Hybrid Engines

To request a copy of a publication send an email to antonio.ficarella02@gmail.com.

2017

"A new approach to calculating endurance in electric flight and comparing fuel cells and batteries", Donateo, T., Ficarella, A., Spedicato, L., Arista, A., Ferraro, M., Applied Energy, Vol. 187, pp. 807-819, 10.1016/j.apenergy.2016.11.100, 2017. 

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.

2016

“Analysis and Optimization of HybridPowertrains for Rotorcraft Applications”, G. Avanzini, A. Carlà, T. Donateo, 6th EASN International Conference , 18-21 October 2016, Porto. 

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.

2015

“Evaluation of emissions of CO2 and air pollutants from electric vehicles in Italian cities”, T. Donateo, F. Licci, A. D’elia, G. Colangelo, D. Laforgia, F. Ciancarelli, Applied Energy 157, 675-687, 2015

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).

2014

“An Integrated Tool to Monitor RenewableEnergy Flows and Optimize the Recharge of a Fleet of Plug-in Electric Vehiclesin the Campus of the University of Salento”, T. Donateo,  P.M. Congedo, M. Malvoni, F. Ingrosso, D. Laforgia, F. Ciancarelli, Proceedings of IFAC World Congress 2014, Vol. 19, Part 1, pp 7861-7866, DOI: 10.3182/20140824-6-ZA-1003.01184, ISBN: 978-3-902823-62-5, ISSN: 1474-6670

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 CO 2 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.

“Effect ofDriving Conditions and Auxiliaries on Mileage and CO2 Emissions of a Gasolineand an Electric City Car”, Teresa Donateo, Fabio Ingrosso, Daniele Bruno, Domenico Laforgia, SAE Technical Paper 2014-01-1812, ISSN 0148-7191, 2014 

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.

“A method to estimate the environmental impact of an electric city car during six months of testing in an Italian city”, T. Donateo, F. Ingrosso, F. Licci, D. Laforgia,  Journal of Power Sources 270, 487-498, 2014

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.

"A General Platform for the Modeling and Optimization of Conventional and More Electric Aircrafts", T. Donateo, M.G. De Giorgi, A. Ficarella, E. Argentieri, E. Rizzo, SAE Technical Paper 2014-01-2187, doi:10.4271/2014-01-2187, 2014.

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).

2013

 “Real Time Implementation of an Optimal PowerManagement Strategy for a Plug-in Hybrid Electric Vehicle”, Teresa Donateo, Enrico Pagliara, Gianfranco Parlangeli, Francesco Adamo, 52nd IEEE Conference on Decision and Control, Florence, Italy, December 10-13, ISBN: 978-146735717-3, Pages 2214-2219, 2013

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.

“Impact of Hybrid and Electric Mobility in aMedium-Sized Historic City”, T. Donateo, F. Ingrosso, F. Lacandia, E.Pagliara, SAE Technical Paper 2013-24-0077, ISSN 0148-7191, 2013

The goal of the investigation is the evaluation of the environmental impact of hybrid and electric mobility in Lecce, a city of about 100,000 inhabitants in southern Italy. The investigation starts from the definition of specific driving cycles for the University campus and Lecce city center under different conditions of traffic and weather. The data acquired in this way are used to evaluate the performance of four typologies of vehicles: a gasoline city car (Smart Fortwo), the corresponding electric version (Smart ED), three range extenders and a plug-in hybrid electric vehicle operating with blended discharge. The simulation of the different power trains is performed with AVL-Cruise and validate through comparison with literature results on the European driving cycle. Particular relevance is given to CO2 emissions that are calculated with a well-to-wheel approach taking into account the average levels of emissions of the national electric grid and with a Life Cycle Assessment methodology.

“DynamicModeling of a P.E.M. Fuel Cell for a Low Consumption Prototype”, T. Donateo, F. Ingrosso, G. Indiveri, A. Damiani, D. Pacella, SAE 2013 World Congress and Exhibition, SAE Technical Paper 2013-01-0480, ISSN 0148-7191, 2013

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. 

“CO2 impact of intelligent plug-in vehicles”, T. Donateo,  WSEAS Transactions on Environment and Development 9 (3) , ISSN: 1790-5079, pp. 240-252, 2013

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). CO2 emissions were calculated with at Well-To-Wheel approach with respect to realistic urban driving patterns.

2012

“An Inter-disciplinary Approach to theDevelopment of a Low-consumption Prototype for the European ShellEco-marathon”,  T. Donateo, F. Ingrosso, A. Nicolì, A. Taurino, 2012 International Conference on Advanced Material and Manufacturing Science (ICAMMS 2012) and 2012 International Conference on Frontiers of Mechanical Engineering, Materials and Energy (ICFMEME 2012), Beijing, China December 20-21, Trans Tech Publications 2012.12 paper M1097, 2012.

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.

“Modeling the Thermal Behavior of InternalCombustion in Hybrid Electric Vehicles with and without Exhaust Gas HeatRecirculation”, T. Donateo, D. Pacella, 2012 Proceedings of the ASME Internal Combustion Engine Division Spring Technical Conference (ICES2012) ISBN number: 9780791844663, May 6-9, 2012

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).

 “A Mobile Test Bench for Fuel Cell ControlStrategies”, T. Donateo, D. Pacella, A. Renna, D. Laforgia, Advances in Environment, Biotechnology and Biomedicine, Proceedings of the 1st WSEAS International Conference on Energy and Environment Technologies and Equipment (EETE’12), ISBN: 978-1-61804-124-1, pp 195-205, 2012

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.

“On-Board Prediction of Future DrivingProfile for energy management of Hybrid Electric Vehicle”, T. Donateo, G. Ciccarese, C. Palazzo, Int. J. Automotive Technology and Management, Vol. 12, No. 3, ISSN (Online): 1741-5012  -  ISSN (Print): 1470-9511, 201,  pp. 232-251, 2012

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.

“A Method for the Prediction of Future Driving Conditions and for the EnergyManagement Optimization of a Hybrid Electric Vehicle”, T. Donateo, D. Pacella, D. Laforgia, International Journal of Vehicle Design, Special Issue on: "Enabling Technologies for Sustainable Vehicle Electrification: Control, Optimisation and Diagnostics", Vol. 58, Nos. 2/3/4, 2012, ISSN (Online): 1741-5314-ISSN (Print): 0143-3369, Vol 58, No. 2-4, 2012, pp. 111-133

Vehicular communications are expected to enable the development of Intelligent Cooperative Systems for solving crucial problems related to mobility: road safety, traffic management etc. Information and Communication Technologies could also play an important role in order to optimise 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 determine future load power demand. An adaptive energy management strategy for series Hybrid Electric Vehicles (HEVs) based on genetic algorithm optimised maps and the Simulation of Urban Mobility (SUMO) predictor is presented here.

“Intelligent usage of internal combustion engines in hybrid electric vehicles”,  T. Donateo, in “Internal combustion engines, Kazimierz Lejda, INTECH, ISBN 979-953-307-1040-5 , 2012

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.

2011

“Structural Frame Development of a Prototype Car with High EnergeticPerformance”, G. Scarselli, R. Luperto, T. Donateo, Proceedings of 13th EAEC European Automotive Congress, Paper code: EAEC13/EAEC2011 C43, ISBN:978-84-615-1794-7,  2011

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.

“Development of an Energy Management Strategyfor Plug-in Series Hybrid Electric Vehicle Based on the Prediction of theFuture Driving Cycles by ICT Technologies and Optimized Maps”, T. Donateo, D. Pacella, D. Laforgia, SAE Paper 2011-01-0892 ISSN 0148-7191, SP 2308 “Advanced Hybrid Vehicle Powertrains, 2011” ISBN 978-0-7680-4747-9

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.

2010 and before

“Simulation and Optimization of the EnergyManagement of ITAN500 in the SUMO Traffic Model Environment”, T. Donateo, D. Pacella, D. Laforgia, International Conference and Exhibition on Ecological Vehicles and Renewable Energies, EVER’10

The paper describes the use of SUMO Traffic Model for the estimation of realistic driving cycles for ITAN500, a plug-in hybrid electric vehicle developed at the University of Salento. The energy performance (fuel consumption and energy battery) of the vehicle is estimated from the driving conditions (velocity, grade, state of the asphalt, etc.) obtained by SUMO according to different traffic scenarios. For each scenario, an optimization of energy performance has been executed with a multi-objective genetic algorithm by considering the parameters of the control strategy as design parameters. The energy flows in the ITAN vehicle were simulated with the help of on-purpose simulation programs developed in Matlab environment. The optimal control strategy for each scenario has been compared with that obtained with respect to the standard European urban driving cycle (ECE-15).

“On-Board Simulation of the Traffic Scenario for the Sustainable Mobility”,  T. Donateo, G. Ciccarese,  P. Marra, D. Pacella, C. Palazzo, Proceedings of the International Workshop "Sustainable Energy and Environmental Protection (SEEP2010): Opportunities for Developing the Regional Economy in Europe", ISBN: 9788890518508 Volume 1, pp 286-292

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.

“On the useof Vehicular Communications for Efficient Energy Management of Hybrid ElectricVehicles”, T. Donateo, G. Ciccarese,  P. Marra, D. Pacella, C. Palazzo, Proceeding of FISITA 2010 World Automotive Congress, paper number F2010 E047, ISBN: 978-963-9058-29-3, 2010

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, energy saving. In this paper, the use of vehicular communications for the energy management of a Hybrid Electric Vehicle (HEV) is presented. The supervisory controller of a HEV should select the power split appropriately at any time in order to optimize the energy management. To this, it could base the control strategy on the future driving profile (speed and related power demand) and try to estimate the last by processing the status information broadcasted by surrounding vehicles (position, speed, acceleration, etc.) and by the infrastructure (i.e. the current status of traffic lights). A simulation tool has been developed with the objective to validate the proposed approach. It consists of a number of components, that are a traffic simulator, a network simulator, a predictor of the future speed profile, a powertrain simulator and an optimizer. A local instance of the traffic simulator (SUMO) running on board of the HEV has been conceived as a predictor. The accuracy of the predictor has been evaluated by considering a number of vehicles moving on the road network of the Ecotekne campus at the University of Salento and by comparing the actual speed profile of a test HEV with that predicted on board. Simulation results have shown that the prediction error, in terms of the root mean square, is quite low and, particularly, its maximum value is about 4 km/h for a horizon duration equal to 60 s.