21 resultados para Volvo Car Corporation

em Universidad Politécnica de Madrid


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TIPO DE BUQUE: Velero de competición capacitado para la regata alrededor del mundo “Volvo Ocean Race.” REGLAMENTOS: Reglas de la clase: Volvo Ocean 60 rule 2000 + changes CLASIFICACIÓN: ABS Guide for Building and Classing Offshore Racing Yachts 1994 incorporating Notice #1 DESPLAZAMIENTO MÁXIMO: 15000 KG CALADO MÁXIMO: 3.75 m ESLORA MÁXIMA: 23.5 m CONSTRUCCIÓN: Casco: Materiales compuestos. Mástil: materiales compuestos sin núcleo o aluminio. INSTALACIÓN ELÉCTRICA: 24V DC con un motor auxiliar y al menos dos alternadores independientes. SISTEMA DE PROPULSIÓN: Vela, aparejo tipo Sloop. Motor propulsivo de emergencia con hélice plegable de dos palas capaz de dar 7 nudos en condiciones de mar en calma ALOJAMIENTO: para 12 tripulantes REQUERIMIENTOS: Desaladora-potabilizadora, radar, GPS, GMDSS, comunicaciones por satélite Inmarsat B y C, sistema de gobierno de emergencia, calefacción, bombas de lastre, sistema de corrección de escora mediante tanques de lastre liquido.

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The goal of the work described in this paper is to develop a visual line guided system for being used on-board an Autonomous Guided Vehicle (AGV) commercial car, controlling the steering and using just the visual information of a line painted below the car. In order to implement the control of the vehicle, a Fuzzy Logic controller has been implemented, that has to be robust against curvature changes and velocity changes. The only input information for the controller is the visual distance from the image center captured by a camera pointing downwards to the guiding line on the road, at a commercial frequency of 30Hz. The good performance of the controller has successfully been demonstrated in a real environment at urban velocities. The presented results demonstrate the capability of the Fuzzy controller to follow a circuit in urban environments without previous information about the path or any other information from additional sensors

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This paper presents the main results of a study on the influence of driving style on fuel consumption and pollutant emissions of diesel passenger car in urban traffic. Driving styles (eco, normal or aggressive) patterns were based on the “eco-driving” criteria. The methodology is based on on-board emission measurements in real urban traffic in the city of Madrid. Five diesel passenger cars, have been tested. Through a statistical analysis, a Dynamic Performance Index was defined for diesel passenger cars. Likewise, the CO, NOX and HC emissions were compared for each driving style for the tested vehicles. Eco-driving reduces by 14% fuel consumption and CO2 emissions, but aggressive driving increase consumption by 40%. Aggressive driving increases NOX emission by more than 40%. CO and HC, show different trends, but being increased in eco-driving style.

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The contributions of driver behaviour as well as surrounding infrastructure are decisive on pollutant emissions from vehicles in real traffic situations. This article deals with the preliminary study of the interaction between the dynamic variables recorded in a vehicle (driving pattern) and pollutant emissions produced over a given urban route. It has been established a “dynamic performance index”-DPI, which is calculated from some driving pattern parameters, which in turn depends on traffic congestion level and route characteristics, in order to determine whether the driving has been aggressive, normal or calm. Two passenger cars instrumented with a portable activity measurement system -to record dynamic variables- and on-board emission measurement equipment have been used. This study has shown that smooth driving patterns can reduce up to 80% NOX emissions and up to 20% of fuel in the same route

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The developments in materials over the last decade have been considerable within the automotive industry, being one of the leaders in innovative product applications. Sustainable product development of an automotive structure requires a balanced approach towards technological, economical and ecological aspects. The introduction of new materials and processes is dependent on satisfying different factors. Competitive and legislative pressures, creating the need for change, affect these factors considerably. The process, direction and speed of change are often reactive. Current paper shows the application of aluminium alloys, for the use in the bottom structure of a car to face the problem for the weight of the entire bottom structure under static load conditions, including stiffness, strength and buckling constraints. In addition to minimized mass and materials' price, the assessment of an environmental impact of materials-candidates during the entire life cycle of the structure is considered.

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Tipo de Buque: Car Carrier. Capacidad de carga: carga 1: 3000 coches sin trailers. Carga 2: Carga combinada para 1500 ml de trailers y coches en el resto de las cubiertas del buque no ocupadas por los trailers. Peso muerto 5800 TPM. Capacidad de conductores: 100 personas en camarotes dobles. Sociedad de clasificación: Det Norske Veritas. Reglamentos: Solas, Marpol, Convenio de líneas de carga. Velocidad: 19 nudos al 85% MCR en pruebas. Autonomía: 4500 millas al 80% MCR y 15% al margen de mar. Tripulación 25 personas.

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The door-closing process can reinforce the impression of a solid, rock-proof, car body or of a rather cheap, flimsy vehicle. As there are no real prototypes during rubber profile bidding-out stages, engineers need to carry out non-linear numerical simulations that involve complex phenomena as well as static and dynamic loads for several profile candidates. This paper presents a structured virtual design tool based on FEM, including constitutive laws and incompressibility constraints allowing to predict more realistically the final closing forces and even to estimate sealing overpressure as an additional guarantee of noise insulation. Comparisons with results of physical tests are performed.

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The development of new-generation intelligent vehicle technologies will lead to a better level of road safety and CO2 emission reductions. However, the weak point of all these systems is their need for comprehensive and reliable data. For traffic data acquisition, two sources are currently available: 1) infrastructure sensors and 2) floating vehicles. The former consists of a set of fixed point detectors installed in the roads, and the latter consists of the use of mobile probe vehicles as mobile sensors. However, both systems still have some deficiencies. The infrastructure sensors retrieve information fromstatic points of the road, which are spaced, in some cases, kilometers apart. This means that the picture of the actual traffic situation is not a real one. This deficiency is corrected by floating cars, which retrieve dynamic information on the traffic situation. Unfortunately, the number of floating data vehicles currently available is too small and insufficient to give a complete picture of the road traffic. In this paper, we present a floating car data (FCD) augmentation system that combines information fromfloating data vehicles and infrastructure sensors, and that, by using neural networks, is capable of incrementing the amount of FCD with virtual information. This system has been implemented and tested on actual roads, and the results show little difference between the data supplied by the floating vehicles and the virtual vehicles.

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The objective of this paper is to design a path following control system for a car-like mobile robot using classical linear control techniques, so that it adapts on-line to varying conditions during the trajectory following task. The main advantages of the proposed control structure is that well known linear control theory can be applied in calculating the PID controllers to full control requirements, while at the same time it is exible to be applied in non-linear changing conditions of the path following task. For this purpose the Frenet frame kinematic model of the robot is linearised at a varying working point that is calculated as a function of the actual velocity, the path curvature and kinematic parameters of the robot, yielding a transfer function that varies during the trajectory. The proposed controller is formed by a combination of an adaptive PID and a feed-forward controller, which varies accordingly with the working conditions and compensates the non-linearity of the system. The good features and exibility of the proposed control structure have been demonstrated through realistic simulations that include both kinematics and dynamics of the car-like robot.

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Intelligent Transportation Systems (ITS) cover a broad range of methods and technologies that provide answers to many problems of transportation. Unmanned control of the steering wheel is one of the most important challenges facing researchers in this area. This paper presents a method to adjust automatically a fuzzy controller to manage the steering wheel of a mass-produced vehicle to reproduce the steering of a human driver. To this end, information is recorded about the car's state while being driven by human drivers and used to obtain, via genetic algorithms, appropriate fuzzy controllers that can drive the car in the way that humans do. These controllers have satisfy two main objectives: to reproduce the human behavior, and to provide smooth actions to ensure comfortable driving. Finally, the results of automated driving on a test circuit are presented, showing both good route tracking (similar to the performance obtained by persons in the same task) and smooth driving.

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Due to its small size and the restrictions on source and listener positions, the design of sound reproduction systems for car cabins is particularly cumbersome. In the present project the measurement of the impulse response between a single loudspeaker and a listener position, with special emphasis on the directional characteristics, will be examined. The propagation paths inside a car are very short, meaning that it is very difficult for the existing commercial measurement systems to resolve the different reflections arriving to the listener. This paper propose a first approach of an algorithm based on time difference of arrival along a measurement technique aiming at finding the reflections and their direction of arrival to the listener. To this end a circular microphone array at a known position is employed, along with Maximum-Length Sequences (MLS) measurement technique. The results are processed so as to extract the directional properties, demonstrate the physical limitations that can influence or prevent this detection in practice. Measurements were carried out in a free-field environment (anechoic chamber) making use of different panels closer around the microphone array. RESUMEN. El diseño de sistemas de reproducción de audio para cabinas de coche es especialmente complicado debido al reducido tamaño del espacio y las restricciones de los altavoces y posiciones de escucha de los ocupantes. En el presente proyecto, se examinan mediciones de la respuesta al impulso entre un altavoz y una posición de escucha con especial énfasis en las características direccionales. Los caminos de propagación de las ondas sonoras dentro de un coche son muy cortos, lo que hace difícil para los instrumentos de medida existentes en el mercado determinar las direcciones de llegada de las diferentes reflexiones que llegan a una posición de escucha. Este trabajo propone una primera aproximación de un algoritmo, basado en las diferencias temporales de llegada de una onda a diferentes puntos de medida, y una particular técnica de medida de la respuesta al impulso para obtener las direcciones de llegada de reflexiones a una posición de escucha. Para ello, se emplea una matriz circular de micrófonos en una posición conocida junto con la técnica de medida MLS (Maximum Length Sequence). Los resultados obtenidos son procesados para extraer la dirección de llegada de las reflexiones acústicas y encontrar las limitaciones que influyan en la detección de dichas reflexiones. Las mediciones se llevan a cabo en un entorno de campo libre y utilizando diferentes superficies reflectantes alrededor de la matriz de micrófonos.

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This article provides a new methodology for estimating fuel consumption and emissions by enabling a correct comparison between freight transportation modes. The approach is developed and integrated as a part of an intelligent transportation system dealing with goods movement. A key issue is related to energy consumption ratios and consequent CO2 emissions. Energy consumption ratios are often used based on transport demand. However, including other ratios based on transport supply can be useful. Furthermore, it is important to indicate which factors are associated with variations in energy consumption and emissions; especially of interest are parameters that have a higher incidence and order of magnitude, in order to fairly compare and understand the difference between transport modes and sub-modes. The study finds that the use of an energy consumption equation can improve the quality of the estimates. The study proposes that coefficients that define the energy consumption equation should be tested to determine market niches and sources of improvement in energy consumption according to the category of vehicles, fuel types used, and classes of products transported.

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Changing factors (mainly traffic intensity and weather conditions) affecting road conditions require a suitable optimal speed at any time. To solve this problem, variable speed limit systems (VSL) ? as opposed to fixed limits ? have been developed in recent decades. This term has included a number of speed management systems, most notably dynamic speed limits (DSL). In order to avoid the indiscriminate use of both terms in the literature, this paper proposes a simple classification and offers a review of some experiences, how their effects are evaluated and their results This study also presents a key indicator, which measures the speed homogeneity and a methodology to obtain the data based on floating cars and GPS technology applying it to a case study on a section of the M30 urban motorway in Madrid (Spain).

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In this paper an on line self-tuned PID controller is proposed for the control of a car whose goal is to follow another one, at distances and speeds typical in urban traffic. The bestknown tuning mechanism is perhaps the MIT rule, due to its ease of implementation. However, as it is well known, this method does not guarantee the stability of the system, providing good results only for constant or slowly varying reference signals and in the absence of noise, which are unrealistic conditions. When the reference input varies with an appreciable rate or in presence of noise, eventually it could result in system instability. In this paper an alternative method is proposed that significantly improves the robustness of the system for varying inputs or in the presence of noise, as demonstrated by simulation.

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Este estudio presenta una comparativa entre un LIDAR modelo LMS-111 (Sick Ltd.) y una cámara de profundidad de uso doméstico: Kinect (Microsoft Corporation), orientada a determinar las condiciones de uso de uno y otro sensor, así como sus ventajas e inconvenientes cuando son empleados en condiciones de campo, en una explotación agrícola. Para ello se realizaron diversos ensayos en una parcela experimental del CSIC-CAR de Arganda del Rey, España. Para los ensayos ambos sensores fueron instalados en un tractor operado remotamente diseñado y construido en el marco del proyecto europeo RHEA. Dicho tractor realizó dos recorridos diferentes: el primero se efectuó en paralelo a un muro y el segundo paralelo a una hilera de olivos. El primer ensayo se realizó con el propósito de cuantificar la uniformidad de las mediciones de ambos sensores y el segundo para validar los resultados en un cultivo real. Los recorridos se realizaron empleando cuatro marchas diferentes, con el objetivo de determinar si los diferentes regímenes de operación del motor influyen sobre la precisión de los sensores. Los resultados muestran que el LIDAR posee un mayor alcance máximo de medición, pero una resolución menor frente a Kinect, muestran además que el LIDAR puede ser operado a cualquier hora del día y condición meteorológica, mientras que Kinect, no puede operar en exteriores, salvo en horas del día con baja intensidad lumínica. Por otra parte la gran desventaja del LIDAR es su coste, 30 veces más alto que Kinect.