The main aim of the work is to gain a better insight into the operation of near-future advanced internal combustion engine strategies. Such understanding is vital for the development of high-efficiency, ultra-low-emissions engines to meet environmental regulations. For example, the European automotive manufacturers have committed to reduce fleet average CO2 emissions to 140g/km by 2008, with 120g/km projected by 2012. Hybridized SI-HCCI-SI engine technology is a potential solution towards achieving such targets in improving fuel consumption and developing near-zero emissions vehicles. Such hybridized operation could enable a reduction in UK CO2 levels of ~0.7million metric tons per annum (for a representative 2.0 l gasoline engine size). Furthermore, the benefits of 99% reduction (c.f. SI) in NOx emissions and virtually no soot emissions during HCCI mode of operation can be realised with this technology. In addition to experimental research, computational modelling has been utilized by the research community to gain insight into the transients associated with such a hybridized engine operation. However, the existing models are empirical in nature and rely on profiles from experiments. This may also be the reason for the absence of numerical analysis to investigate the effect of the complex and dynamic transient phenomena on the regulated emissions. The proposed research involves the development of an advanced, predictive phenomenological model to simulate the SI-HCCI-SI engine transients. The model will be validated against measurements and further improved with the help of some new experiments suggested in this proposal. The proposed work comprises of three parts: 1) Development of a novel computational model to account for spontaneous multi point ignition (HCCI-like) as well as premixed flame propagation (SI-like) during the transients. The model includes detailed chemical kinetics description and accounts for inhomogeneities in composition and temperature, thus proving beneficial in understanding the impact of the transient processes on CO, HC and NOx emissions. 2) Understanding transient-like operation by carrying out cost-effective experiments involving operating conditions representative of the complex transient phenomena. These measurements will also be used in validating the formulated model. 3) Model validation against experimental results obtained from fully variable valve timing (FVVT) capable SI-HCCI-SI transient engine operation. Overall, this congruent experimental and modelling approach involves sharing the know-how and expertise between academic research and industrial partners aimed at realising ultra-low emissions engine performance.

Hybrid electric vehicles (HEV) are far more complex than conventional vehicles. There are numerous challenges facing the engineer to optimise the design and choice of system components as well as their control systems. At the component level there is a need to obtain a better understanding of the basic science/physics of new subsystems together with issues of their interconnectivity and overall performance at the system level. The notion of purpose driven models requires models of differing levels of fidelity, e.g. control, diagnostics and prognostics. Whatever the objective of these models, they will differ from detailed models which will provide a greater insight and understanding at the component level. Thus there is a need to develop a systematic approach resulting in a set of guidelines and tools which will be of immense value to the design engineer in terms of best practice. The Fundamental Understanding of Technologies for Ultra Reduced Emission Vehicles (FUTURE) consortium will address the above need for developing tools and methodologies. A systematic and unified approach towards component level modelling will be developed, underpinned by a better understanding of the fundamental science of the essential components of a FUTURE hybrid electrical vehicle. The essential components will include both energy storage devices (fuel cells, batteries and ultra-capacitors) and energy conversion devices (electrical machine drives and power electronics). Detailed mathematical models will be validated against experimental data over their full range of operation, including the extreme limits of performance. Reduced order lumped parameter models are then to be derived and verified against these validated models, with the level of fidelity being defined by the purpose for which the model is to be employed. The work will be carried out via three inter-linked work packages, each having two sub-work packages. WP1 will address the detailed component modelling for the energy storage devices, WP2 will address the detailed component modelling for the energy conversion devices and WP3 will address reduced order modelling and control optimisation. The tasks will be carried out iteratively from initial component level models from WP1 and WP2 to WP3, subsequent reduced order models developed and verified against initial models, and banks of linear-time invariant models developed for piecewise control optimisation. Additionally, models of higher fidelity are to be obtained for the purpose of on-line diagnosis. The higher fidelity models will be able to capture the transient conditions which may contain information on the known failure modes. In addition to optimising the utility of healthy components in their normal operating ranges, to ensure maximum efficiency and reduced costs, further optimisation, particularly at the limits of performance where component stress applied in a controlled manner is considered to be potentially beneficial, the impact of ageing and degradation is to be assessed. Methodologies for prognostics developed in other industry sectors, e.g. aerospace, nuclear, will be reviewed for potential application and/or tailoring for purpose. Models for continuous component monitoring for the purpose of prognosis will differ from those for control and diagnosis, and it is envisaged that other non-parametric feature-based models and techniques for quantification of component life linked to particular use-case scenarios will be required to be derived. All members of the consortia have specific individual roles as well as cross-discipline roles and interconnected collaborative activities. The multi-disciplinary nature of the proposed team will ensure that the outputs and outcomes of this consortia working in close collaboration with an Industrial Advisory Committee will deliver research solutions to the HEV issues identified.

The UK government is determined to address the challenges of tackling climate change and maintaining energy security in a way that minimises costs and maximises benefits to the economy. Among all sources of CO2 emissions in the UK, the energy supply accounts for about 40%, followed by the transport for over 25%. To meet the target of cutting greenhouse gas emissions by 80% by 2050, large proportion of electricity generated from low carbon sources integrated with mass adoption of electric vehicles (EV) offer a great potential. Likewise, the Chinese 12th National Economic and Social Development Five-Year Plan has set the target of 3.5% reduction per unit of GDP in both energy use and carbon dioxide emissions, and identified new energy and clean energy vehicles among the seven priority industries in the next five years from 2012. It is clear that both countries are fully committed to a planned 'decarbonisation' of their respective energy systems. However, both face the challenges of planning and building the suitable infrastructure, and of managing the resources to ensure future power systems operate more reliably, more flexibly, and more economically, by integrating and coordinating the actions of all actors. It has been widely recognized that electric vehicles could both benefit from and help to drive forward the development of smart grids where renewable resources are widely and substantially employed. However, a number of technical challenges are still open for further exploitation. The proposed collaborative interdisciplinary research will investigate and develop an intelligent grid interfaced vehicle eco-charging (iGIVE) system for more reliable, more flexible and efficient, and more environmental friendly smart gird solutions for seamless integration of distributed low-carbon intermittent power generation and large number of EVs. To achieve this, a multilayer hierarchical power and information flow framework for monitoring and optimal control of the EV charging while minimising the volume of information passed to the utility control centers will be investigated first. Within this framework, a variable rate bi-directional high performance EV battery charging unit based on a patented technology will be developed, and battery management and optimal EV charging and discharging dispatching strategies will be investigated. Other issues associated to the charging stations, such as electromagnetic interference and harmonics generation and their impact on environment and electricity grid will also be studied. Finally, simulation platform will be built to investigate the interactions of EV-related different participants and their impact on the grid operations. A test bed to verify the design will be developed and a joint UK-China joint laboratory on smart grid and EV integration will be established, bringing together key academic and industry partners in smart grid and EV from UK and China. Both system operators and EV industry in the UK, China and other parts of the world will benefit considerably from the development of intelligent EV eco-charging systems when a large number of EVs are adopted by the public and greater amounts of renewable power are utilized, as they provide an adaptive and intelligent framework and EV charging systems to economically, efficiently and environment-friendly accommodate charging requirements as well as providing ancillary service to the grid integrated with larger amounts of intermittent renewable energy sources and thereby enable the decarbonisation of the electricity supply industry and the transport sector.

The ability to store and release energy on demand is essential to an energy future that is based on clean, non-polluting and sustainable renewable energy. This includes both electrical and thermal energy and a large number of technologies are being developed to fulfil this need. Energy storage will become a major industry in our century and will employ hundreds of thousands of people globally. Energy storage will be everywhere - in large scale batteries connected to electrical networks, in homes to store energy generated from solar panels and in cars, replacing petrol engines. In order to meet this challenge and to ensure that UK plays an important role in this industry we will form a Centre of Doctoral Training in to train researchers at the highest level to help form and influence the direction of Energy Storage technologies. Our students will receive training in all aspects of energy but concentrating on the core technologies of electrochemical storage (batteries and supercapacitors), mechanical storage, thermal storage and superconducting magnetic energy storage. They will have the opportunity to interact with industrialists and gain experience in running a grid connected Lithium-ion battery. They will also undertake a major three-year research project allowing them to specialise in the topic of their choice.

The Cranfield IMRC vision is to grow the existing world class research activity through the development and interaction between:Manufacturing Technologies and Product/Service Systems that move UK manufacturing up the value chain to provide high added value manufacturing business opportunities.This research vision builds on the existing strengths and expertise at Cranfield and is complementary to the activities at other IMRCs. It represents a unique combination of manufacturing research skills and resource that will address key aspects of the UK's future manufacturing needs. The research is multi-disciplinary and cross-sectoral and is designed to promote knowledge transfer between sectors. To realise this vision the Cranfield IMRC has two interdependent strategic aims which will be pursued simultaneously:1.To produce world/beating process and product technologies in the areas of precision engineering and materials processing.2.To enable the creation and exploitation of these technologies within the context of service/based competitive strategies.