Design of a Fail-Operational Electric Vehicle Propulsion System

he global electric vehicle (EV) market continues to grow rapidly, with over 15 million units sold in 2024 alone. As manufacturers respond with increasingly diverse model ranges, the industry faces critical challenges around energy efficiency, safety, and system reliability, particularly in propulsion systems as electric mobility expands into commercial and public transport sectors. 

​This project aims to develop fault-tolerant propulsion system architectures that enhance operational safety, durability, and consumer confidence in future electric vehicles. It focuses on intelligent fault management through the design of control strategies that support resilience, anomaly detection, and adaptive system responses under varied conditions. ​ 

​The outcome will be a validated framework for intelligent fault-handling, achieved by evaluating proposed architectures across a range of operating scenarios in both nominal and degraded states. This will involve simulation-based modelling using tools such as MATLAB/Simulink for control and system dynamics, and finite element tools (e.g., ANSYS or COMSOL) for structural or electromagnetic analysis where appropriate. AI-based techniques will be applied to implement dynamic threshold setting and improve fault detection and system responsiveness. The findings will support the development of robust, maintainable, and reliable electric vehicle propulsion platforms for future applications. 

The successful applicant will join a vibrant interdisciplinary team and benefit from strong supervisory support. The role will also involve engagement with potential industry stakeholders. This research aligns with BCU’s 2030 strategy on sustainability, climate resilience, and digital innovation. 

This project builds on ongoing research activities and team expertise in Mechatronics, Electrical Drives, and Automotive Engineering. It draws particularly on prior work in high-integrity electromechanical actuation systems and self-reconfigurable architectures developed for aerospace applications. Mathematical modelling and simulation expertise using established platforms will provide a strong methodological foundation. Lessons learned from aerospace design practices will inform the development of a novel fail-operational propulsion system architecture that enhances the reliability and operational longevity of future electric vehicles. 

​The research is expected to produce a validated propulsion system capable of maintaining functional, albeit degraded, performance in the event of system faults. This fail-operational capability introduces a safety mechanism whereby vehicles can continue to a safe location following failure. Such functionality is particularly valuable in both conventional and autonomous EVs, offering improved passenger safety, reduced disruption to traffic, and mitigation of risks to pedestrians and other road users. The system will also enable enhanced fault isolation, maintainability, and resilience under variable operating conditions. 

​The contribution to knowledge lies in translating fail-operational principles, commonly used in aerospace, into the electric vehicle domain. The project introduces a novel framework for intelligent fault handling and adaptive threshold setting using AI techniques, addressing a gap in the current research landscape. These findings will support the advancement of reliable, safety-critical EV systems and contribute to emerging practices in smart mobility. The work also aligns with BCU’s research strategy and national priorities related to sustainability, climate resilience, and digital innovation. 

​The research will set the direction for propulsion architecture in future electric vehicles. It is expected to contribute to both academic and industrial communities through several high-calibre peer-reviewed publications, conference engagement, and a doctoral thesis. It will also support knowledge exchange and strengthen the university’s role in driving innovation in sustainable transport. 

​​Entry Requirements: 

• ​To apply for our Engineering PhD Research Degree you should have, or expect to be awarded, a Master’s degree in a relevant subject area from a British or overseas university.  
• ​Exceptional candidates without a Master’s degree, but holding a first class or upper second class Bachelor’s degree in a relevant subject area, may be considered.  
• ​We also welcome enquiries from potential PhD researchers with appropriate levels of professional experience.  

​Essential Criteria: 

• ​Demonstrated knowledge and interest in electric vehicle technologies, electromechanical systems dynamics, and fault-tolerant design 
• ​Good understanding of classical control theory and its application in real-time or safety-critical systems 
• ​Strong mathematical and analytical skills, particularly in system modelling and simulation 
• ​Practical experience with simulation tools such as MATLAB/Simulink or equivalent platforms for control and system dynamics 
• ​Sound understanding of engineering principles related to propulsion systems, electric drives, or multi-domain dynamic systems 
• ​Ability to work independently, manage time effectively, and engage in collaborative, interdisciplinary research 
• ​Excellent written and verbal communication skills 
• ​Meets the university’s English language requirements (IELTS 6.5 overall with no component below 6.0, or equivalent) 

​Desirable Criteria: 

• ​Experience working in an industrial or R&D environment related to propulsion systems, control, or reliability engineering 
• ​Familiarity with AI or data-driven techniques for modelling, threshold-setting, or control optimisation 
• ​Knowledge of fault detection and isolation (FDI) systems and intelligent control algorithms 
• ​Experience using co-simulation environments or finite element tools such as ANSYS, COMSOL, or similar 
• Understanding of automotive safety standards, system reliability, or fail-operational architectures 
• ​Evidence of relevant project or lab-based work, including simulation, modelling, or prototype validation 
• Willingness to engage with stakeholders and contribute to impact through knowledge exchange and sustainable transport innovation