Studio e ottimizzazione di un propulsore Diesel per un piccolo velivolo senza pilota

Studio e ottimizzazione di un propulsore a detonazione a gasolio per un piccolo velivolo senza pilota.

Agent-based simulation for renewable energy incentive design

In this thesis, we propose a novel approach to model the diffusion of residential PV systems. For this purpose, we use an agent-based model where agents are the families living in the area of interest. The case study is the Emilia-Romagna Regional Energy plan, which aims to increase the produc- tion of electricity from renewable energy. So, we study the microdata from the Survey on Household Income and Wealth (SHIW) provided by Bank of Italy in order to obtain the characteristics of families living in Emilia-Romagna. These data have allowed us to artificial generate families and reproduce the socio-economic aspects of the region. The families generated by means of a software are placed on the virtual world by associating them with the buildings. These buildings are acquired by analysing the vector data of regional buildings made available by the region. Each year, the model determines the level of diffusion by simulating the installed capacity. The adoption behaviour is influenced by social interactions, household’s economic situation, the environmental benefits arising from the adoption and the payback period of the investment.

Studio e ottimizzazione dell'albero motore di un piccolo Diesel per aeroplani senza pilota

Studio e ottimizzazione dell'albero motore di un piccolo Diesel per aeroplani senza pilota per uso civile quale monitoraggio etc.

Studio e ottimizzazione della rimotorizzazione di un elicottero a turbina con un motore diesel

Studio del dimensionamento del radiatore e del condotto di scarico con eiettore per un motore V12 montato su elicottero.

Sviluppo ed analisi di un sistema dual-fuel diesel/benzina per combustioni di tipo RCCI

Nel presente lavoro è progettato e sviluppato un sistema dual-fuel diesel/benzina per combustioni di tipo RCCI, e sono esposti i risultati sperimentali in termini di prestazioni ed emissioni. E' inoltre descritto e implementato un algoritmo di stima dell'MFB50 a partire dalla sola misura della velocità motore.

Studio e ottimizzazione di un propulsore Diesel applicato a un drone

Progettazione di un motore Diesel 2 tempi sulla base commerciale di un TM100Kb a benzina di derivazione karting. Il motore è capace di 5kW di potenza ad un peso contenuto. La progettazione è orientata agli aspetti sia termodinamici che dinamici. Si effettua una serie di verifiche per capire l'efficienza e l'uso di componenti originali.

Sviluppo di un sistema di sovralimentazione assistito elettricamente per un motore diesel 3.0L V6 ad alta potenza specifica

Questa tesi di laurea nasce dall’esperienza maturata presso l’azienda FCA Italy (Fiat Chrysler Automobiles S.p.A., ex VM Motori) nello stabilimento situato a Cento in provincia di Ferrara, in particolare all’interno dell’ufficio di Ricerca Avanzata CRM (Centro Ricerca Motori), divisione del reparto R&D (Research and Development). Tale esperienza viene riassunta (in piccola parte) in questo elaborato di Tesi, che tratta tematiche inerenti allo sviluppo di un sistema di sovralimentazione assistito elettricamente, applicato ad un propulsore Diesel 3.0L V6 destinato ai segmenti “Premium” del mercato. Il sistema utilizzato, che ha come componente principale un compressore attuato da una macchina elettrica, appartiene all’insieme delle tecnologie cosiddette di e-boosting. Questo tipo di tecnologia, fortemente innovativa e ad oggi non ancora presente sul mercato, ha le potenzialità per rappresentare un significativo passo avanti nel processo di riduzione delle emissioni, dei consumi e del miglioramento delle performance dei moderni motori endotermici alternativi, al punto che un numero crescente di costruttori di motori sta oggi studiando soluzioni come quella oggetto di questo elaborato. L’obiettivo è stato quindi quello di definire, applicare e gestire il sistema di e-boost a banco motore e, successivamente, caratterizzarlo dal punto di vista energetico e testarne le effettive potenzialità. Le fasi in cui ho apportato il mio contributo sono state, in particolare, quelle di definizione e integrazione dei nuovi componenti all’interno del layout motore preesistente, di realizzazione e implementazione delle strategie di controllo in un sistema dedicato in grado di gestire efficacemente i componenti, e di sperimentazione al banco prova. I risultati conseguiti al termine dell’attività sono quindi inerenti allo sviluppo e validazione del sistema di controllo, alla valutazione delle performance del propulsore risultante e alla caratterizzazione e analisi critica del sistema di e-boost dal punto di vista energetico.

Studio ed ottimizzazione di un sistema di raffreddamento per un elicottero diesel.

Studio ed ottimizzazione di un sistema di raffreddamento per un elicottero diesel. Individuazione della configurazione più conveniente.

Simulazione dinamica swirl in motore diesel

Simulazione CFD di un condotto di aspirazione di un motore Diesel.

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.

A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

Gasoline emissions dominate over diesel in formation of secondary organic aerosol mass

Although laboratory experiments have shown that organic compounds in both gasoline fuel and diesel engine exhaust can form secondary organic aerosol (SOA), the fractional contribution from gasoline and diesel exhaust emissions to ambient SOA in urban environments is poorly known. Here we use airborne and ground-based measurements of organic aerosol (OA) in the Los Angeles (LA) Basin, California made during May and June 2010 to assess the amount of SOA formed from diesel emissions. Diesel emissions in the LA Basin vary between weekdays and weekends, with 54% lower diesel emissions on weekends. Despite this difference in source contributions, in air masses with similar degrees of photochemical processing, formation of OA is the same on weekends and weekdays, within the measurement uncertainties. This result indicates that the contribution from diesel emissions to SOA formation is zero within our uncertainties. Therefore, substantial reductions of SOA mass on local to global scales will be achieved by reducing gasoline vehicle emissions.

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.