394 resultados para All terrain vehicles


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A novel replaceable, modularized energy storage system with wireless interface is proposed for a battery operated electric vehicle (EV). The operation of the proposed system is explained and analyzed with an equivalent circuit and an averaged state-space model. A non-linear feedback linearization based controller is developed and implemented to regulate the DC link voltage by modulating the phase shift ratio. The working and control of the proposed system is verified through simulation and some preliminary results are presented.

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Bidirectional Inductive Power Transfer (IPT) systems are preferred for Vehicle-to-Grid (V2G) applications. Typically, bidirectional IPT systems consist of high order resonant networks, and therefore, the control of bidirectional IPT systems has always been a difficulty. To date several different controllers have been reported, but these have been designed using steady-state models, which invariably, are incapable of providing an accurate insight into the dynamic behaviour of the system A dynamic state-space model of a bidirectional IPT system has been reported. However, currently this model has not been used to optimise the design of controllers. Therefore, this paper proposes an optimised controller based on the dynamic model. To verify the operation of the proposed controller simulated results of the optimised controller and simulated results of another controller are compared. Results indicate that the proposed controller is capable of accurately and stably controlling the power flow in a bidirectional IPT system.

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Large scale solar plants are gaining recognition as potential energy sources for future. In this paper, the feasibility of using electric vehicles (EVs) to control a solar powered micro-grid is investigated in detail. The paper presents a PSCAD/EMTDC based model for the solar powered micro-grid with EVs. EVs are expected to have both the vehicle-to-grid (V2G) and grid-to-vehicle (G2V) capability, through which energy can either be injected into or extracted from the solar powered micro-grid to control its energy imbalance. Using the model, the behaviour of the micro-grid is investigated under a given load profile, and the results indicate that a minimum number of EVs are required to meet the energy imbalance and it is time dependent and influenced by various factors such as depth of charge, commuting profiles, reliability etc...

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Investigation of the epigenome of sporadic pituitary tumours is providing a more detailed understanding of aberrations that characterise this tumour type. Early studies, in this and other tumour types adopted candidate-gene approaches to characterise CpG island methylation as a mechanism responsible for or associated with gene silencing. However, more recently, investigators have adopted approaches that do not require a priori knowledge of the gene and transcript, as example differential display techniques, and also genome-wide, array-based approaches, to 'uncover' or 'unmask' silenced genes. Furthermore, through use of chromatin immunoprecipitation as a selective enrichment technique; we are now beginning to identify modifications that target the underlying histones themselves and that have roles in gene-silencing events. Collectively, these studies provided convincing evidence that change to the tumour epigenome are not simply epiphenomena but have functional consequences in the context of pituitary tumour evolution. Our ability to perform these types of studies has been and is increasingly reliant upon technological advances in the genomics and epigenomics arena. In this context, other more recent advances and developing technologies, and, in particular, next generation or flow cell re-sequencing techniques offer exciting opportunities for our future studies of this tumour type.

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This paper provides a three-layered framework to monitor the positioning performance requirements of Real-time Relative Positioning (RRP) systems of the Cooperative Intelligent Transport Systems (C-ITS) that support Cooperative Collision Warning (CCW) applications. These applications exploit state data of surrounding vehicles obtained solely from the Global Positioning System (GPS) and Dedicated Short-Range Communications (DSRC) units without using other sensors. To this end, the paper argues the need for the GPS/DSRC-based RRP systems to have an autonomous monitoring mechanism, since the operation of CCW applications is meant to augment safety on roads. The advantages of autonomous integrity monitoring are essential and integral to any safety-of-life system. The autonomous integrity monitoring framework proposed necessitates the RRP systems to detect/predict the unavailability of their sub-systems and of the integrity monitoring module itself, and, if available, to account for effects of data link delays and breakages of DSRC links, as well as of faulty measurement sources of GPS and/or integrated augmentation positioning systems, before the information used for safety warnings/alarms becomes unavailable, unreliable, inaccurate or misleading. Hence, a monitoring framework using a tight integration and correlation approach is proposed for instantaneous reliability assessment of the RRP systems. Ultimately, using the proposed framework, the RRP systems will provide timely alerts to users when the RRP solutions cannot be trusted or used for the intended operation.

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This project makes a contribution to knowledge about the successful leadership practices that enhance education for young people with a disability in a Queensland Secondary School. The project used a critical ethnographic approach with a variety of data collection methods and analysis. For example, the use of work diaries, semi-structured interviews, document analysis and observation. These leadership practices were found to be relevant to the development of inclusive schools for all learners.The most powerful leadership practices found were those used by the leader to challenge, interupt and replace exsisting discourse and processes that led to exclusion of students with a disability.

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A method for calculating visual odometry for ground vehicles with car-like kinematic motion constraints similar to Ackerman's steering model is presented. By taking advantage of this non-holonomic driving constraint we show a simple and practical solution to the odometry calculation by clever placement of a single camera. The method has been implemented successfully on a large industrial forklift and a Toyota Prado SUV. Results from our industrial test site is presented demonstrating the applicability of this method as a replacement for wheel encoder-based odometry for these vehicles.

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The work presented in this report is aimed to implement a cost-effective offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. Understandably, the objectives of a practical optimisation problem are conflicting each other and the minimisation of one of them necessarily implies the impossibility to minimise the other ones. This leads to the need to find a set of optimal solutions for the problem; once such a set of available options is produced, the mission planning problem is reduced to a decision making problem for the mission specialists, who will choose the solution which best fit the requirements of the mission. The goal of this work is then to develop a Multi-Objective optimisation tool able to provide the mission specialists a set of optimal solutions for the inspection task amongst which the final trajectory will be chosen, given the environment data, the mission requirements and the definition of the objectives to minimise. All the possible optimal solutions of a Multi-Objective optimisation problem are said to form the Pareto-optimal front of the problem. For any of the Pareto-optimal solutions, it is impossible to improve one objective without worsening at least another one. Amongst a set of Pareto-optimal solutions, no solution is absolutely better than another and the final choice must be a trade-off of the objectives of the problem. Multi-Objective Evolutionary Algorithms (MOEAs) are recognised to be a convenient method for exploring the Pareto-optimal front of Multi-Objective optimization problems. Their efficiency is due to their parallelism architecture which allows to find several optimal solutions at each time

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Despite rising levels of safe-sex knowledge in Australia, sexually transmitted infection notifications continue to increase. A culture-centred approach suggests it is useful in attempting to reach a target population first to understand their perspective on the issues. Twenty focus groups were conducted with 89 young people between the ages of 14 and 16 years. Key findings suggest that scientific information does not articulate closely with everyday practice, that young people get the message that sex is bad and they should not be preparing for it and that it is not appropriate to talk about sex. Understanding how young people think about these issues is particularly important because the focus groups also found that young people disengage from sources of information that do not match their own experiences.

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This paper addresses the topic of real-time decision making by autonomous city vehicles. Beginning with an overview of the state of research, the paper presents the vehicle decision making & control systemarchitecture, explains the subcomponents which are relevant for decision making (World Model and Driving Maneuver subsystem), and presents the decision making process. Experimental test results confirmthe suitability of the developed approach to deal with the complex real-world urban traffic.

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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e. the autonomous vehicles’ ability to make appropriate driving decisions in city road traffic situations. After decomposing the problem into two consecutive decision making stages, and giving a short overview about previous work, the paper explains how Multiple Criteria Decision Making (MCDM) can be used in the process of selecting the most appropriate driving maneuver.

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This thesis addresses the topic of real-time decision making by driverless (autonomous) city vehicles, i.e. their ability to make appropriate driving decisions in non-simplified urban traffic conditions. After addressing the state of research, and explaining the research question, the thesis presents solutions for the subcomponents which are relevant for decision making with respect to information input (World Model), information output (Driving Maneuvers), and the real-time decision making process. TheWorld Model is a software component developed to fulfill the purpose of collecting information from perception and communication subsystems, maintaining an up-to-date view of the vehicle’s environment, and providing the required input information to the Real-Time Decision Making subsystem in a well-defined, and structured way. The real-time decision making process consists of two consecutive stages. While the first decision making stage uses a Petri net to model the safetycritical selection of feasible driving maneuvers, the second stage uses Multiple Criteria Decision Making (MCDM) methods to select the most appropriate driving maneuver, focusing on fulfilling objectives related to efficiency and comfort. The complex task of autonomous driving is subdivided into subtasks, called driving maneuvers, which represent the output (i.e. decision alternatives) of the real-time decision making process. Driving maneuvers are considered as implementations of closed-loop control algorithms, each capable of maneuvering the autonomous vehicle in a specific traffic situation. Experimental tests in both a 3D simulation and real-world experiments attest that the developed approach is suitable to deal with the complexity of real-world urban traffic situations.

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Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This mobility prediction model is trained using sample executions of motion primitives on representative terrain, and predicts the future outcome of control actions on similar terrain. Using Gaussian process regression allows us to exploit its inherent measure of prediction uncertainty in planning. We integrate mobility prediction into a Markov decision process framework and use dynamic programming to construct a control policy for navigation to a goal region in a terrain map built using an on-board depth sensor. We consider both rigid terrain, consisting of uneven ground, small rocks, and non-traversable rocks, and also deformable terrain. We introduce two methods for training the mobility prediction model from either proprioceptive or exteroceptive observations, and report results from nearly 300 experimental trials using a planetary rover platform in a Mars-analogue environment. Our results validate the approach and demonstrate the value of planning under uncertainty for safe and reliable navigation.

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The Independent Music Project is centred around the development and creation of new music, and includes research into copyright, business models of the future, new technologies, and new audiences. The music industry is undergoing the most radical changes it has faced in almost a century. New digital technologies have made the production, distribution, and promotion of recorded music accessible to anyone with a personal computer. People can now make high-quality digital copies of music and distribute them globally within minutes. Even bastions of the established industries, such as EMI and Columbia, are struggling to make sense of the new industry terrain. The whole employment picture has changed just as radically for people who wish to make a living from music. In Australia, many of the avenues that provided employment for musicians have either disappeared or dramatically shrunk. The advertising industry no longer provides the level of employment it used to prior to the Federal deregulation of the industry in 1992. In many places, new legislative pressures on inner-city and suburban venues have diminished the number of performance spaces that musicians can work in. Just as quickly, new sectors have opened to professional musicians: computer games, ringtones, sound-enabled toys and web advertising all present new opportunities to the enterprising musician. The opportunity to distribute music internationally without being signed to a major label is very attractive to many aspiring and established professionals. No doubt the music industry will face many more challenges as technologies continue to change, as global communication gets easier and faster, and as the challenges to copyright proliferate and change. These challenges cannot be successfully met on a single front. They require research and expertise from all sectors being affected, and this is why the independent music project (IMP) exists.