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The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

The aviation sector has played a significant role in shaping the world into what it is today. The rapid growth of global economies and the corresponding sharp rise in the number of people now wanting to travel on business and for pleasure, has largely been responsible for the development of this industry. With a predicted rise in Revenue Passenger Kilometers (RPK) by over 150% in the next 20 years, the industry will correspondingly be a significant contributor to environmental emissions. Under such circumstances optimizing aircraft trajectories for lowered emissions will play a critical role amongst various other measures, in mitigating the probable environmental effects of increased air traffic. Aircraft trajectory optimization using evolutionary algorithms is a novel field and preliminary studies have indicated that a reduction in emissions is possible when set as objectives.

Testing real-time vehicular systems challenges the tester to design test cases for concurrent and sequential input events, emulating unexpected user and usage profiles. The vehicle response should be robust to unexpected user actions. Sequence Covering Arrays (SCA) offer an approach which can emulate such unexpected user actions by generating an optimized set of test vectors which cover all possible t-way sequences of events. The objective of this research was to find an efficient nonfunctional sequence testing (NFST) strategy for testing the robustness of real-time automotive embedded systems measured by their ability to recover (prove-out test) after applying sequences of user and usage patterns generated by combinatorial test algorithms, considered as “noisy” inputs. The method was validated with a case study of an automotive embedded system tested at Hardware-In-the-Loop (HIL) level. The random sequences were able to alter the system functionality observed at the prove-out test.

The installation of essential systems into aircraft wings involves numerous labour-intensive processes. Many human operators are required to perform complex manual tasks over long periods of time in very challenging physical positions due to the limited access and confined space. This level of human activity in poor ergonomic conditions directly impacts on speed and quality of production but also, in the longer term, can cause costly human resource problems from operators' cumulative development of musculoskeletal injuries. These problems are exacerbated in areas of the wing which house multiple systems components because the volume of manual work and number of operators is higher but the available space is reduced. To improve the efficiency of manual work processes which cannot yet be automated we therefore need to consider how we might redesign systems installations in the enclosed wing environment to better enable operator access and reduce production time.

The quantitative assessment and comparison of different hybrid vehicle options has traditionally been done on the basis of measuring or estimating the vehicle's fuel economy over predefined drive-cycles. In general, little or no consideration has been given to the more subjective and difficult to quantify vehicle requirements, such as trying to understand which derivative will be the most “fun” vehicle to drive. A lack of understanding in this area of vehicle performance sufficiently early within the development life-cycle so as to be in a position to influence the vehicle design, can lead to a compromised powertrain architecture which will ultimately increase the risk of product failure. The work presented within this paper constitutes part of the overall design activities associated with the LIFECar programme. The aim of the LIFECar consortium is to manufacture a lightweight, fuel cell hybrid electric sports vehicle.

This paper gives an overview of the development of a number of loss models for the pushing metal V-belt CVT. These were validated using a range of experimental data collected from two test rigs. There are several contributions to the torque losses and new models have been developed that are based upon relative motion between belt components and pulley deflections. Belt slip models will be proposed based upon published theory, expanded to take account of new findings from this work. The paper introduces a number of proposals to improve the efficiency of the transmission based on redesign of the belt geometry and other techniques to reduce frictional losses between components. These proposed efficiency improvements have been modelled and substituted into a complete vehicle simulation to show improvements in vehicle fuel economy over a standard European drive cycle.

This paper describes and demonstrates the use of an assembly centric design algorithm as an aid to achieving minimal hard tooling assembly concepts. The algorithm consists of a number of logically ordered design methodologies and also aids the identification of other enabling technologies. Included in the methodologies is an innovative systems analysis tool that enables the comparison of alternative assembly concepts, and the prediction and control of the total assembly error, at the outline stage of the design.

As the essential of future driver assistance system, brake-by-wire system is capable of performing autonomous intervention to enhance vehicle safety significantly. Regenerative braking is the most effective technology of improving energy consumption of electrified vehicle. A novel brake-by-wire system scheme with integrated functions of active braking and regenerative braking, is proposed in this paper. Four pressure-difference-limit valves are added to conventional four-channel brake structure to fulfill more precise pressure modulation. Four independent isolating valves are adopted to cut off connections between brake pedal and wheel cylinders. Two stroke simulators are equipped to imitate conventional brake pedal feel. The operation principles of newly developed system are analyzed minutely according to different working modes. High fidelity models of subsystems are built in commercial software MATLAB and AMESim respectively.

Recently, the development of braking assistance system has largely benefit the safety of both driver and pedestrians. A robust prediction and detection of driver braking intention will enable driving assistance system response to traffic situation correctly and improve the driving experience of intelligent vehicles. In this paper, two types unsupervised clustering methods are used to build a driver braking intention predictor. Unsupervised machine learning algorithms has been widely used in clustering and pattern mining in previous researches. The proposed unsupervised learning algorithms can accurately recognize the braking maneuver based on vehicle data captured with CAN bus. The braking maneuver along with other driving maneuvers such as normal driving will be clustered and the results from different algorithms which are K-means and Gaussian mixture model (GMM) will be compared.

Simulations are presented which fully couple both the aerodynamics and cooling flow for a model of a fully engineered production saloon car (Jaguar XJ) with a two-tier cooling pack. This allows for the investigation of the overall aerodynamic impact of the under-hood cooling flow, which is difficult to predict experimentally. The simulations use a 100 million-element mesh, surface wrapped and solved to convergence using a commercially available RANS solver (STARCCM+). The methodology employs representative boundary conditions, such as rotating wheels and a moving ground plane. A review is provided of the effect of cooling flows on the vehicle aerodynamics, compared to published data, which suggest cooling flow accounts for 26 drag counts (0.026 Cd). Further, a sensitivity analysis of the pressure drop curves used in the porous media model of the heat exchangers is made, allowing for an initial understanding of the effect on the overall aerodynamics.

The vehicle dynamics control systems are traditionally based upon utilizing wheel brakes as actuators. However, there has been recently strong interest in the automotive industry for introduction of other vehicle dynamics actuators, in order to improve the overall vehicle stability, responsiveness, and agility features. This paper considers various actuators such as active rear and central differentials and active front and rear steering, and proposes design of related yaw rate control systems. Different control subsystems such as reference model, feedback and feedforward control, allocation algorithm, and time-varying controller limit are discussed. The designed control systems are verified and compared by computer simulation for double lane change and slalom maneuvers.

Significant effort has been applied to the introduction of automation for the structural assembly of aircraft. However, the equipping of the aircraft with internal services such as hydraulics, fuel, bleed-air and electrics and the attachment of movables such as ailerons and flaps remains almost exclusively manual and little research has been directed towards it. The problem is that the process requires lengthy assembly methods and there are many complex tasks which require high levels of dexterity and judgement from human operators. The parts used are prone to tolerance stack-ups, the tolerance for mating parts is extremely tight (sub-millimetre) and access is very poor. All of these make the application of conventional automation almost impossible. A possible solution is flexible metrology assisted collaborative assembly. This aims to optimise the assembly processes by using a robot to position the parts whilst an operator performs the fixing process.

In this paper, gear ratios of a two-speed transmission system are optimized for an electric passenger car. Quasi static system models, including the vehicle model, the motor, the battery, the transmission system, and drive cycles are established in MATLAB/Simulink at first. Specifically, since the regenerative braking capability of the motor is affected by the SoC of battery and motors torque limitation in real time, the dynamical variation of the regenerative brake efficiency is considered in this study. To obtain the optimal gear ratios, iterations are carried out through Nelder-Mead algorithm under constraints in MATLAB/Simulink. During the optimization process, the motor efficiency is observed along with the drive cycle, and the gear shift strategy is determined based on the vehicle velocity and acceleration demand. Simulation results show that the electric motor works in a relative high efficiency range during the whole drive cycle.

In today's aircraft the diagnostic and prognostic systems play a crucial part in aircraft safety while reducing the operating and maintenance costs. Aircraft are very complex in their design and require consistent monitoring of systems to establish the overall vehicle health status. Most diagnostic systems utilize advanced algorithms (e.g. Bayesian belief networks or neural networks) which usually operate at system or sub-system level. The sub-system reasoners collect the input from components and sensors to process the data and provide the diagnostic/detection results to the flight advisory unit. Several sources of information must be taken into account when assessing the vehicle health, to accurately identify the health state in real time. These sources of information are independent system-level diagnostics that do not exchange any information/data with the surrounding systems.

Co-production of aircraft is resulting in demands for higher standards of manufacturing quality to ensure that parts and sub-assemblies from different companies and countries are compatible and interchangeable. As a result the existing method of building aerostructure using large numbers of dedicated manufacturing jigs and assembly tools, is now seen as being commercially undesirable, and technologically flawed. This paper considers an alternative, potentially more cost-effective, approach that embraces digital design, manufacturing, and inspection techniques, and in which reference and tooling features are incorporated into the geometry of the component parts. Within the aerospace industry this technology is known as ‘Flyaway Tooling’.

The effect of local fuel concentration on cyclic variability in combustion and engine performance in a lean burn stratified charge engine has been investigated. The fuel concentration in a plane close to the spark plug was measured for a large number of cycles using laser-induced fluorescence (LIF) and simultaneous measurement of in-cylinder pressure in an one-cylinder optical research engine. It could be shown quantitatively that the fuel concentration in a small region close to the spark plug has a dominating effect on the subsequent pressure development for lean mixtures. Variations in the mixture concentration in the vicinity of the spark plug contribute significantly to cyclic variation in combustion. Measurement of the flame area in the same plane 20 °CA after ignition revealed that the direction of growth of the established flame is not significantly influenced by the stoichiometry.

A mild hybrid powertrain with crankshaft mounted integrated motor generator (IMG) and torque controlled infinitely variable transmission (IVT) has shown clear potential for fuel economy (FE) enhancement. It also makes significant driveability and performance improvements possible which are a condition for customer satisfaction and subsequent marketability. The hybrid powertrain supervisory control strategy presented here uses the energy recovered during braking events for power assist, hence improving FE and driveability compromises. This is achieved by operating the engine at its best brake specific fuel consumption (BSFC) point during steady state conditions without deteriorating the transient response as a result of the comparatively fast IMG torque response. This paper demonstrates the launch manoeuvre and general driveability improvements achieved in simulation with validated models.

Current modelling capability for engine icing accretion prediction is still limited for App. C. To further validate icing codes in complex engine geometries, it is necessary to perform additional experimental work in relevant geometrical and environmental conditions. Within the frame of ICE GENESIS [1], an experiment has been setup to replicate the condition at the inlet of an engine first stage compressor. This paper describes the choices for the design of the engine compressor model, the setup within the icing wind tunnel and the methodology employed to obtain the results. Additionally, more effort has been focused on obtaining accurate ice shapes using a 3D scanning system. Results of 3D scans are given.

This paper considers rhe use of structurally integrated location and reference features to simplify and to reduce the lead time and costs of assembling large aerospace structures. The location features are selected to fulfil a specific function based on restraint requirements and the necessary degree of precision to ensure that the Product Key Characteristics are achieved. Analysis of how to use structurally integrated location and reference features, indicates that their introduction will not be successful unless there is an integrated design team with a thorough understanding of the manufacturing processes and capabilities, the assembly processes, and the enabling technologies. The assembly of a single nose rib to a section of front spar is used as a typical assembly problem. Three alternative assembly processes are briefly described and used to illustrate the need for the industry to adopt an holistic approach to the design of aerostructure.

The present work focuses on developing an integrated airframe, distributed propulsion, and power management methodology for liquid-hydrogen-fuelled HALE UAVs. Differently from previous studies, the aim is to assess how the synergies between the aforementioned sub-systems affect the integrated system power requirement, production, and distribution. A design space exploration study was carried out to assess the influence of distributing motor-driven fans on three different airframes, namely a tube-and-wing, a triple-fuselage, and a blended-wing-body. For the considered range of take-off masses from 5,000 to 15,000 kg, the 200 kW payload power requirement under examination was found to re-shape the endurance trends. In fact, the drop in specific fuel consumption due to the engine design point change alters the trends from nearly flat to a 25% maximum endurance increase when moving towards heavier take-off masses.