Despite of the fact that electrical cars are under development and have the potential to provide alternatives for short distance light duty transport, the internal combustion engine will continue to be the main power unit in vehicles for several decades to come. Compared with extensive research on combustion and after-treatment systems, little work has been completed with respect to engine system control optimisation, leaving considerable room to improve fuel economy and lower emissions. Current engine calibration process relies on deriving static tabular relationships and the corresponding values between each calibrated engine operating point, with closed-loop feedback control to adjust the settings accordingly for air-fuel ratio control in real engine operation so as to meet the performance targets and emissions legislation. Such a widely adopted method, however, is not efficient in achieving the best fuel economy of the vehicle due to the constraints in the time duration and cost of engine-bed based calibration. Environmental conditions changes, the time required for the closed-loop control to respond, cycle-by-cycle variations, and cylinder-to-cylinder variations make the current engine control impossible to handle the the optimisation of the engine functionalities. The development trend for future engines is towards an on-board intelligence for control and calibration and some research activities for the development of model based control systems are reported in literature. However, feasible strategies to control the engine operation cycle-by-cycle and cylinder-by-cylinder are not yet available. Expanding the work of the applicants in the related areas for many years, the overall Goal of this project is to use a combination of joint efforts from 3 research groups with expertise of engine technology, control technology and computing algorithm in order to develop and test a new engine control and calibration methodology with on-line intelligence built in. This overall goal will be achieved through realising the following objectives: (1) To develop a full real-time multi-cylinder engine model for cylinder-resolved-control purpose (2) To develop a novel engine control strategy involving optimization of control points and control point locations, and multi-objective evaluation of test cycle performance (3) To develop dynamic multi-objective evolutionary algorithms for online engine control optimization (4) To demonstrate the implementation of the engine control models initially on Hardware-in-the-Loop (HIL) dSPACE system and then further rapid prototyping on a test engine. (5) To compare the engine performance using the new techniques with traditional calibration and control approaches, and demonstrate improvements in terms of engine output, fuel consumption, and emissions. The new engine control methodology will be evaluated on a new Jaguar gasoline direct injection (GDI) engine model.

Carbon anodes for Li-ion batteries (LIBs) are regarded as one limiting factor preventing Li-ion batteries from being a viable option for transport applications (which require higher capacity for extended driving ranges) or grid storage applications (which require long cycle life). Compared to carbon, silicon has a much higher energy density and has been the focus of considerable research effort in recent years, stimulating the formation of high-profile, high-investment university spin-out companies such as Amprius and Nexeon. Silicon is the second most abundant element in the earth's crust and is thus a sustainable battery material candidate from a cost and availability perspective. However, despite its desirable properties for Li-ion batteries, it is also renowned for its drawbacks, namely large volume expansion, pulverisation and continued lithium loss through chemical reactions with the electrolyte (which the lithium ions diffuse in). Such phenomena have hindered the successful widespread uptake of this material in commercial Li-ion batteries, despite the myriad of global research groups working on finding ways to make it viable, e.g. by nano-structuring. Project AMorpheuS presents an alternative way to fabricate Si anodes that does not rely on complex, costly nanostructuring or attempting to control electrode architectures. The approach is simply to deposit from solution using electrodeposition methods and to passivate the amorphous thin films with polymer chemistries that have already been shown to be effective as binders for Si electrodes. A fundamental understanding of the structural and surface properties of these electrodes will be obtained during realistic battery operation so as to identify the optimum Si alloy and polymer chemistry and optimise performance rationally. This project will develop Si electrodes that are not exclusively destined for use in Li-ion systems but can also be reversibly cycled in Na-ion and Li-S batteries. A variety of Si-alloy chemistries will be explored, including Si-Sn alloys, since these show considerable promise as anodes for Na-ion batteries. A goal is to develop the first Si-based Na anode. This flexibility opens up numerous technology transfer opportunities in a variety of emerging battery systems focused on higher energy, sustainable, and safer technologies (e.g. Li-ion, Na-ion and LiS, respectively). The new batteries will be tested in the UK's first full battery prototyping line in a non-commercial environment. Fully understanding what occurs in a battery as it is charged / discharged is complex. The battery is a closed system with constantly changing domains. Central to the success of this project is the application of in-situ characterisation techniques for analysing real-time, dynamic structural and surface changes that occur as Li ions pass back and forth between the anode and cathode (or why they do not). This knowledge will subsequently guide continued improvements in electrode designs. The major techniques proposed to gain a comprehensive understanding of the chemistry occurring in the battery as it is charged/discharged are multinuclear NMR and X-ray computed tomography. These techniques have provided battery researchers with a wealth of vital, real-time insight - especially regarding failure mechanisms in silicon materials. Project AMorpheuS's approach will reduce the need for additional processing of materials in the electrodes, e.g., (i) high surface area carbons (which need energy-intense mixing processes) and (ii) industry-standard binders (which require toxic solvents to enable them to be processed into coatings). This strategy will reduce production time and eliminate toxic chemicals. These improvements will significantly reduce manufacturing cost and increase the UK's energy security.

Warwick IMRC will be active in two focus sectors as follows:Intelligent and Eco-Friendly VehiclesThe future of road transport will undoubtedly require vehicles to become more intelligent. This will facilitate the reduction in the number of accidents, improve infrastructure utilization, thereby reducing congestion, and help to minimize environmental impact through more efficient vehicle dynamics. The application of intelligence will allow significant changes to the construction of vehicles and the reduction of unladen weight, since structures to absorb impact damage will become redundant if collision avoidance systems are installed. The research will investigate the impact of intelligent systems on vehicle design, the technologies required, changes in manufacturing processes, final test implications and vehicle maintenance and upgrade throughout the product lifetime. In addition, aspects of the driver -vehicle interface will be researched to minimize the impact of such technology on driver satisfaction . In parallel with this work research will be conducted on materials, fuels and propulsion schemes that will offer more eco-friendly vehicle solutions. The existing hybrids group will investigate computer models that can help in the definition and optimization of next generation propulsion systems. Other teams will investigate the potential for using agricultural waste or non food crops to produce new chemical food stocks in energy efficient processes and go on to determine the most effective ways of using the chemicals to manufacture materials and fuels for next generation vehicles. Thus research will be integrated with activities planned for the TSB/EPSRC/DfT/AWM low-carbon vehicle demonstrator programme.Next Generation HealthcareA major challenge for the healthcare industry is to deliver high quality care at the time of need at minimum cost and with maximum customer/supplier (patient/healthcare practitioner) satisfaction. There are many challenges that can be addressed through the application of design, technology and management processes. Many of the lessons learnt in other industries can be adapted to address these challenges and in particular the processes used in lean manufacturing are thought to be especially relevant. Projects in this area will include hospital based initiatives such as robotically assisted rehabilitation, primary care research in health centres and doctors' surgeries, remote diagnostic systems applicable to the long-term ill living at home and the application of best practice in new product introduction to improve the roll-out and acceptance of innovation in the healthcare industry. Areas of opportunity include working closely with companies such as GE Healthcare and hospitals in the development of preventative early health (rather than the current retrospective diagnosis driven system), incorporation of advanced analysis approaches in diagnostic equipment and exploring the application of scanning technologies in non-medical and mental health applications. The WIMRC will build on the developing partnership with the Strategic Health Authority with a shared agenda of technology driven change and the location of the NHS Institute for Innovation and Improvement on the Warwick campus.

Degradation of lithium battery cells is a complex process occurring over multiple temporal and spatial domains. Improved understanding of cell health is a prerequisite for expanded use of Li-ion battery technology in many challenging applications. Early detection of changes in critical parameters would enable performance assessment and degradation forecasting, as well as providing a route to predict the most likely eventual failure modes. Parameter detection requires the ability to measure a diverse set of static and dynamic properties that elucidate the state of a battery system. To enable efficient and safe battery operation, diagnostic schemes need to be fast, accurate, and reliable, work in near real-time, and detect potential faults as early as possible; to enable widespread practical adoption, parameter detection must be achieved with minimal added cost. In tandem, the need to run accurate in-service battery models is critical, and would enable model-based control. Second only to safety monitoring of voltage and temperature, state-of-charge (SOC) estimation is the most important function of a battery management system (BMS). Better BMS SOC could help maximize battery performance and lifetime, but is often accurate to only +/- 10% - and simple methods to improve this accuracy do not currently exist. Models capable of predicting Li-ion performance under modest conditions are highly advanced. But significant progress is still needed to couple operational models suitable for the diagnosis and prognosis of degradation and failure with models of degradation mechanisms. Generally faults and the resulting degradation manifest as capacity or power fade and often state-of-the-art techniques such as X-ray CT, open circuit voltage measurements, and thermal measurements are used to characterise the degradation. This proposal brings together a world-class team to address the critical issue of degradation and health estimation for leading lithium-ion-battery chemistries. We place particular focus on Translational Diagnostics, which we define as diagnostic methods that translate across length scales, across different domains, and across academic research into industry practice. Key outputs from our work will be a suite of new and validated diagnostic tools integrated with battery models for both leading and emerging lithium-ion and sodium- ion battery chemistries. We aim to ensure that these diagnostic tools are capable of cost-effective deployment on both small and large battery systems, and able to run in real time with sufficient accuracy and reliability, such that safer, more durable and lower cost electrochemical energy storage systems can be achieved

Production and recovery of energy and industrial materials from novel biological sources reduces our dependency on the Earth's finitie mineral petrochemical resources and helps the UK economy to become a low carbon economy. Recovering energy and valuable resources such as metals from waste materials is an attractive but challenging prospect. The valuable materials are usually present in wastes at very low levels and present as a highly complex mixture. This makes it very difficult to concentrate and purify them in an economically sustainable manner. In recent years there have been exciting advances in our understanding of ways in which microorganisms can extract the energy locked up in the organic compounds found in wastewater and in the process generate electricity. This is achieved in devices known as microbial fuel cells (MFC). In an MFC microorganisms on the anode oxidize organic compounds and in doing so generte electrons. These electrons are passed into an electrical circuit and transferred to the MFC cathode where they usually react with oxygen to form water, sustaining an electric current in the process. In theory MFC can be configured such that, rather than conversion of oxygen to water at the cathode they could convert metal ions to metals or drive the synthesis of valuable chemicals. It is our aim to develop such systems that use energy harvested from wastewater to recover metals from metal-containing wastestreams and for the synthesis of valuable chemicals, ultimately from CO2. This project will bring together experts from academia and industry to devise ways in which this can be achieved and will form the foundation of a research programme where scientists working on fundamental research and those with the skills to translate laboratory science to industrial processes will work together to develop sustainable processes for the production of valuable resources from waste.