Nigel Groome Studentship: AI-Enhanced Battery State of Health Estimation Using Ring Probabilistic Logic Neural Networks
PhD
Key facts
Start dates
September 2026
Application deadline
20 April 2026
Location
Course length
Full time: 3 years
School(s)
More details
Eligibility: Home UK/EU and International applicants
Bursary p.a: The stipend is at the UKRI rate (currently £20,780 for the academic year 2025/26)
Fees: University fees at the home rate and bench fees will be met by the University for the 3 years. Visa and associated costs are not funded.
Overview
Accurate battery State of Health (SOH) estimation is vital for electric vehicle safety and longevity. Current models often fail to balance accuracy with computational efficiency. Collaborating with Jaguar Land Rover, this research proposes the Ring Probabilistic Logic Neural Network (RPLNN). Unlike opaque deep learning modules, the RPLNN fuses neural computation with probablilistic logic rules within a ring-based structure. This framework enhances interpretability, data efficiency, and resistance to drift, addressing critical limitations in existing AI-based SOH estimation methods.
Additional details
The studentship requires you to undertake the equivalent of up to 6 hrs of teaching per week on average, during semester time, and to include preparation and marking (but no more than 20 hrs per week), and to participate in a teaching skills course. Teaching, preparation and skills courses would all be without further remuneration.
How to apply
Entry requirements
Essential Criteria
- A Master's degree (or equivalent) in Electrical Engineering, Control Engineering, Mechatronics or Robotics, with a heavy emphasis on dynamic system theory, or closely related discipline
- Strong academic background in applied intelligent control techniques, machine learning or artificial intelligence
- Knowledge of control systems, system modelling, and data-driven modelling approaches
- Proven ability to discretise continuous-time models and implement real-time estimation algorithms
- Experience with MATLAB/Simulink, including Control System Toolbox, System Identification Toolbox, or Deep Learning Toolbox
- Understanding of battery systems, electrochemical energy storage, or battery management systems (BMS)
- Ability to develop and implement algorithms for modelling, estimation, or control applications
- Strong analytical thinking, problem-solving ability, and capability to conduct independent research
- Excellent written and verbal communication skills in English
- Motivation to conduct high-quality research leading to publications in international peer-reviewed journals and conferences
International applications
English language requirements
International/EU applicants must have a valid IELTS Academic test certificate (or equivalent) with an overall minimum score of 6.0 and no score below 5.5 issued in the last 2 years by an approved test centre.
Application process
Apply directly via our application portal, making sure to select the MPhil/PhD in Architecture as your chosen course and using the nalme of the studentship as your title. Please be sure to include the following in your application:
- Contact information of two referees, or full reference letters
- Copies of your previous degree certificates and transcrips
- A scan of your passport
- Evidence of English language proficiency in-line with university requirements (international only)
- A CV and cover letter
- Evidence of ability to cover the fee difference (international only)
Supervisors: Dr Aydin Azizi
External Advisors: Mr Burak Celen and Dr Farhad Salek
Project Contact: Shahab Resalati (sresalati@brookes.ac.uk)
Part time MPhil/PhD study will be exceptionally considered (Home Fee status applicants only)
Tuition fees
Questions about fees?
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