Accepting PhD Students

    PhD projects

    Coventry University Trailblazers PhD studentship: https://www.coventry.ac.uk/research/research-opportunities/research-students/research-studentships/new-painternal-temperature-sensing-towards-advanced-thermal-management-for-lithium-ion-batteriesge/

    He also welcomes discussions from prospective students and researchers interested in joining his research group. Please contact him (haijun.ruan@coventry.ac.uk).

    Willing to speak to media

    Calculated based on number of publications stored in Pure and citations from Scopus
    20142024

    Research activity per year

    Personal profile

    Biography

    Dr. Haijun Ruan is Assistant Professor of Battery Systems at Coventry University and Visiting Researcher at Imperial College London. He works with Dr. Taz Amietszajew, Prof. Yue Guo, Dr. Cheng Zhang, and Prof. Rohit Bhagat on multiple research projects at Centre for Advanced Low Carbon Propulsion Systems (C-ALPS) at Coventry University.

    He obtained the PhD (2019) and Bachelor (2014) degrees in electrical engineering at Beijing Jiaotong University, China. During his PhD period, he was a visiting student researcher with Purdue University, West Lafayette, USA, in 2018. His PhD research activities mainly focused on the modeling, low-temperature heating, and charging for lithium-ion batteries in electric vehicles and energy storage systems. He got Merit Student of Beijing (2014), National Scholarship (2013, 2014, 2016, and 2018), and Zhixing scholarship (top scholarship for postgraduate students at Beijing Jiaotong University, 2019).

    In early 2020, he came to the UK to join the University of Southampton as a Research Fellow. In Aug. 2020, he joined the Dyson School of Design Engineering as a Research Associate, working with Dr. Billy Wu, Prof. Gregory Offer, and Dr. Huizhi Wang on multiple research projects at Electrochemical Science & Engineering (ESE) group at Imperial College London. He was supported by the Faraday Institution Industry Fellowship, which allowed him to translate his work on battery diagnostics and control into real-world applications, with the goal of extending battery lifetime. 

    Research Interests

    Dr. Haijun Ruan focuses on lithium-ion battery, AI/machine learning, and fuel cells, including:

    • Modelling (Electrical, Electrochemical, Thermal & Degradation)
    • Thermal management (Preheating, & Cooling)
    • Fast charging
    • Diagnostics & Prognostics
    • Lifetime extension (Derating)
    • Digital twin
    • Smart batteries

    He sits on the editorial board of the Journal of Power and Energy and the topical advisory panel of the World Electric Vehicle Journal. He acted as the guest editor for several journals, such as Frontiers in Energy Research, Energies, and World Electric Vehicle Journal.

    Vision Statement

    Dr. Haijun Ruan aims to conduct energy storage research from the fundamental science to integration and systems engineering, aiming at investigating the problems that tend to emerge in real-world applications

    Expertise related to UN Sustainable Development Goals

    In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

    • SDG 7 - Affordable and Clean Energy
    • SDG 11 - Sustainable Cities and Communities
    • SDG 13 - Climate Action

    Education/Academic qualification

    Electrical Engineering, Doctorate, Optimal heating and charging methods for lithium-ion batteries under the low-temperature environment , Beijing Jiaotong University

    20142019

    Award Date: 9 Oct 2019

    External positions

    Visiting Researcher, Imperial College London

    Mar 2023 → …

    Research Associate, Imperial College London

    Aug 2020Feb 2023

    Research Fellow, University of Southampton

    Feb 2020Aug 2020

    Keywords

    • TL Motor vehicles. Aeronautics. Astronautics
    • Electric Vehicles
    • Lithium ion battery
    • TK Electrical engineering. Electronics Nuclear engineering
    • Energy systems
    • TA Engineering (General). Civil engineering (General)
    • Artificial Intelligence
    • Machine Learning
    • Deep learning

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