This report presents architectures, designs and chemistries for novel static soluble lead acid batteries, with the objective of producing a lightweight lead acid battery for improved specific energy. The demands for lightweight lead-acid batteries come from an expanding hybrid electric vehicle market demanding improved battery specific energy. There are several avenues for improving battery specific energy; the main two are improved active material utilisation efficiency and grid weight reduction. Both of these have been focuses of this project. Two approaches have been taken in this project, the first is focussed on the electrode design. Design modifications have been achieved by using novel grid materials to reduce weight and novel electrode designs to improve active material utilisation. Battery electrodes were built from titanium and the active material was applied as a thin film of lead. Characterisation of lead coatings on several material geometries under different plating regimes was conducted. A novel thin-film active material battery was designed, built and tested satisfactorily to industrial standards. The second battery system being investigated has the active materials solvated in the methanesulphonic acid electrolyte during the discharged state. Due to the high solubility of lead in this Pb-CH3SO3H electrolyte, lead-acid batteries with this chemistry have a theoretical specific energy of 35.7 Ah l-1. This compares favourably with the specific energy for a conventional spiral wound VRLA battery at 44.4 Ah l-1. These soluble lead acid batteries operate by a mechanism whereby cycling is stripping and plating lead and lead dioxide onto the electrodes. Active material utilisation in this type of lead-acid battery is not limited in the same way as conventional lead-acid batteries, as the discharge product is not electrically insulating, as is lead sulphate. The operation mechanism was improved by using additives in the electrolyte to maintain a quality deposit and preserve charge efficiency, voltage efficiency and active mass utilisation. In addition, the use of a separator membrane and novel carbon-polymer electrodes improved battery performance further. The behaviour of a static soluble lead acid battery during cycling with and without additives and a cell membrane is characterised and the results are used to develop a 6 V battery. The results of the 6 V battery cycling under HEV simulated cycling are presented and discussed.

The battery in an EV is designed according to a power to energy ratio and is a trade-off in the design of the pack. It also suffers from effects such as rate capacity effect, ripple effects and inefficiency under charging. These effects result in losses through which the capacity and life span of the batteries are compromised affecting range and drivability. In this thesis a novel development path resulting in a novel Power and Energy Management Strategy (PEMS) is presented. The effects of (dis)charging a battery are researched and converted to an energy optimisation formula and result in reduced power demand for the converter which reduces weight. The resulting Power Management Strategy (PMS) aims to recover energy more efficiently into UC while responding fast to a change in demand. The effects of converters on the battery current ripple are researched and discussed, resulting in an optimal topology layout, improved battery life and reduced losses. Through the use of Markov Chain analysis and a newly derived Bias function a predictive Energy Management Strategy (EMS) is developed which is practical to use in EVs. This resulted in a PEMS which because of the fast PMS results in a fast response time. The use of Markov Chain results in predictive EMS and improves the efficiency of the energy sources and allows the design to be reduced in size. Through the design methodology used the parallel topology (the battery converter parallel to the UC Module) was rated preferred choice over battery only and battery with UC Module. The rating was based on capacity, ripple control, weight, 10 year cost, potential for motor controller efficiency improvement, range and efficiency. v The combination of method and PEMS resulted in an improved life expectancy of the pack to over 10 year (up from 7) while increasing range and without sacrificing drivability.

Eco-urban electric cars (EC) are superior to conventional cars in terms of the operation cost and carbon footprint. However, the performance of EC in terms of their maximum speed and power, initial and maintenance cost and reliability in the available power is lower than conventional cars. The reliability in available energy can be viewed as the main concerns when comparing EC to conventional cars. Reliability in available energy is highly dependent upon the efficiency of the power system as well as the type and size of batteries. Type and size of batteries have a significant effect on the maintenance cost as well as the initial cost. This thesis is focused on two aspects of the research in electric cars, namely, (i) selection and size optimisation of components, and (ii) improving the reliability of the available energy. Traditionally, a robust design approach is adopted in design of the power system of cars. This is mainly aimed at providing the user with the luxury of using the car wherever there is a suitable road and whenever they want to use the car. This flexibility, however, comes with the price of heavier and more expensive power systems. By incorporating data on the dominant usage of an EC and adopting a deterministic design and optimisation method more cost-effective power systems, more compatible with the usage can be obtained. In this study, a power system simulation tool is developed. Using the simulation tool, the performance of the power system components can be analysed for different usage scenarios. Case studies are conducted. Each case is based on a dominant usage defined for a two-person EC driven in Kayseri city in Turkey. For each case, the best power system configuration is obtained. Another original contribution of this thesis is in the context of the reliability of the available energy, by providing a decision support system - a route planning advisor - that helps the user to select the most suitable route in terms of a variety of criteria both conventional, such as travelling time and travelling distance, as well as EC-related such as, available power, vicinity to a charging station. The optimiser of the developed multi criteria route planning advisor (MCRPA) tool is based on a robust hybrid Dijkstra - A* - NSGA-II algorithm. MCRPA incorporates information on EC characteristics (such as power system, aerodynamic shape, weight), city characteristics (current traffic flows, road types, speed limits, altitude, whether conditions), and city charging stations characteristics (capacity, charging level, crowding density). Carrying out case studies, the efficiency and performance of the MCRPA is evaluated.

More-electric aircraft have been the focus of considerable development in recent years. Increased utilisation of electrical systems on-board the latest generation of aircraft has seen an increase in fuel efficiency, through improved electrical derivation from the gas turbine engine and weight savings from the replacement of mechanical and hydraulic transmission systems. The advancement of power electronic and DC breaker devices has led to the reconsideration of DC power distribution systems for standalone networks. Aircraft can benefit from this through the reduced transmission losses, improved controllability and intelligent networking.Through the use of a multiphase synchronous generator, connected to a diode rectifier, a standalone DC network capable of providing power with redundancy can be produced. The aim of this research project is to investigate the effects that phase number, connection topology and winding pitch have on the behaviour of an AC generator connected to a passive diode rectifier. This thesis develops the methodology for determining the number of phases and the topology of the generator. Static and dynamic modelling is conducted through the use of computer finite element modelling and circuit simulation. The dynamic circuit simulation model is configured using parameters obtained from experimental data. The experimental test-rig, which is constructed to be reconfigurable in phase number, connection topology and winding pitch, is used to validate the simulation and provide detailed results on the steady-state operation of the generator-rectifier system. Open-circuit faults are introduced to assess the fault tolerance of the system and the effects of the inherent phase redundancy on the generator performance.

Vibration isolation is an important requirement for many engineering systems. In particular, in the context of vibration isolation for light-weight automotive vehicles that exhibit wide variation in sprung mass, several limitations are associated with passive isolation systems. Such passive systems cannot obtain wide variations in the suspension parameters which required for reliable performance. While these technical drawbacks can be overcome by implementing active systems, these are associated with an increase in complexity, cost and potentially negative impact on reliability. In this context, composite fluid materials, which combine different components in a way that enhances an isolator’s performance, could represent a possible alternative approach with promising potential. However, the application of composite fluid materials for vibration isolations is still an underdeveloped area. The composite fluid material that is the subject of this research is referred to as Foam Filled Fluid (FFFluid). It is composed of three components, namely compressible (foam) particles, a viscous carrier fluid and a packaging material. This composite material has recently been investigated for applications in impact energy management but is not understood in anti-vibration application. Thus, the objective of this research was to understand the mechanisms, to characterise design parameters and to predict the responses of such composite material when used for vibration isolation systems. A theoretical understanding of the working principle for a FFFluid-based isolator was first achieved. Then, experimental work was conducted to assess the performance of such a device. The characterisation of the composite material was carried out via a systematic study; this study was then validated by an experimental -ivprogramme based on a Design of Experiments approach. Finally, empirical prediction models of the system were extracted by analysing the obtained data statistically. The conducted research shows that a FFFluid-based isolator possesses several advantages over commonly used existing solutions. Its main benefit is the potential capability of adjusting stiffness and damping coefficients by changing one component or more of this composite material. It was shown that increasing the volume of the composite material led to increased stiffness and damping coefficients. Besides, increasing the ratio of fluid in the mixture caused to increase the stiffness coefficient. The most important parameters that have an influence on the response of FFFluid were: the size of foam, the ratio of foam to fluid, volume of the material and fluid viscosity. Therefore, empirical models were established based on these parameters, the accuracy of these models were 85% Through the study of this novel material, the application of the FFFluid concept as a vibration isolator solution was studied. In practice, the design parameters of such a system could be adjusted through a control mechanism, to provide an adaptive solution. This could represent a suitable means to bridge the gap between passive and active suspension system in the context of vibration isolation for light-weight vehicles.

The European Union (EU) aims to reduce overall carbon dioxide emissions at least 80% by 2050. For road transport, this involves at least a 95% reduction target for 2050, compared to 1990 levels. Most commentators believe that achieving this target requires a transition from internal combustion engine vehicles (ICEVs) to battery electric vehicles (BEVs). However, such transition demands fundamental changes in the whole automotive value chain. This research argues that the required changes in the automotive value chain might be achieved by i) an industrial structure enabling the mass production of BEVs ii) understanding and supporting the development of newcomers that are in the majority of micro, small and medium sized enterprises (SMEs) in emerging BEV sector and iii) use of target instruments by governments to accelerate the development of BEV value chain and industrial structure. Based on this strategy, three stage study was performed. This involved i) exploring the present BEV industry structure and compatible future structure ii) exploring the approach of SMEs to emerging BEV sector to understand and support these actors and iii) developing and trialling a novel framework enabling the pre-implementation analysis of putative policy measures. In each stage of the research, different methodologies were used. This included an analysis of supply chain for BEVs in North-West Europe (NWE); semi-structured in-depth interviews with SMEs throughout NWE and development and application of an “adaptive neuro-fuzzy inference system” (ANFIS) based framework. This study contributes to the body of knowledge by investigating the implications of BEVs on the supply chains and exploring what competences and capacities might be needed for mass production of BEVs in Europe. Secondly, this research proposed that economic growth and emission reduction targets established in the existing economic strategy of the EU (Europe 2020 strategy) might be achieved, and a significant contribution to achieve the 2050 emission reduction target might be made by supporting SME development. Support areas for SMEs were also identified. Lastly, to support national governments in making informed decisions, an ANFIS framework providing an ex-ante impact of various innovation decisions was offered.

Although hybrid electric vehicles (HEVs) generally improve fuel economy (FE) compared to conventional vehicles, evidence of higher FE variability in HEVs compared to conventional vehicles indicates that apart from the improvement in FE, the reduction of FE variability is also of significant importance for HEVs. Over the years research on how to optimise powertrain component sizes of HEVs has generally focused on improving FE over a given driving pattern; FE variability over a realistic range of driving patterns has generally been overlooked, and this can lead to FE benefits of HEVs not being fully realised in real-world usage. How to reduce the FE variability in HEVs due to variation in driving patterns through the optimisation of powertrain component sizes is considered as the research question. This research proposes a new methodology in which powertrain components are optimised over a range of driving patterns representing different traffic conditions and driving styles simultaneously. This improves upon the traditional methodology followed in the reviewed literature, where an optimisation is performed for each individual driving pattern. An analysis shows that the traditional methodology could produce around 20% FE variability due to variation in driving patterns. This study considers a computer simulation model of a series-parallel Toyota Prius HEV for the investigation. Four powertrain components, namely, internal combustion engine, generator, motor, and battery of the Toyota Prius are optimised for FE using a genetic algorithm. For both the proposed and traditional methodologies, the powertrain components are optimised based on 5 standard driving patterns representing different traffic conditions and driving styles. During the optimisation, the proposed methodology considers all the 5 driving patterns simultaneously, whereas the traditional methodology considers each driving pattern separately. The optimum designs of both the methodologies and the simulation model of the Toyota Prius which is the benchmark vehicle for this study are evaluated for FE over the aforementioned 5 standard driving patterns and also 10 real-world driving patterns of a predefined route consisting of urban and highway driving patterns. The proposed methodology provides a single optimum design over the 5 standard driving patterns, whereas the traditional methodology provides 5 different optimum designs, one for each driving pattern. The single optimum design produced by the proposed methodology is independent of the sequence of driving patterns. The proposed methodology reduces FE variability by 5.3% and up to 48.9% with comparable average FE compared to the Toyota Prius and traditional methodology, respectively over the 10 real-world driving patterns, whereas none of the optimum designs of the traditional methodology is able to reduce FE variability compared to the Toyota Prius. This research provides a promising direction to address customer concerns related to FE in the real-world and improves understanding of the effect of driving patterns on the design of powertrain components.

The energy management system (EMS) of hybrid electric vehicle controls the operation of two power plants; electric machine/battery and typically engine. Hence the fuel economy and emissions of hybrid vehicles strongly depend on the EMS. It is known that considering the future trip demand in devising an EMS control strategy enhance the vehicle and component performances. However existing such acausal EMS cannot be used in real time and would require prior knowledge of the trip vehicle speed profile (trip demand). Therefore rule based EMS which considers instantaneous trip demand in devising a control strategy are used. Such causal EMS are real time capable and simple in design. However rule based EMS are tuned for a set of driving cycles and hence their performance is vulnerable in real world driving. The research question is “How to design a real time capable acausal EMS for a plug in hybrid electric vehicle (PHEV) that can adapt to the uncertainties of real world driving”. In the research, the design and evaluation of a proposed EMS to deal and demonstrate in scenarios expected in real world driving respectively were considered. The proposed rule based acausal EMS is formulated over the estimated vehicle trip energy and driving information. Vehicle trip energy is the electric (battery) energy required to meet the trip demand estimated using known driving information. Driving information that can be considered are driver style, route distance and road types like urban and extra urban, with traffic as a sub function. Unlike vehicle speed, vehicle trip energy is shown to be relatively less dynamic in real world driving. For the proposed EMS evaluation, a commonly used parallel PHEV model was simulated. For driving information EMS was not integrated to a navigation system but manually defined. Evaluation studies were done for a driver, and traffic was not considered for simplicity. In the thesis, vehicle performance and credentials for real world applicability (real time capability and adaptability) of the proposed acausal EMS are demonstrated for various scenarios in real world driving; varied initial SOC, sequence of road types, trip distance and trip energy estimation. Over the New European Driving Cycle (NEDC) the proposed EMS vehicle performance is compared to a conventional rule based EMS. The proposed EMS fuel economy improvement is up to 11% with 5 times fewer number of engine stop-starts. Similarly in the validation study, with no prior knowledge of trip vehicle speed profile, the fuel economy improvement is up to 29% with 7 times fewer number of engine stop-starts. The simulation duration of the proposed EMS is as good as conventional rule based EMS. Hence the proposed EMS is potentially real time capable. The proposed EMS can adapt to a wide variation in trip energy (±15%) estimation and still perform better than the conventional rule based EMS. The proposed EMS can tolerate variation in trip demand estimation and no prior knowledge of trip vehicle speed profile is required, unlike other acausal EMS studies in the literature. A new PHEV EMS has been formulated. Through simulation it has been seen to deliver benefit in vehicle performance and real world applicability for varied scenarios as expected in real world driving. The key new step was to use vehicle trip energy in the formulation, which enabled rule based EMS to be acausal and potentially real time capable.

The more electric aircraft initative results in significant challenges in the design of aircraft electrical power systems. Different power system architectures are currently being studied by the engineering community. In this thesis, a promising single DC bus-based, multiple-source multiple-load power system is investigated in terms of power management and stability. Due to its inherent modularity and ease of implementation, droop control, as a decentralised control method, has been widely used to cope with power sharing among parallel sources in the studied architecture. The thesis proposes a comparative study of different droop control approaches by focusing on steady-state power sharing performance and stability. • Different droop control methods may lead to different stability margins. Until now, the effect of different droop control schemes on system stability has not been fully investigated. The thesis presents the control scheme for current-mode and voltage-mode systems, derives the corresponding output impedance of the source subsystem and analyses the stability of the power system. Based on the developed mathematical model, comprehensive modal analysis of the power system is performed. • A generalised analytical impedance analysis is extended to a multi-source multi-load power system. To facilitate the analysis, the thesis proposes the concept of “global droop gain” as an important factor to determine the V-I bus characteristic and the stability behaviour of a parallel sources based DC system. • Considering the tradeoff between voltage regulation and power sharing accuracy in droop control, this thesis proposes an improved voltage regulation method in multi-source based DC electrical power system. Due to the absence of additional controllers or communication lines, the proposed approach can be relatively easily implemented in a small scale DC electrical power system. The proposed approach effectively improves the load sharing accuracy under high droop gain circumstances with consideration of cable impedance. Optimal droop gain settings are investigated and the selection of individual droop gains has been described in order to reduce the distribution losses. Finally, the above-mentioned analytical results are confirmed by time-domain simulations and experimental results.

Fuel cell vehicles (FCVs), are one possible solution to address transportation-related climate change, urban air pollution and fossil fuel resource depletion. To solve these issues they need to displace internal combustion engine vehicles (ICEVs), the aim of this thesis is to understand whether FCVs can achieve this. First case studies of successful historical innovations are explored. Second the consumer adoption of battery electric vehicles (BEVs) is studied in detail by using questionnaire surveys and in-depth interviews. Finally, consumer attitudes and perceptions towards FCVs are investigated by conducting in-depth interviews and a FCV trial. From all of these results this thesis finds that FCVs have fewer benefits as perceived by consumers compared to BEVs and ICEVs. This means that consumers may preferentially adopt BEVs and will not be attracted to FCVs. This thesis makes recommendations on how to improve the attributes of FCVs so that they have more benefits for consumers. These efforts would increase the likelihood of consumers adopting FCVs. However, this thesis suggests that the adoption of FCVs still looks unlikely and that fuel cell (FC) stakeholders should seek to concentrate their efforts towards applications of FCs that have viable market entry potential.