Ingineria Automobilului

Ingineria Automobilului Society of Automotive Engineers of Romania Romanian Automobile Register DISTRIBUTED WITH AUTOTEST MAGAZINE Vol. 7, no. 4 (29) / 2013 International Congress of the Society of Automotive Engineers of Romania Grand Hamster E4WD DACIA Hybrid Concept Car Experimental Study of the Energy Efficiency of Cars Simulations of a Compression Ignition Engine Engine Powered by Different Fuel Blends when Changing Injection Parameters SIAR IS AFFILIATED TO INTERNATIONAL FEDERATION OF AUTOMOTIVE ENGINEERING SOCIETIES EUROPEAN AUTOMOBILE ENGINEERS COOPERATION

AUTOMOTIVE TRANSMISSIONS FUNDAMENTALS. SELECTION DESIGN AND APPLICATION. SECOND EDITION Authors: Harald Naunheimer, Bernd Bertsche, Joachim Ryborz, Wolfgang Novak Publisher : Springer-Verlag Berlin Heidelberg Published: 2004 ISBN: 978-3-642-16213-8 This book gives a full account of the development process for automotive transmissions. Main topics: Overview of the traffic-vehicle-transmission system Mediating the power flow in vehicles Selecting the ratios Vehicle transmission systems, basic design principles Typical designs of vehicle transmissions Layout and design of important components, e.g. gearshifting mechanisms, moving-off elements, pumps, retarders Transmission control units Product development process Manufacturing technology of vehicle transmissions Reliability and testing The book covers manual, automated manual and automatic transmissions as well as continuously variable transmissions and hybrid drives for passenger cars and commercial vehicles. Furthermore, final drives, power take-offs and transfer gearboxes for 4-WD-vehicles are considered. ALTERNATIVE CARS IN THE 21 ST CENTURY. A NEW PERSONAL TRANSPORTATION PARADIGM. SECOND EDITION Author: Robert Q. Riley Author: Robert Q. Riley Publisher : SAE International Published: 2004 ISBN: 0-7680-0874-3 Contents: Personal Mobility in Crisis Personal Mobility Vehicles for the 21st century The Technology of Fuel Economy Alternative Fuels Electric and Hybrid Vehicles Three-Wheel Cars with Tilting Three-Wheel Vehicle Information Safety and Low-Mass Vehicles Intelligent Transportation Systems Alternative Cars in Europe

Automobile Engineering versus Automotive Engineering Ingineria Automobilelor versus Ingineria Autovehiculelor Could be the Automobile Engineering one of the open windows for the Romanian Automotive Engineering scientific research? A sharper glance slices like a diamond shatters of the inert, dusty window of the Romanian industry and reveals a rather discouraging picture. At the very foundation of the scientific research, no matter the field, resides the specific social demand to innovating, up-to-dating, competing and performing. But for years, the Romanian Automotive Industry focuses almost exclusively on passenger cars. There is a good reason for it: former famous factories (i.e. ROMAN, Tractorul, ARO) had diminished or ceased their activities; next to them, powerful research and design institutions were developing their activities. Within this context, from the heights built-up by media, the Automobile Engineering looks downwards to its poorer, less spotlighted relatives. The scientific research developed by the decreased number of the university professors and researcher that could provide some innovation for the truck, tractors, buses and special vehicles industry seems to be pointless. As a result, the interest in developing / innovating / manufacturing this kind of vehicles or components for these vehicles continuously decreased. Nevertheless, I believe that the scientific research within the Automotive Engineering field should pay attention to the whole lifecycle (designing, manufacturing, using, maintaining, decommissioning and disassembling) to all the automotive categories. I led the Military Vehicles and Transportation Department of the Military Technical Academy more than 10 years. During all this time I have developed, along with my colleagues, a new concept, which we called mobile terrestrial bearing platform for technical systems (PMT-PST). According to a systemic approach, it consists of a basic module, wheeled or tracked propelled, on which different systems were mounted: weapon systems (cannons, mortars, rocket launchers etc.), command and control systems, radar installations, day-and-night surveillance systems, medical evacuation systems (MEDEVAC), recovery and technical maintenance systems, communication systems, assault vehicles and so on. These vehicles became, consequently, combat vehicles, mobile command nodes, surveillance stations or different special vehicles. Moreover, they could be armored or not and they could be fitted with personnel or goods transportation modules, able to perform within a modern warfare environment. The activity of research-development-testing consisted of both the classic approach of the wheeled or tracked vehicles designing, manufacturing and maintenance, and the specific elements of the particular type of installed equipment (such as the weapon system s stabilization, protection against enemy fire, mobility and progression capacity in difficult conditions, unique fuel refueling, vehicle s buoyancy, etc.). The good results achieved in time were due, among others, to the excellent co-operation with the remaining specialist of the former specialized industrial branches as well as with the other Technical Universities in Romania. The previous given examples testify the fact that by reuniting the technical capacities and the human resources, the Romanian research in this branch of activity could significantly get involved in developing and innovating various special vehicles or their components. The existence of high level competencies in this filed within the Automotive Departments of various Universities provides an important, but not enough known and used resource by the Romanian specialized companies. So, who takes the first step? Professor Minu MTREA, Eng., PhD Secretary General of SIAR Former Head of the Military Vehicles and Transportation Department of the Military Technical Academy Summary Ingineria Automobilului No. 29 (vol. 7, no. 4) 3 Automobile Engineering versus Automotive Engineer Simularea funcţionării unui motor cu aprindere Ingineria Automobilelor versus Ingineria Autovehiculelor prin comprimare alimentat cu biocombustibili 5 International Congress of the Society of Automotive Engineers of Romania SIAR în cazul modificării parametrilor de injecţie Automotive Motor Mobility Ambient AMMA 2013 15 High Order Spectral Analysis of a Measured Automotive Parameter Congresul Internaţional al Societăţii Inginerilor de Automobile Analiza spectrală de ordin superior a semnalului unei mărimi din România SIAR mecanice măsurate în transmisia unui automobil. Modele 8 Experimental Study of the Energy Efficiency of Cars matematice obţinute prin identificare Studiul experimental al eficienţei energetice a automobilelor 20 University Research: Symposium EV&HV 2013 Innovation in 12 Simulations of a Compression Ignition Engine Powered Electric and Hybrid Mobility Automotive Engineering by Different Fuel Blends when Changing Injection Parameters Research Centre, University of Piteşti. 1 november 2013 3

ROMANIAN AUTOMOBILE REGISTER General Manager George-Adrian DINCĂ Technical Manager Flavius CÂMPEANU AUTO TEST Chief Editor Lorena BUHNICI Editors Radu BUHĂNIŢĂ Emilia PETRE SOCIETY OF AUTOMOTIVE ENGINEERS OF ROMANIA President: Conf. dr. ing. Adrian CLENCI, University of Piteşti Honorary President: Prof. dr. ing. Eugen NEGRUŞ, University Politehnica of Bucharest Vice-president: Prof. dr. ing. Cristian ANDREESCU, University Politehnica of Bucharest Vice-president: Prof. dr. ing. Nicolae BURNETE, Technical University of Cluj-Napoca Vice-president: Prof. dr. ing. Anghel CHIRU, University Transilvania of Braşov Vice-president: Prof. dr. ing. Victor OŢĂT, University of Craiova Vice-president: Prof. dr. ing. Ioan TABACU, University of Piteşti General Secretary of SIAR: Prof. dr. ing. Minu MITREA, Military Technical Academy of Bucharest SCIENTIFIC AND ADVISORY EDITORIAL BOARD Prof. Dennis ASSANIS University of Michigan, Michigan, USA Prof. Rodica A. BĂRĂNESCU University of Iilinois, Chicago College of Engineering, USA Prof. Nicolae BURNETE Technical University of Cluj-Napoca, Romania Eng. Eduard GOLOVATAI-SCHMIDT Schaeffler AG & Co. KG Herzogenaurach, Germany Prof. Peter KUCHAR University for Applied Sciences, Konstanz, Germany Prof. Mircea OPREAN University Politehnica of Bucharest, Romania 4 Contact: Calea Griviţei 391 A, sector 1, cod poştal 010719, Bucureşti, România Tel/Fax: 021/202.70.17 E-mail: autotest@rarom.ro www.rarom.ro www.autotestmagazin.ro SIAR Contact Faculty of Transport University POLITEHNICA of Bucharest Splaiul Independenţei 313 Room JC 005 Cod poştal 060032, sector 6 Bucureşti, România Tel/Fax: 021/316.96.08 E-mail: siar@siar.ro www.ingineria-automobilului.ro www.siar.ro PRINTING ART GROUP INT SRL Str. Vulturilor 12-14, sector 3 Bucureşti Full or partial copying of text and pictures can be done only with Auto Test Magazine approval, of the Romanian Automobile Register and of SIAR Prof. Giovanni CIPOLLA Politecnico di Torino, Italy Dr. Felice E. CORCIONE Engines Institute, Naples, Italy Prof. Georges DESCOMBES Conservatoire National des Arts et Metiers de Paris, France Prof. Cedomir DUBOKA University of Belgrade, Serbia Prof. Pedro ESTEBAN Institute for Applied Automotive Research, Tarragona, Spain Prof. Radu GAIGINSCHI Technical University Gheorghe Asachi of Iaşi, Romania Prof. Berthold GRÜNWALD Technical University of Darmstadt, Germany HONORARY COMMITTEE OF SIAR AVL List Romania Werner MOSER Romanian Automobile Register RAR George-Adrian DINCĂ The National Union of Road Hauliers from Romania UNTRR Florian MIHUŢ EDITORIAL BOARD Prof. Nicolae V. ORLANDEA Retired Professor, University of Michigan Ann Arbor, USA Prof. Victor OŢĂT University of Craiova, Romania Prof. Pierre PODEVIN Conservatoire National des Arts et Metiers de Paris, France Prof. Andreas SEELIGER Institute of Mining and Metallurgical Machine, Engineering, Aachen, Germany Prof. Ulrich SPICHER Kalrsuhe University, Karlsruhe, Germany Prof. Cornel STAN West Saxon University of Zwickau, Germany Prof. Dinu TARAZA Wayne State University, USA Editor in chief: Prof. Dr. -Ing. habil. Prof. E. h. Dr. h.c. Cornel STAN Executive editor: Prof. dr. ing. Mircea OPREAN, University Politehnica of Bucharest Deputy chief editor: Prof. dr. ing. Gheorghe-Alexandru RADU, University Transilvania of Braşov Prof. dr. ing. Ion COPAE, Military Technical Academy of Bucharest Conf. dr. ing. Ştefan TABACU, University of Piteşti Redactors: Conf. dr. ing. Adrian SACHELARIE, University Gheorghe Asachi of Iaşi Conf. dr. ing. Ilie DUMITRU, University of Craiova S.l. dr. ing. Cristian COLDEA, Technical University of Cluj-Napoca S.l. dr. ing. Marius BĂŢĂUŞ, University Politehnica of Bucharest S.l. dr. ing. Gheorghe DRAGOMIR, University of Oradea Editorial secretary: Prof. dr. ing. Minu MITREA, General Secretary of SIAR Automotive Engineering: print edition publication, 2006 (ISSN 1842-4074), electronic edition, 2007 (ISSN 2284-5690). New Series of the Journal of Automotive Engineers (RIA), printed in 1992-2000

AUTOMOTIVE MOTOR MOBILITY AMBIENT AMMA 2013 International Congress of the Society of Automotive Engineers of Romania SIAR Congresul Internaţional al Societăţii Inginerilor de Automobile din România SIAR Professor Eng. Nicolae BURNETE Ph. D., Congress President Technical University of Cluj-Napoca nicolae.burnete@auto.utcluj.ro The opening festivity Mr. Günter Hohl presentation of the paper-work During 17 to 19 October 2013, Alma Mater Napocensis, Technical University of Cluj-Napoca organized Automotive Motor Mobility Ambient AMMA 2013 - International Congress of Society of Automotive Engineers of Romania SIAR, under the high patronage of FISITA (International Federation of Automotive Engineering Societies), accompanied by a suite of events that focused the attention of Romanian and foreign specialists in the field of automotive engineering and road transport. The host of SIAR Congress was for the third time Automotive and Transport Department of the Technical University of Cluj-Napoca, one of the poles of excellence in applied and fundamental research in the automotive industry, with wide recognition nationally and internationally. All events centered around AMMA International Congress in 2013 made the city of Cluj-Napoca to become, for a few days, an international center for automotive engineering, providing opportunities for useful contacts and information to date on the major issues of vehicle development and environment. Mobility of ideas, goods and people characterize contemporary society, one of the main elements of the future development of human society and the automotive industry is an important factor in this direction. Aware of the importance of addressing current and future issues that face the automotive engineering, the participants in the International Congress AMMA 2013 and aims to address them, discuss and formulate solutions in an appropriate scientific framework, confirmed the presence of a number of specialists academic, economic and social, both in the country and abroad. Departments of interest AMMA International Congress 2013 were directly related to scientific research in the field of automotive engineering, ideas, inventions and new and emerging technologies related to the following topics: hybrid and electric vehicles, advanced propulsion systems, vehicle design, advanced engineering and computer simulation, road safety and traffic control, materials and innovative technologies, green vehicles and pollution caused by internal combustion engines. The Congress provided an opportunity for all professionals in the automotive and environmental engineering (researchers, designers, users and producers) to achieve a fruitful exchange of views and to contribute to the growth of education in these areas. More than 275 participants at the congress had the opportunity to be actively involved in the scientific papers presented in plenary and in sections, workshops, exhibitions, leisure. AMMA 2013 opening of the Congress brought in front of participants: Günter Hohl - FISITA representative, former President of the EAEC (European Cooperation Automotive Engineers) Gigel Paraschiv - Secretary of State, Ministry of National Education, Aurel Vlaicu - Rector of the Technical University of Cluj-Napoca, Horia Dorin Uioreanu - Cluj County Council President Mihnea Ioraş - Subprefect of Cluj Adrian Clenci - President SIAR, Gheorghe-Alexandru Radu - Academy of Technical Sciences of Romania, Stefan Kanya - regional Director Europe - AVL List GmbH. After the official opening of the congress plenary session presentation took place. 5

6 Evolution of the autovehicle global production Industrial orizontal areas with development induced by the evolution of the romanian automobile industry The opening of the exhibition The first paper, presented in plenary by Günter Hohl, entitled FISITA and the Automotive World started with an overview of FISITA, putting into evidence the fact that it represents more than 170,000 engineers worldwide, having an important role innovation in the automotive engineering, development of various industry standards and the scientific support organization. SIAR members in that SIAR is part of FISITA participate in the global effort to develop engineering and road transport vehicles. FISITA and EAEC Congresses are opportunities to show unity and efforts of Automotive Engineers. It was further shown an evolution of vehicles, both international inventors and Romanian, remembering the Belu Barbu, Dimitrie Leonida, Aurel Persu and others, along with changes in automotive production in Romania. It was stressed the important role that the car industry has both the European economy and the world is said that this is the engine of Europe. Also mentioned the fact that although the number of companies producing vehicles fell from 36 in 1970 to 15 in 2000, increased diversity of models (sedan, sports car, SUV... the pick -up, MPV, hatchback, SW, coupe, roadster) from 3-15, then recalled the target in terms of environmental protection, namely a better air quality and reduce vehicle noise. Automotive future involving new technologies: environmentally friendly electric cars and interconnected and autonomous vehicles. In conclusion, cars, buses and trucks will remain the main option for the transport of people and goods, will increase environmental protection requirements, and educating the public on the importance of environmentally friendly transport will increase. A second paper, presented in Parliament by George Druţă adviser ACAROM, entitled The auto industry in Romania, developments and prospects for development said the comprehensive development of the automotive industry is shaken marked migrations Inter-zonal and hierarchy changes. He was presented the evolution of automobile production worldwide, continuing with the main pillars of the automotive industry in Romania: Dacia - Renault and Ford Romania. After describing the evolution of sales of new motor vehicles presented exports of cars and vans and emphasized that it supports both domestic production and the entire national economy. There was an overview of the major automotive suppliers in Romania, emphasizing that the top 20 suppliers/manufacturers globally, 13 produce auto parts in Romania. Components sector remains attractive and relatively competitive in the Central -Eastern Europe. It highlighted the role ACAROM programs to increase competitiveness and opportunities of a regional cluster, the work ending by presenting perspectives of automotive industry in ACAROM vision. From AVL GmbH, Stefan Kania presented The connected powertrain TM. After stressing that AVL is the largest development, simulation and testing technology of powetrain in the world (with 6,200 employees and a 12.5% investment in research and innovation) were presented aims to develop transmission and new concepts in automotive engineering. Based on a hybrid vehicle demonstration in 2004, with emissions of only 90-98 g/km of CO, with a 1.2l engine with 3 cylinders, developing 60 kw, since 2006 an optimized turbo-hybrid has been presented, also the connected vehicle equipped with the system of driving direction keeper, smart cruise control and the concept of CONNECTED POWERTRAIN TM. Also was presented control architecture and changes to this system and AVL system RANGE EXTENDER. Cristian Nevzoreanu, Public Affairs Director of Renault Technologie Roumanie, presented the paper ROMANIA A Competences Center for Renault.

From the outset it was noted that in the 14 years since is in Romania, Renault has invested here 2 billion, has reached a total of 18,000 employees and performed 5.5 million hours of training, after who pointed out that Romania is the second country of Renault Planet. It was emphasized that Renault is present in Romania on long term, with a full branch self development: design, engineering, testing, industrialization, manufacturing, international logistics, marketing, after-sales. Among the latest models that have been launched are both new Logan MCV - launched in May 2013 and the new Duster - launched in September 2013. It insisted on the presence of Renault Technologie Roumanie the only automotive development center in Eastern Europe and the largest such center outside France s Renault. Also was presented the Titu Technical Center, the various types of possible tests, and testbeds of network equipment along with test tracks and talked about the production of the new Energy TCe90 engine - codenamed H4Bt. Finally, they were presented and possible areas of youth development programs master engineers dedicated <Automotive Projects Engineering (IPA)>, conducted by RTR in partnership with technical universities in the country. Simultaneously with the implementation and presentation of the congress, companies and organizations with activities in the field of automotive engineering, motor, mobility and environment organized exhibition stands with specific themes. Among the exhibitors were found companies design and computer simulation in the automotive industry, turbochargers repair specific components, importers and distributors of automotive oils, aerosols and specialty products, automotive repair, automotive maintenance products, fasteners, power Images from the exhibition tools and pneumatic, chemical, hand tools specialized manufacturers of diesel injection systems, automotive battery manufacturers, suppliers of solutions for auto damage assessment etc. Simultaneously with the implementation and presentation of the congress, companies and organizations with activities in the field of automotive engineering, motor, mobility and environment organized exhibition stands with specific themes. Among the exhibitors were found companies design and computer simulation in the automotive industry, turbochargers repair specific components, importers and distributors of automotive oils, aerosols and specialty products, automotive repair, automotive maintenance products, fasteners, power tools and pneumatic, chemical, hand tools specialized manufacturers of diesel injection systems, automotive battery manufacturers, suppliers of solutions for auto damage assessment etc. The congress took place in 2013 AMMA while remaining specific activities a number of themed workshops to the students, young researchers and professionals with experience in the automotive and maintenance products. Workshops conducted during the congress had the following main topics: Determining fuel consumption in real operating conditions (Karl Kock - AVL Graz Austria), Introducing the application aided design Catia V6 (CENIT), Modern service technologies (Autodiga). In these workshops have explained some basic concepts and specific equipment used in the measurements, i.e. stands for experimental tests. Some of the equipment related to determining fuel consumption in real terms are installed directly on the vehicle, being relatively easy to install on motorcycles, cars and trucks, allowing precise monitoring of the operation of fuel supply and exhaust gas systems. Were also recorded characteristic values of other auxiliary systems of the engine, among which may be mentioned cooling, lubrication, ignition and starter. The whole process of doing experimental research have specific equipment installed on vehicles so that they can be subjected to a test protocol on the circuit characteristic, everyday traffic conditions, respectively. Equipment this way installed facilitated the fuel consumption determination both in traffic and circuit. Paper presentation within sections of the AMMA 2013 was of great interest and assistance proved so numerous and the discussions continued after completion of exposure. 7

Ingineria Automobilului Experimental Study of the Energy Efficiency of Cars Studiul experimental al eficienţei energetice a automobilelor Eng. Mihail IACOB mihail.iacob@gmail.com Eng. George ENE email: ene_george@yahoo.com Eng. Marian-Eduard RĂDULESCU email: radulescu1961@yahoo.com Professor Eng. Ion COPAE, Ph.D. Military Technical Academy of Bucharest, email: copaeion@yahoo.com ABSTRACT The article presents the problem of establishing energy efficiency of cars, which considers both power performance and fuel consumption of their. Study is based on experimental data obtained from tests of cars equipped with on-board computer and embedded transducers. interconnections between them. In the classic sense of the literature, the references of dynamics belong only start-up, typically the accelerator start-up time and space. Broadly speaking, dynamics refers to the whole movement, it only for the fact that the dynamics represents any variation in time. Similarly, in the classic sense of the literature, the references of fuel saving refer only to fuel consumption, expressed in various forms. Broadly speaking, we should question and about other issues, for example those relating to the use of fuel energy input for the engine efficiency, for propulsion etc. Lately, it puts more and more the problem that refers at increasing energy efficiency of a car, which aims dynamics and fuel saving interrelated each other [1, 2, 3]. In other words, it does not want a high dynamic energy without consider the effort to get it; for this reason, the main efforts are directed towards improving economic efficiency more than towards improving dynamics, obviously because of the limited oil resources. This effort is understandable, given that the car is a means of transport with very low efficiency, wasting a lot of energy introduced with the fuel. Efforts aimed at improving energy efficiency targets simultaneously fuel saving and dynamics, but in one sense: lower fuel consumption by affecting dynamics limits imposed. In this regard, recent studies and research in this area operate with the concept called ERFC (Emphasis on Reducing Fuel Consumption) with quantitative expression that signifies what percentage of dynamic performance is sacrificed for fuel economy [1]. ERFC criteria value is determined by the relationship: C ERFC = C c c C C r p (1) where: C c - current fuel consumption, C r achieved fuel consumption, C p - potential fuel consumption (possibly reduced). For example, if we want to reduce fuel consumption in 2035 to 62.5% of the current value by sacrificing dynamic performance by 50%, of equation (1) is made of a relatively fuel consumption: C = C ERFC( C C ) = 1 r c c p (2) = 1 0, 5(1 0, 625) = 0, 8125 as can be noticed in figure 1 [1]. As stated, the size ERFC is actually a criterion of energy efficiency Nowadays, the car is one of representative mechatronic products, an excellent example of integrating software of mechanical, electronic and informatics components. From the beginning until today, the car revolutionized transportation and it concentrated the most significant engineering effort to improve continuously its performance. Among the main requirements, which are imposed on cars, are also those relating to their dynamics and fuel saving; usually, these two requirements can not be satisfied simultaneously to the desired maximum level. In the specialty literature, the study of dynamics and fuel saving is performed separately from each other, without resorting to the Fig.1. Consumption calculation by implementing criteria ERFC 8 8

Fig.2. Forecast for 2035 to dynamic and fuel saving Fig.3. Criterion for energy efficiency kc for operation with gasoline because fuel economy is based primarily on reducing the dynamics of the car. In order not to affect drastically the dynamics, the building companies will have to improve manufacturing technologies and to adopt new constructive measures. The experts in the field believe that it will have a big impact the weight of the car, meaning significantly reducing it. For example, if it aims to achieve ERFC value of 50% (Figure 1), the current car must weigh with 10% less. As a consequence to the above, in Figure 2 presents the forecast for the year 2035 on the dynamics and fuel saving of a middle class car based on the degree of implementation ERFC compared to the current situation was targeted for dynamic time starting from zero speed to 100 km/h, and for economical fuel consumption per 100 km traveled by car [1]. Figure 2 shows that in 2035 the dynamics decreases and fuel saving increases with increasing value ERFC. If it will be not implemented ERFC 2035, the fuel saving of the current remains the same and the dynamics will be improved mainly due to decreasing vehicle mass. In order to emphasize energy efficiency, some experimental researches were carried out with a Skoda Octavia fitted with fuel injection engine and with power plant liquefied petroleum gas (LPG), which covered most functional regimes encountered in normal operation with a movement with a normal driving style. The analyze of energy efficiency of the car was based on experimental data by defining and setting the criteria for assessing the energy efficiency by comparing it to the two fuels using the concept of equivalent energy efficiency; these criteria should evaluate the use of quantitative energy introduced with the fuel, which are the consequences of this use in terms of energetic plan and which are the factors that influence 9

Fig.4. Mean of tests energy efficiency criterion kc for operation with LPG Fig.5. Fuel consumption per 100 kilometers on petrol and LPG operation the most energy efficiency. The first criterion for calculation the energy efficiency is the ratio of the kinetic Wcin energy of the car and the k = 100 (3) energy c introduced with the fuel [3]: Wi where the two energies are determined by the following relations: 2 mv a W = cin (4) CQS 2 h i p respectively: W = (5) i V In these expressions were noted: m a vehicle weight, C h - hourly fuel consumption of the engine, Q i - lower heating value of the fuel, S p - space map, v [m/s], V [km/h] - vehicle speed. Figure 3a shows the results which were obtained for 50 tests when engine is running with gasoline. As will be noted from Figure 3c, for these all tests, 34.86% of the energy input with the fuel is actually used for driving the vehicle. The values of this ratio vary in the range 25.33 40.73%. Since equation (3) calls from the kinetic energy of the car, which is the effective displacement energy consumed and the energy introduced with the fuel that is the most Fig.6. Average values/tests of energy efficiency criterion k ws 10

Fig.7. Average values/tests of energy efficiency criteria k cm and k cp important criterion in assessing the energy efficiency; this criterion has a dynamic component W cin and a fuel saving component W i. If it uses fuel consumption per 100 km, C 100, then the equation (5) becomes: i p 100 W = ρqs C (6) i 100 where ρ is fuel density. The equation (6) is useful when it is desired that in the study of energy efficiency to consider the fuel price P [lei/liter], not only the dynamic and fuel saving elements. As noted, the equation (6) shows two sizes which depend on fuel type, ρ and Q i, both lower for LPG. Figure 4 presents the results which were obtained for 50 tests when the engine is running on LPG. As will be noted from Figure 4a, in all of these samples 30.15% of the energy input to the fuel is actually used for move the vehicle, the value is of 4.71% less than that of the value when it is used the gasoline. Sample values of this ratio vary in the range 19.28 37.87%. Taking into account the price P, density ρ and lower calorific power Q i for these two fuels, then it gets an average equivalent relation in the case of LPG, as shown in Fig. 4b and calculated with the formula: P ρ Q b g ig k = k ce c P ρ g b Q ib (7) As shown, this time the car equivalent energy efficiency increases, meaning that the average value of all tests increased to 44.13%, exceeding the 9.27% amount of gasoline (34.86%). In equation (7) the index b refers at gasoline and subscript g refers at liquefied petroleum gas. This equation shows that LPG is favored if we speak about price (P b = 6.01 lei/liter; P g = 2.85 lei/liter - on experiments) but it is disfavored if we speak about density (r b = 0.74 kg/ liter; r g = 0.54 kg/liter) and lower calorific value (Q ib = 47300 kj/ kg; Q ig = 45000 kj/kg): as a result, the first factor equivalent ratio increases the ratio and the other two decrease it. In this regard, it should be noted that if there is a LPG equivalent consumption, so consumption compared to gasoline. Equivalent fuel consumption per 100 km is calculated from an expression of type (7): C = C 100e 100 P P ρ Q g b ib ρ Q b g ig (8) which shows that the price of gas is a factor that reduces the equivalent consumption, and the density and the lower calorific value increases it. Under these conditions, fig.5a shows average values of equivalent consumption of LPG/tests and, compared, in fig.5b gasoline consumption per 100 km driven. As noted in figure 5a, equivalent to LPG consumption for the all tests is 7.7 litres/100 km, compared to the value of consumption of 11.3 litres/100km during the experiments. In addition, it is noted that the two graphs equivalent to LPG consumption value is close to that of gasoline consumption (7.4 litres/100 km), is only 4.1% higher. The second criterion for calculation of energy efficiency is the ratio of energy introduced with fuel and space traveled by car: k ws Wi = (9) S p the numerator resorting to the fuel saving, and the denominator the dynamics. Figure 6 presents k ws ratio values for both fuels, from which it appears that in the case of LPG to scroll through one kilometer is required a fuel energy of 2.04 times higher than gasoline for the all tests, in average. If in this case it is defined a ratio k wse equivalent with gasoline (Figure 6b), the energy requirements per unit distance is about 1.4 higher than LPG. Two other criteria for the calculation of energy efficiency is the ratio of the volumetric fuel consumption and torque M e, respectively engine power P e : k cm C C v v = ; k = (10) cp M P e where C v is the fuel consumption - in milliliters (ml). In Figure 7 are shown the average values of the last two samples for the calculation the energy efficiency criteria for both fuels. The graphs on the left show that the time to achieve a torque of 1 Nm is necessary a fuel volumetric consumption for all tests volume increased by 74.7% in the case of LPG; if is relates to the gasoline, the equivalent consumption is increased by 19.7% for LPG. Similarly, the graphs on the right show that in order to obtain a power of 1 kw is necessary a fuel volumetric consumption for all tests increased by 58.4% in the case of LPG; if it relates to the gasoline, the equivalent consumption is increased by 46,4 % for LPG. Similarly, other criteria which refer at energy efficiency of the vehicle were defined and it was examined the influence of factors on them by using the information theory. The studies have shown that the high equivalent energy efficiency for LPG and the price which it is much lower represent two arguments which lead to the conclusion that it is more advantageous to use LPG as fuel compared to gasoline. BIBLIOGRAPHY 1. Bandivadekar A. and others. On the Road in 2035. Report, Laboratory for Energy and the Environment, Massachusetts Institute of Technology, 2008 2. Cheah H., Heywood J. Meeting US passenger vehicle fuel economy standards in 2016 and beyond. Energy Policy 39, 2011, pg. 454-466 3. Copae I., Lespezeanu I., Cazacu C. Dinamica autovehiculelor. Publisher ERICOM, Bucharest, 2006 e 11

Ingineria Automobilului Simulations of a Compression Ignition Engine Powered by Different Fuel Blends when Changing Injection Parameters Simularea funcţionării unui motor cu aprindere prin comprimare alimentat cu biocombustibili în cazul modificării parametrilor de injecţie ABSTRACT This paper studied using computer simulation the influence of parameters in the electronic control unit ECU on the functional optimization of a compression ignited engine Renault K9K fuelled with bio fuels B10 and B20. To obtain this objective a model in the AVL Boost software has been made for a compression ignited engine that was implemented an element ECU with fuel injection control by loading the input maps on each drive channel. Following the computer simulations the optimization of fuel injection was studied by ECU parameters to obtain the same results from the combustion process for each type of bio fuel. Engine performance was evaluated based on the quantity of heat released obtained from the combustion process in the cylinder to compare with the properties of mixtures of fuels used in the simulation. To increase the quantity of heat released from the burning process was commissioned by ECU parameters increasing the quantity of fuel injected with 12 Eng. Călin ICLODEAN Technical University of Cluj-Napoca calin.iclodean@auto.utcluj.ro Professor Eng. Nicolae BURNETE Ph. D., Technical University of Cluj-Napoca nicolae.burnete@auto.utcluj.ro increasing the bio component by enlarging the injection time. INTRODUCTION Studies and researches on the operation of the compression ignition engine in the optimum economic pole provides opportunities to optimize energy parameters and therefore to achieve aspirations about current fuel consumption, pollutant emissions and specific power in the process of burning. Computer simulation allows for optimal economic zone, thereby constituting a fundamental step for the development of simulation models underlying data provision and strategies to calibrate the motors perform best. AVL Boost application is a suite of simulation software tools with which you can design, create, develop and study a large variety of internal combustion engine. Preprocessing program used for initial input data and the characteristics of the motor which will be designed as a model for the simulation. After assembling the elements for the engine, mathematical equations and algorithms of the model behind the Graphical User Interface GUI analyze and calculate the processes required during the simulations. The pressures, temperatures and flow rates are obtained from gas dynamics equations and solutions are averages of the pipe cross-section [1]. Fig. 1. The compression ignition engine Renault K9K in AVL Boost. THE MODEL USED IN COMPUTER SIMULATION PROCESS Compression ignition engine Renault K9K is a turbocharged with Common Rail, and the model built in AVL Boost application is shown in Figure 1. The combustion model used in the computer simulation was selected Mixing Controlled Combustion MCC model that determines the quantity of heat release and pollutant emissions based on the quantity of fuel in the cylinder and the turbulent kinetic energy introduced of fuel injection. The implemented injection law was irate, a law that defines the injection by an approximation based on the pul- 12

Parameters Fuelling [mg] Start of Injection [ RAC] Flow Time [kg/h] Speed [rot/min] Minimum Correction Baseline Map Maximum Correction Minimum Correction Baseline Map Maximum Correction Minimum Correction Baseline Map Maximum Correction 800 3.22 3.54 3.89-5.00-2.00 1.00 0.31 0.34 0.37 1000 3.25 3.58 3.94-6.00-3.00 0.00 0.39 0.43 0.47 1500 2.98 3.28 3.61-9.00-6.00-3.00 0.54 0.59 0.65 2000 2.99 3.29 3.62-9.50-6.50-3.50 0.72 0.79 0.87 2500 3.12 3.43 3.77-8.25-5.25-2.25 0.94 1.03 1.13 3000 2.95 3.25 3.58-6.25-3.25 2.25 1.06 1.17 1.29 3500 2.99 3.29 3.62-7.00-4.00-1.00 1.25 1.38 1.52 4000 3.07 3.38 3.72-8.25-5.25-2.25 1.47 1.62 1.78 4500 2.95 3.24 3.56-8.75-5.75-2.75 1.59 1.75 1.93 Table 1. Baseline Map and Correction Map of the Electronic Control Unit [4] verized fuel flow through the injector per unit time slots. To do this, in the equations for the calculation of the law of injection the density data, fuel injection time expressed in crankshaft rotation angle at the beginning and at the end of the injection, and data on the amount of fuel injected during the entire duration of the injection has been introduced [2]. The electronic control units ECU introduced in the model used in the computer simulation process management aims injection on the Baseline Map containing benchmarks for engine operation at steady state values compared with the signals provided the sensor and the actuator output. Injection maps for the building model are designed to optimize injection parameters controlled by the ECU to obtain maximum power with low fuel consumption and low emissions. When these conditions are not complied the ECU intervenes, and corrects the required parameters using correction maps to achieve the results (Table 1). THE RESULTS OF THE SIMULATION PROCESS To determine defining values for the engine cycle computer simulations were made using diesel fuel for the model built in AVL Boost Fig. 3. Rate of Heat Released from the computer simulations. Fig. 4. NOx emissions from the computer simulations. 13

Fig. 5. CO emissions from the computer simulations. Fig. 6. The Rate of Heat Released by changes of injection parameters. Fig. 7. The NOx emissions by changes of injection parameters. From the performed simulations with mixtures of biofuel the heat released from burning was decreased between 1.5% and 2% for B10 biofuel blends, and between 2% and 2.5% for B20 biofuel blends, because of the low calorific value of the biofuel [4]. NOx emissions resulting from computer simulations, increased in proportion with the percentage of oxygen in biofuel blends. Biofuel used in computer simulations in the engine generates an increase of NOx emissions of up to 1.5% for B10 biofuel blends and 2.5% for B20 biofuel blends. By increasing the quantity of the injected fuel to change the injection parameters in order to increase the quantity of heat released from burning process the NOx emissions increase in up to a value of 2% for B10 biofuel blends, and up to 3% for B20 biofuel blends. CO emissions have decreased by 2.5% when using B10 biofuel blend, or 5% when using B20 biofuel blend due to oxygen content and cetane number blend which rises with the increasing concentration of biofuel in the blend. Research has shown a decrease of CO emissions by up to 3.7% for B10 biofuel blends and up to the value of 6.8% for B20 biofuel blends. Fig. 8. The CO emissions by changes of injection parameters. application, and the simulations were repeated using B10 biofuel, respective B20 biofuel [3]. The engine performance was evaluated based on the amount of heat release obtained from the combustion process in the cylinder to compare the properties of mixtures of fuels used in the simulation. The conclusion was that a bigger quantity of heat release was obtained from the combustion process under conditions of low concentration of biofuel in the blend increased, because it has a 14 lower calorific value and a density greater than diesel fuel. The evolution of maximum heat released by the combustion process is shown in Figure 3, NOx emissions in Figure 4 and CO emissions in Figure 5. CHANGE OF INJECTION PARAMETERS The computer simulations followed the following logic: increasing the quantity of heat released from burning. For this purpose, the ECU simulation parameters have been modified to inject a higher quantity of fuel for greater percentage of biofuel concentration of the mixture [2]. The simulation results during the combustion for the maximum heat release in the cylinder and emissions of NOx and CO generated from the change of the injection parameters are shown in Figures 6, 7 and 8. CONCLUSIONS Following the computer simulations it was found that B10 and B20 biofuel blends with up to 98% and 95% of the energy potential of diesel fuel. REFERENCES [1] AVL BOOST version 2011, Users Guide, AVL List GmbH, Graz, Austria, Document no. 01.0104, Edition 07.2011; [2] Iclodean, C., Burnete, N., Computer Simulation of CI Engines Fuelled with Biofuels by Modelling Injection irate Law, Research Journal of Agricultural Science, CNC- SIS Clasa B+, No. 44 (1), 2012, ISSN: 2066-1843; [3] Burnete, N., ș.a., Motoare Diesel și Biocombustibili pentru transportul urban, Editura Mediamira, Cluj- Napoca, 2008, ISBN: 978-973-713-217-8; [4] Iclodean, C., Burnete, N., Influence of the Electronic Control Unit on Optimization Function of the Compression Ignition Engines Powered with Biofuels, IJE, CNC- SIS Clasa B+, Tome XI, Fascicule 3, 2013, ISSN: 1584-2665.

Ingineria Automobilului High Order Spectral Analysis of a Measured Automotive Parameter Analiza spectrală de ordin superior a semnalului unei mărimi mecanice măsurate în transmisia unui automobil. Modele matematice obţinute prin identificare 1. INTRODUCTION The classic theory of a measured mechanical amount generally deals with fundamental statistic amounts, such as average, dispersion, median value and so on. This won t lead to an intimate analysis of the real phenomenon, since the measured amount is considered somehow to be rather quasi-constant. Although the spectral analysis, based on the Fourier Transform provides some information about the signal s spectrum, it has been proven to have a serious lack: it considers the spectrum to be timesteady and the Fourier Transform takes into account all the frequencies as being developed in the same time. But in the real life, the spectra are time-variable; they change from one moment to another. Moreover, the classic analysis can t separate the linear part of the signal from the non-linear one. Hence, along with the time-analysis, should be also applied a multispectral analysis, which is able to separate the linear part from the non-linear one and a time-frequency analysis that is able to offer valuable information about the time variation of the signal s spectra. In 15 Assoc. prof. Eng. Marin MARINESCU marin_s_marinescu @yahoo.com Eng. Marian TRUŢĂ Military Technical Academy of Bucharest this respect, fig. 1 depicts a normal signal that has been achieved from a tested vehicle. It represents the torque acting on a transmission shaft of a military vehicle. The signal was achieved as given in fig. 2. 2. DATA SELF- CORRELATION IN THE TIME ANALYSIS To establish the confidence level of the measured data, a self-correlation analysis should be applied before anything else. Thus, if the self-correlation is poor, the signal should be abandoned, since it is not trustful. To perform this kind of analysis, the signal is previously cut into pieces. Usually, the signal is divided into two equal parts that are reciprocally compared using the self-correlation function as given by: (1) where n is the number of the one half of the data, x i is a certain value, h is the time-gap between two consecutive values of the data vector and m is the maximum allowed gap. Fig. 3 depicts the graph of the self-correlation function for the achieved signal. The signal theory states that the two sides of the selfcorrelation are rather symmetric and they have a slight tendency to zero, than the data are well self-correlated. The poorer the symmetry, the more non-linear behavior. The faster trend to zero, the poorer selfcorrelation. From the presented figure one can notice the data are well correlated but the signal isn t linear. Fig. 1. Test signal and classically modeled Fig. 2. Transducer mounting 3. SPECTRAL (FREQUENCY) ANALYSIS The spectral analysis can be performed in a mono-spectral way or in a multi-spectral way as well. The first type is also called a Fourier analysis and it assigns the whole spectrum of frequencies to a single moment of time. So, the spectrum contains both the linear component and the non-linear one on the same graphic. The multi-spectral analysis is able to separate the nonlinear part from the linear one and the most used one is the bi-spectral analysis. 3.1 Mono-spectral analysis The most used spectra in this kind of analysis are the amplitude spectra of the signal. To reach these spectra, the Fourier Transform (that decomposes the signal) will be written, as: (2) that, using the real part and imaginary part of the equation, can be also be written as: where: (3) Fig. 3. Self-correlation function of the signal (4) is the amplitude of the signal that gives the amplitude of the spectra. In these equations x(t) is the signal in continuos time (the Fourier Transform can be also applied in discrete time, as will be used in this case), f is the frequency and t is the continuos time. Of course, j = 1 is the imaginary number. Since the amplitude of the spectrum depicts the values of the energy that is dissipated on the correspondent frequencies, it means that on the frequencies that have high peaks, the system dissipates its highest energies. So, these frequencies are, somehow, characteristic and they will be either filtered (if one knows them as coming from a 15

Fig. 4. The amplitude spectra of the signal Fig. 6. Filtered signal specific, identifiable noise) or taken into account (if they are useful). It is noticeable that the system dissipates energy on some frequencies that have high peaks. They correspond to 3.2 3.5 Hz, 7.5 7.8 Hz and 14.6 14.9 Hz. The question is: are these bands useful or they belong to some specific noise? During the tests, when preparing the shaft for tests, the balancing counterweights had to be removed, so the shaft became unbalanced. Considering the angular speed of the engine, which was kept rather constant, and also considering the transmission ratios on the driveline from the engine to the shaft, one could notice that these frequencies are noisy. Moreover, the second and the third bands are integer multiples of the first one, which should be considered as the base oscillation, while the others should be its second and third order harmonics. Hence, a filter had to be instated. 3.2 Used filter Since the signal is discrete, a digital filter is used. Many filters have been analyzed and a Butterworth Infinite Impulse Response filter has been chosen. The filter s order was stated at six, value that came into being starting from both the filter s stability and computing time. Fig. 5 gives the main characteristic features of the mentioned filter. Since there was no reliable information that the other two frequencies are indeed second order and third order harmonics of the first frequency, the same model of filter was applied to the resulting signal, after it was processed by the first filter. Nothing happened, the filtered signal (from the first filter) was completely overlapping on the genuine signal (the computed filtering errors were lower than 3.25%); hence, even filtering on the subsequent frequencies, no improvements occurred. That really means the other two peaks belong to the second and third order harmonics of the first peak s frequency. In conclusion, applying the designed filter over the original signal on the stop-band frequency of 3.2 3.5 Hz, the other two frequencies will be automatically eliminated, since they are nothing but superior order harmonics of the mentioned frequency. Using the coherence function, the linear part could be separated from the non-linear one. A view in this respect is given by fig. 7 that provides the separation of the linear part from the non-linear one; both of them overlapped on the genuine signal. 3.3 Multi-spectral analysis Multi-spectral analysis assumes the using of the cummulants. The higher is the order of the cummulant, the higher will be the order of the multi-spectral analysis. There is one step between the order of the analysis and the used cummulant. Thus, to perform a second order spectral analysis, a third order cummulant will be used, as this Fig. 7. Signal separation paper reveals. So, the third order cummulant is given in discrete time, by: (5) where M {} is the averaging operator, * x( n), x ( n) are the signal and its complex conjugate while k and r are the used regressors; hence, the bi-spectrum will be written as: (6) where f 1 and f 2 are the frequencies of the linear and the non-linear part respectively. The images given in fig. 8 represent the amplitude of the bi-spectrum of the signal. For a better picturing, and to make the necessary idea about the influence of the filter upon the non-linear part of the Fig. 5. IIR, Butterworth, sixth order, 3.2 3.5 Hz, band-stop filter 16

Fig. 8 The bi-spectrum of the signal. a - 2D bi-spectrum, non-filtered signal; b - 3D bi-spectrum, non-filtered signal; c - 2D bi-spectrum, filtered signal; d - 3D bi-spectrum, filtered signal signal, the upper part of the figure contains the images of the bi-spectrum when applied to the genuine signal. Consequently, the lower part of the figure gives the images of the same signal, but previously filtered. One can notice that the filtered signal has lost a lot of peaks around the main one (in the middle of the diagrams). In the graphs, f l and f n are the frequencies of the linear and non-linear components, respectively. So, the busier the field of the 2D representation, the more the non-linear component is present in the signal. After filtering, the non-linear component decreases in importance. 4. SYSTEM S TIME- IDENTIFICATION MATHEMATICAL MODEL After processing the data, a mathematical model should be issued. A method is to use the time-identification algorithms. The Theory of Signals provides a wide range of algorithms, depending on a lot of factors. One of the most important is the number of inputs and outputs. The considered system has one input and one output, so it is SISO (Single Input Single Output). To get the model means to determine the transfer function. An ARX (Auto Regressive with exogene inputs) model was considered in this situation, given by: (7) where A and B are polynomials and e is the error. Applying this algorithm according to its characteristics (given in fig. 9), the transfer function in discrete time was obtained. Using a Z transform, the transfer function in continuos time was obtained; hence, the differential equation that duplicates the real signal is given by (8) This is the wanted mathematical model. For a more suggestive view, fig. 9 gives, on the same diagram (upper left) the genuine signal (blue curve) and the model s one (red curve). In green, there is the modeling error. One can notice that the blue curve (genuine signal) is almost completely covered by the red one, so the model is excellent. Moreover, the equation is stable, according to its impulse response. 17

Fig. 9. The features of the ARX mathematic model 5. SYSTEM S FREQUENCY- IDENTIFICATION MATHEMATICAL MODEL This method assumes the use of the so-called regressor, of different orders. A regressor is nothing else but a history value of the signal. Assume a discrete-time signal actual value as x(k). It s first order regressor is x(k 1) and so on. So, the model is built up by the signal s historical values and it works as a prediction of the actual value starting from its past one(s). So, for a SISO system, using the first order regressor, the equation describing the phenomenon, based 18 on the frequency-identification algorithm, is given by: (9) where y(k) is the output and x(k) is the input, in discrete time. Fig. 10 depicts the graphical representation of the already filtered genuine signal (blue curve), its mathematical model as obtained with this method, and the modeling error. As in the time-identification method, the red curve overlaps almost completely the blue one, so the error is quite low. But there is still a difference. Using only the first order regressor, the error is slightly bigger than in the previ- Fig. 10. Results of the frequency-identification mathematical model

Fig. 11. Born-Jordan Transform ous case. Of course, the regressor order can be increased, but the computing time will also increase while the error won t decrease significantly. Applying the algorithm to the analyzed signal, the mathematical model is given by equation (10). As expected, this equation is using the discrete time (the actual value in the time-positioning vector). Using specific methods, it can be translated into continuos time, but it is quite complicate. Most of the time it is used just the way it is now, in discrete time. (10) 6. SYSTEM S TIME- FREQUENCY- IDENTIFICATION MATHEMATICAL MODEL Eventually, the last method to achieve a mathematical model is Fig. 12. Spectrogram the spectral-temporal method. From the very beginning should be mentioned that this method is a non-parametric one. Should a parametric method be used, mathematical models with equations are obtained. Should a non-parametric method be used, only graphical representations are obtained. The most used transforms are the bilinear ones. These transforms are both in continuous time and discrete time. Most of them belong to the so-called Cohen class that has the general equation given by: (11) Of course, all the terms of the above given general transform can be explained, but this will take a lot of room and time in this paper. So, the representations will be more suggestive. Fig. 11 depicts the Born-Jordan, discrete time transform. For a better analysis, the signal and the spectrum of the signal were also attached. The field of the transform is providing the weight of the nonlinear component. So, the emptier the field, the less energy of the non-linear component, so the less importance in the signal it has. Two more representations are used to reveal the structure of the signal. One of them is the spectrogram, as depicted in fig. 12. It provides a very good information about the time evolution of the frequency spectra of the signal. It was obtained by applying second power of the Short Term Fourier Transform, as given by equation (12): (12) Eventually, the results obtained by the Stockwell Transform, as given by equation (13), are depicted in fig. 13. This transform is a sort of a phase-corrected wavelet transform and it is very good to be used whenever comes about revealing the non-linear component of a signal. (13) Fig. 13. Signal (red curve) and Stockwell Transform which is also, very complex in its expression. 7. CONCLUSIONS The classic analysis of a signal, which is eventually the time history of a mechanical amount, measured by electrical means, doesn t provide intimate information about its behavior. Using the new techniques of time, frequency and time-frequency analysis, one can get more specific information about the evolution of that specific amount. Moreover, these techniques are able to provide high-reliable mathematical models for the measured amount. A new perspective is therefore open and the mechanical phenomena can be better interpreted. REFERENCES [1] Bitmead, R. - Modeling and Identification for Control - University of California, Berkeley, 1999 [2] Ilie, C.O., Marinescu, M., Oloeriu, F. - Getting a mathematical model of the vehicle s dynamics using regressions - Second international congress automotive, safety and environment, SMAT 2008, 23-25 October, 2008 Craiova, Romania, ISBN 978-606-510-253-8, ISBN 978-606-510-245-3 [3] Longin Iacobescu, Ioan Filip, Marin Marinescu - Rezolvarea unor probleme care apar in procesarea datelor experimentale. Filtrarea software a semnalelor - The 32 nd International Scientific Conference of the Military Technical Academy Modern Technologies in the 21 st Century, Bucharest, 1-2 November 2007 [4] Marinescu, M., Vilău, R., Mitrea M. - Mechanical faults identification using spectral analysis of a measured signal - ESFA 2009, November 12-14, Bucharest, ISSN 2067-1083 [5] Marinescu, M. - The importance of filtering the signals of the measured mechanical amounts - MTA Review nr. 1/2010, Bucureşti, pp. 7-14, ISSN 1843-339 [6] Marinescu, M., Vilău, R., Truţă, M., Fieraru, O. - A method to obtain a generalized model of the pressure evolution within the braking system of a vehicle - International Journal of Modern Manufacturing Technologies, ISSN 2067-3604 [7] Marinescu, M. - Parametric (polynomial) method to issue a mathematical model starting from a measured signal of a mechanical amount - The 6 th International Conference New challenges in the field of military sciences 2009 18 19 November, 2009, Budapest, Hungary, ISBN 978-963-87706-6-0 [8] *** Signal Processing Toolbox, http://mathworks.com [9] *** Frequency Selective Filters. 2001 [10] *** Filter Design using MAT- LAB s remez. 2001 19

Ingineria Automobilului University Research Cercetare Universitară Symposium EV&HV 2013 Innovation in electric and hybrid mobility Automotive Engineering Research Centre, University of Piteşti. 1 november 2013 Simpozionul EV&HV 2013 Inovare în Mobilitatea Electrică şi Hibridă Centrul de cercetare Ingineria Automobilului, Universitatea din Piteşti. 1 noiembrie 2013 Assoc. Prof. Ph D. Eng. Dănuţ Gabriel Marinescu Executive Director - Research Center Automotive Engineering University of Pitesti The Research Center Automotive Engineering within the University of Pitesti organized on November 1, 2013 the second edition of the National Symposium EV & HV - Innovation in hybrid and electric mobility. The event was held under the patronage of the Society of Automotive Engineers of Romania - SIAR and brought together experts from the economic environment, research institutes and universities, with interests in electric and hybrid mobility. Opening the symposium, the speakers Prof.PhD.eng. Ion Tabacu - Director of the Research Center Automotive Engineering, Prof.PhD.eng. Sebastian Pârlac Vice-rector of the University of Pitesti and engineer Cristian Liviu Popescu - Manager of Innovation Projects within the Renault Technologie Roumanie, highlighted the need to develop the cooperation between the academic and economic environment in the domain of green vehicles. Within the symposium there have addressed both aspects of design and construction of the electric and hybrid vehicles and the work of the research teams in the fields of electro- mobility and renewable energies. This year, the event EV & HV 2013 has broadened its thematic area by including the domain of hybrid propulsion of thermal-hydraulic type. There were presented the following papers: Comparison between a thermal/ electrical vehicle from physical client equirements point of view - Ioan Teleagă, Cristian Liviu Popescu - Renault Technologie Roumanie; Schneider Electric solutions for the electric vehicle charging infrastructure - Vlad Rovo, Petre Butu - Schneider Electric Romania; Toyota HSD - Hybrid Synergy Drive - Bogdan Dumitrescu - TOY- OTA Pitesti; Determination of motion power and of the running efficiency of an electric vehicle - Aurelian Crăciunescu, Leonard Melcescu and Adrian Baltateanu - Polytechnic University of Bucharest; Hybrid electric car. Present and perspectives for the ICSI Râmnicu Vâlcea - Adrian Enache, Michael Culcer - National Research & Development Institute for Cryogenics and Isotopic Technologies - ICSI Râmnicu Vâlcea; Elastic wave propagation in functionally graded materials - Erol Senocak, collaborator of the Univer- 20 20

sity of Pitesti; Hydraulic Hybrid System for the automotive propulsion - Horia Abăitancei - SCHAFFLER Romania; Contribution to the promotion of electromobility within the University of Pitesti the EcoLOGIC program 2002-2013 - Danut Gabriel Marinescu - University of Pitesti. The exhibition organized on this occasion hosted a series of electric and hybrid vehicles: Toyota Prius Plug-in - presented by Toyota Pitesti, the concept of electric vehicle with autonomy range extension using the fuel cell - presented by ICSI Râmnicu Vâlcea for the first time at such events within the academia environment and the latest Renault ZE electric vehicles - presented by the Renault engineering center of Romania. University of Pitesti presented two of the achievements of teachers and students teams in 2011-2013: KartEL - the electric propulsion kart developed with Alseca SRL funding and SOLARom the solar vehicle developed with EFES SRL funding. KartEL won the first place in the electric drive section of the international competition Challenge Kart Low-Cost, held in 2012 on the Renault - Dacia testing slopes at Merişani - Arges, and at Nevers - France in 2013. They were also exposed to the concepts realized in the Alternative Propulsion Systems for Cars - Alternative and Renewable Energies laboratory within the ECOLogic program during 2002-2013: Dacia ELECTRA - an electric vehicle built on Dacia Logan platform, Dacia GRAND SANDERO Hybrid UtilityVehicle a LPG - Electric hybrid vehicle built on Dacia Logan MCV platform, Dacia HAMSTER a diesel-electric hybrid vehicle built on the Dacia Sandero platform and the functional model Grand Hamster Electricway 4WD a diesel -electric hybrid vehicle (Plug-in) built on the Dacia Duster platform. Starting this year, the symposium EV&HV has a junior formula with an educational role, especially dedicated to students. The first edition of EV&HV - Junior was held in early June 2013 in collaboration with Renault Technologie Roumanie. Talon de abonament Doresc să mă abonez la revista Auto Test pe un an (12 apariţii Auto Test şi 4 apariţii supliment Ingineria Automobilului ) Numele... Prenumele... Societatea... Funcţia... Tel... Fax:... E-mail... Adresa...... Cod poştal.... Oraşul... Ţara... Preţul abonamentului anual pentru România: 65 lei. Plata se face la Banca Română de Dezvoltare (BRD) Sucursala Calderon, cont RO78BRDE410SV19834754100. Subscription Form I subscribe to the Auto Test magazine for one year (12 issues of Auto Test and 4 issues of it s supplement Ingineria Automobilului ) Name... Surname... Society... Position... Tel... Fax:... E-mail... Adress...... Postal Code.... City...Country... Yearly subscription price: Europe 40 Euro, Other Countries 40 Euro. Payment delivered to Banca Română de Dezvoltare (BRD) Calderon Branch, Account RO38BRDE410SV18417414100 (SWIFT BIC: BRDEROBU). 21

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