Commercially available Hybrid Electric Vehicles (HEVs) have been around for more than ten years. However, their market share remains small. Focusing only on the improvement of fuel economy, the design tends to reduce the size of the internal combustion engine in the HEV, and uses the electrical drive to compensate for the power gap between the load demand and the engine capacity. Unfortunately, the low power density and the high cost of the combined electric motor drive and battery packs dictate that the HEV has either worse performance or much higher price than the conventional vehicle. In this research, a new design philosophy for parallel HEV is proposed, which uses a full size engine to guarantee the vehicle performance at least as good as the conventional vehicle, and hybridizes with an electrical drive in parallel to improve the fuel economy and performance beyond the conventional cars. By analyzing the HEV fuel economy versus the increasing of the electrical drive power on typical driving conditions, the optimal hybridization electric power capacity is determined. Thus, the full size engine HEV shows significant improvement in fuel economy and performance, with relatively short cost recovery period. A new control strategy, which optimizes the fuel economy of parallel configured charge sustained hybrid electric vehicles, is proposed in the second part of this dissertation. This new approach is a constrained engine on-off strategy, which has been developed from the two extreme control strategies of maximum SOC and engine on-off, by taking their advantages and overcoming their disadvantages. A system optimization program using dynamic programming algorithm has been developed to calibrate the control parameters used in the developed control strategy, so that the control performance can be as close to the optimal solution as possible. In order to determine the sensitivity of the new control strategy to different driving conditions, a passenger car is simulated on different driving cycles. The performances of the vehicle with the new control strategy are compared with the optimal solution obtained on each driving condition with the dynamic programming optimization. The simulation result shows that the new control strategy always keeps its performance close to the optimal one, as the driving condition changes.

The simulation tools that are used to model vehicle systems have not been advancing as quickly as the growth of research and technology surrounding the advancements of vehicle technology itself. A topological vehicle systems modelling package would use Modelica to take advantage of the flexibility and modularity of the language, the inherent multi-domain workspace and analytical accuracy of model equations. This package is defined through the use of SuperBlocks, a generalized model that allows the user to select and parameterize the appropriate sub-system directly within the workspace. This palette of SuperBlocks would be implemented within MapleSim6 to create MapleCar. This provides a customized balance between speed and accuracy after taking advantage of advanced graph-theoretic solutions methods used in MapleSim. MapleCar provides several advantages to a user over conventional tools. The SuperBlocks would ease the required steps to model a full vehicle system by providing clear, simple connections to quickly get a simulation assembled. Next, each SuperBlock is represented by a model that contains a replaceable model, a Modelica function which allows its internal model to be changed through a user-friendly parameter selection. The combination of sub-systems accessible directly through a parameter allows a variety of vehicle systems to be easily assembled, as well as provide a container for future models to be shared and published. A short demonstration of connecting these vehicle SuperBlocks from the MapleCar package is provided using MapleSim6. The generalized vehicle component palette provides a straight-forward, customizable drag-and-drop interface to assist in generating vehicle models for simulation. Conclusions and recommendations are provided at the end.

Electric vehicle technology is an interdisciplinary field in continuous development. It appears to be a margin for improvements. The Division for Electricity at Uppsala University is doing significant research in the field. The present thesis investigates electric machines for vehicular applications, both in the driveline and in the traction motor. Section 1 presents a driveline with two galvanically isolated voltage levels. A low power side is operated at the optimum voltage of the batteries, while a high power side is operated at a higher voltage leading to higher efficiencies in the traction motor. Both sides are coupled through a flywheel that stabilizes the power transients inherent to a drive cycle. A review of electric machine topologies for electric vehicles is presented in Section 2. The permanent magnet excited machine is the most suitable technology for an electric driveline. Section 3 is devoted to numerical models applied to electric machines. The equivalent circuit of a motor/generator with two sets of windings is first presented. This machine couples both sides of the driveline and drives the rotor of the flywheel. The electric parameters are calculated with custom FEM models. A discussion on slotless machines concludes with a simple model to analyze the magnetic field from one static 3D simulation. The tooth ripple losses in solid salient poles are also analyzed with a novel FEM approach. A complete description of the losses in electric machines gives a proper background for further discussion on efficiency. Section 4 presents the experimental work constructed to validate the theoretical models. The experiments include an axial flux, single wounded prototype, an axial flux, double wound prototype and a planed radial flux coreless prototype. Section 5 focuses on traction motors for electric vehicles. A simulated prototype illustrates a design and calculation process. The loss theory and the numerical methods presented in Section 3 are applied.

The classification of vehicle types and their attributes for various traffic modelling exercises is a common occurrence. The increasing use of microsimulation packages, which are based on modelling individual vehicles through the road network, points to the importance of having proper vehicle attributes specified in order to achieve the modelling results that match real-life conditions. / The use of a customised vehicle fleet instead of the default types that are usually built into microsimulation software will allow more accurate estimation of traffic performance indicators, such as speeds, travel times, capacity, fuel consumption etc. Most notably the accurate classification of vehicles is essential for reliable vehicle emissions modelling to occur, since the type and fuel used by vehicles has a significant effect on their emissions performance. To this end there are a number of databases that can be used for vehicle classification, these include but are not limited to: Australian Bureau of Statistics Motor Vehicle Census Data; Austroads Vehicle Classifications; Fleet composition models produced by Bureau of Transport Economics. / This thesis describes the development of the customised vehicle fleet to be used in Paramics microsimulation modelling package by Quadstone in the UK. Vehicle fleet profiles were developed for South Australian urban and rural conditions based on Australian Bureau of Statistics Motor Vehicle Census data and supplemented with other sources of vehicle kinematics and physical characteristics. / Thesis (MEng(TransportSystemsEng))--University of South Australia, 2005

One of the important components of Intelligent Transport Systems (ITS) are the Advanced Traveller Information Systems (ATIS) that provide traffic information to manage traffic flow on existing road networks more efficiently. / Variable Messages Signs (VMS) are one of the key instruments of ATIS for providing en-route traveller information. These signs offer significant potential to resolve urban traffic management issues, such as reducing congestion and increasing network efficiency. The system also delivers considerable personal benefits by assisting drivers to make route choice decisions. / Much research has validated the effectiveness of VMS information on route choice decisions, however, the relationship between route choice behaviour and information content is still not clear. Also, the results show large variation when factors such as the influence of road type, toll roads and degree of congestion are considered. / The primary aims of this research are to investigate route choice behaviour in response to the message content of VMS and to develop route choice models targeted on an arterial road in the Adelaide Central Business District (CBD). The study investigates the influences of VMS message content on drivers taking into account their differing characteristics and experience, including socio-economic factors and trip characteristics. / Two major surveys, a stated preference (SP) survey and a revealed preference (RP) survey, were performed. An anonymous mail-back SP survey questionnaire was conducted with residents along a target route in Adelaide in order to collect drivers' route choice behaviour in response to hypothetical VMS messages. The RP survey was conducted to collect data in the real world situation. A VMS message was displayed to drivers and actual route choice behaviour was measured using anonymous mail-back questionnaires and by observation of traffic volumes. A total of 245 (of 1000 distributed) and 183 (of 500 distributed) replies were used for model development. / A binary logit approach was employed to develop route choice models using data obtained from the SP survey. Goodness-of-fit and hypothesis testing of the model showed that the developed models fitted the data well and estimated parameters were statistically significant at the 5% level. / Thesis (MEng(TransportSystemsEng))--University of South Australia, 2004.

No description available.

With modern day computer power, developing intelligent vehicles is fast becoming a reality. An Intelligent Vehicle is a vehicle equipped with sensors and computing that allow it to perceive the world around it, and to decide on appropriate action. Vision cameras are a good choice to sense the environment. One key task of the camera in an intelligent vehicle is to detect and localise the obstacles, which is the preparation of path planning. Stereo vision based obstacle detection is used in this research. It does not analyse semantic meaning of image features, but directly measures the 3-D coordinates of image pixels, and thus is suitable for obstacle detection in an unknown environment. In this research, a novel correlation based stereo vision method is developed which greatly improves its accuracy while maintaining its real-time performance. Since a vision system provides a large amount of data, extracting refined information may sometimes be complex. In obstacle detection tasks, the purpose is to distinguish the obstacle pixels from the ground pixels in the disparity image. V-Disparity image approach is used in this research to detect the ground plane, however this approach relies heavily on sufficient road features. In this research, a correlation method to locate the ground plane in the disparity image, even without significant road features, is developed. Moreover, traditional V-Disparity images have difficulties detecting non-flat ground, thus having limited applications. This research also develops a method to detect non-flat ground using V-Disparity images, thus greatly widening its application.

The classification of vehicle types and their attributes for various traffic modelling exercises is a common occurrence. The increasing use of microsimulation packages, which are based on modelling individual vehicles through the road network, points to the importance of having proper vehicle attributes specified in order to achieve the modelling results that match real-life conditions. / The use of a customised vehicle fleet instead of the default types that are usually built into microsimulation software will allow more accurate estimation of traffic performance indicators, such as speeds, travel times, capacity, fuel consumption etc. Most notably the accurate classification of vehicles is essential for reliable vehicle emissions modelling to occur, since the type and fuel used by vehicles has a significant effect on their emissions performance. To this end there are a number of databases that can be used for vehicle classification, these include but are not limited to: Australian Bureau of Statistics Motor Vehicle Census Data; Austroads Vehicle Classifications; Fleet composition models produced by Bureau of Transport Economics. / This thesis describes the development of the customised vehicle fleet to be used in Paramics microsimulation modelling package by Quadstone in the UK. Vehicle fleet profiles were developed for South Australian urban and rural conditions based on Australian Bureau of Statistics Motor Vehicle Census data and supplemented with other sources of vehicle kinematics and physical characteristics. / Thesis (MEng(TransportSystemsEng))--University of South Australia, 2005

No description available.

The classification of vehicle types and their attributes for various traffic modelling exercises is a common occurrence. The increasing use of microsimulation packages, which are based on modelling individual vehicles through the road network, points to the importance of having proper vehicle attributes specified in order to achieve the modelling results that match real-life conditions. / The use of a customised vehicle fleet instead of the default types that are usually built into microsimulation software will allow more accurate estimation of traffic performance indicators, such as speeds, travel times, capacity, fuel consumption etc. Most notably the accurate classification of vehicles is essential for reliable vehicle emissions modelling to occur, since the type and fuel used by vehicles has a significant effect on their emissions performance. To this end there are a number of databases that can be used for vehicle classification, these include but are not limited to: Australian Bureau of Statistics Motor Vehicle Census Data; Austroads Vehicle Classifications; Fleet composition models produced by Bureau of Transport Economics. / This thesis describes the development of the customised vehicle fleet to be used in Paramics microsimulation modelling package by Quadstone in the UK. Vehicle fleet profiles were developed for South Australian urban and rural conditions based on Australian Bureau of Statistics Motor Vehicle Census data and supplemented with other sources of vehicle kinematics and physical characteristics. / Thesis (MEng(TransportSystemsEng))--University of South Australia, 2005