The paper describes the design, the test and the optimization of a prototype for the European Shell Eco-Marathon (SEM) competition. The design step includes the definition of vehicle shape, materials, structure, tires, power-train and control with an inter-disciplinary approach. The test phase was performed both numerically and experimentally. The vehicle, named Carla 2012 has been build at the DII (Department of Innovation Engineering) at Università Del Salento and tested on the facilities available at the Nardò Technical Center and was able to satisfy all the specifics of SEM regulation in 2012 edition. The optimization step is aimed at defining an innovative powertrain and an high-efficiency race strategy in order to achieve 3000 km with the equivalent of 1 liter of gasoline.

The present study aims at the implementation of a Matlab/Simulink environment to assess the performance (thrust, specific fuel consumption, aircraft/engine mass, cost, etc.) and environmental impact (greenhouse and pollutant emissions) of conventional and more electric aircrafts. In particular, the benefits of adopting more electric solutions for either aircrafts at given missions specifications can be evaluated. The software, named PLA.N.E.S, includes a design workflow for the input of aircraft specification, kind of architecture (e.g. series or parallel) and for the definition of each component including energy converter (piston engine, turboprop, turbojet, fuel cell, etc.), energy storage system (batteries, super-capacitors), auxiliaries and secondary power systems. It is also possible to setup different energy management strategies for the optimal control of the energy flows among engine, secondary equipment and storage systems during the mission. The tool is designed to be integrated with a multi-objective optimization environment. In the present investigation the tools has been applied to a regional airliner (ATR 72-600) as a case study and two options for the propulsion system were considered: conventional and More Electric Aircraft. In order to validate the proposed turboprop model, the results obtained with PLA.N.E.S. were compared to nominal literature data and numerical values obtained with the Gas Turbine Simulation Program (GSP).

Vehicular communications are expected to enable the development of Intelligent Cooperative Systems to be exploited for solving crucial problems related to mobility: road safety, traffic management etc. Information and Communication Technologies could also play a very important role in order to optimize the energy management of conventional, hybrid and electrical vehicles and, thus, to reduce their environment impact. In particular, vehicular communications could be used to predict driving conditions with the objective to determinate future load power demand. An adaptative energy management strategy for series hybrid electric vehicles based on genetic algorithm optimized maps and the SUMO (Simulation of Urban Mobility) predictor is presenter here. The control stategy paremeters are optimized over a series of possible mini cycles (duration $60s$) obteined by a K-means clustering algorithm. These references mini cycles are colled centroids. The centroids are abteined with respect at $60s$ time windowed standard driving cycles (UDDS, EUDC, etc) and realistic driving cycles acquired.

The present investigation describes the results of a research project (P.R.I.M.E.) aimed at testing the performance and the environmental impact of an electric city car in Italian cities. The vehicle considered in the project is the Daimler AG Smart ForTwo Electric Drive. A Smart ED vehicle was tested at the University of Salento for six months over different driving conditions (routes, traffic, use of auxiliaries). A data acquisition system has been designed on purpose and assembled on board to provide information about driving cycle and energy flows. The system was also used to evaluate the losses of energy during recharges due to the battery cooling system. The experimental tests were used to identify the average, minimum and maximum consumption of electricity in the Smart ED in Lecce according to driving conditions and in particular according to the usage of auxiliaries. The measured data of electric consumption have been used to quantify the emissions of CO2 and pollution of the vehicle using information about the Italian electricity production mix of each recharging event and the emissions factors of the Italian power plants with an innovative and comprehensive methodology.

Abstract: - A mobile test bench for testing energy management strategies for fuel cell hybrid electric vehicle has been obtained by modifying a Volksbot RT3 differential drive mobile robot. The robot provides the University of Salento with a low-cost system to test models and develop control strategies applicable to real scale vehicles. In fact, the prototype has been developed with the goal of implementing any control strategies by setting the instantaneous power split between the fuel cell and the batteries. H2Volks can be moved in two modes: a free mode that allow the user to simulate and acquire realistic driving cycles and a controlled mode that can be used to test different control strategies over the same driving cycle. In particular, a control strategy presented by the authors in a previous investigation has been implemented on the H2-VOLKS.

Electric flight is of increasing interest in order to reduce emissions of pollution and greenhouse gases in the aviation field in particular when the takeoff mass is low, as in the case of lightweight cargo transport or remotely controlled drones. The present investigation addresses two key issues in electric flight, namely the correct calculation of the endurance and the comparison between batteries and fuel cells, with a mission-based approach. As a test case, a light Unmanned Aerial Vehicle (UAV) powered exclusively by a Polymer Electrolyte Membrane fuel cell with a gaseous hydrogen tank was compared with the same aircraft powered by different kinds of Lithium batteries sized to match the energy stored in the hydrogen tank. The mass and the volume of each powertrain were calculated with literature data about existing technologies for propellers, motors, batteries and fuel cells. The empty mass and the wing area of the UAV were amended with the mass of the proposed powertrain to explore the range of application of the proposed technologies. To evaluate the efficiency of the whole powertrain a simulation software was used instead of considering only level flight. This software allowed an in-depth analysis on the efficiency of all sub-systems along the flight. The secondary demand of power for auxiliaries was taken into account along with the propulsive power. The main parameter for the comparison was the endurance but the takeoff performance, the volume of the powertrain and the environmental impact were also taken into account. The battery-based powertrain was found to be the most suitable for low-energy applications while the fuel cell performed better when increasing the amount of energy stored on board. The investigation allowed the estimation of the threshold above which the fuel cell based powertrain becomes the best solution for the UAV.

Wind and fluid flow represent some of the most attractive renewable energy sources for addressing climate change, pollution and energy insecurity issues. Wind harvesting technologies, in particular, are the fastestgrowing electric technologies in the world because of their efficiency and lower environmental impact with respect to traditional energy sources, despite exhibiting major drawbacks such as big infrastructure investment and environment invasiveness, producing high levels of noise and requiring the need of large areas for their installation. A single wind turbine can produce megawatts of power and they have the potential to cover the entire world's energy demand in the next few years, but they have a technological limit in a cut-in wind speed of about 4 m s(-1), below which the turbines do not operate, excluding them as an energy source for slow air flows. At the same time most of the wind available in the environment is below the turbines' threshold speed. In this paper we show that small flags, made by piezoelectric thin film on flexible polymers and whose shape resembles the dry leaves of trees, can efficiently act as harvesters of energy from wind at extremely low speed, such as from a gentle blow or breath. We demonstrate that piezoelectricity on flexible polymers is achievable by depositing a thin film of piezoelectric aluminium nitride (AlN), sandwiched between metal electrodes with columnar grains coherent through the polycrystalline layers, on Kapton substrates. The prototype flags have a natural curling due to the release of the residual stress of the layers. While the curling is essential for the activation of the maximum flag oscillation, this system is so elastic and light that oscillations start at a cut-in flow speed of 0.4 m s(-1), the lowest reported so far, with an open circuit peak to peak voltage of 40 mV. The voltage increases to 1.2 V when the flag is flattened and parallel to the fluid flow lines, with a generated power of 0.257 mW cm(-3)

A tool has been developed to integrate electric vehicles into a general systems for the energy management and optimization of energy from renewable sources in the Campus of the University of Salento. The tool is designed to monitor the status of plug-in vehicles and recharging station and manage the recharging on the basis of the prediction of power from the photovoltaic roofs and usage of electricity in three buildings used by the Department of engineering. The tool will allow the surplus of electricity from photovoltaic to be used for the recharge of the plug-in vehicles. In the present investigation, the benefits in terms of CO2 and costs of the scheduled recharge with respect to free recharge are evaluated on the basis of the preliminary data acquired in the first stage of the experimental campaign.

The use of a hybrid powertrain for a conventional single main rotor helicopter is investigated, with the objective of assessing its feasibility and its potential impact on improving safety, especially for single-engine rotorcraft. The study is focused on the characteristics of the powertrain and required battery pack. It is based on a simple analysis of power required in forward flight and the estimate of the total energy required for a powered landing maneuver after thermal engine failure. Current technologies are considered as well as expected improvements, especially as far as energy density and power density of the battery are concerned. The latter analysis is based on current trends for battery and motors technologies, in order to determine the technological breakthrough limit.

The EU6d Emission Regulation requires Real Driving Emissions as an additional type approval requirement within the 2017 - 2020 timeframe in order to take into account the influence of the road profile, the ambient conditions and the traffic situation as well as the behavior of the driver. The new test uses Portable Emissions Monitoring System (PEMS) to measure on-board emissions. The trip sequence shall consist of a urban, a rural and a motorway sections with specific requirements in terms of distance and average speed for each section. For example, the overall trip duration shall be between 90 and 120 minutes. Due to these strong requirements, the execution of RDE measurements has to be preceded by an accurate planning of the route to reduce test failure risk and, consequently, experimental costs. The aim of the present investigation is to present a procedure to build a cycle for real driving emissions that minimizes the distance, is robust with respect to the uncertainties of traffic conditions and satisfy the requirements of the regulations. The procedure has been applied to routes from and to the Department of Engineering for Innovation. Moreover, a preliminary analysis of the effect of instantaneous speed and acceleration on real drive emissions is presented.

Information and Communication Technologies can play a very important role in order to optimize the energy usage of hybrid and electrical vehicles and, thus, to reduce their environmental impact. In particular, vehicular communications can be exploited to spread information useful to predict future driving conditions and, then, future load power demand of vehicles. In the present investigation, the potentiality of ICT to reach this goal has been analyzed numerically with respect to a plug-in hybrid electric vehicle and a battery electric vehicle. The simulation of the driving scenario and the prediction of future speed profile on board of a vehicle have been obtained with the use of a vehicular traffic simulator (SUMO). CO 2 emissions were calculated with at Well-To-Wheel approach with respect to realistic urban driving patterns.

The paper proposes an analytical methodology that uses empirical based models and CFD simulations to efficiently evaluate design alternatives in the conversion of a diesel engine to either CNG dedicated or dual fuel engines. The procedure is performed in five steps. Firstly, a database of different combustion chambers that can be obtained from the original piston is obtained. The chambers in the database differ for the shape of the bowl, the value of the compression ratio, the offset of the bowl and the size of the squish region. The second step of the procedure is the selection, from the first database, of the combustion chambers able to resist to the mechanical stresses due to the pressure and temperature distribution at full load. For each combination of suitable combustion chamber shape and engine control parameters (ignition/injection crank angle, EGR, etc.), a CFD simulation is used to evaluate the combustion performance of the engine. Then, a post-processing procedure is used to evaluate the detonation tendency and intensity of each combination. All the tools developed for the application of the method have been linked in the ModeFrontier optimization environment in order to perform the final choice of the combustion chamber. The overall process requires not more of a week of computation on the four processor servers considered for the optimization. Moreover, the selected chambers can be obtained from the original piston of the engine. Therefore, the conversion cost of the engine is quite small compared with the case of a completely new piston. The paper also describes the application of the procedure to two different engines.

The aim of the proposed investigation is to design and analyze the performance of a hybrid electric power system for multicopter and to evaluate its performance. To this, the overall power request was assumed to be satisfied in three possible ways: a battery (electric power system), a generator powered by a two-stroke internal combustion engine (thermal power system), and both battery and engine (hybrid power system). The fuel stored on board was calculated for each configuration by keeping constant the overall mass. In the hybrid case, the engine also allows the battery to be recharged during the flight with an on/off behavior of the engine. Electric mode is started when the batteries are sufficiently charged and can produce the required propulsive power. This mode goes on as long as the state of charge (SOC) is above a minimum value. When the SOC is lower than this value, the batteries let the engine be restarted by the generator. Then, the engine generates both the power for propulsion and to recharge the battery. After a sensitivity analysis, an optimization has been performed by considering different thresholds for the battery state of charge to shift from electric to recharge mode and by taking into account different values of the recharge current. The methodology was applied to two different multicopters and the proposed powertrains were simulated with a backward approach starting from experimental time histories of required electric power.

The design of a hybrid electric powertrain requires a complex optimization procedure because its performance will strongly depend on both the size of the components and the energy management strategy. The problem is particular critical in the aircraft field because of the strong constraints to be fulfilled (in particular in terms of weight and volume). The problem was addressed in the present investigation by linking an in-house simulation code for hybrid electric aircraft with a commercial many-objective optimization software. The design variables include the size of engine and electric motor, the specification of the battery (typology, nominal capacity, bus voltage), the cooling method of the motor and the battery management strategy. Several key performance indexes were suggested by the industrial partner. The four most important indexes were used as fitness functions: electric endurance, fuel consumption, take-off distance and powertrain volume. A design able to fulfill all the targets set by the industrial partner was found using an elimination-by-aspect approach applied to the overall Pareto front. The results of the algorithm were post-processed and some metrics were used to evaluate the performance of the genetic algorithm in solving the proposed optimization problem.

A simulation software for the assessment of performance, costs and environmental impact of conventional and advanced configuration aircraft has been developed and validated. The software is named PLA.N.E.S. (PLAtform for New Environment-friendly Solutions), and includes a sizing routine and a mission simulator. The simulation is performed with the so-called backward paradigm, i.e. the flight conditions along the mission (altitude and speed versus time) are assumed to be known. Accordingly, the instantaneous power request of the aircraft to meet that flight mission and the corresponding instantaneous fuel consumption are calculated. In the case of advanced powertrains, it is also possible to choose different energy management strategies for the optimal control of the energy flows among engine, secondary equipment and storage systems during the mission. The components currently modeled in PLA.N.E.S. include energy converters (piston and Wankel engines, turboprop, fuel cell, etc.), energy storage systems (batteries, super-capacitors), auxiliaries and secondary power systems. The tool is designed to be integrated with a multi-objective optimization environment. In the present investigation PLA.N.E.S. has been applied to a Medium Altitude Medium Endurance (MAME) Unmanned Aerial Vehicle (UAV) as a case study to compare an experimentally validated Wankel-based powertrain with a proposed turbocharged diesel piston-prop system.

An adaptative energy management strategy for series hybrid electric vehicles based on optimized maps and the SUMO (Simulation of Urban MObility) predictor is presented here. The first step of the investigation is the off line optimization of the control strategy parameters (already developed by the authors) over a series of reference mini driving cycles (duration of 60s) obtained from standard driving cycles (UDDS, EUDC, etc) and realistic driving cycles acquired on the ITAN500 HEV. The optimal variables related to each mini driving cycle are stored in maps that are then implemented on the ITAN500 vehicles. When the vehicle moves, a wireless card is used to exchange information with surrounding vehicle and infrastructure. These information are used by a local instance of the SUMO traffic prediction tool (run on board) to predict the driving conditions of the HEV in the future period of time T=60s. The predicted driving cycle is compared with the reference mini driving cycles and the most similar one is found. The optimal control strategy parameters mapped for that reference cycle are then used to select the power-split in the future time window. This process is repeated every T seconds obtaining an adaptative control strategy which do not requires much computational power on board. The proposed approach has been compared numerically with the “no knowledge” approach and the “full knowledge” approach. In the “no knowledge” case, the energy management was optimized for NEDC and then applied to three realistic driving cycles. In the “full knowledge” approach the energy management was optimized for each realistic driving cycle. The “full knowledge” approach allows the best fuel consumption to be obtained but requires the knowledge of the whole vehicle mission while the “no knowledge” method gives poor results since it cannot exploit the potentiality of a PHEV. The proposed approach allows good results to be obtained in terms of fuel consumption thanks to a better usage of the internal combustion engine.

This investigation describes the dynamic modeling of a PEM (Polymer Electrolyte Membrane) fuel cell applied to a commercial 1kW dead end anode configuration. The system is tested and validated through some initial experiments. The model allows the characterization of the polarization curve, the evaluation of cell performance in terms of efficiency and consumption and the estimation of water production. To this purpose, an experimental set-up has been created using an electronic DC load (connected to a computer by RS232 serial communication) and an NI DAQ CompactRio evaluation board. The target is studying and testing solutions to improve performance, in particular with reference to hydrogen recovery solution from the purge valve. The fuel cell model has been interfaced with a 3D race simulator that is able to reproduce the environment of the competition and the specification of the vehicle. This allows the analysis of the driver’s single lap results in terms of performance and fuel consumption according to the goals of the competition. In the present investigation the rules of the Shell Eco Marathon 2012 competition have been taken into account. Thanks to the developed tool, the driver is able to choose the best race strategy both interactively or with the help of a external optimizer.

This investigation describes the results of an experimental and numerical research project aimed at comparing mileage and CO2 emissions from two different commercial versions of Daimler AG Smart ForTwo car: conventional (gasoline) and electric (ED). The investigation includes numerical simulations with the AVL CRUISE software package and on-board acquisitions. A data acquisition system has been designed for this purpose and assembled on board of the Smart ED. The system is composed by a GPS antenna with USB interface, two current transducers, a NI-DAQ device and a netbook computer with a LabView-VI. This system provided on-board information about driving cycle and current flows, gathered simultaneously by GPS, transducers and NI-DAQ. The system was also used to evaluate the losses of energy during the recharge of the electric car. The two cars have been tested over a wide range of driving conditions related to different routes, traffic conditions and use of on-board accessories (i.e. Air Conditioning and radio). The CO2 emissions have been evaluated with a Well-to-Wheel approach.

Renewable and alternative fuels have numerous advantages compared to fossil fuels as they are biodegradable, providing energy security and foreign exchange saving and addressing environmental concerns, and socio-economic issues as well. Therefore renewable fuels can be predominantly used as fuel for transportation and power generation applications. In view of this background, effect of nozzle and combustion chamber geometry on the performance, combustion and emission characteristics have been investigated in a single cylinder, four stroke water cooled direct injection (DI) compression ignition (CI) engine operated on dual fuel mode using Honge methyl ester (HOME) and producer gas induction. In the present experimental investigation, an effort has been made to enhance the performance of a dual fuel engine utilizing different nozzle orifice and combustion chamber configurations. In the first phase of the work, injector nozzle (3, 4 and 5 hole injector nozzle, each having 0.2, 0.25 and 0.3 mm hole diameter and injection pressure (varied from 210 to 240 bar in steps of 10 bar) was optimized. Subsequently in the next phase of the work, combustion chamber for optimum performance was investigated. In order to match proper combustion chamber for optimum nozzle geometry, two types of combustion chambers such as hemispherical and re-entrant configurations were used. Re-entrant type combustion chamber and 230 bar injection pressure, 4 hole and 0.25 mm nozzle orifice have shown maximum performance. Results of investigation on HOME-producer gas operation showed 4-5% increased brake thermal efficiency with reduced emission levels. However, more research and development of technology should be devoted to this field to further enhance the performance and feasibility of these fuels for dual fuel operation and future exploitations.

The paper analyzes data about recharge of electric cars in Rome during 2013 as a part of a national research project (P.R.I.M.E.). The electric vehicles were recharged through the public Enel Distribuzione recharging infrastructure. For each recharge, the initial and final time were registered together with the electricity absorbed from the grid. The total number of recharges was about 7700. The first step of the investigation is the statistical analysis of the distribution of recharges in daily time slots in order to analyze the recharge behavior of Italian drivers. For each day and for each time slot, literature data from the Italian national grid operator (Terna) were used to retrieve the energy mix used to produce electricity in that day and in that time slot. In the third step, electricity generation mixes were used to obtain emission factors for greenhouse (CO2) and pollutant emissions (CO, NOx, HC and particulate). Using information about the electric consumption of vehicles registered in Rome, the emission factors in g/km were obtained and compared with the limits set by European legislation for conventional (gasoline and diesel).

The proposed investigation aims at increasing the endurance of a small unmanned aerial vehicle (UAV) where the power request for propulsion can be satisfied by means of a battery and a fuel cell. The hybrid configuration allows the required power to be obtained at take-off and the fuel cell to support the battery in order to maintain the state of charge (SOC) in the other phases of flight. This operating mode avoids deep discharging, when the battery SOC falls down a suitable threshold, and overcharging, which exposes to risk of explosion in case of lithium batteries. The cost of adding different capacity batteries was evaluated in terms of the increase of mass and consequently decrease of endurance. The power split was conveniently defined at take-off to prevent from excessive hydrogen consumption and to maximize the endurance with respect to the non-hybrid configuration in which the only fuel cell is used.

The paper proposes a simulation approach to evaluate the power required by a rotorcraft in standard flight missions and in emergency landing maneuvers, and the corresponding fuel consumption, in order to compare the feasibility and potential fuel savings for different hybrid power systems. More in detail, three options are analyzed, namely electrification of the tail rotor, fully hybrid electric propulsion and electric emergency landing. Weight penalty and potential fuel saving for the proposed hybridization schemes are evaluated for an Agusta-Westland A109 twin engine helicopter model. Nonetheless the discussed methods of analysis have general validity for single main rotor helicopter configurations. Two different scenarios are considered in this investigation: current technologies for batteries and motors and improved electrical components, with performance projections as of 2040. According to this analysis, electrification of the tail rotor and parallel hybridization are feasible with available technology, whereas a fully electrical power system for emergency landing could be developed only in the future. Finally, a parallel hybrid electric power system is sized according to the analysis of power request over four different missions. Fuel savings are evaluated for different energy management strategies. According to the results of this investigation, the parallel hybrid electric power system with present-day and future technologies can save fuel up to 5% and 12%, respectively, with an appropriate energy management strategy.

The present investigation addresses the problem of evaluating the endurance of hybrid electric aircraft and discusses the effect of battery specifications and the engine working points on fuel economy. In particular, the endurance per unit mass of fuel of a hybrid power system is calculated by assuming a constant power-level flight performed with alternate cycles of battery charging and discharging (ON-OFF strategy). The computation of the fuel economy requires accurate models for the time, the power and the energy associated with battery charging and discharge processes. In order to reach this goal, two approaches proposed in literature to evaluate electric endurance were discussed, amended and validated through comparison with experimental data. A model for constant-current/constant voltage battery charge was also presented and validated with literature experimental data. In order to explain how these models can be applied to real applications, a parallel hybrid power system was sized and analyzed for a medium-altitude long-endurance unmanned aerial vehicle. Lithium polymer batteries and two stroke diesel engines were considered and three different hybridization degrees were analyzed. The results showed a trade-off between electric flight time and overall endurance per unit mass of fuel and an improvement up to 12% in fuel consumption with respect to a non-hybrid case with the same engine.

Negli ultimi anni particolare attenzione è stata data, da parte della comunità scientifica, allo sviluppo di soluzioni tecnologiche per veicoli ibridi plug-in e in particolare per l’ottimizzazione della gestione dei flussi energetici al fine di minimizzare consumi ed emissioni. In questa memoria si presenta una strategia auto-adattativa di gestione dell'energia per i veicoli ibridi elettrici in configurazione serie basata su mappe ottimizzate per i diversi componenti e su predizioni di profili di velocità effettuate da SUMO (Simulation of Urban MObility). Il primo passo della ricerca è stato quello di eseguire l'ottimizzazione off-line dei parametri della strategia di controllo basata su una serie di mini cicli di guida, ottenuta da cicli di guida standard (UDDS, NEDC, ecc.) e cicli di guida reale acquisiti dal veicolo ITAN500 (prototipo realizzato dall’Università del Salento). Le variabili ottimizzate ottenute per ogni mini ciclo di guida vengono memorizzate in mappe che saranno implementate sull'ITAN500. Il sistema proposto prevede uno scambio di informazioni con i veicoli circostanti e le infrastrutture. Tali informazioni sono utilizzate da un simulatore di traffico locale eseguito a bordo, per predire le condizioni di guida dell'HEV in un periodo di tempo futuro (T=60s). Il ciclo di guida predetto viene confrontato con i mini cicli di guida di riferimento per trovare quello più simile e per selezionare i relativi parametri ottimi. I risultati presentati dimostrano che la procedura sviluppata è in grado di gestire in modo ottimale il funzionamento del motore termico consentendo di farlo funzionare per gran parte della missione solo quando si trova in condizioni di massimo rendimento.

The chapter describes the optimal usage of an internal combustion engine in an intelligent hybrid electric vehicle able to sense its surrounding and adapt the energy management strategy to the actual driving conditions. After an introduction on hybrid electric vehicles and their challenges, the chapter describes the role of Information and Communication Technologies in the reduction of greenhouse emissions. Then, the chapter focuses on different approaches presented in literature on the usage of information about traffic and weather conditions for the optimal energy management of hybrid electric vehicles. In particular, the chapter describes the application of the prediction&maps approach developed at the University of Salento for the optimization of the engine usage in the ITAN500 plug-in hybrid electric vehicle. Finally, the chapter proposes four metrics to evaluate the performance of the proposed method: the percentage of mission performed before reaching the lowest allowed value for battery state of charge (CBD%), the percentage of mission execute with the engine turned ON (EngON%), the average efficiency of the engine (AEE), calculated according to its actual temperature and the overall well-to-wheel emissions of CO2.

This work aims at comparing different many-objective techniques for the optimization of mission and parallel hybrid electric power system for aircraft. In particular, this work considers, as input of the optimization, the specification of the flight mission, the size of the main components and the energy management strategy for a Medium Altitude Long Endurance Unmanned Aerial Vehicle (MALE-UAV). The goals of the optimization are maximization of electric endurance, minimization of overall fuel consumption, improvement of take-off performance and minimization of the additional volume of the hybrid electric solution with respect to the initial conventional power system. The optimization methods considered in this study are those included in the ModeFRONTIER optimization environment: NSGA-II, MOGA-II, MOSA (Multi Objective Simulated Annealing algorithm) and Evolutionary Strategy of type (µ/ρ + λ)-ES. Initially, appropriate metrics are used to compare the proposed methods in a simplified problem with only two objective functions. Then a complete optimization is performed, in order to underline the degradation of the proposed optimization methods as the size of the problem increases and to define the best method according to the number of objective functions.

A first-order lumped-parameter model for the prediction of thermal behavior of a single-cylinder gasoline engine for Hybrid Electric Vehicles (HEVs) has been implemented. The model is coupled with a zero-dimension in-cylinder model that evaluates the working cycle of the engine according to the actual operating conditions and calculates the temperature of the exhaust gases, the overall efficiency of the engine and the exhaust gases flow rate. The model takes into account the possibility of using exhaust gas heat recirculation in order to enhance engine warm-up during cold start which improves its efficiency. The supervisory strategy takes into account not only predicted speed and ambient and road conditions along a future time window but also actual battery state of the charge and engine temperature to select the optimal power split between the ICE-generator group and the batteries. The proposed model represents an improvement with respect to a previous investigation of the authors where the temperature of the engine were assumed to increase/decrease of on Celsius degree in each seconds according to the state of the engine (ON/OFF).

The present work aims at the numerical prediction of the performance of a Contra-Rotating Propellers (CRP) system for a Remotely Piloted Aerial Vehicles (RPAV). The CRP system was compared with an equivalent counter-rotating propellers configuration which was set by considering two eccentric propellers which were rotating at the same speed. Each contra-rotating test case was built by varying the pitch angle of blades of the rear propeller, while the front propeller preserved the original reconstructed geometry. Several pitch configurations and angular velocities of the rear propeller was simulated. Comparisons showed an improvement of the propulsive efficiency of the contra-rotating configuration in case of larger pitch angles combined with slower angular velocities of the rear propeller.

A cost saving procedure for the optimization of a CNG converted diesel engine is proposed. The procedure is performed in five steps. Firstly, a database of different combustion chambers that can be obtained from the original piston is obtained. The chambers in the database differ for the shape of the bowl, the value of the compression ratio, the offset of the bowl and the size of the squish region. In the second step of the procedure, an empirical method is used to extract from the first database, only the combustion chambers able to resist to the mechanical stresses due to the pressure and temperature distribution at full load. For each combination of suitable combustion chamber shape and ignition timing, a CFD simulation is used to evaluate the combustion performance of the engine. Then, an empirical post-processing procedure is used to evaluate the detonation tendency and intensity of each combination. All the tools developed for the application of the method have been linked in the ModeFrontier optimization environment in order to perform the final choice of the combustion chamber. The overall process requires not more of a week of computation on the 4 processor servers considered for the optimization. Moreover, the selected chambers can be obtained from the original piston of the engine. Therefore, the conversion cost of the engine is quite small compared with the case of a completely new piston. The procedure can be applied to diesel engines to be converted to either CNG dedicated or dual fuel combustion. The main aspects and challenges to be taken into account in both cases are also analyzed.

Vehicular communications could be exploited for energy management of vehicles. We propose a system which provides that a vehicle estimates its future speed profile gathering status messages broadcasted by the surrounding vehicles and/or the infrastructure and inputting them in a traffic simulator used as a predictor. The system has been validated by simulation considering an urban scenario inspired to the Ecotekne campus at the University of Salento and a Manhattan scenario, very challenging in relation to the prediction of the speed profile. Simulation results have shown that the prediction error is quite low for the first scenario. In the Manhattan scenario, the error is quite high in case each vehicle limits itself to send messages only to its neighbours and does not transmit the information regarding its route. However, the error can be significantly reduced if route information is broadcasted and the infrastructure relays the messages transmitted by vehicles. The proposed system has been tested in the Ecotekne campus.

Abstract: Information and Communication Technologies could play a very important role in order to optimize the energy management of conventional, hybrid and electrical vehicles and, thus, to reduce their environmental impact. In particular, vehicular communications could be used to predict driving conditions with the objective to determinate future load power demand. To this, we propose a system which allows to estimate future speed profile on board of a vehicle by gathering state messages that surrounding vehicles and/or infrastructure broadcast and by inputting them to a traffic simulator (SUMO) used as a predictor. The system has been validated by a simulation model which considers a number of vehicles moving on the road network of the Ecotekne campus at the University of Salento. The actual speed profile of a target vehicle has been compared with that estimated on board for prediction horizon duration values ranging from 1 s to 60 s. Simulation results have shown that, even if the horizon duration is set to 60 s, the prediction error, in terms of the root mean square, is lower than 4 km/h. Afterwards, the system has been implemented on real vehicles and its functionalities have been tested in the campus road network

This chapter analyzes the main challenges in the application of ”simulation optimization” to the design of engine components, with particular reference to the combustion chamber of a Direct Injection Diesel engine evaluated via Computational Fluid Dynamic (CFD) codes.

A Real Time implementation of an Optimal Control Strategy for a Plug-in Hybrid Electric Vehicle is presented. The optimization aimed at minimizing the overall CO2 emission of the vehicle by considering a Well-To-Wheel approach: the control objective has been achieved by applying the Pontryagin’s Minimum Principle to a mathematical model of an experimental Plug-In Series Hybrid Electric Vehicle, the ITAN500. Realistic urban driving cycles have been used in the present investigation, in order to obtain more accurate and truthful results in terms of CO2 emissions and fuel consumption, rather than those achievable by using standard speed profiles. Some important issues in terms of how to determine a suitable realtime behavior using a Hardware In the Loop (HIL) framework have been deeply discussed. Results in terms of Partial and Full Knowledge of the driving cycle have been presented.

A sizing and simulation platform has been developed for the optimization of advanced configurations for aircrafts including, but not limited to, more electric, hybrid-electric, turbo-compound piston engines and fuel cell systems. In the present investigation the software has been applied to the simulation of a medium-altitude, medium-endurance unmanned aerial vehicle (UAV) equipped with a two-stroke diesel engine with a single stage turbo-compressor. The engine was simulated with a 1D code (AVL-Boost) taking into account several values of speed, air-fuel ratio and flight altitude. The behavior of the waste-gate valve at the different flight levels was also accounted for. The Willans line method is used to obtain the seal level and in flight performance map of scaled engines with the same configuration. The power requests of a reference 128 kW engine and two scaled engines along the mission have been compared with the available power to discuss the potentiality of hybrid electric and turbo-compound configurations.

The Shell Eco-marathon every year challenges high school and college student teams coming from around the world to design, build and test energy efficient vehicles. With annual events in the Americas, Europe and Asia, the winners are the teams that go the farthest distance using the least amount of energy. In the present paper the development of a structural frame for a Prototype car attending the competition is presented. The team is composed by students, researchers and professors from different scientific sectors of University of Salento and is called “Salento Eco Team”: the main objective of the team work is to identify the best solutions to achieve the target of the competition through a multidisciplinary investigation of all the technical aspects concerning the development of a ground vehicle with high energetic performance. The competition is based on general official rules provided by the Shell Ecomarathon organizers fixing the criteria of participation for the different teams. Participating teams can enter as Prototypes (three- or four-wheel vehicles) or Urban Concept (four-wheel vehicles similar in appearance to regular cars and which are fit for on-road use). Starting from the lesson learned at the first participation an optimization process has been implemented aimed to improve the global efficiency of the vehicle. The first aspect taken in account has concerned the choice of the structural materials for the car frame. In the first version the choice of the steel has led to a solution with weight properties not permitting high performance during the race: therefore, the use of aluminium alloys and structural concepts taken from the aerospace experiences has allowed the elaboration of structural solutions with high ratios of robustness to weight. The investigation has led to the identification of a solution optimized in terms of structural concept and the effect of the weight saving on the energetic performance has been evaluated. The next step of this study is the Prototype construction and test.