978 resultados para parallel hybrid vehicle
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The aim of this thesis is to describe hybrid drive design problems, the advantages and difficulties related to the drive. A review of possible hybrid constructions, benefits of parallel, series and series-parallel hybrids is done. In the thesis analytical and finite element calculations of permanent magnet synchronous machines with embedded magnets were done. The finite element calculations were done using Cedrat’s Flux 2D software. This machine is planned to be used as a motor-generator in a low power parallel hybrid vehicle. The boundary conditions for the design were found from Lucas-TVS Ltd., India. Design Requirements, briefly: • The system DC voltage level is 120 V, which implies Uphase = 49 V (RMS) in a three phase system. • The power output of 10 kW at base speed 1500 rpm (Torque of 65 Nm) is desired. • The maximum outer diameter should not be more than 250 mm, and the maximum core length should not exceed 40 mm. The main difficulties which the author met were the dimensional restrictions. After having designed and analyzed several possible constructions they were compared and the final design selected. Dimensioned and detailed design is performed. Effects of different parameters, such as the number of poles, number of turns and magnetic geometry are discussed. The best modification offers considerable reduction of volume.
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A hybrid electric vehicle is a fast-growing concept in the field of vehicle industry. Nowadays two global problems make manufactures to develop such systems. These problems are: the growing cost of a fuel and environmental pollution. Also development of controlled electric drive with high control accuracy and reliability allows improving of vehicle drive characteristics. The objective of this Diploma Thesis is to investigate the possibilities of electrical drive application for new principle of parallel hybrid vehicle system. Electric motor calculations, selection of most suitable control system and other calculations are needed. This work is not final work for such topic. Further investigation with more precise calculations, modeling, measurements and cost calculations are needed to answer the question if such system is efficient.
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Die Luftverschmutzung, die globale Erwärmung sowie die Verknappung der endlichen Ressourcen sind die größten Bedenken der vergangenen Jahrzehnte. Die Nachfrage nach jeglicher Mobilität steigt rapide. Dementsprechend bemüht ist die Automobilindustrie Lösungen für Mobilität unter dem Aspekt der Nachhaltigkeit und dem Umweltschutz anzubieten. Die Elektrifizierung hat sich hierbei als der beste Weg herausgestellt, um die Umweltprobleme sowie die Abhängigkeit von fossilen Brennstoffen zu lösen. Diese Arbeit soll einen Einblick über die Umweltauswirkungen des Hybridfahrzeuges Toyota Prius geben. Hierbei findet eine Gliederung in vier verschiedene Lebensphasen statt. Im Anschluss bietet die Sachbilanz die Möglichkeit die Umweltauswirkungen mit verschiedenen Antriebsmöglichkeiten und Brennstoffen zu vergleichen. Das Modell hat gezeigt, dass der Toyota Prius während der Nutzung einen hohen Einfluss auf das Treibhauspotenzial aufweist. Durch die Nutzung anderer Brennstoffe, wie beispielsweise Ethanol oder Methanol lassen sich die Auswirkungen am Treibhauspotenzial sowie der Verbrauch an abiotischen Ressourcen reduzieren. Vergleicht man die Elektromobilität mit der konventionellen, so ist festzustellen, dass diese Art der Mobilität die derzeit beste Möglichkeit zur Reduzierung der Umweltbelastungen bietet. Die Auswirkungen der Elektromobilität sind im hohen Maße abhängig von der Art des verwendeten Strommixes.
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To obtain the desirable accuracy of a robot, there are two techniques available. The first option would be to make the robot match the nominal mathematic model. In other words, the manufacturing and assembling tolerances of every part would be extremely tight so that all of the various parameters would match the “design” or “nominal” values as closely as possible. This method can satisfy most of the accuracy requirements, but the cost would increase dramatically as the accuracy requirement increases. Alternatively, a more cost-effective solution is to build a manipulator with relaxed manufacturing and assembling tolerances. By modifying the mathematical model in the controller, the actual errors of the robot can be compensated. This is the essence of robot calibration. Simply put, robot calibration is the process of defining an appropriate error model and then identifying the various parameter errors that make the error model match the robot as closely as possible. This work focuses on kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial-parallel hybrid robot. The robot consists of a 4-DOF serial mechanism and a 6-DOF hexapod parallel manipulator. The redundant 4-DOF serial structure is used to enlarge workspace and the 6-DOF hexapod manipulator is used to provide high load capabilities and stiffness for the whole structure. The main objective of the study is to develop a suitable calibration method to improve the accuracy of the redundant serial-parallel hybrid robot. To this end, a Denavit–Hartenberg (DH) hybrid error model and a Product-of-Exponential (POE) error model are developed for error modeling of the proposed robot. Furthermore, two kinds of global optimization methods, i.e. the differential-evolution (DE) algorithm and the Markov Chain Monte Carlo (MCMC) algorithm, are employed to identify the parameter errors of the derived error model. A measurement method based on a 3-2-1 wire-based pose estimation system is proposed and implemented in a Solidworks environment to simulate the real experimental validations. Numerical simulations and Solidworks prototype-model validations are carried out on the hybrid robot to verify the effectiveness, accuracy and robustness of the calibration algorithms.
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Hybridiajoneuvosovellukset vaativat usein sekä korkea- että matalajännitejärjestelmän. Korkeajännitejärjestelmä sisältää yleensä energiavaraston, joka on joko superkondansaattori tai korkeajänniteakusto, dieselgeneraattorin tai range extenderin ja ajokäytön. Korkeajännitejärjestelmään liitetään usein myös erilaisia apukäyttöjä kuten kompressoreita ja hydraulipumppuja. Matalajännitejärjelmä koostuu yleensä ohjausyksiköistä, ajovaloista, yms. laitteista. Perinteisesti matalajännitejärjestelmää on syötetty dieselmoottorin laturista, mutta korkeajännitejärjestelmien myötä DC/DC-hakkurin käyttäminen korkea- ja matalajännitejärjestelmien välillä on herättänyt kiinnostusta, koska tällöin laturin voisi poistaa ja matalajänniteakustoa pienentää. Tässä työssä kuvatun monilähöisen tehonmuokkaimen invertterisilta soveltuu apukäyttöjen ajamiseen, ja erotettu DC/DC-hakkuri matalajännitejärjestelmän syöttämiseen. Tässä työssä käydään läpi edellä mainitun tehonmuokkaimen suunnittelu, keskittyen eritoten laitteen korkeajänniteosien mitoitukseen ja termiseen suunniteluun. DC/DC-hakkurin osalta perinteisiä piistä valmistettuja IGBT transistoreja vertaillaan piikarbidi MOSFET transistoreihin. Lämpömallilaskujen paikkaansapitävyyttä tutkitaan suorittamalla prototyyppilaitteelle hyötysuhdemittaus, jonka tuloksia verrataan laskettuihin tuloksiin. Lämpömallin parannusmahdollisuuksia käsitellään myös hyötysuhdemittauksen tulosten perusteella.
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In this paper we consider hybrid (fast stochastic approximation and deterministic refinement) algorithms for Matrix Inversion (MI) and Solving Systems of Linear Equations (SLAE). Monte Carlo methods are used for the stochastic approximation, since it is known that they are very efficient in finding a quick rough approximation of the element or a row of the inverse matrix or finding a component of the solution vector. We show how the stochastic approximation of the MI can be combined with a deterministic refinement procedure to obtain MI with the required precision and further solve the SLAE using MI. We employ a splitting A = D – C of a given non-singular matrix A, where D is a diagonal dominant matrix and matrix C is a diagonal matrix. In our algorithm for solving SLAE and MI different choices of D can be considered in order to control the norm of matrix T = D –1C, of the resulting SLAE and to minimize the number of the Markov Chains required to reach given precision. Further we run the algorithms on a mini-Grid and investigate their efficiency depending on the granularity. Corresponding experimental results are presented.
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In this paper we introduce a new algorithm, based on the successful work of Fathi and Alexandrov, on hybrid Monte Carlo algorithms for matrix inversion and solving systems of linear algebraic equations. This algorithm consists of two parts, approximate inversion by Monte Carlo and iterative refinement using a deterministic method. Here we present a parallel hybrid Monte Carlo algorithm, which uses Monte Carlo to generate an approximate inverse and that improves the accuracy of the inverse with an iterative refinement. The new algorithm is applied efficiently to sparse non-singular matrices. When we are solving a system of linear algebraic equations, Bx = b, the inverse matrix is used to compute the solution vector x = B(-1)b. We present results that show the efficiency of the parallel hybrid Monte Carlo algorithm in the case of sparse matrices.
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This thesis studies the minimization of the fuel consumption for a Hybrid Electric Vehicle (HEV) using Model Predictive Control (MPC). The presented MPC – based controller calculates an optimal sequence of control inputs to a hybrid vehicle using the measured plant outputs, the current dynamic states, a system model, system constraints, and an optimization cost function. The MPC controller is developed using Matlab MPC control toolbox. To evaluate the performance of the presented controller, a power-split hybrid vehicle, 2004 Toyota Prius, is selected. The vehicle uses a planetary gear set to combine three power components, an engine, a motor, and a generator, and transfer energy from these components to the vehicle wheels. The planetary gear model is developed based on the Willis’s formula. The dynamic models of the engine, the motor, and the generator, are derived based on their dynamics at the planetary gear. The MPC controller for HEV energy management is validated in the MATLAB/Simulink environment. Both the step response performance (a 0 – 60 mph step input) and the driving cycle tracking performance are evaluated. Two standard driving cycles, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Driving Schedule (HWFET), are used in the evaluation tests. For the UDDS and HWFET driving cycles, the simulation results, the fuel consumption and the battery state of charge, using the MPC controller are compared with the simulation results using the original vehicle model in Autonomie. The MPC approach shows the feasibility to improve vehicle performance and minimize fuel consumption.
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Mode of access: Internet.
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Mode of access: Internet.
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Mode of access: Internet.
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"DOE/CS-0102/1."
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Energy Department, Washington, D.C.
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Energy Department, Washington, D.C.
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Mode of access: Internet.