Search Results

As long as a tire steers about a titled kingpin pivot, the point coming in contact with the road moves along its perimeter. This movement affects the determination of kingpin moments caused by the tire forces, especially for large steering angles. The movement, however, has been neglected in the literature on the steerable-tire-kinematics-related topics. In this investigation, the homogeneous transformation is employed to develop a kinematic model of a steering tire in which the instantaneous ground-contact point on the tire is considered. The moments about the kingpin axis caused by tire forces are then computed based on the kinematics. A four-wheel-car model is constructed for determining the kingpin moment of steering system during the low-speed cornering maneuver. The result shows that the displacement of the ground-contact point along the tire perimeter is significant for large steering angles.

In the ANNIE project - Applications of Neural Networks to Integrated Ergonomics - BE96-3433, a tool for integrating ergonomics into the design process is developed. This paper presents some features in the current ANNIE as applied to the design of car interiors. A variant of the ERGOMan mannequin with vision is controlled by a hybrid system for neuro-fuzzy simulation. It is trained by using an Elite system for registration of movements. An example of a trajectory generated by the system is shown. A fuzzy model is used for comfort evaluation. An experiment was performed to test its feasibility and it showed very promising results.

The rising environmental awareness has led to a growing interest in electric and lightweight vehicles. Four-wheeled Ultra-Efficient Lightweight Vehicles (UELVs) have the potential to improve the quality of urban life, reduce environmental impact and make efficient use of land. However, the safety of these vehicles in terms of dynamic behaviour needs to be better understood. This paper aims to provide a quantitative assessment of the handling behaviour of UELVs. An analytical single-track model and a numerical simulation by VI-CarRealTime are analysed to evaluate the dynamic performance of a UELV compared to a city car. This analysis shows that the lightweight vehicle has a higher readiness (i.e. lower reaction time to yaw rate) for step steering and lower steering effort (i.e. higher steady-state value). Experimental analysis through real-time driving sessions on the Dynamic Driving Simulator assesses vehicle responses and subjective perception for different manoeuvres.

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.

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.

The paper deals with the bifurcation analysis of a simple mathematical model describing an automobile running on an even surface. Bifurcation analysis is adopted as the proper procedure for an in-depth understanding of the stability of steady-state motion of cars (either cornering or running straight ahead). The aim of the paper is providing the fundamental information for inspiring further studies on vehicle dynamics with or without a human driver. The considered mechanical model of the car has two degrees of freedom, nonlinear tire characteristics are included. A simple driver model is introduced. Experimental validations of the model are produced. As a first step, bifurcation analysis is performed without driver (fixed control). Ten different combinations of front and rear tire characteristics (featuring understeer or oversteer automobiles) are considered. Steering angle and speed are varied. Many different dynamical behaviors of the model are found.

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.

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.

Dynamic tests have been performed on carbon fiber racing seats following the FIA regulations. The tests have shown, in rear impact tests, a relatively strong rebound leading to large forward bending of neck, and, in side impact tests, very large lateral displacement of the head, the latter protruding dangerously towards hard portions of the car structure. Stiffening the seat back by steel struts results in reducing strongly both the motion and the acceleration of the head. Simulations of the dynamics of the tests have been done with multi-body models, including the Hybrid III dummy and seat deflection, by means of the program VEDYAC. It has been found that computer simulation can predict very accurately the result of a test, provided the numerical models have been carefully calibrated to match the dummy tolerance bands. Once they have been calibrated and validated with a number of tests, the computer models can be very useful to extend the test results to different test conditions.

The ride comfort of three Alfa Romeo cars, namely Giulietta (1955), Alfetta (1972) and 159 (2005) has been assessed both objectively and subjectively. The three cars belong to the same market segment. The aim is to let young engineers or graduate students understand how technology has evolved and eventually learn a lesson from the assessed trend. A number of cleats have been fixed at the ground and the three cars have traversed such uneven surface. The objective assessment of the ride comfort has been performed by means of accelerometers fixed at the seat rails, additionally a special dummy developed at Politecnico di Milano has been employed. The subjective assessment has been performed by a panel of passengers. The match between objective and subjective ratings is very good. Simple mathematical models have been employed to establish a (successful) comparison between experimental and computational results. The ride comfort differs substantially among the cars.

IAV has developed a strategy for transmission ratio selection that serves AMT, ATs, CVTs and Hybrid drivetrains. Since the power demand dependent strategy is applicable to all transmission types, it is possible to implement the same character of vehicle behavior. As a result, a manufacturer specific vehicle characteristic can be given to the complete range of powertrains. This universal field of application is made possible by the choice of ratio being dependent on the drivers demand of traction power instead of the usual dependency concerning the accelerator position and the vehicle velocity. Therefore, as opposed to conventional shifting strategies, the selected transmission ratio guarantees the demanded traction power. In the case of insufficient power at the actual transmission ratio, the engine speed will be increased.

We introduce in this paper a new Instrumented Steering Wheel (ISW) for ADAS development. The ISW has been designed, constructed and employed with satisfactory results. The ISW is able to measure three forces, three moments and the grip force at each hand of the driver. The ISW has been used for ADAS activities on an instrumented road vehicle. The aim was to use both the vehicle states and the ISW data for evaluating the driver behaviour. Two research activities were performed. The first activity refers to monitoring the driver behaviour during tests on a track. The second activity refers to the use of haptic ISWs, able to improve the ADAS systems. Referring to the first activity, the greatest majority of drivers applied always the same sequence of forces (pull, radial, tangential) either during emergency manoeuvres, either during slow speed curving.

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.

This work focuses on the analysis of the vertical dynamics of an agricultural tractor, investigating the influence of suspensions' parameters on riding comfort and contact forces. The use of lugged tires coupled with the operation over banked, irregular and deformable tracks, determines significant levels of vertical acceleration over several components of the tractor. These operating conditions have a direct effect on the driver, whose alertness and efficiency are undermined by the exposure to high levels of acceleration for a long time. Secondly, variations of the normal and traction forces provided by the tires affect the quality of tillage and other operations. The paper presents a multi-body vehicle model of a tractor interfaced with a tire-soil contact model allowing to take into account soil's deformation and tread pattern design.

Tire-road interaction is one of the main concerns in the design of control strategies for active/semi-active differentials oriented to improve handling performances of a vehicle. In particular, the knowledge of the friction coefficient at the tire-road interface is crucial for achieving the best performance in any working condition. State observers and estimators have been developed at the purpose, based on the measurements traditionally carried out on board vehicle (steer angle, lateral acceleration, yaw rate, wheels speed). However, until today, the problem of tire-road friction coefficient estimation (and especially of its maximum value) has not completely been solved. Thus, active control systems developed so far rely on a driver manual selection of the road adherence condition (anyway characterized by a rough and imprecise quality) or on a conservative tuning of the control logic in order to ensure vehicle safety among different tire-road friction coefficients.

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.

Future human exploration roadmaps involve the development of temporary or permanent outposts on Moon and Mars. The capability of providing astronauts with proper conditions for living and working in extraterrestrial environments is therefore a key issue for the sustainability of those roadmaps, and closed-loop Environment Control and Life Support Systems (ECLSSs) and bio-regenerative plants represent the necessary evolution of current technologies for complying with the challenging requirements imposed. This paper presents the architectural design of a terrestrial plant to be exploited to test and validate air and water management technologies for a biological life support system in a closed environment. The plant includes a crew area and a plant growth area. These two spaces can be considered as either a unique volume or two separated environments with reduced contact, e.g. for plant harvesting or other up-keeping activities.

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.

The paper is focused on both the subjective and the objective ride comfort evaluation of farm tractors. The experimental measurement of the relevant accelerations occurring at the tractor body, at the cabin and at the seat was performed on a number of different farm tractors. A subjective rating of the ride comfort level was performed by considering five different drivers. The comfort index was computed according with ISO 2631 and other standards. The acceleration of the seated subject was computed by means of a proper mechanical model of a farm tractor and derived at different positions on the subject body. It turned out that the acceleration of the lower torso was particularly relevant for establishing a matching between the subjective perception and the objective measurement and computation. A number of indices have been derived from the measured data which are able to correlate the subjective driver feeling with the measured accelerations.

A comprehensive research is presented aiming at assessing the ride comfort of subjects seated into road or off-road vehicles. Although many papers and books have appeared in the literature, many issues on ride comfort are still to be understood, in particular, the paper investigates the mutual effects of the posture and the vibration caused mostly from road unevenness. The paper is divided into two parts. In the first part, a mathematical model of a seated subject is validated by means of actual measurements on human subjects riding on a car. Such measurements refer to the accelerations acting at the subject/seat interface (vertical acceleration at the seat cushion and horizontal acceleration at the seat back). A proper dummy is used to derive the seat stiffness and damping.