Improving the fuel efficiency of the IC engine is important to meet the growing demand for non-renewable energy, and to reduce the emission of carbon dioxide - a major contributor to global warming. Advanced feed-back control strategies offer an important way of improving engine efficiency for existing designs. But to fully exploit these control strategies, a cost effective, durable, and real-time method of measuring engine cylinder pressure is needed since existing sensors are far too expensive and are seriously undermined by long-term durability issues. The search for alternative means of cylinder pressure reconstruction for production engines has continued for two decades. This search is now of critical importance for both conventional and future HCCI engines. Two indirect pressure reconstruction methodologies have been proposed using either measured crank-shaft motion or measured engine-casing vibration. But although numerous methods have been suggested to exploit these two approaches not one single method has yet been fitted to a production engine. There are two reasons for this: i) the most promising method (recurrent neural network model) is still in need of a suitably tuned training methodology, and ii) fixed-parameter reconstruction models will not in general produce accurate pressure reconstruction on a different engine (even of the same type) owing to the effect of variability arising from normal differences in materials, manufacture, operating conditions, and component wear. A fully adaptive reconstruction technique is needed. This proposal aims to create a robust adaptive cylinder-pressure reconstruction methodology for production engines, and to test this methodology on real engine data. This is timely because preliminary studies point very favourably to the most suitable architecture for multi-cylinder pressure reconstruction, but as yet, it is not known how to train these models, even for application to single test engines. A detailed understanding of the stochastic parameter fitting problem is needed. Only then is it likely a suitable training strategy can be designed. More importantly, to address the needs of an adaptive system, a way has to be found to allow fixed-parameter systems become variable-parameter models. Three novel variable-parameter schemes are proposed and these will be appropriately tested. The big question however is how should such variable-parameter schemes be trained for adaptive reconstruction? This question will be addressed in the project.

The basic function of a car suspension is to support the weight of the vehicle, maximise the friction between the tyres and the road surface, provide steering stability with good handling, and ensure the comfort of the passengers. The dynamics of a moving car are generally considered from two perspectives, viz. ride and handling, three important issues being vibration isolation, road holding and cornering. The car suspension system attempts to solve the challenges unique to each, by (i) absorbing energy while travelling over rough roads and dissipating it without causing undue oscillation of the vehicle, (ii) maintaining the wheel geometry to maximise tyre contact with the road, (iii) reacting the weight of the car during cornering, so as to minimise body roll. Although car suspensions have evolved and improved over the years, the three fundamental components remain springs, dampers (shock absorbers) and anti-roll bars. In essence, the springs absorb the oscillatory motion of the wheels; the shock absorbers control unwanted spring motion by damping vibratory motions, the kinetic energy of the suspension movement being converted into heat energy which is dissipated by hydraulic fluid; the anti-roll bars then provide additional stability, combatting the roll of the car on its suspension as it corners, by resisting the vertical movement of one wheel relative to the other, which results in a more level ride. There are, of course, numerous variations and different configurations of suspension, and a car usually has a different design on the front and back. However, whilst suspension systems are a fundamental element of any vehicle and may appear to be relatively simple, designing and implementing them to balance passenger comfort with handling is a complex task. Soft suspensions provide a smooth ride, but result in body roll or pitch during braking, acceleration and cornering, whilst stiff suspensions minimise body motion and allow cars to be driven more aggressively, albeit at the expense of ride quality. To overcome the limitations of conventional suspension systems, over the years, various alternative suspension technologies have been developed. For example, hydrostatic, hydrogas, hydropneumatic and hydraulic - an innovation which has previously been exploited in motorsport. However, these also have their limitations and/or are too expensive for production cars. Recent advances in linear electromagnetic machines, facilitated by advances in magnetic materials, power electronics and digital control systems, may, however, make it possible to introduce a totally new suspension technology. This is the subject of the proposed research, which envisages using a single linear motor at each wheel in place of the conventional shock absorber and spring system. The main benefit of employing linear motors is that they can move much faster than conventional fluid-based damper suspension systems, and can, therefore, respond quickly enough to virtually eliminate all movement and vibration of the body of a car under all driving and road conditions, and to counter body roll, by automatically stiffening the suspension when cornering, thereby giving the driver a greater sense of control and hence improving safety.The research programme will address the design optimisation of force-dense, energy-efficient linear electrical motors and the associated mathematical algorithms which will be necessary to provide the required active control of the suspension system. The utility of the developed suspension technology will be demonstrated on a quarter car rig, and the resulting vehicle performance improvements will also be quantified by simulations over the full range of ride, handling and stability.

The basic function of a car suspension is to support the weight of the vehicle, maximise the friction between the tyres and the road surface, provide steering stability with good handling, and ensure the comfort of the passengers. The dynamics of a moving car are generally considered from two perspectives, viz. ride and handling, three important issues being vibration isolation, road holding and cornering. The car suspension system attempts to solve the challenges unique to each, by (i) absorbing energy while travelling over rough roads and dissipating it without causing undue oscillation of the vehicle, (ii) maintaining the wheel geometry to maximise tyre contact with the road, (iii) reacting the weight of the car during cornering, so as to minimise body roll. Although car suspensions have evolved and improved over the years, the three fundamental components remain springs, dampers (shock absorbers) and anti-roll bars. In essence, the springs absorb the oscillatory motion of the wheels; the shock absorbers control unwanted spring motion by damping vibratory motions, the kinetic energy of the suspension movement being converted into heat energy which is dissipated by hydraulic fluid; and the anti-roll bars provide additional stability, combatting the roll of a car on its suspension as it corners, by resisting the vertical movement of one wheel relative to the other, which results in a more level ride. There are, of course, numerous variations and different configurations of suspension, and a car usually has a different design on the front and back. However, whilst suspension systems are a fundamental element of any vehicle and may appear to be relatively simple, designing and implementing them to balance passenger comfort with handling is a complex task. Soft suspensions provide a smooth ride, but result in body roll or pitch during braking, acceleration and cornering, whilst stiff suspensions minimise body motion and allow cars to be driven more aggressively, albeit at the expense of ride quality. To overcome the limitations of conventional suspension systems, over the years, various alternative suspension technologies have been developed. For example, hydrostatic, hydrogas, hydropneumatic and hydraulic - an innovation which has previously been exploited in motorsport. However, these also have their limitations and/or are too expensive for production cars. Recent advances in linear electromagnetic machines, facilitated by advances in magnetic materials, power electronics and digital control systems, may, however, make it possible to introduce a totally new suspension technology. This is the subject of the proposed research, which envisages using a single linear motor at each wheel in place of the conventional shock absorber and spring system. The main benefit of employing linear motors is that they can move much faster than conventional fluid-based damper suspension systems, and can, therefore, respond quickly enough to virtually eliminate all movement and vibration of the body of a car under all driving and road conditions, and to counter body roll by automatically stiffening the suspension when cornering, thereby giving the driver a greater sense of control and, hence, improving safety. The research programme will address the design optimisation of force-dense, energy-efficient linear electrical motors and the associated mathematical algorithms which will be necessary to provide the required active control of the suspension system. The utility of the developed suspension technology will be demonstrated on a quarter car rig, and the resulting vehicle performance improvements will also be quantified by simulations over the full range of ride, handling and stability.

Vehicle energy management (EM) systems currently concentrate on controlling the drivetrain to deliver the requested power to the wheels optimally from one or more energy sources, depending on the level of hybridisation of the drivetrain. Despite the existence of a vast range of such systems, encompassing rule-based to optimisation-based schemes, a number of challenges remain and opportunities exist to realise the next generation of more efficient EM control. The Green Adaptive Control for Future Interconnected Vehicles project aims to directly address these challenges by developing, implementing and testing EM systems that will now be global (simultaneous optimisation of the drivetrain energy, auxiliary systems energy and driving speed rather than only of the drivetrain energy), predictive (optimisation over a 'look ahead' horizon rather than just based on the instantaneous power demand), and newly adaptive (taking into account driver's preferences, traffic and other environmental conditions). The ultimate goal is to reduce by more than 3-5% the fuel consumption of the future fleet of passengers and light duty vehicles for a range of drivetrain architectures (conventional, electric and hybrid electric) and auxiliary systems (cooling systems, and other). To reach this objective this project will design, implement and demonstrate a new generation of EM together with an Adaptive Cruise Control system, which will automatically drive the vehicle at the most appropriate speed. For this to be effective, we also need to make the drivers aware of the benefits and to make small changes in their driving behaviour. Indeed, substantial reductions in energy consumption can be achieved by making small changes to the behaviour of a large number of drivers. Human factors methods will be used in this research to optimise the design of such new EM control systems. The proposed EM systems will have three operating modes: Autonomous, Coaching and Manual, which are all based on the same three layers structure. The first one is the Perception layer, which has the purpose of gathering navigation (e.g. route) information, driving information (e.g. the vehicle position, speed and acceleration), information related to the surrounding vehicles, and finally infrastructure conditions (e.g. the state of the next traffic lights series). We will use this information to feed the Decision layer, which is where the intelligence of the system will lay, and which will also be the core of our project. In the Autonomous mode, the system will manage the car in a much smarter way than a human driver by selecting, case by case, the most appropriate vehicle speed and acceleration taking into account all environmental constraints such as road characteristics, desired time to destination and traffic conditions. Once the EM and speed will be optimised, the Action layer will safely drive the vehicle at the most appropriate speed thanks to the Adaptive Cruise Control system. Even if drivers are not always keen to accept such autonomous systems and want to drive according to their personal style, significant fuel reduction may be achieved by using predictive optimisation, in which the system tries to anticipate the future power demand, which is predicted by the system itself according to the information available. Indeed, by selecting the Manual operating mode, the driver behaviour will be predicted by using a mathematical model that will be appositely developed in this project and eventually we will use such prediction to optimise the EM and reduce fuel consumption. Finally, while using the Coaching operating mode, the most appropriate speed will be calculated by the system and then recommended to the driver by using an appropriate haptic (and possibly visual and acoustic) Human Machine Interface, but the driver will maintain the freedom and the responsibility of keeping the preferred speed.

The scale of the investment (in power generation, transmission and charging infrastructure) that is required to support the widespread adoption of Electric Vehicles (EVs) is massive. This, combined with natural delays associated with fleet turnover and consumer acceptance and adoption of new technology, suggests that the transition to a predominantly grid-supplied EV fleet will be gradual and often infrastructure-limited. This Prosperity Partnership proposes a new and faster route to full fleet electrification. We propose to develop a Thermal Propulsion System (TPS) that, combined with a matched hybrid energy recovery system, will be capable of powering an EV from an energy dense liquid fuel at the same or lower economic and environmental cost than would be incurred by importing electricity to the vehicle from the grid. By utilising a globally established refuelling network of proven capacity, the TPS technology that will be delivered by this partnership will enable the widespread adoption of zero-emissions capable, electrically driven, vehicles ahead of the required infrastructure developments of the grid-dependent Battery Electric Vehicle (BEV) and the hydrogen Fuel Cell Electric Vehicle (FCEV). This will lighten the burden on the UK's electricity generating capacity and distribution network as BEV and FCEV usage increases, allowing valuable time for the required development of grid and charging infrastructures while simultaneously providing an option for low carbon transport at times of low renewable input to the grid. This work is of substantial national importance to the UK's manufacturing sector. The research will protect the role of the TPS, and the UK's well-established engine manufacturing expertise, within the rapidly growing low-emission vehicle sector of the automotive market. The UK government predict that the global market for these low-emissions vehicles could be worth £1.0-2.0 trillion per year by 2030, and £3.6-7.6 trillion per year by 2050. The UK's automotive supply chain as a whole would benefit from the world leading technology that this Partnership seeks to provide. This Partnership combines the industry knowledge, design and manufacturing resources of Jaguar Land Rover (JLR), with the academic expertise of two of the UK's leading TPS research groups. The University of Oxford are world-leaders in the development of optical diagnostics and the study of in-cylinder phenomena: sprays, combustion and emissions. The University of Bath are similarly expert in the study of air handling, waste heat recovery and the systems-level analysis and modelling of vehicle powertrain. The research is divided into interrelated "Grand Challenges". Jaguar Land Rover will lead the TPS concept design and evaluation. The University of Oxford will perform fundamental experimental studies on mixing, ignition, combustion and emissions formation under extreme lean-burn and highly dilute conditions relevant to hybrid-focused TPS operation. The data from these experiments will be used at Oxford to develop and validate new predictive models that, in turn, will feed back into concept design process at JLR and systems models at the University of Bath. Oxford will also develop new and improved measurement tools and methods for the experiments. The University of Bath will investigate low-grade and high-grade heat recovery, air-handling and boosting systems--demonstrating and evaluating concepts on a prototype multi-cylinder TPS and feeding back in to JLR's concept design process. Bath will also perform extensive systems and vehicle modelling of the TPS system (using models validated against Oxford's data) in a hybrid powertrain to optimise system-level energy balance and demonstrate the target systems-level energy recovery in a virtual environment.