New SR drive with integrated charging capacity for plug-in hybrid electric vehicles (PHEVs)

Plug-in hybrid electric vehicles (PHEVs) provide much promise in reducing greenhouse gas emissions and, thus, are a focal point of research and development. Existing on-board charging capacity is effective but requires the use of several power conversion devices and power converters, which reduce reliability and cost efficiency. This paper presents a novel three-phase switched reluctance (SR) motor drive with integrated charging functions (including internal combustion engine and grid charging). The electrical energy flow within the drivetrain is controlled by a power electronic converter with less power switching devices and magnetic devices. It allows the desired energy conversion between the engine generator, the battery, and the SR motor under different operation modes. Battery-charging techniques are developed to operate under both motor-driving mode and standstill-charging mode. During the magnetization mode, the machine's phase windings are energized by the dc-link voltage. The power converter and the machine phase windings are controlled with a three-phase relay to enable the use of the ac-dc rectifier. The power converter can work as a buck-boost-type or a buck-type dc-dc converter for charging the battery. Simulation results in MATLAB/Simulink and experiments on a 3-kW SR motor validate the effectiveness of the proposed technologies, which may have significant economic implications and improve the PHEVs' market acceptance.

From science gateways to commercial solutions

The European CloudSME project that incorporated 24 European SMEs, besides five academic partners, has finished its funded phase in March 2016. This presentation will provide a summary of the results of the project, and will analyze the challenges and differences when developing “SME Gateways”, when compared to “Science Gateways”. CloudSME started in 2013 with the aim to develop a cloud-based simulation platform for manufacturing and engineering SMEs. The project was based around industry use-cases, five of which were incorporated in the project from the start, and seven additional ones that were added as an outcome of an open call in January 2015. CloudSME utilized science gateway related technologies, such as the commercial CloudBroker Platform and the WS-PGRADE/gUSE Gateway Framework that were developed in the preceding SCI-BUS project. As most important outcome, the project successfully implemented 12 industry quality demonstrators that showcase how SMEs in the manufacturing and engineering sector can utilize cloud-based simulation services. Some of these solutions are already market-ready and currently being rolled out by the software vendor companies. Some others require further fine-tuning and the implementation of commercial interfaces before being put into the market. The CloudSME use-cases came from a very wide application spectrum. The project implemented, for example, an open marketplace for micro-breweries to optimize their production and distribution processes, an insole design validation service to be used by podiatrists and shoe manufacturers, a generic stock management solution for manufacturing SMEs, and also several “classical” high-performance computing case-studies, such as fluid dynamics simulations for model helicopter design, and dual-fuel internal combustion engine simulation. As the project generated significant impact and interest in the manufacturing sector, 10 CloudSME stakeholders established a follow-up company called CloudSME UG for the future commercialization of the results. Besides the success stories, this talk would also like to highlight the difficulties when transferring the outcomes of an academic research project to real commercial applications. The different mindset and approach of academic and industry partners presented a real challenge for the CloudSME project, with some interesting and valuable lessons learnt. The academic way of supporting SMEs did not always work well with the rather different working practices and culture of many participants. Also, the quality of support regarding operational solutions required by the SMEs is well beyond the typical support services academic institutions are prepared for. Finally, a clear lack of trust in academic solutions when compared to commercial solutions was also imminent. The talk will highlight some of these challenges underpinned by the implementation of the CloudSME use-cases.

Novel Automotive Waste Heat Recovery Techniques

The United States transportation industry is predicted to consume approximately 13 million barrels of liquid fuel per day by 2025. If one percent of the fuel energy were salvaged through waste heat recovery, there would be a reduction of 130 thousand barrels of liquid fuel per day. This dissertation focuses on automotive waste heat recovery techniques with an emphasis on two novel techniques. The first technique investigated was a combination coolant and exhaust-based Rankine cycle system, which utilized a patented piston-in-piston engine technology. The research scope included a simulation of the maximum mass flow rate of steam (700 K and 5.5 MPa) from two heat exchangers, the potential power generation from the secondary piston steam chambers, and the resulting steam quality within the steam chamber. The secondary piston chamber provided supplemental steam power strokes during the engine's compression and exhaust strokes to reduce the pumping work of the engine. A Class-8 diesel engine, operating at 1,500 RPM at full load, had a maximum increase in the brake fuel conversion efficiency of 3.1%. The second technique investigated the implementation of thermoelectric generators on the outer cylinder walls of a liquid-cooled internal combustion engine. The research scope focused on the energy generation, fuel energy distribution, and cylinder wall temperatures. The analysis was conducted over a range of engine speeds and loads in a two cylinder, 19.4 kW, liquid-cooled, spark-ignition engine. The cylinder wall temperatures increased by 17% to 44% which correlated well to the 4.3% to 9.5% decrease in coolant heat transfer. Only 23.3% to 28.2% of the heat transfer to the coolant was transferred through the TEG and TEG surrogate material. The gross indicated work decreased by 0.4% to 1.0%. The exhaust gas energy decreased by 0.8% to 5.9%. Due to coolant contamination, the TEG output was not able to be obtained. TEG output was predicted from cylinder wall temperatures and manufacturer documentation, which was less than 0.1% of the cumulative heat release. Higher TEG conversion efficiencies, combined with greater control of heat transfer paths, would be needed to improve energy output and make this a viable waste heat recovery technique.

Development of an innovative non rule-based energy management strategy for a Hybrid Electric Vehicle, structured for predictive driving controls based on external information knowledge

Recently, the interest of the automotive market for hybrid vehicles has increased due to the more restrictive pollutants emissions legislation and to the necessity of decreasing the fossil fuel consumption, since such solution allows a consistent improvement of the vehicle global efficiency. The term hybridization regards the energy flow in the powertrain of a vehicle: a standard vehicle has, usually, only one energy source and one energy tank; instead, a hybrid vehicle has at least two energy sources. In most cases, the prime mover is an internal combustion engine (ICE) while the auxiliary energy source can be mechanical, electrical, pneumatic or hydraulic. It is expected from the control unit of a hybrid vehicle the use of the ICE in high efficiency working zones and to shut it down when it is more convenient, while using the EMG at partial loads and as a fast torque response during transients. However, the battery state of charge may represent a limitation for such a strategy. That’s the reason why, in most cases, energy management strategies are based on the State Of Charge, or SOC, control. Several studies have been conducted on this topic and many different approaches have been illustrated. The purpose of this dissertation is to develop an online (usable on-board) control strategy in which the operating modes are defined using an instantaneous optimization method that minimizes the equivalent fuel consumption of a hybrid electric vehicle. The equivalent fuel consumption is calculated by taking into account the total energy used by the hybrid powertrain during the propulsion phases. The first section presents the hybrid vehicles characteristics. The second chapter describes the global model, with a particular focus on the energy management strategies usable for the supervisory control of such a powertrain. The third chapter shows the performance of the implemented controller on a NEDC cycle compared with the one obtained with the original control strategy.

Powertrain Architectures and Technologies for New Emission and Fuel Consumption Standards

New powertrain design is highly influenced by CO2 and pollutant limits defined by legislations, the demand of fuel economy in for real conditions, high performances and acceptable cost. To reach the requirements coming from both end-users and legislations, several powertrain architectures and engine technologies are possible (e.g. SI or CI engines), with many new technologies, new fuels, and different degree of electrification. The benefits and costs given by the possible architectures and technology mix must be accurately evaluated by means of objective procedures and tools in order to choose among the best alternatives. This work presents a basic design methodology and a comparison at concept level of the main powertrain architectures and technologies that are currently being developed, considering technical benefits and their cost effectiveness. The analysis is carried out on the basis of studies from the technical literature, integrating missing data with evaluations performed by means of powertrain-vehicle simplified models, considering the most important powertrain architectures. Technology pathways for passenger cars up to 2025 and beyond have been defined. After that, with support of more detailed models and experimentations, the investigation has been focused on the more promising technologies to improve internal combustion engine, such as: water injection, low temperature combustions and heat recovery systems.

Development of a thermochemical/biological process to convert waste biomass into new resources

The increasing attention to environmental issues of recent times encourages us to find new methods for the production of energy from renewable sources, and to improve existing ones, increasing their energy yield. Most of the waste and agricultural residues, with a high content of lignin and non-hydrolysable polymers, cannot be effectively transformed into biofuels with existing technology. The purpose of the study was to develop a new thermochemical/ biological process (named Py-AD) for the valorization of scarcely biodegradable substances. A complete continuous prototype was design built and run for 1 year. This consists into a slow pyrolysis system coupled with two sequential digesters and showed to produce a clean pyrobiogas (a biogas with significant amount of C2-C3 hydrocarbons and residual CO/H2), biochar and bio-oil. Py-AD yielded 31.7% w/w biochar 32.5% w/w oil and 24.8% w/w pyrobiogas. The oil condensate obtained was fractionated in its aqueous and organic fraction (87% and 13% respectively). Subsequently, the anaerobic digestion of aqueous fraction was tested in a UASB reactor, for 180 days, in increasing organic loading rate (OLR). The maximum convertible concentration without undergoing instability phenomena and with complete degradation of pyrogenic chemicals was 1.25 gCOD L digester-1 d-1. The final yield of biomethane was equal to 40% of the theoretical yield and with a noticeable additional production equal to 20% of volatile fatty acids. The final results confirm that anaerobic digestion can be used as a useful tool for cleaning of slow pyrolysis products (both gas and condensable fraction) and the obtaining of relatively clean pyrobiogas that could be directly used in internal combustion engine.

Design of an innovative electric vehicle simulator for Charging Systems' End-of-Line Testing

The trend related to the turnover of internal combustion engine vehicles with EVs goes by the name of electrification. The push electrification experienced in the last decade is linked to the still ongoing evolution in power electronics technology for charging systems. This is the reason why an evolution in testing strategies and testing equipment is crucial too. The project this dissertation is based on concerns the investigation of a new EV simulator design. that optimizes the structure of the testing equipment used by the company who commissioned this work. Project requirements can be summarized in the following two points: space occupation reduction and parallel charging implementation. Some components were completely redesigned, and others were substituted with equivalent ones that could perform the same tasks. In this way it was possible to reduce the space occupation of the simulator, as well as to increase the efficiency of the testing device. Moreover, the possibility of conjugating different charging simulations could be investigated by parallelly launching two testing procedures on a unique machine, properly predisposed for supporting the two charging protocols used. On the back of the results achieved in the body of this dissertation, a new design for the EV simulator was proposed. In this way, space reduction was obtained, and space occupation efficiency was improved with the proposed new design. The testing device thus resulted to be way more compact, enabling to gain in safety and productivity, along with a 25% cost reduction. Furthermore, parallel charging was implemented in the proposed new design since the conducted tests clearly showed the feasibility of parallel charging sessions. The results presented in this work can thus be implemented to build the first prototype of the new EV simulator.

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.

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.

THERMAL CHARACTERIZATION OF COMBUSTION CHAMBER COMPONENTS IN A GASOLINE TURBOCHARGED DIRECT INJECTION (GTDI) ENGINE

This report is a PhD dissertation proposal to study the in-cylinder temperature and heat flux distributions within a gasoline turbocharged direct injection (GTDI) engine. Recent regulations requiring automotive manufacturers to increase the fuel efficiency of their vehicles has led to great technological achievements in internal combustion engines. These achievements have increased the power density of gasoline engines dramatically in the last two decades. Engine technologies such as variable valve timing (VVT), direct injection (DI), and turbocharging have significantly improved engine power-to-weight and power-to-displacement ratios. A popular trend for increasing vehicle fuel economy in recent years has been to downsize the engine and add VVT, DI, and turbocharging technologies so that a lighter more efficient engine can replace a larger, heavier one. With the added power density, thermal management of the engine becomes a more important issue. Engine components are being pushed to their temperature limits. Therefore it has become increasingly important to have a greater understanding of the parameters that affect in-cylinder temperatures and heat transfer. The proposed research will analyze the effects of engine speed, load, relative air-fuel ratio (AFR), and exhaust gas recirculation (EGR) on both in-cylinder and global temperature and heat transfer distributions. Additionally, the effect of knocking combustion and fuel spray impingement will be investigated. The proposed research will be conducted on a 3.5 L six cylinder GTDI engine. The research engine will be instrumented with a large number of sensors to measure in-cylinder temperatures and pressures, as well as, the temperature, pressure, and flow rates of energy streams into and out of the engine. One of the goals of this research is to create a model that will predict the energy distribution to the crankshaft, exhaust, and cooling system based on normalized values for engine speed, load, AFR, and EGR. The results could be used to aid in the engine design phase for turbocharger and cooling system sizing. Additionally, the data collected can be used for validation of engine simulation models, since in-cylinder temperature and heat flux data is not readily available in the literature..

Automotive diesel engine transient operation: modeling, optimization and control

Traditionally, the study of internal combustion engines operation has focused on the steady-state performance. However, the daily driving schedule of automotive engines is inherently related to unsteady conditions. There are various operating conditions experienced by (diesel) engines that can be classified as transient. Besides the variation of the engine operating point, in terms of engine speed and torque, also the warm up phase can be considered as a transient condition. Chapter 2 has to do with this thermal transient condition; more precisely the main issue is the performance of a Selective Catalytic Reduction (SCR) system during cold start and warm up phases of the engine. The proposal of the underlying work is to investigate and identify optimal exhaust line heating strategies, to provide a fast activation of the catalytic reactions on SCR. Chapters 3 and 4 focus the attention on the dynamic behavior of the engine, when considering typical driving conditions. The common approach to dynamic optimization involves the solution of a single optimal-control problem. However, this approach requires the availability of models that are valid throughout the whole engine operating range and actuator ranges. In addition, the result of the optimization is meaningful only if the model is very accurate. Chapter 3 proposes a methodology to circumvent those demanding requirements: an iteration between transient measurements to refine a purpose-built model and a dynamic optimization which is constrained to the model validity region. Moreover all numerical methods required to implement this procedure are presented. Chapter 4 proposes an approach to derive a transient feedforward control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient.