Actuator PHM exploiting multi- physics digital twin and machine learning PhD

To ensure safe and efficient operation, electric actuators should be controlled on a suitable operative environment, which includes temperature and pressure as well. This includes:  

1. Having an accurate battery management system (BMS) which mainly rely on the estimation of battery health states including SOC, SOH, RUL and ISC early occurrence is highly required which means, an efficient prognostics and health management (PHM) system. 
2. Isolation and handling actuator faults by incorporating the physics of the motor, the load, and the effect of the servo-controller (for nominal operations, overload faults, and coupling loss faults). 

The outlined project falls within the realm of Systems Engineering and Mechatronics, particularly focusing on the optimization and safety of electric actuator systems. These systems are integral components in a wide variety of applications, from industrial automation and robotics to automotive systems and aerospace. Given the rapid growth of automation and smart technologies, the relevance of this area today is high. As industries increasingly rely on machines and automation to improve efficiency and reduce costs, ensuring the reliable operation of components like electric actuators becomes vital. This is especially true in critical applications where a failure could result in significant financial loss, environmental damage, or harm to human lives. Moreover, the inclusion of advanced battery management and fault detection mechanisms highlights the intersection of this field with the growing trends in energy efficiency and predictive maintenance. By optimizing the management of battery systems (which are pivotal for actuator operation) and incorporating real-time fault detection, the project touches on key aspects of modern engineering practices: energy sustainability, system reliability, and proactive maintenance. Overall, this project is relevant in the context of the ongoing industrial shift towards greater automation and the need for more sophisticated control and management systems that can adapt to complex operational environments while ensuring safety and efficiency. 

The Project Focus/Aim is to develop and implement an advanced control system for electric actuators, ensuring their safe, efficient, and reliable operation in diverse environments. This involves two main goals:  

1. Optimisation of the Battery Management System (BMS): The aim is to implement an accurate BMS that effectively monitors and manages the health states of the battery powering the actuator. This includes ensuring the State of Charge (SOC), State of Health (SOH), Remaining Useful Life (RUL), and Internal Short Circuit (ISC) are within optimal ranges. The system should also incorporate a Prognostics and Health Management (PHM) system for early detection and prediction of potential battery health issues, enhancing the longevity and reliability of the actuator.  
2. Real-time Isolation and Handling of Actuator Faults: The project aims to design a system capable of identifying and managing faults that may occur during the operation of the actuator. This involves understanding the physics of the motor, the load it is handling, and the role of the servo-controller in the system. The focus is on managing different fault scenarios efficiently, including those during nominal operations, during overloads, and coupling loss faults. By promptly isolating and handling these faults, the system can prevent damage or failure of the actuator, ensuring its ongoing performance and safety. 

Cranfield University is wholly postgraduate, and is famous for its applied research in close collaboration with Industry. At Cranfield, the candidate will be based within the Manufacturing theme at the Centre for Digital Engineering and Manufacturing (CDEM). The Centre hosts cutting-edge simulation and visualisation facilities. The student will have access to high-end computers for simulating the complex nature of maintenance.  

The PhD aims to:

1. Enhance Reliability and Longevity: By optimizing the Battery Management System (BMS) and implementing an effective Prognostics and Health Management (PHM) system, the project is expected to significantly enhance the reliability and longevity of electric actuators. Early detection and prediction of potential battery health issues can prevent catastrophic failures, thereby extending the useful life of the actuators.  
2. Improve Safety: The real-time isolation and handling of actuator faults aim to prevent potential damage or failure of the actuator, thereby enhancing its safety. By understanding the physics of the motor, the load, and the servo-controller's role, the project can manage different fault scenarios effectively and maintain the integrity of the actuator even under challenging conditions.  
3. Operational Efficiency: The ability to manage and mitigate faults in real-time means that actuators can maintain optimal performance even when faced with unexpected issues. This ensures continuous and efficient operation, minimizing downtime and maximizing productivity.  
4. Cost Savings: By preventing unexpected failures and extending the life of the actuators, the project can result in significant cost savings. This includes reducing the need for frequent replacements and maintenance, as well as avoiding potential losses due to operational downtime. 

Reasons to complete your PhD at Cranfield University:

1. Opportunity for travel not only in the UK but also internationally, 
2. Applied research, which significant and current challenges around sustainability in through-life engineering,
3. We have allocated funding to enable training through internal and external courses, which will substantially enhance the PhD experience. 

You will gain from the experience in numerous ways, whether it be transferable skills in the technical area of optimisation, or soft skills including presentation skills, project management, and communication skills. There are also numerous employability opportunities that the PhD will offer whether it be in Industry or in Academia.

Entry requirements

 We are inviting applicants with a First or upper Second Class degree equivalent qualification in an engineering background, or an alternative quantitative focused discipline.

Funding

This studentship is open to both UK and International applications. This is a self funded PhD opportunity.

Find out more about tuition fees.

How to apply

If you are eligible to apply for this research opportunity, please complete the online application form.

For further information please contact Dr Samir Khan.

Please bear in mind that the application deadline for this post is 26 March 2025.

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