Development of a Predictive Control Function for a Plug-in Hybrid Electric Vehicle with Electrically-heated Catalyst

This master thesis work is focused on the development of a predictive EHC control function for a diesel plug-in hybrid electric vehicle equipped with a EURO 7 compliant exhaust aftertreatment system (EATS), with the purpose of showing the advantages provided by the implementation of a predictive control strategy with respect to a rule-based one. A preliminary step will be the definition of an accurate powertrain and EATS physical model, starting from already existing and validated applications. Then, a rule-based control strategy managing the torque split between the electric motor (EM) and the internal combustion engine (ICE) will be developed and calibrated, with the main target of limiting tailpipe NOx emission by taking into account EM and ICE operating conditions together with EATS conversion efficiency. The information available from vehicle connectivity will be used to reconstruct the future driving scenario, also referred to as electronic horizon (eHorizon), and in particular to predict ICE first start. Based on this knowledge, an EATS pre-heating phase can be planned to avoid low pollutant conversion efficiencies, thus preventing high NOx emission due to engine cold start. Consequently, the final NOx emission over the complete driving cycle will be strongly reduced, allowing to comply with the limits potentially set by the incoming EURO 7 regulation. Moreover, given the same NOx emission target, the gain achieved thanks to the implementation of an EHC predictive control function will allow to consider a simplified EATS layout, thus reducing the related manufacturing cost. The promising results achieved in terms of NOx emission reduction show the effectiveness of the application of a predictive control strategy focused on EATS thermal management and highlight the potential of a complete integration and parallel development of involved vehicle physical systems, control software and connectivity data management.

Analysis of the impact of stationary energy storage systems in trolleybus grids using Simulink-based modelling

The voltage profile of the catenary between traction substations (TSSs) is affected by the trolleybus current intake and by its position with respect to the TSSs: the higher the current requested by the bus and the further the bus from the TSSs, the deeper the voltage drop. When the voltage drops below 500V, the trolleybus is forced to decrease its consumption by reducing its input current. This thesis deals with the analysis of the improvements that the installation of an BESS produces in the operation of a particularly loaded FS of the DC trolleybus network of the city of Bologna. The stationary BESS is charged by the TSSs during off-peak times and delivers the stored energy when the catenary is overloaded alleviating the load on the TSSs and reducing the voltage drops. Only IMC buses are considered in the prospect of a future disposal of all internal combustion engine vehicles. These trolleybuses cause deeper voltage drops because they absorb enough current to power their traction motor and recharge the on board battery. The control of the BESS aims to keep the catenary voltage within the admissible voltage range and makes sure that all physical limitations are met. A model of FS Marconi Trento Trieste is implemented in Simulink environment to simulate its daily operation and compare the behavior of the trolleybus network with and without BESS. From the simulation without BESS, the best location of the energy storage system is deduced, and the battery control is tuned. Furthermore, from the knowledge of the load curve and the battery control trans-characteristic, it is formulated a prediction of the voltage distribution at BESS connection point. The prediction is then compared with the simulation results to validate the Simulink model. The BESS allows to decrease the voltage drops along the catenary, the Joule losses and the current delivered by the TSSs, indicating that the BESS can be a solution to improve the operation of the trolleybus network.

Optimization and development of low environmental impact propulsion systems

The aim of the Ph.D. research project was to explore Dual Fuel combustion and hybridization. Natural gas-diesel Dual Fuel combustion was experimentally investigated on a 4-Stroke, 2.8 L, turbocharged, light-duty Diesel engine, considering four operating points in the range between low to medium-high loads at 3000 rpm. Then, a numerical analysis was carried out using a customized version of the KIVA-3V code, in order to optimize the diesel injection strategy of the highest investigated load. A second KIVA-3V model was used to analyse the interchangeability between natural gas and biogas on an intermediate operating point. Since natural gas-diesel Dual Fuel combustion suffers from poor combustion efficiency at low loads, the effects of hydrogen enriched natural gas on Dual Fuel combustion were investigated using a validated Ansys Forte model, followed by an optimization of the diesel injection strategy and a sensitivity analysis to the swirl ratio, on the lowest investigated load. Since one of the main issues of Low Temperature Combustion engines is the low power density, 2-Stroke engines, thanks to the double frequency compared to 4-Stroke engines, may be more suitable to operate in Dual Fuel mode. Therefore, the application of gasoline-diesel Dual Fuel combustion to a modern 2-Stroke Diesel engine was analysed, starting from the investigation of gasoline injection and mixture formation. As far as hybridization is concerned, a MATLAB-Simulink model was built to compare a conventional (combustion) and a parallel-hybrid powertrain applied to a Formula SAE race car.

Analysis and improvements of four-wire power converters for electric vehicle chargers

A robust and well-distributed backbone charging network is the priority to ensure widespread electrification of road transport, providing a driving experience similar to that of internal combustion engine vehicles. International standards set multiple technical targets for on-board and off-board electric vehicle chargers; output voltage levels, harmonic emissions, and isolation requirements strongly influence the design of power converters. Additionally, smart-grid services such as vehicle-to-grid and vehicle-to-vehicle require the implementation of bi-directional stages that inevitably increase system complexity and component count. To face these design challenges, the present thesis provides a rigorous analysis of four-leg and split-capacitor three-phase four-wire active front-end topologies focusing on the harmonic description under different modulation techniques and conditions. The resulting analytical formulation paves the way for converter performance improvements while maintaining regulatory constraints and technical requirements under control. Specifically, split-capacitor inverter current ripple was characterized as providing closed-form formulations valid for every sub-case ranging from synchronous to interleaved PWM. Outcomes are the base for a novel variable switching PWM technique capable of mediating harmonic content limitation and switching loss reduction. A similar analysis is proposed for four-leg inverters with a broad range of continuous and discontinuous PWM modulations. The general superiority of discontinuous PWM modulation in reducing switching losses and limiting harmonic emission was demonstrated. Developments are realized through a parametric description of the neutral wire inductor. Finally, a novel class of integrated isolated converter topologies is proposed aiming at the neutral wire delivery without employing extra switching components rather than the one already available in typical three-phase inverter and dual-active-bridge back-to-back configurations. The fourth leg was integrated inside the dual-active-bridge input bridge providing relevant component count savings. A novel modified single-phase-shift modulation technique was developed to ensure a seamless transition between working conditions like voltage level and power factor. Several simulations and experiments validate the outcomes.

Performance assessment of vehicular connectivity in hybrid electric vehicles for fuel and emissions reduction

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of global warming. Recently, several metropolitan cities introduced Zero-Emissions Zones where the use of the Internal Combustion Engine is forbidden to reduce localized pollutants emissions. This is particularly problematic for Plug-in Hybrid Electric Vehicles, which usually work in depleting mode. In order to address these issues, the present thesis presents a viable solution by exploiting vehicular connectivity to retrieve navigation data of the urban event along a selected route. The battery energy needed, in the form of a minimum State of Charge (SoC), is calculated by a Speed Profile Prediction algorithm and a Backward Vehicle Model. That value is then fed to both a Rule-Based Strategy, developed specifically for this application, and an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS). The effectiveness of this approach has been tested with a Connected Hardware-in-the-Loop (C-HiL) on a driving cycle measured on-road, stimulating the predictions with multiple re-routings. However, even if hybrid electric vehicles have been recognized as a valid solution in response to increasingly tight regulations, the reduced engine load and the repeated engine starts and stops may reduce substantially the temperature of the exhaust after-treatment system (EATS), leading to relevant issues related to pollutant emission control. In this context, electrically heated catalysts (EHCs) represent a promising solution to ensure high pollutant conversion efficiency without affecting engine efficiency and performance. This work aims at studying the advantages provided by the introduction of a predictive EHC control function for a light-duty Diesel plug-in hybrid electric vehicle (PHEV) equipped with a Euro 7-oriented EATS. Based on the knowledge of future driving scenarios provided by vehicular connectivity, engine first start can be predicted and therefore an EATS pre-heating phase can be planned.

Analisi energetica al variare dello state of charge di propulsori ibridi e plug-in operanti nel ciclo WLTP con propulsore termico a punto fisso stechiometrico

Il presente lavoro propone la stesura di un codice in ambiente MATLAB per l'analisi energetica di powertrain ibridi operanti nel ciclo WLTP con il particolare funzionamento del motore termico benzina a punto fisso stechiometrico. Nello specifico, il codice prende dei dati in input tramite un'interfaccia grafica ed avvia una simulazione, i cui risultati principali corrispondono ad emissioni di anidride carbonica per chilometro percorso ed ai chilometri percorsi con un litro di carburante. Queste sono le due grandezze che questo lavoro si prefigge di ottimizzare, dalle quali proviene la scelta del particolare funzionamento del motore termico. Sono state implementate due differenti strategie di controllo, una generale ed una più particolare. La simulazione con la strategia generale è stata applicata a tre differenti scenari reali, con le caratteristiche tecniche di tre veicoli realmente esistenti che vengono inserite nell'interfaccia grafica. I risultati provenienti da queste simulazioni sono stati poi analizzati e discussi nel dettaglio, anche con l'ausilio di grafici a supporto della spiegazione. La strategia di controllo particolare non è stata applicata a scenari reali ma ha portato alla definizione di una ipotetica architettura di powertrain ibrido, alla quale la sopracitata strategia si adatta al meglio. Dopo aver proposto miglioramenti e possibili ulteriori sviluppi di questo lavoro, sono state tratte le conclusioni generali, allargando il tutto al contesto più ampio in cui si va ad inserire.

ICE Emissions Estimation through Machine-learning techniques to support real-world R&D experiments

The emissions estimation, both during homologation and standard driving, is one of the new challenges that automotive industries have to face. The new European and American regulation will allow a lower and lower quantity of Carbon Monoxide emission and will require that all the vehicles have to be able to monitor their own pollutants production. Since numerical models are too computationally expensive and approximated, new solutions based on Machine Learning are replacing standard techniques. In this project we considered a real V12 Internal Combustion Engine to propose a novel approach pushing Random Forests to generate meaningful prediction also in extreme cases (extrapolation, very high frequency peaks, noisy instrumentation etc.). The present work proposes also a data preprocessing pipeline for strongly unbalanced datasets and a reinterpretation of the regression problem as a classification problem in a logarithmic quantized domain. Results have been evaluated for two different models representing a pure interpolation scenario (more standard) and an extrapolation scenario, to test the out of bounds robustness of the model. The employed metrics take into account different aspects which can affect the homologation procedure, so the final analysis will focus on combining all the specific performances together to obtain the overall conclusions.

Parametric combustion modeling for ethanol-gasoline fuelled spark ignition engines

Ethanol-gasoline fuel blends are increasingly being used in spark ignition (SI) engines due to continued growth in renewable fuels as part of a growing renewable portfolio standard (RPS). This leads to the need for a simple and accurate ethanol-gasoline blends combustion model that is applicable to one-dimensional engine simulation. A parametric combustion model has been developed, integrated into an engine simulation tool, and validated using SI engine experimental data. The parametric combustion model was built inside a user compound in GT-Power. In this model, selected burn durations were computed using correlations as functions of physically based non-dimensional groups that have been developed using the experimental engine database over a wide range of ethanol-gasoline blends, engine geometries, and operating conditions. A coefficient of variance (COV) of gross indicated mean effective pressure (IMEP) correlation was also added to the parametric combustion model. This correlation enables the cycle combustion variation modeling as a function of engine geometry and operating conditions. The computed burn durations were then used to fit single and double Wiebe functions. The single-Wiebe parametric combustion compound used the least squares method to compute the single-Wiebe parameters, while the double-Wiebe parametric combustion compound used an analytical solution to compute the double-Wiebe parameters. These compounds were then integrated into the engine model in GT-Power through the multi-Wiebe combustion template in which the values of Wiebe parameters (single-Wiebe or double-Wiebe) were sensed via RLT-dependence. The parametric combustion models were validated by overlaying the simulated pressure trace from GT-Power on to experimentally measured pressure traces. A thermodynamic engine model was also developed to study the effect of fuel blends, engine geometries and operating conditions on both the burn durations and COV of gross IMEP simulation results.

MODELING OF TRANSFER PATH FOR DETERMINATION OF COMBUSTION AND NOISE METRICS ON DIESEL ENGINES

Determination of combustion metrics for a diesel engine has the potential of providing feedback for closed-loop combustion phasing control to meet current and upcoming emission and fuel consumption regulations. This thesis focused on the estimation of combustion metrics including start of combustion (SOC), crank angle location of 50% cumulative heat release (CA50), peak pressure crank angle location (PPCL), and peak pressure amplitude (PPA), peak apparent heat release rate crank angle location (PACL), mean absolute pressure error (MAPE), and peak apparent heat release rate amplitude (PAA). In-cylinder pressure has been used in the laboratory as the primary mechanism for characterization of combustion rates and more recently in-cylinder pressure has been used in series production vehicles for feedback control. However, the intrusive measurement with the in-cylinder pressure sensor is expensive and requires special mounting process and engine structure modification. As an alternative method, this work investigated block mounted accelerometers to estimate combustion metrics in a 9L I6 diesel engine. So the transfer path between the accelerometer signal and the in-cylinder pressure signal needs to be modeled. Depending on the transfer path, the in-cylinder pressure signal and the combustion metrics can be accurately estimated - recovered from accelerometer signals. The method and applicability for determining the transfer path is critical in utilizing an accelerometer(s) for feedback. Single-input single-output (SISO) frequency response function (FRF) is the most common transfer path model; however, it is shown here to have low robustness for varying engine operating conditions. This thesis examines mechanisms to improve the robustness of FRF for combustion metrics estimation. First, an adaptation process based on the particle swarm optimization algorithm was developed and added to the single-input single-output model. Second, a multiple-input single-output (MISO) FRF model coupled with principal component analysis and an offset compensation process was investigated and applied. Improvement of the FRF robustness was achieved based on these two approaches. Furthermore a neural network as a nonlinear model of the transfer path between the accelerometer signal and the apparent heat release rate was also investigated. Transfer path between the acoustical emissions and the in-cylinder pressure signal was also investigated in this dissertation on a high pressure common rail (HPCR) 1.9L TDI diesel engine. The acoustical emissions are an important factor in the powertrain development process. In this part of the research a transfer path was developed between the two and then used to predict the engine noise level with the measured in-cylinder pressure as the input. Three methods for transfer path modeling were applied and the method based on the cepstral smoothing technique led to the most accurate results with averaged estimation errors of 2 dBA and a root mean square error of 1.5dBA. Finally, a linear model for engine noise level estimation was proposed with the in-cylinder pressure signal and the engine speed as components.

Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.

Spontaneous-combustion propensity of New Zealand coals under adiabatic conditions

Pulverised New Zealand coal samples have been tested from an initial temperature of 40 degreesC and reacted adiabatisally in an oven with oxygen to provide a full temperature history of auto-oxidation up to the self-sustained process of combustion. This procedure produces a self-heating rate index, R-70, calculated as the ratio of the time taken to reach 70 degreesC (degreesC/h). The R-70 index is a measure of the coal's propensity to spontaneous combustion. R-70 values for New Zealand coals are much higher than any previously published results. They show a rank dependence, whereby subbituminous coals have the highest propensity to spontaneous combustion (14.91-17.23 degreesC/h). A lignite sample has an R-70 value of 7.76 degreesC/h, and high-volatile bituminous B coals have R-70 values of 0.31-2.23 degreesC/h. Samples stored for 2 years show the same rank trend. The nature of this trend is most likely a function of the internal surface area of the coal that governs the available sites for oxidation. Calculating the Suggate rank; for any New Zealand coal can be used to rare its propensity to spontaneous combustion. Resin bodies in the subbituminous coal show no propensity to spontaneous combustion. (C) 2001 Elsevier Science B.V. All rights reserved.

Catalytic combustion of toluene on Pt zeolite coated cordierite foams

The catalytic properties of Pt based cordierite foam catalysts have been evaluated in catalytic combustion of toluene (800 ppm in air). The catalysts contain identical Pt content (0.1%) which was introduced by three different ways: Pt ion exchange on MFI zeolite and then coating on the foam; Pt ion exchange after zeolite coating and finally Pt directly wet impregnated on the cordierite foam. The catalytic behaviour of Pt foam based catalysts was compared with that of PtMFI zeolite under powder form. Pt exchanged MFI supported on the cordierite foams present an improvement of activity for toluene combustion of about 50 degrees C on the light off temperature (T-50%). The enhanced performance of the structured catalysts is due not only to the open structure of foams and homogeneous thin layers catalyst deposited on their cell walls, but also to the fact that the size and location of Pt particles present in MFI zeolite are changed during the dipping step. Indeed, as prepared Pt samples and those used in the preparation of the slurry were observed by transmission electron microscopy revealing that the chemical interaction of PtMFI zeolite with the binder and detergent, both present in the slurry, leads to an increase of Pt particles size which were found to migrate from internal pores to the external surface of zeolite crystallites thereby increasing catalytic activity. (C) 2011 Elsevier B.V. All rights reserved.

Impact of thermal proofing of a church on its indoor air-quality - The combustion of candles and incense as a source of pollution

Some years ago, a parish in Geneva decided to reduce heating costs by insulating its church to make it more energy efficient. Three years after the last renovations, it was observed that the internal surfaces of the naves had already become dusty compared with the customary frequency of 10-12 years. Dust even deposited on various surfaces during religious services. Our investigation showed that nearly all the dust found inside the church may in fact be soot from incense and candle combustion. Incense appears to be a significant source of polycyclic aromatic hydrocarbons. With a mechanical ventilation system and petrol lamps resembling candles the problem can be resolved.

Basin-internal derivation of hydrocarbons in the Witwatersrand Basin, South Africa: evidence from bulk and molecular δ13C data

Gold in the quartz-pebble conglomerates of the late Archean Witwatersrand Basin, South Africa, is often intimately associated with carbonaceous matter of organic/biogenic origin which occurs in the form of stratiform carbon seams and paragenetically late bitumen nodules. Both carbon forms are believed to be formed by solidification of migrating hydrocarbons. This paper presents bulk and molecular chemical and stable carbon isotope data for the carbonaceous matter, all of which are used to provide a clue to the source of the hydrocarbons. These data are compared with those from intra-basinal shales and overlying dolostone of the Transvaal Supergroup. The delta C-13 values of the extracts from the Witwatersrand carbonaceous material show small differences (up to 2.4 parts per thousand) compared to the associated insoluble organic matter. This suggests that the auriferous rocks were stained by mobile hydrocarbons produced by thermal and oxidative alteration of indigenous bitumens, a contribution from hydrocarbons derived from intra-basinal Witwatersrand shales cannot be excluded. Individual aliphatic hydrocarbons of the various carbonaceous materials were subjected to compound specific isotope analysis using on-line gas chromatography/combustion/stable isotope ratio mass spectrometry (GC/C/IRMS). The limited variability of the molecular parameters and uniform delta C-13 values of individual n-alkanes (-31.1 +/- 1.7 parts per thousand) and isoprenoids (-30.7 +/- 1.1 parts per thousand) in the Witwatersrand samples exclude the mixing of oils from different sources. Carbonaceous matter in the dolostones shows distinctly different bulk and molecular isotope characteristics and thus cannot have been the source of the hydrocarbons in the Witwatersrand deposits. All the various forms of Witwatersrand carbon appear indigenous to the Witwatersrand Basin, and the differences between them are explained by variable, in general probably short (centimeter- to meter-scale) hydrocarbon migration during diagenesis and subsequent hydrothermal infiltration. (C) 2001 Elsevier Science B.V. All rights reserved.