Modeling, Optimization and Analysis of Electromobility Systems
Abstract: Due to an increase in environmental awareness and an improved understanding on the impact of human activity on our planet’s climate, there is a strong desire both from governments and the general public to reduce harmful pollution and emissions. This requires action on different fronts, like decarbonizing electricity generation, industrial activity and not least the transport sector. This thesis aims to contribute to the development of a sustainable road transport system. There are several technologies that could achieve this goal, but the scope of this work is limited to automotive electrification in the form of hybrid and battery electric vehicles. Such vehicles currently seem to be the most promising technology, having a larger market share than e.g fuel cell electric vehicles. In order to increase the pace of automotive electrification it is necessary to understand the factors that are currently hindering its adoption. First, the higher cost of electrified vehicles when compared with their conventional counterpart is seen by most potential buyers as their main drawback, despite lower operating and maintenance costs. Second, their limited range and long recharging times cause range anxiety on the drivers and generate concerns over the capabilities of the vehicles to provide the expected service and level of convenience. Finally, the lack of charging infrastructure poses a challenge for potential users.In order to develop an understanding on how to address these issues, the present work takes a holistic approach that starts with the development of performance and cost models for the main components required in an electromobility system. These models are used to optimize the design of an electric powertrain for passenger vehicles. Three electrical machine topologies and two powertrain concepts are considered in this optimization. The results point out that significant cost benefits can be obtained from an increase in the top speed of the electric traction machine as well as the addition of a second speed to the transmission. Additionally, the developed methodology allows exploring a large space of search in a way that reduces development times and associated costs.Moving the focus to a higher level of abstraction, the described models are used to analyze the implications of deploying alternative forms of charging infrastructures in a national context. This analysis shows that a large deployment of a dynamic charging infrastructure accessible by both passenger and commercial vehicles significantly reduces the societal cost of electrification. This is due to the possibility of reducing the required battery capacity on-board the vehicles without affecting their driving range.
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