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The urge to limit the environmental impacts of human activities within the safe operating space of planetary boundaries to save the Earth is scientifically and politically agreed upon. Based on the Paris agreement, Science-Based Targets (SBTs) are set as Environmental Impact (EI) targets for companies to help them operate within the planetary boundaries. This research aims to develop a dynamic decision support tool for decision making on strategic directions of product families that satisfy not only their profit targets but also their environmental impact targets (SBTs). The proposed methodology applies a suggested framework to assess the Future-oriented Environmental Impact of product families, including a technology prediction model (logistic model) to capture market changes and the consequences of market changes on the EIs of product families. The proposed methodology also includes a Total Profit model and optimisation model (genetic algorithm) to allocate SBTs to product families. Moreover, the application of two suggested matrices, including relative Future-oriented Environmental Impact – Total Profit matrix and the Environmental Impact Reduction Requirement ratio – Total Profit matrix, offers strategic directions to product families towards operationalising SBTs.

Although magnetic gears are more expensive and larger than mechanical gears for a given power rating, they are more efficient. They also offer the advantage of physical separation between the driving and driven shafts which can be in different environments, e.g., in water and in air. Recent research has focused on rotary magnetic gears, with limited work on linear to rotary and vice versa motion conversions, which is desirable in many applications such as wave energy harvesting. This thesis focuses on the development of the theory and design optimisation of a novel linear-rotary magnetic gear derived from a variable reluctance permanent magnet (transverse-flux) rotational machine topology. The configuration of a linear to rotary magnetic gear is developed and discussed. A design optimisation methodology is implemented based on finite element analysis. Using this methodology, optimal proportions and dimensions of a linear to rotary magnetic gear demonstrator are determined. It is shown that increasing the magnet thickness results in the increase transmitted torque, but with diminishing returns. The optimal results showed that the maximum torque density obtained about 11.3 kNm/m³. The proposed design methodology is successfully applied to the design of a two-pole (on the rotor) magnetic gear. A demonstrator is built and successfully tested, and theoretical predictions are validated. Based on the demonstrator in this study, the use of a linear-rotary magnetic gear for applications such as wave energy harvesting looks promising.

This thesis is mainly concerned with the modelling of an electromagnetic regenerative shock absorber with mechanical motion rectifier (MMR), and its performance evaluation when it is implemented in the suspension of a road vehicle. Unlike a conventional regenerative shock absorber, the inclusion of a sprag-clutch within the MMR module enables the conversion of bi-directional rotational motion into unidirectional rotary input to the coupled electromagnetic generator. Previous studies have shown that the dynamics of a regenerative shock absorber with MMR can be modelled as a piecewise linear system produced by the engagement and disengagement of sprag-clutches within the MMR. It is seen that the MMR based system potentially works as a switchable inerter in parallel with a switchable damper. To characterise the proposed energy harvesting technique, the system is initially discussed when one terminal of the design is blocked, which allows further validations through experiments. In order to comprehensively study dynamics of MMR system, its energy harvesting as well as mechanical power flow performance are evaluated. Additionally, an analogy between the electrical and mechanical active and reactive power flow, using forcecurrent analogy is carried out. This allows better understanding of the power transmission between sub-systems. Moreover, the output of a conventional regenerative shock absorber is generally coupled with an electrical rectifier to convert the AC voltage signal to DC signal for either energy storage or charging electronic devices. In this work, to justify the usage of each rectifier, the electrical rectifier-based regenerative shock absorber is studied in both electrical and mechanical systems. The discussion is further extended to compare performances between electrical rectifiers and MMR in different scenarios. It is shown that MMR is able to offer much superior performance than electrical rectifiers, typically for lower power application. To validate theoretical predictions, the MMR based regenerative shock absorber is tested in a hydraulic Instron machine. A dynamic model of the proposed design is implemented, and its parameters are estimated from the measured data. In order to establish whether MMR allows acceptable energy harvesting performance when incorporated into the suspension of road vehicles, the first step is to investigate the characteristics of the vibration environment. By using the concept of mechanical impedance and mobility, dynamics of the vibration source is studied when the regenerative shock absorber is incorporated into a road vehicle. According to the vibration source characteristic results, the implementation of the MMR based regenerative shock absorber in the suspension system of road vehicles is discussed. The result shows that MMR enables better performance under certain conditions, but it results in a high jerk motion (excessive change of acceleration) as a trade-off. Finally, the procedure for the design of a mechanical motion rectified regenerative shock absorber for a road vehicle suspension system is presented. The proposed design guidelines enable a designer to select desirable parameters for the regenerative shock absorber based on the system constraints and the application environment.

The thesis is concerned with a small-scale compressed air energy storage (SS-CAES) system. Although these systems have relatively low energy density, they offer advantages of low environmental impact and ease of maintenance. The thesis focuses on solving a number of commonly known problems related to the perturb and observe (P&O) maximum power point tracking (MPPT) system for SS-CAES, including confusion under input power fluctuation conditions and operating point dither. A test rig was designed and built to be used for validation of the theoretical work. The rig comprised an air motor driving a permanent magnet DC generator whose power output is controlled by a buck converter. A speed control system was designed and implemented using a dSPACE controller. This enabled fast convergence of MPPT. Four MPPT systems were investigated. In the first system, the air motor characteristics were used to determine the operating speed corresponding to MPP for a given pressure. This was compared to a maximum efficiency point tracking (MEPT) system. Operating at the maximum power point resulted in 1% loss of efficiency compared to operating at the maximum efficiency point. But MPPT does not require an accurate model of the system that is needed for MEPT, which also requires more sensors. The second system that was investigated uses a hybrid MPPT approach that did not require a prior knowledge system model. It used the rate of change of power output with respect to the duty cycle of the buck converter as well as the change in duty cycle to avoid confusion under input power fluctuations. It also used a fine speed step in the vicinity of the MPP and a coarse speed step when the operating point was far from the MPP. Both simulation and experimental results demonstrate the efficiency of this proposed system. The third P&O MPPT system used a fuzzy logic approach which avoided confusion and eliminated operating point dither. This system was also implemented experimentally. A speed control system improved the controllable speed-range by using a buck-boost converter instead. The last MPPT system employed a hybrid P&O and incremental inductance (INC) approach to avoid confusion and eliminate operating point dither. The simulation results validate the design. Although the focus of the work is on SS-CAES, the results are generic in nature and could be applied to MPPT of other systems such as PV and wind turbine.

Sleep is an important part of everyday life. It directly affects daytime cognition and general performance. In children, sleep is a crucial requirement for growth and learning and lack of sleep may manifest itself as a long lasting developmental deficit. Sleep disorders which disrupt the normal continuity of sleep therefore benefit from early identification and treatment. A common cause of sleep disruption is sleep disordered breathing which can be associated with frequent arousals from sleep. Many relevant areas of sleep research continue to generate new and interesting findings utilising biosignals such as EEGs. Respiratory cycle related EEG change (RCREC) is a good example of this. The method for quantification of RCREC relies on the appropriate application of signal processing and the signals involved in the procedure are polysomnographic. Furthermore, RCREC is thought to reflect morbid micro-arousals in sleep and is hence also of clinical importance. Given that the field of RCREC research is a recently established one, there is much room for constructive investigation. The current state of RCREC research is therefore expanded in this thesis. The method for calculation of respiratory cycle related EEG change (RCREC) is replicated and expanded in this project. Shortcomings of the method have been identified and accounted for where appropriate. In particular, the sensitivity of RCREC to airflow signal segmentation is addressed and alternative segmentation approaches are suggested. The general influence of airflow segmentation on RCREC is investigated and a mathematical explanation for RCREC sensitivity is given. Additionally, the ability of RCREC related parameters to predict daytime cognitive functions is assessed. Results suggest that RCREC parameters are capable of predicting quality of episodic memory, power (speed) of attention and internal processing speed.