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The simulation of heat exchanger air flow characteristics in a sub-scale wind tunnel test requires an accurate representation of the full-scale pressure drop across the element. In practice this is normally achieved using laminations of various porous materials and honeycombs on the basis of experience and ad hoc data. In view of this, a series of measurements of the pressure drop, in both the near and far field, across screens with porosity (β) in the range 0.41 ≺ β ≺ 0.76 are reported. The aim being to establish a relationship between the porosity and the pressure drop characteristics of a given material at various angles of inclination to the free-stream flow. Furthermore, the effect of screen depth was investigated using honeycombs. This data will facilitate detailed design and accurate representation of the flow characteristics at sub scale.

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.

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.

In automotive aerodynamics much use has been made of generic reference models for research and correlation. Research work has been conducted mostly on small-scale versions of the models to investigate flow regimes and aerodynamic force and moment characteristics while correlation tests have made use of full-scale models to compare results between wind tunnels. More recently reference geometries have also been used as test cases in the validation of computational techniques. This paper reviews the design characteristics and use of several key reference models. The advantages and disadvantages of these designs and also the applicability of the results in providing guidelines for the development of production vehicles are discussed. It is advocated that when researchers choose to use simple models, existing reference geometries should be employed.

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.

This paper outlines the procedure used to assess the performance of a Lane Keeping Assistance System (LKAS) in a virtual test environment using the newly developed Euro NCAP Lane Support Systems (LSS) Test Protocol, version 1.0, November 2015 [1]. A tool has also been developed to automate the testing and analysis of this test. The Euro NCAP LSS Test defines ten test paths for left lane departures and ten for right lane departures that must be followed by the vehicle before the LKAS activates. Each path must be followed to within a specific tolerance. The vehicle control inputs required to follow the test path are calculated. These tests are then run concurrently in the virtual environment by combining two different software packages. Important vehicle variables are recorded and processed, and a pass/fail status is assigned to each test based on these values automatically.

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.

Cooling drag, typically known as the difference in drag coefficient between open and closed cooling configurations, has traditionally proven to be a difficult flow phenomenon to predict using computational fluid dynamics. It was seen as an academic yardstick before the advent of grille shutter systems. However, their introduction has increased the need to accurately predict the drag of a vehicle in a variety of different cooling configurations during vehicle development. This currently represents one of the greatest predictive challenges to the automotive industry due to being the net effect of many flow field changes around the vehicle. A comprehensive study is presented in the paper to discuss the notion of defining cooling drag as a number and to explore its effect on three automotive models with different cooling drag deltas using the commercial CFD solvers; STARCCM+ and Exa PowerFLOW.

Water is always present in jet fuel, usually in a mixture of forms. At very low temperatures this phenomenon can lead to the formation of ice crystals within the aircraft fuel system, which can then stay in suspension within the entire volume of fuel. Pumps within the fuel system transfer fuel around the system. Pumps such as boost pumps that are typically used in fuel systems are protected by a weave type filter mesh at the inlet. Ice accretion on the surface of this mesh has operational implications as it can cause non optimal fuel flow. In this investigation, two fundamental tools are being used: 1) a high fidelity MATLAB model of a mesh strainer, pick-up line and pump, and 2) a test rig of the modelled system. The model is being used to investigate fuel system performance when exposed to fuel containing water/ice contaminants at cold temperatures.

A modern benchmark for passenger cars - DrivAer model - has provided significant contributions to aerodynamics-related topics in automotive engineering, where three categories of passenger cars have been successfully represented. However, a reference model for high-performance car configurations has not been considered appropriately yet. Technical knowledge in motorsport is also restricted due to competitiveness in performance, reputation and commercial gains. The consequence is a shortage of open-access material to be used as technical references for either motorsport community or academic research purposes. In this paper, a parametric assessment of race car aerodynamic devices are presented into four groups of studies. These are: (i) forebody strakes (dive planes), (ii) front bumper splitter, (iii) rear-end spoiler, and (iv) underbody diffuser.

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.

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.

The aerodynamic drag of future low emission vehicles will need to be low. Unfortunately, vehicle shapes that result in low drag coefficients - of the order of 0.15 - are often aerodynamically unstable in crosswinds. The addition of wheels, transmission, radiators, suspension, steering, brakes, air ducts and wing mirrors can easily increase this drag coefficient to 0.24 and above and produce an undesirable lift distribution. The Aero-Stable Carbon Car (ASCC) is a research project, in conjunction with industrial partners, to design and build a practical 3 to 4 seat low drag car (CD less than 0.20) with an acceptable lift distribution (front to rear) which is also stable in crosswinds and in yaw through a series of low speed wind tunnel tests performed in the Cranfield College of Aeronautics 8′ × 6′ wind tunnel facility.

The simulation of natural-like snow conditions in a controlled environment such as an Icing Wind Tunnel (IWT) is a key component for safe, efficient and cost-effective design and certification of future aircraft and rotorcraft. Current capabilities do not sufficiently match the properties of natural snow, especially in terms of size and morphology. Within the Horizon 2020 project ICE GENESIS, a new technology has been developed aiming to better recreate natural snowflakes. The focus of the newly developed system was the generation of falling snow in a temperature range of +1°C to -4°C. Ground measurements and flight test campaigns have been performed to better characterize these conditions and provide requirements for wind tunnel facilities. The calibration results of the new snow generation system as well as snow accretion data on a NACA0012 test article with a chord length of 0.377 m are presented.

This paper focuses on the investigation of the nature, process and effects of ice accretion on different feed pump strainers upstream of the aircraft feeding system. A suitable test rig was designed to circulate Jet A-1 containing water/ice contaminants at cold temperatures through the strainers. Following an extensive literature review, a number of screening tests were performed. These provided a strong base for an exhaustive study of fuel icing in the dynamic environment offered by the test rig. The effects of the rate of fuel cooling on the nature of ice were examined. As expected, it was observed that the yield of ice generated on the mesh screen increased with the water concentration in the fuel. It was also revealed that at higher cooling rates, a crust of snow formed on top of softer ice on the mesh screen.

A 3D Navier-Stokes CFD model of a wheel located within a wheelhouse cavity has been produced. Both a stationary wheel on a fixed ground and a rotating wheel on a moving ground were considered. Extensive comparisons with the results of a wind tunnel investigation based on the same geometry are presented. These consist of three force coefficients and pressures on the internal faces of the cavity. Comparison with the experimental results gave encouraging agreement. It was found that the rotating wheel produced more drag than the stationary wheel whilst shroud drag decreased when the groundplane was moving compared to when it was stationary.

One main objective is to find out how these parameters interact and optimal driver control gain and driver preview time are obtained. Some steps further, neuromuscular dynamics is considered and the system becomes different from the simplified driver-vehicle system studied before. New optimal driver control gain and driver preview time could be obtained for both tensed and relaxed muscle state. Final step aims at analysing the full system considering driver, neuromuscular, steer-by-wire and vehicle models. The steer-by-wire system could potentially have a significant influence on the vehicle when the driver is at impaired state, which could be represented by setting higher response delay time or smaller preview time. Vehicle's stability and active safety could also be improved by introducing the steer-by-wire system.

Autonomous vehicles have been shown to increase safety for drivers, passengers, and pedestrians and can also be used to maximize traffic flow, thereby reducing emissions and congestion. At the same time, governments around the world are promoting the usage of battery electric vehicles (BEVs) to reduce and control the emissions of CO2. This has made the development of autonomous vehicles and electric vehicles a very active research area and has prompted a significant amount of government funding. This article presents the detailed design of a low-cost platform for the development of an autonomous electric vehicle. In particular, it focuses on the design of the electrical architecture and the control strategy, tailored around the usage of affordable sensors and actuators. The specifications of the components are extensively discussed in relation to the performance target.

Bus drivers are a group at risk of often suffering from musculoskeletal problems, such as low-back pain, while bus passengers on the last-row seats experience accelerations of high values. In this paper, the contribution of K-seat in decreasing the above concern is investigated with a detailed simulation study. The K-seat model, a seat with a suspension that functions according to the KDamper concept, which combines a negative stiffness element with a passive one, is benchmarked against the conventional passive seat (PS) in terms of comfort when applied to different bus users’ seats. More specifically, it is tested in the driver’s and two different passengers’ seats, one from the rear overhang and one from the middle part. For the benchmark shake, both are optimized by applying excitations that correspond to real intercity bus floor responses when it drives over a real road profile.

Dents on the aircraft skin are frequent and may easily go undetected during airworthiness checks, as their inspection process is tedious and extremely subject to human factors and environmental conditions. Nowadays, 3D scanning technologies are being proposed for more reliable, human-independent measurements, yet the process of inspection and reporting remains laborious and time consuming because data acquisition and validation are still carried out by the engineer. For full automation of dent inspection, the acquired point cloud data must be analysed via a reliable segmentation algorithm, releasing humans from the search and evaluation of damage. This paper reports on two developments towards automated dent inspection. The first is a method to generate a synthetic dataset of dented surfaces to train a fully convolutional neural network. The training of machine learning algorithms needs a substantial volume of dent data, which is not readily available.