High-frequency global navigation satellite system’s receivers for airborne gravimetry

The development of global navigation satellite systems (GNSS) provides a solution of many applied problems with increasingly higher quality and accuracy nowadays. Researches that are carried out by the Bavarian Academy of Sciences and Humanities in Munich (BAW) in the field of airborne gravimetry are based on sophisticated data processing from high frequency GNSS receiver for kinematic aircraft positioning. Applied algorithms for inertial acceleration determination are based on the high sampling rate (50Hz) and on reducing of such factors as ionosphere scintillation and multipath at aircraft /antenna near field effects. The quality of the GNSS derived kinematic height are studied also by intercomparison with lift height variations collected by a precise high sampling rate vertical scale [1]. This work is aimed at the ways of more accurate determination of mini-aircraft altitude by means of high frequency GNSS receivers, in particular by considering their dynamic behaviour.

The impact of flood and post-flood cleaning on airborne microbiological and particle contamination in residential houses

In January 2011, Brisbane, Australia, experienced a major river flooding event. We aimed to investigate its effects on air quality and assess the role of prompt cleaning activities in reducing the airborne exposure risk. A comprehensive, multi-parameter indoor and outdoor measurement campaign was conducted in 41 residential houses, 2 and 6 months after the flood. The median indoor air concentrations of supermicrometer particle number (PN), PM10, fungi and bacteria 2 months after the flood were comparable to those previously measured in Brisbane. These were 2.88 p cm-3, 15 µg m-3, 804 cfu m-3 and 177 cfu m-3 for flood-affected houses (AFH), and 2.74 p cm-3, 15 µg m-3, 547 cfu m-3 and 167 cfu m-3 for non-affected houses (NFH), respectively. The I/O (indoor/outdoor) ratios of these pollutants were 1.08, 1.38, 0.74 and 1.76 for AFH and 1.03, 1.32, 0.83 and 2.17 for NFH, respectively. The average of total elements (together with transition metals) in indoor dust was 2296 ± 1328 µg m-2 for AFH and 1454 ± 678 µg m-2 for NFH, respectively. In general, the differences between AFH and NFH were not statistically significant, implying the absence of a measureable effect on air quality from the flood. We postulate that this was due to the very swift and effective cleaning of the flooded houses by 60,000 volunteers. Among the various cleaning methods, the use of both detergent and bleach was the most efficient at controlling indoor bacteria. All cleaning methods were equally effective for indoor fungi. This study provides quantitative evidence of the significant impact of immediate post-flood cleaning on mitigating the effects of flooding on indoor bioaerosol contamination and other pollutants.

Relating urban airborne particle concentrations to shipping using carbon based elemental emission ratios

This study demonstrates a novel method for testing the hypothesis that variations in primary and secondary particle number concentration (PNC) in urban air are related to residual fuel oil combustion at a coastal port lying 30 km upwind, by examining the correlation between PNC and airborne particle composition signatures chosen for their sensitivity to the elemental contaminants present in residual fuel oil. Residual fuel oil combustion indicators were chosen by comparing the sensitivity of a range of concentration ratios to airborne emissions originating from the port. The most responsive were combinations of vanadium and sulfur concentration ([S], [V]) expressed as ratios with respect to black carbon concentration ([BC]). These correlated significantly with ship activity at the port and with the fraction of time during which the wind blew from the port. The average [V] when the wind was predominantly from the port was 0.52 ng.m-3 (87%) higher than the average for all wind directions and 0.83 ng.m-3 (280%) higher than that for the lowest vanadium yielding wind direction considered to approximate the natural background. Shipping was found to be the main source of V impacting urban air quality in Brisbane. However, contrary to the stated hypothesis, increases in PNC related measures did not correlate with ship emission indicators or ship traffic. Hence at this site ship emissions were not found to be a major contributor to PNC compared to other fossil fuel combustion sources such as road traffic, airport and refinery emissions.

A three-phase to single-phase matrix converter based bi-directional IPT system for charging electric vehicles

This paper presents a novel three-phase to single-phase matrix converter (TSMC) based bi-directional inductive power transfer (IPT) system for vehicle-to-grid (V2G) applications. In contrast to existing techniques, the proposed technique which employs a TSMC to drive an 8th order high frequency resonant network, requires only a single-stage power conversion process to facilitate bi-directional power transfer between electric vehicles (EVs) and a three-phase utility power supply. A mathematical model is presented to demonstrate that both magnitude and direction of power flow can be controlled by regulating either relative phase angles or magnitudes of voltages generated by converters. The viability of the proposed mathematical model is verified using simulated results of a 10 kW bi-directional IPT system and the results suggest that the proposed system is efficient, reliable and is suitable for high power applications which require contactless power transfer.

Contactless and replaceable modularized battery energy storage system for electric vehicles

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.

Controller synthesis of a bidirectional inductive power interface for electric vehicles

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.

Control of solar powered micro-grids using electric vehicles

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...

A unique battery/supercapacitor direct integration scheme for hybrid electric vehicles

Battery/supercapacitor hybrid energy storage systems have been gaining popularity in electric vehicles due to their excellent power and energy performances. Conventional designs of such systems require interfacing dc-dc converters. These additional dc-dc converters increase power loss, complexity, weight and cost. Therefore, this paper proposes a new direct integration scheme for battery/supercapacitor hybrid energy storage systems using a double ended inverter system. This unique approach eliminates the need for interfacing converters and thus it is free from aforementioned drawbacks. Furthermore, the proposed system offers seven operating modes to improve the effective use of available energy in a typical drive cycle of a hybrid electric vehicle. Simulation results are presented to verify the efficacy of the proposed system and control techniques.

A comparative study of airborne particulate pollution at two bus stations of different site geography

Airborne particulate pollutant is considered to be one of the major harmful emissions produced by vehicle engines as it has been directly linked to serious health problems. Passengers spend long times at bus stations and may be exposed to high concentrations of pollution. Particle pollution at two bus stations in Brisbane, Australia were monitored. The two bus stations consisted of markedly different site geography and surroundings with one situated in a street canyon and the other elevated above ground level. The same flow of traffic operated through both stations. Real time measurements of ultrafine particle concentration, size distribution and meteorological conditions were carried out on the platform continuously over several days. The results showed that the particle number concentrations were significantly different at the two stations, suggesting that the layout of site geometry and surroundings was a dominant determining factor through the injection of fresh air into the station platforms and the rates of dilution.

Willingness-to-pay for infrastructure investments for alternative fuel vehicles

This study investigates potential demand for infrastructure investment for alternative fuel vehicles by applying stated preference methods to a Japanese sample. The potential demand is estimated on the basis of how much people are willing to pay for alternative fuel vehicles under various refueling scenarios. Using the estimated parameters, the economic efficiency of establishing battery-exchange stations for electric vehicles is examined. The results indicate that infrastructural development of battery-exchange stations can be efficient when electric vehicle sales exceed 5.63% of all new vehicle sales. Further, we find a complementary relationship between the cruising ranges of alternative fuel vehicles and the infrastructure established.

Practical visual odometry for car-like vehicles

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.

Real-time decision making for autonomous city vehicles

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.

Multiple criteria-based real-time decision making by autonomous city vehicles

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.

Real-time decision making by driverless city vehicles : a discrete event driven approach

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.