he digital revolution in the latter part of the twentieth century has resulted in the increased use and development of Cyber-Physical Systems. Two of which are Unmanned Aerial Systems (UAS) and Integrated Vehicle Health Management (IVHM). Both are relatively new areas of interest to academia, military, and commercial organisations. Designing IVHM for a UAS is no easy task – the complexity inherent in UAS, with projects involving multiple partners/organisations; multiple stakeholders are also interested in the IVHM. IVHM needs to justify itself throughout the life of the UAS, and the lack of established knowledge makes it hard to know where to start. The establishment and analysis of requirements for IVHM on UAS is known to be important and costly – and for IVHM a complex one. There are multiple stakeholders to satisfy and ultimately the needs of the customer, all demanding different things from the IVHM, and with limited resources they need to be prioritised. There are also many hindrances to this: differences in language between stakeholders, customers failing to see the benefits, scheduling conflicts, no operational data. The contribution to knowledge in this thesis is the IVHM Requirements Deployment (IVHM-RD) – a method for a designer of UAS IVHM to build a tool which can consolidate and evaluate the various stakeholder’s requirements. When the tool is subsequently populated with knowledge from individual Subject Matter Experts (SMEs), it provides a prioritised set of IVHM requirements. The IVHM-RD has been tested on two design cases and generalised for the use with other designs. Analysis of the process has been conducted and in addition the results of the design cases have been analysed in three ways: how the results relate to each design case, comparison between the two cases, and how much the relationships between requirements are understood. A validation exercise has also been conducted to establish the legitimacy of the IVHM-RD process. This research is likely to have an impact on the elicitation and analysis of IVHM requirements for UAS – and the wider design process of IVHM. The IVHM-RD process should also prove of use to designers of IVHM on other assets. The populations of the design cases also provide information which could be useful to other designer and future research.

The full text will be available at the the end of the embargo period: 29th Jul 2026

Electrical contacts provide a well-proven solution to switching various loads in a wide variety of applications, such as power distribution, control applications, automotive and telecommunications. However, electrical contacts are known for limited reliability due to degradation effects upon the switching contacts due to arcing and fretting. Essentially, the life of the device may be determined by the limited life of the contacts. Failure to trip, spurious tripping and contact welding can, in critical applications such as control systems for avionics and nuclear power application, cause significant costs due to downtime, as well as safety implications. Prognostics provides a way to assess the remaining useful life (RUL) of a component based on its current state of health and its anticipated future usage and operating conditions. In this thesis, the effects of contact wear on a set of electromagnetic relays used in an avionic power controller is examined, and how contact resistance combined with a prognostic approach, can be used to ascertain the RUL of the device. Two methodologies are presented, firstly a Physics based Model (PbM) of the degradation using the predicted material loss due to arc damage. Secondly a computationally efficient technique using posterior degradation data to form a state space model in real time via a Sliding Window Recursive Least Squares (SWRLS) algorithm. Health monitoring using the presented techniques can provide knowledge of impending failure in high reliability applications where the risks associated with loss-of-functionality are too high to endure. The future states of the systems has been estimated based on a Particle and Kalman-filter projection of the models via a Bayesian framework. Performance of the prognostication health management algorithm during the contacts life has been quantified using performance evaluation metrics. Model predictions have been correlated with experimental data. Prognostic metrics including Prognostic Horizon (PH), alpha-Lamda (α-λ), and Relative Accuracy have been used to assess the performance of the damage proxies and a comparison of the two models made.

Yes / Underpinned by a contemporary view of automotive systems as cyber-physical systems, characterised by progressively open architectures increasingly defined by their interaction with the users and the smart environment, this paper provides a critical and up-to-date review of automotive Integrated Vehicle Health Management (IVHM) systems. The paper discusses the challenges with prognostics and intelligent health management of automotive systems, and proposes a high-level framework, referred to as the Automotive Healthcare Analytic Factory, to systematically collect and process heterogeneous data from across the product lifecycle, towards actionable insight for personalised healthcare of systems. / Jaguar Land Rover funded research “Intelligent Personalised Powertrain Healthcare” 2016-2019

This thesis presents a novel hybrid prognostic methodology, integrating physics-based and data-driven prognostic models, to enhance the prognostic accuracy, robustness, and applicability. The presented prognostic methodology integrates the short-term predictions of a physics-based model with the longer term projection of a similarity-based data-driven model, to obtain remaining useful life estimations. The hybrid prognostic methodology has been applied on specific components of two different engineering systems, one which represents accelerated, and the other a nominal degradation process. Clogged filter and fatigue crack propagation failure cases are selected as case studies. An experimental rig has been developed to investigate the accelerated clogging phenomena whereas the publicly available Virkler fatigue crack propagation dataset is chosen after an extensive literature search and dataset analysis. The filter clogging experimental rig is designed to obtain reproducible filter clogging data under different operational profiles. This data is thought to be a good benchmark dataset for prognostic models. The performance of the presented methodology has been evaluated by comparing remaining useful life estimations obtained from both hybrid and individual prognostic models. This comparison has been based on the most recent prognostic evaluation metrics. The results show that the presented methodology improves accuracy, robustness and applicability. The work contained herein is therefore expected to contribute to scientific knowledge as well as industrial technology development.