Pipicelli, Michele (2024) The paths towards the decarbonisation of the transport sector: a multi-level analysis of electrified vehicles. [Tesi di dottorato]

Anteprima

Testo Pipicelli_Michele_36.pdf Download (19MB) | Anteprima

Abstract

Climate change is a present and real problem on a global scale, which requires fast actions to mitigate it. Different solutions can help to achieve this objective, with the reduction of CO2 as one of the most promising. Indeed, international policies have been proposed to address this issue, reducing the carbon intensity of modern technological society. Specifically, this work aims to analyze different vehicle technologies that can reduce the carbon footprint of the transport sector. Electrification, renewable liquid fuels, hydrogen, and driving automation systems are all technologies that can effectively contribute to higher energy efficiency and lower carbon emissions. Assessing all those technologies in a unique global and comprehensive study on the transport sector is somewhat complicated. For this reason, the work is structured in two main parts: the assessment of powertrain technology and the assessment of driving automation systems for different vehicle classes. Instead, the technology combinations are proposed to be analyzed with a specific case study. Regarding powertrains, the impact of different propulsion systems has been analyzed through a properly developed simulation framework evaluating different key performance indicators, including total cost of ownership, operational expenditures, wheel-to-wheel greenhouse gases, energy consumption, recharging time, and vehicle range. The analysis has involved passenger, light commercial, medium-duty, and heavy-duty vehicles. The methodology adopted has allowed us to define thresholds for fuel, electricity, and powertrain costs for which particular vehicular solutions offer better economic indicators. Sensitivity analysis on fuel and electricity emissions factors has allowed the definition of optimal powertrain for each scenario to decarbonize the fleets efficiently. Regarding driving automation systems, autonomous vehicles are promoted to reduce road accidents and improve road safety with a relevant impact on society. Besides social aspects, the driving automation system, exploiting the data gathered by their sensor and intelligent infrastructures, can be used to improve the energy management of the vehicles. This optimization can be made at the single vehicle or fleet levels. Many works have addressed the potential benefits of driving automation systems on vehicle energy efficiency. However, those works usually neglect the energy consumption of the DAS system, focusing only on the powertrain. Through statistical methods and a case study, this work evaluates the net energy efficiency of autonomous vehicles compared to human-driving operated twin vehicles. Statistical results show that for light-duty vehicles, the energy demands of the driving automation system are relevant, and concur to a net worsening of the vehicle energy consumption. The scenario changes, looking to more energy-demanding vehicles, such as medium and heavy-duty trucks, for which no or slight improvement can be expected, respectively. A detailed case studio analysis with a detailed vehicle model has also partially confirmed the light-duty results.

Downloads

Actions (login required)

Modifica documento