Abstract

Traffic congestion today is a major problem in almost all of the metropolitan areas of the world. An increasing level of congestion results in negative impacts on the urban environment. These include environmental pollution, energy problems and traffic accidents. The analysis of these problems and the predictions of the impacts of any transport policies that could be devised to deal with them are very critical to their success. Traffic problems are almost the same in most modern cities either in developed countries or less economically developed countries.The driving cycle for a vehicle is the representation of a speed–time sequenced profile, which is developed for a specific area or city. It is an important requirement in the evaluation of the driver’s behaviour and the performance of vehicles for a number of applications, mainly in the area of environmental studies. For example, fuel consumption and emissions’ predictions need information input on the characteristics of driving patterns of traffic. The applications of driving cycle analysis can be extended however, to many more other areas. The motivation for this research is to investigate the detailed impacts of travel demand management (TDM) measures, thatare already in application. This is to improve the network performance, using driving cycle analysis. It is important to explicitly assess these measures using a micro-level detailed approach in order to comprehend overall results in terms of emissions and network performance. These understandings will benefit government agencies and policy makers in their planning and appraisals. It will also benefit public transport providers to improve their service in attracting and retaining their customers.The developments of the real world driving cycles in Edinburgh and Abu Dhabi have been presented in this research. The analysis of real world data, which has been obtained from monitoring traffic conditions in both cities using the GPS tracking of traffic, is presented. This data was collected from trips which have been carried out on a number of traffic corridors in both cities. The assessment of various parameters of traffic (i.e. speed, time percentage spent on acceleration, deceleration, idling, cruising and cycle duration) and their statistical validity, produced a real world driving cycle for the buses as well as the private cars. Two TDM measures have been considered; bus lanes and traffic calming measures. At each corridor, a handheld GPS device was used to record speed, acceleration, deceleration and distances driven. This data enabled the analysis of driving cycles for the buses and for the private cars. The driving cycle analysis and investigations have further been investigated using regression analysis techniques. The results suggest that the approach shows potential but further research is needed with more data available. The results suggest that the driving cycle analysis approach would be very useful to have a better understanding of driving behaviour and also the detailed impacts of the transport policies on traffic. In terms of bus lanes and traffic calming measures, the results show some positive impacts of these policies, while there are evidences of some negative impacts as well. These findings would be very valuable for the policy decision makers. It is recommended from this research that the driving cycle analysis could be utilised effectively in the assessment of TDM measures. Further investigations and analysis of driving cycle is urgently recommended in a number of research directions. Combined GIS and GPS data could also enhance the development in this research. Document type: Thesis

Abstract

The purpose of this paper is to present the results of an investigation as to the interconnection between main exterior factors which can influence the power consumption during the vehicle movement in the conditions of real operation. According to the results of theoretic researches, there was determined an influence of every factor on the power consumption during vehicle movement in the modes typical for Lutsk city. There was established a contribution of the factors into the total power consumption on micro and macro levels. As a result of the study it was evaluated that an influence of a driver on a power consumption is situated within 50…80 %, an influence of an air resistance is up to 10 %, an influence of a longitudinal profile and a road resistance varies within 20…35 %. According to the results of experiments, there were determined the bus driving modes in urban conditions, and according to their results, there was built an average graph of bus movement in Lutsk city. There was made a mathematic modelling of electric vehicle movement, along with that there was taken into account the most probable range of change of the exterior factors, namely vehicle acceleration, road resistance, air resistance. It was proved that while speed is growing, the influence of road resistance and of air resistance is growing up and has a parabolic character, along with that the contribution of a driver is decreasing. The contribution of the study consists in that, There were proposed the coefficients of taking into consideration the influence of exterior factors on the power consumption by the vehicle and there was built a mathematic model for their determination. These coefficients of taking into consideration the influence of exterior factors on the power consumption give a possibility to evaluate the critical influences and to make an operative decision about the minimization of power consumption as for some specific vehicles, and for an enterprise. Further researches will focus on the plotting of telemetric means of informing, in a mode of real time, of the drivers of the vehicles, of the controllers of an enterprise about the exterior influences, that will give a possibility to make the appropriative decisions instantly. Besides, the given results can be used in order to determine the level of qualification of a driver, the state of road pavement, will give a possibility to find some more rational layout of bus stops, traffic lights, to optimize the routes of vehicles movement.

Abstract

Hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) are evolving rapidly since the introduction of Toyota Prius into the market in 1997. As the world needs more fuel-efficient vehicles to mitigate climate change, the role of HEVs and PHEVs are becoming ever more important. While fuel economies of HEVs and PHEVs are superior to those of internal combustion engine (ICE) powered vehicles, they are partially powered by batteries and therefore they resemble characteristics of battery electric vehicles (BEVs) such as dependence of fuel economy on ambient temperatures. It is also important to understand how different extent of hybridization (a.k.a., hybridization ratio) affects fuel economy under various driving conditions. In addition, it is of interest to understand how HEVs and PHEVs compare with BEVs at a similar vehicle weight. This study investigated the relationship between vehicle mass and vehicle performance parameters, mainly fuel economy and driving range of PHEVs focused on 2018 and 2019 model years using the test data available from fuel economy website of the US Environmental Protection Agency (EPA). Previous studies relied on modeling to understand mass impact on fuel economy for HEV as there were not enough number of HEVs in the market to draw a trendline at the time. The study also investigated the effect of ambient temperature for HEVs and PHEVs and kinetic energy recovery of the regenerative braking using the vehicle testing data for model year 2013 and 2015 from Idaho National Lab (INL). The current study assesses current state-of-art for PHEVs. It also provides analysis of experimental results for validation of vehicle dynamic and other models for PHEVs and HEVs. Document type: Article