Design and Optimization of Linear Doubly-Fed Induction Machine for Wireless Charging Operation of Novel Vactrain System

Master Thesis (2021)
Author(s)

A. Becetti (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

J. Dong – Mentor (TU Delft - DC systems, Energy conversion & Storage)

P Bauera – Graduation committee member (TU Delft - DC systems, Energy conversion & Storage)

Domenico Lahaye – Graduation committee member (TU Delft - Mathematical Physics)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2021 Belkassem Becetti
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Belkassem Becetti
Graduation Date
29-07-2021
Awarding Institution
Delft University of Technology
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

With the aim to reduce the CO2 emissions in the transportation sector, there have been significant developments in the recent few years where novel ground transport systems operating at airline speeds using all-electric propulsion have emerged to provide a sustainable alternative to classical methods of
transport such as air travel. These novel systems however use sub-systems for suspension and propulsion that produce significant power loss when compared to traditional rail on wheels. Hence, the aim of this project is to investigate a new system proposed in [1] which aims to use the same concept of Hyperloop
involving pods traveling at high speeds in vacuum tubes to minimize drag and thus reduce the energy requirements as well. Unlike Hyperloop, the system aims to use wheels for suspension and a multi-mode linear motor for charging and propulsion where the power supply is integrated into the overall system.

First, an overview of the system is presented before proceeding to the main content of this thesis where the Linear Doubly Fed Induction Machine (LDFIM), the machine intended to perform the charging operation for the vactrain system, is initially designed using an analytical model based on theoretical equations and formulae which is then validated using the Finite Element Method (FEM). Afterwards, the machine is optimized using the Genetic Algorithm (GA) method to enhance its performance. The optimized model is also validated in FEM and all of the results and design parameters for this specific machine are delivered in this report. It is deduced that the LDFIM is capable of performing according to the required performance standards and a sufficiently high efficiency is achieved.

After completing the design of the LDFIM, an outlook on the system’s propulsion is discussed before conducting a benchmarking study where the investigated system is compared to Hyperloop by applying the two concepts in a scenario setting and assessing their performance in a variety of criteria. The results
demonstrate the capability of the investigated system in reducing the energy and material requirements for ultra-high speed travel making it a promising candidate for a future transport system.

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