NTHU-UoL Dual PhD Programme between National Tsing Hua University in Taiwan and the University of Liverpool in the UK is a well-established programme, where students spending 2 years at both institutions. Working with world leading academics and research capabilities the PhD candidates will spend two years in each institution. Upon successful defence of their research work, the candidates will obtain dual PhD degrees.

Applications are invited for a fully funded joint PhD program between the University of Liverpool (UoL), UK and the National Tsing-Hua University (NTHU), Taiwan. The program focuses on locating and sizing electric vehicle (EV) charging stations using multi-stage stochastic optimization. The primary objective is to develop an optimization tool integrated with a spatial model to identify optimal locations for EV charging stations within a region.

Project Background

As part of the global shift towards sustainability, the transportation sector is increasingly adopting electric vehicles (EVs) over traditional vehicles. Despite the growing adoption of EVs, driven by governmental incentives, there is a pressing need to establish sufficient charging infrastructure.

Optimal placement of charging stations is essential, considering factors such as demand, social equity, and integration with transportation networks while discouraging overreliance on private transport. Establishing a robust, equitable, and scalable charging infrastructure is recognised as crucial by many countries. Key considerations in the rollout of charging infrastructure include energy system integration, grid benefits, and minimising pavement clutter. While previous research has explored charging infrastructure from spatial and mathematical optimisation perspectives, a comprehensive approach that considers spatial, energy, and sociodemographic factors simultaneously is lacking.

This project aims to address this gap by developing a tool to assist planners and policymakers in locating EV charging stations based on specified criteria and available data. The research objectives include identifying critical parameters influencing charging station placement, formulating a multi-stage optimisation problem to maximise utilisation and ensure equitable distribution, and creating an interactive tool for stakeholders to visualise optimal charging station locations based on regional needs and constraints. This tool aims to empower local stakeholders to strategically deploy charging infrastructure tailored to their specific contexts, informing local planning and policymaking for the optimal establishment of EV charging infrastructure.

Overview of the PhD program

The successful PhD candidate will spend the first two years at UoL, followed by two years at NTHU. At UoL, the student will join the Department of Civil and Environmental Engineering within the School of Engineering, where they will formulate their research problem and conduct an intensive literature review in the field of EV charging placement studies and operations research methodologies. They will familiarise themselves with the transport network plan and model for the UK and Taiwan, as well as sociodemographic data available at a spatial scale. Additionally, the student will self-train in GIS modelling tools and macroscopic transport modelling tools with guidance from the UoL lead supervisor and is encouraged to take transport-related modules offered at UoL.

Training will be provided to initiate these investigations. At NTHU, the student will join the Department of Industrial Engineering and Engineering Management, undertaking courses in Integer Programming and Network Analysis, Stochastic Optimisation, Nonlinear Programming, and Operations Research. The student will be closely supervised by both lead supervisors throughout the program.

Candidate suitability

This cross-disciplinary project is suitable for candidates with backgrounds in Transportation Engineering, Civil Engineering, Industrial Engineering, Operations Research, or related disciplines. The ideal candidate should have an interest in computational methods and applying these techniques to address complex problems in advanced technologies. Coding skills are highly desirable.

We want all of our staff and Students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We are committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances. For example, If you have a disability you may be entitled to a Disabled Students Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result. We believe everyone deserves an excellent education and encourage students from all backgrounds and personal circumstances to apply.

Applicant Eligibility

Candidates will have, or be due to obtain, a Master’s Degree or equivalent from a reputable University in an appropriate field of Engineering. Exceptional candidates with a First Class Bachelor’s Degree in an appropriate field will also be considered.

Application Process

Candidates wishing to apply should complete the University of Liverpool application form [How to apply for a PhD - University of Liverpool] applying for a PhD in Civil Engineering and uploading: Degree Certificates & Transcripts, an up-to-date CV, a covering letter/personal statement and two academic references.

Please note – all formal applications must be made via the University of Liverpool online application form.

Locating and sizing electric vehicle charging stations through multi-stage stochastic optimisation

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