. In well calibrated electronically controlled diesel engines these spikes are narrow and are encompassed by a wider NOx spike. Decision trees have been shown to pinpoint the exact location of measured opacity spikes in real time thus enabling targeted PM reduction with near zero NOx penalty. A calibrated dimensional model has been used to demonstrate the possible reduction of particulate matter with targeted injection pressure pulses. Post injection strategy optimized for near stoichiometric combustion has been shown to provide additional benefits. Empirical models have been used to calculate emission tradeoffs over the entire FTP cycle. An empirical model based transient calibration has been used to demonstrate that such targeted transient modifiers are more beneficial at lower engine-out NOx levels.

INTEGRATION D’UN OBSERVATOIRE URBAIN SUR GOOGLE MAPS : Cas des infrastructures de la santé de la ville de Douala Cameroun

The spectacular advances computer science applied to geographic information systems (GIS) in recent times has favored the emergence of several technological solutions. These developments have given rise to enormous opportunities for digital management of the territory. Among the technological solutions, the most famous Google Maps offers free online mapping dynamic exhaustive of the Maps. In addition to meet the enormous needs of urban indicators geotagged information, we did work on this project “Integration of an urban observatory on Google Maps.” The problem of geolocation in the urban observatory is particularly relevant in the sense that there is currently no data (descriptive and geographical) reliable on the urban sector; we must stick to extrapolate from data old and obsolete. This helps to curb the effectiveness of urban management to make difficult investment programming and to prevent the acquisition of knowledge to make cities engines of growth. The use of a geolocation tool coupled to the data would allow better monitoring of indicators Our project's objective is to develop an interactive map server (WebMapping) which map layer is formed from the resources of the Google Maps servers and match information from the field to produce maps of urban equipment and infrastructure of a city data to the client's request To achieve this goal, we will participate in a study of a GPS location of strategic sites in our core sector (health facilities), on the other hand, using information from the field, we will build a postgresql database that will link the information from the field to map from Google Maps via KML scripts and PHP appropriate. We will limit ourselves in our work to the city of Douala Cameroon with the sectors of health facilities with the possibility of extension to other areas and other cities. Keywords: Geographic Information System (GIS), Thematic Mapping, Web Mapping, data mining, Google API.

Design and Use of an Alternative Fuel Testing Apparatus and Assessment of the Feasibility of Biodiesel

Petroleum supply and environmental pollution issues constantly increase interest in renewable low polluting alternative fuels. Published test results show decreased pollution with similar power output and fuel consumption from Internal Combustion Engines (ICE) burning alternative fuels. More specifically, diesel engines burning biodiesel derived from plant oils and animal fats not only reduce harmful exhaust emissions but are renewable and environmentally friendly. To validate these claims and assess the feasibility of alternative fuels, independent engine dynamometer and emissions testing was performed. A testing apparatus capable of making relevant measurements was designed, built, and used to test and determine the feasibility of biodiesel. The apparatus marks the addition of a valuable testing tool to the University and provides a foundation for future experiments. This thesis will discuss the background of biodiesel, testing methods, design and function of the testing apparatus, experimental results, relevant calculations, and conclusions.

Reconstitution of mitochondrial ATP synthase into lipid bilayers for structural analysis

Mitochondrial F(1)F(o)-ATP synthase is a molecular motor that couples the energy generated by oxidative metabolism to the synthesis of ATP. Direct visualization of the rotary action of the bacterial ATP synthase has been well characterized. However, direct observation of rotation of the mitochondrial enzyme has not been reported yet. Here, we describe two methods to reconstitute mitochondrial F(1)F(o)-ATP synthase into lipid bilayers suitable for structure analysis by electron and atomic force microscopy (AFM). Proteoliposomes densely packed with bovine heart mitochondria F(1)F(o)-ATP synthase were obtained upon detergent removal from ternary mixtures (lipid, detergent and protein). Two-dimensional crystals of recombinant hexahistidine-tagged yeast F(1)F(o)-ATP synthase were grown using the supported monolayer technique. Because the hexahistidine-tag is located at the F(1) catalytic subcomplex, ATP synthases were oriented unidirectionally in such two-dimensional crystals, exposing F(1) to the lipid monolayer and the F(o) membrane region to the bulk solution. This configuration opens a new avenue for the determination of the c-ring stoichiometry of unknown hexahistidine-tagged ATP synthases and the organization of the membrane intrinsic subunits within F(o) by electron microscopy and AFM.

Performance and emissions testing of a small two stroke engine using mid-level ethanol blends

With the introduction of the mid-level ethanol blend gasoline fuel for commercial sale, the compatibility of different off-road engines is needed. This report details the test study of using one mid-level ethanol fuel in a two stroke hand held gasoline engine used to power line trimmers. The study sponsored by E3 is to test the effectiveness of an aftermarket spark plug from E3 Spark Plug when using a mid-level ethanol blend gasoline. A 15% ethanol by volume (E15) is the test mid-level ethanol used and the 10% ethanol by volume (E10) was used as the baseline fuel. The testing comprises running the engine at different load points and throttle positions to evaluate the cylinder head temperature, exhaust temperature and engine speed. Raw gas emissions were also measured to determine the impact of the performance spark plug. The low calorific value of the E15 fuel decreased the speed of the engine along with reduction in the fuel consumption and exhaust gas temperature. The HC emissions for E15 fuel and E3 spark plug increased when compared to the base line in most of the cases and NO formation was dependent on the cylinder head temperature. The E3 spark plug had a tendency to increase the temperature of the cylinder head irrespective of fuel type while reducing engine speed.

Reynolds-stress turbulence model in the KIVA code for engine simulation

A Reynolds-Stress Turbulence Model has been incorporated with success into the KIVA code, a computational fluid dynamics hydrocode for three-dimensional simulation of fluid flow in engines. The newly implemented Reynolds-stress turbulence model greatly improves the robustness of KIVA, which in its original version has only eddy-viscosity turbulence models. Validation of the Reynolds-stress turbulence model is accomplished by conducting pipe-flow and channel-flow simulations, and comparing the computed results with experimental and direct numerical simulation data. Flows in engines of various geometry and operating conditions are calculated using the model, to study the complex flow fields as well as confirm the model’s validity. Results show that the Reynolds-stress turbulence model is able to resolve flow details such as swirl and recirculation bubbles. The model is proven to be an appropriate choice for engine simulations, with consistency and robustness, while requiring relatively low computational effort.

Modeling of diesel particulate filter filtration and regeneration for transient driving schedules

Due to their high thermal efficiency, diesel engines have excellent fuel economy and have been widely used as a power source for many vehicles. Diesel engines emit less greenhouse gases (carbon dioxide) compared with gasoline engines. However, diesel engines emit large amounts of particulate matter (PM) which can imperil human health. The best way to reduce the particulate matter is by using the Diesel Particulate Filter (DPF) system which consists of a wall-flow monolith which can trap particulates, and the DPF can be periodically regenerated to remove the collected particulates. The estimation of the PM mass accumulated in the DPF and total pressure drop across the filter are very important in order to determine when to carry out the active regeneration for the DPF. In this project, by developing a filtration model and a pressure drop model, we can estimate the PM mass and the total pressure drop, then, these two models can be linked with a regeneration model which has been developed previously to predict when to regenerate the filter. There results of this project were: 1 Reproduce a filtration model and simulate the processes of filtration. By studying the deep bed filtration and cake filtration, stages and quantity of mass accumulated in the DPF can be estimated. It was found that the filtration efficiency increases faster during the deep-bed filtration than that during the cake filtration. A “unit collector” theory was used in our filtration model which can explain the mechanism of the filtration very well. 2 Perform a parametric study on the pressure drop model for changes in engine exhaust flow rate, deposit layer thickness, and inlet temperature. It was found that there are five primary variables impacting the pressure drop in the DPF which are temperature gradient along the channel, deposit layer thickness, deposit layer permeability, wall thickness, and wall permeability. 3 Link the filtration model and the pressure drop model with the regeneration model to determine the time to carry out the regeneration of the DPF. It was found that the regeneration should be initiated when the cake layer is at a certain thickness, since a cake layer with either too big or too small an amount of particulates will need more thermal energy to reach a higher regeneration efficiency. 4 Formulate diesel particulate trap regeneration strategies for real world driving conditions to find out the best desirable conditions for DPF regeneration. It was found that the regeneration should be initiated when the vehicle’s speed is high and during which there should not be any stops from the vehicle. Moreover, the regeneration duration is about 120 seconds and the inlet temperature for the regeneration is 710K.