<p>Reversing with a trailer is very difficult and many drivers hesitate to even try it. This thesis examines if active steering, particularly AFS (Active Front Steering), can be used to provide assistance.</p><p>For analysis and controller design a simple geometric model of car and trailer is used. The model seems to be accurate enough at the low speeds relevant for trailer reversing. It is shown that the only trailer dependent model parameter can be estimated while driving. This enables use with different trailers.</p><p>Different schemes to control the system are tested. The main approach is to use the steering wheel as reference for some appropriate output signal, for example the angle between car and trailer. This makes reversing with a trailer more like reversing without a trailer. To turn left, the driver simply turns the steering wheel left and drives. Test driving, as well as theoretical analysis, shows that the resulting system is stable. Of the eight drivers that have tested this type of control, five found it to be a great advantage while two considered it more confusing than helpful.</p><p>A major problem with this control approach has to do with the way AFS is constructed. With AFS, the torque required to turn the front wheels results in a reaction torque in the steering wheel. Together with the reference tracking controllers, this makes the steering wheel unstable. Theoretical analysis implies that this problem has to be solved mechanically. One solution would be to combine AFS with electric power steering.</p><p>This thesis also presents a trajectory tracking scheme to autonomously reverse with a trailer. Starting from the current trailer position and the desired trajectory an appropriate turning radius for the trailer is decided. Within certain limits, this will stabilize the car as well. The desired trajectory can be programmed beforehand, but it can also be saved while driving forward. Both variants have been tested with good results.</p>

A superimposed steering system is the combination of a conventional steering system with an electric motor which is used to alter the steering angle imposed by the driver. The potential benefits are increased agility, automatic compensation for lateral wind forces and decreased braking distance (in combination with an electronic stability program). In this thesis we implement a model and a controller for a superimposed steering system thus achieving the first of these potential benefits. The vehicle model is based on the single-track or bicycle model. Unlike most other publications, the motor model in this thesis goes down to the level of the electrical dynamics of the motor. The model is divided into three main modules (vehicle module, steering module and friction module) as well as several submodules to ensure easy adaptability. The overall control objective consists of increasing vehicle agility by achieving a variable ratio between the steering wheel angle and the actual road wheel angle as a function vehicle velocity. We divide the controller into a torque and a current controller. The actual controller is derived in three steps starting from an analog torque controller as well as an analog current controller then moving to a digital torque controller. In doing so we use the model matching, feedback linearization and state feedback control techniques. The model and the controller are evaluated using the parameters of a small truck and different road scenarios. Finally, the Validation Square technique is applied to assess the validity of the results.

Reversing with a trailer is very difficult and many drivers hesitate to even try it. This thesis examines if active steering, particularly AFS (Active Front Steering), can be used to provide assistance. For analysis and controller design a simple geometric model of car and trailer is used. The model seems to be accurate enough at the low speeds relevant for trailer reversing. It is shown that the only trailer dependent model parameter can be estimated while driving. This enables use with different trailers. Different schemes to control the system are tested. The main approach is to use the steering wheel as reference for some appropriate output signal, for example the angle between car and trailer. This makes reversing with a trailer more like reversing without a trailer. To turn left, the driver simply turns the steering wheel left and drives. Test driving, as well as theoretical analysis, shows that the resulting system is stable. Of the eight drivers that have tested this type of control, five found it to be a great advantage while two considered it more confusing than helpful. A major problem with this control approach has to do with the way AFS is constructed. With AFS, the torque required to turn the front wheels results in a reaction torque in the steering wheel. Together with the reference tracking controllers, this makes the steering wheel unstable. Theoretical analysis implies that this problem has to be solved mechanically. One solution would be to combine AFS with electric power steering. This thesis also presents a trajectory tracking scheme to autonomously reverse with a trailer. Starting from the current trailer position and the desired trajectory an appropriate turning radius for the trailer is decided. Within certain limits, this will stabilize the car as well. The desired trajectory can be programmed beforehand, but it can also be saved while driving forward. Both variants have been tested with good results.

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No description available.

Attempts to assess psychological stress rely heavily upon subjective techniques which measure changes in perceived mental loading and situational awareness (Hart and Staveland 1988, Reid and Nygren 1988, Lemyre and Tessier 2003, 1998). Although quantitative methodologies do exist, for example monitoring changes in the cardiopulmonary system (Gelfand et al. 2004, Harada et al. 2006), such parameters are subject to influence by factors other than stress. Psychological stress is known to influence the effectiveness of the innate immune system, leading to an increased risk of infection and immune-related disease (Dhabhar et al. 1996, Boscarino et al. 1999, Altemus et al. 2006). Leukocytes, primarily neutrophils have been identified as an essential component of this mechanism - periods of increased psychological stress have been shown to stimulate neutrophils to release reactive oxygen species into surrounding healthy tissues (Mian et al. 2003). The exact biochemical pathways by which this occurs have not yet been fully elucidated. However, this mechanism has become the basis for a novel in vitro technique (McLaren et al. 2003) which has the potential and sensitivity to rapidly quantify and discriminate between changes in psychological stress, resulting from exposure to short-term low-level everyday life-stressors. Aims The overall aim of this research was to further explore the relationship between short-term psychological stress and altered immune responsiveness. Leukocyte coping capacity (LCC) is a luminol-dependent chemiluminescent technique for the assay of reactive oxygen species production in whole blood samples. The feasibility of applying this test as an objective, quantitative, diagnostic measure of altered mental workload (mental stress), in the assessment of ergonomics within automotive research and development was examined. Methods Leukocyte activity was determined from whole blood, using a luminol-dependent, in vitro, chemiluminescent technique referred to as Leukocyte Coping Capacity (LCC). 2 The technique measures reactive oxygen species production following phorbol 12-myristate 13-acetate (PMA) stimulation. Subjective psychological measures, including likert scales and the NASA task load index were employed to assess perceived stress and altered mental workload. Other traditional physiological parameters including heart rate, systolic and diastolic blood pressure and core body temperature were also measured. The ability of each parameter to detect and discriminate between related short-term stressors was investigated, and results were correlated with post-test changes in leukocyte activity. To investigate the mechanism of stress induced leukocyte activation, standard ELISA was used to assess post-stressor plasma concentration changes in nine mediators including Adrenaline, Noradrenaline, Cortisol, E-Selectin, L-Selectin, Interleukin-1β, Interleukin-6, Endothelin-1, and Tumour Necrosis Factor-α. All 5 studies involved the use of mental stressors that were associated with either driving or the ergonomics of driving. Participants were moderately fit and healthy, aged between 20 and 65 years. Study one assessed the ability of the LCC technique to objectively discriminate between two closely related stressors (performing a simple manoeuvre in two different vehicles). Study two investigated leukocyte sensitivity, by testing whether a quantifiable response was elicited following exposure to a low-level stressor lasting seconds. The third study was used to explore the mechanism of leukocyte activation following short-term low-level stress. In addition to testing the viability of leukocyte responsiveness as an objective quantitative ergonomic assay for use within the motor industry, study four investigated how the magnitude of leukocyte responsiveness changed following repeated exposure to the same stressor. The final study used leukocyte reactivity to investigate how mental loading was affected during the interaction with three different motor vehicle control interfaces, whilst simultaneously maintaining lane discipline within a simulated driving environment.

Trucks are responsible for the major part of inland freight and so, they are a backbone of the modern economy but they are also a large consumer of energy. In this context, a dominating vehicle is a truck with heavy load on a long trip. The aim with look-ahead control is to reduce the energy consumption of heavy vehicles by utilizing information about future conditions focusing on the road topography ahead of the vehicle. The possible gains with look-ahead control are evaluated by performing experiments with a truck on highway. A real-time control system based on receding horizon control (RHC) is set up where the optimization problem is solved repeatedly on-line for a certain horizon ahead of the vehicle. The experimental results show that significant reductions of the fuel consumption are achieved, and that the controller structure, where the algorithm calculates set points fed to lower level controllers, has satisfactory robustness to perform well on-board in a real environment. Moreover, the controller behavior has the preferred property of being intuitive, and the behavior is perceived as comfortable and natural by participating drivers and passengers. A well-behaved and efficient algorithm is developed, based on dynamic programing, for the mixed-integer nonlinear minimum-fuel problem. A modeling framework is formulated where special attention is given to properly include gear shifting with physical models. Fuel equivalents are used to reformulate the problem into a tractable form and to construct a residual cost enabling the use of a shorter horizon ahead of the vehicle. Analysis of errors due to discretization of the continuous dynamics and due to interpolation shows that an energy formulation is beneficial for reducing both error sources. The result is an algorithm giving accurate solutions with low computational effort for use in an on-board controller for a fuel-optimal velocity profile and gear selection. The prevailing approach for the look-ahead problem is RHC where main topics are the approximation of the residual cost and the choice of the horizon length. These two topics are given a thorough investigation independent of the method of solving the optimal control problem in each time step. The basis for the fuel equivalents and the residual cost is formed from physical intuition as well as mathematical interpretations in terms of the Lagrange multipliers used in optimization theory. Measures for suboptimality are introduced that enables choosing horizon length with the appropriate compromise between fuel consumption and trip time. Control of a hybrid electric powertrain is put in the framework together with control of velocity and gear. For an efficient solution of the minimum-fuel problem in this case, more fuel equivalence factors and an energy formulation are employed. An application is demonstrated in a design study where it is shown how the optimal trade-off between size and capacity of the electrical system depends on road characteristics, and also that a modestly sized electrical system achieves most of the gain. The contributions develop algorithms, create associated design tools, and carry out experiments. Altogether, a feasible framework is achieved that pave the way for on-board fuel-optimal look-ahead control.

L’atténuation des bruits gênants dans une automobile est classiquement réalisée par ajustement des caractéristiques mécaniques du véhicule : masse, raideur et amortissement. C’est une approche dite passive. Malheureusement, elle induit un ajout de masse important pour traiter les basses fréquences. Le contrôle actif de bruit (atténuation d’un bruit par superposition d’un contrebruit) est actuellement envisagé comme une solution possible à ce problème. L’objectif de cette thèse est d’évaluer les performances atteignables par cette solution. Un système acoustique étant par essence fortement résonant, sa modélisation sur une large plage de fréquence conduit à des modèles d’ordre élevé, pour l’obtention desquels une méthode d’identification appropriée doit être utilisée. C’est la méthode dessous espaces par approche fréquentielle dans le domaine continu qui a été retenue.La traduction du cahier des charges conduit à un problème de régulation multivariable H1 multi-objectif et multi-modèle avec contrainte de stabilité forte. Par ailleurs, actionneurs et capteurs ne sont pas colocalisés et on ne mesure pas la perturbation à rejeter. La volonté d’évaluer au plus près les performances atteignables justifie la résolution du problème par optimisation non lisse. Cette approche évite tout pessimisme, mais nécessite de par son caractère local une bonne initialisation et une structuration du régulateur parcimonieuse.La méthodologie proposée a été validée en simulation et expérimentalement. Elle permet une évaluation et une comparaison précises des performances atteignables en fonction des contraintes sur les mesures et les moyens d’action disponibles. / Classical methods used for noise reduction in cars are based on adjusting the mechanical properties: mass, stiffness and damping. They are qualified as passive and induce significative addition of weight for reducing low frequency noises. Active noise control is seen as a possible solution to achieve low frequency noise attenuation and weight reduction.The goal of this work is to evaluate achievable performances with such solution.Acoustic enclosures are known to be resonant systems of highorder. Obtaining a model of it, therefore requires a suitable identification method. The approach chosen is based on subspace methods. It processes data in the frequency domain for obtaining a continuous time model.The control problem derived from the specifications is a MIMO H1, multi-objective and multi-model problem with a strong stability constraint. Futhermore, actuators and sensors are not-colocated, and no measure of the disturbance is available. In order to precisely evaluate the achievable performances, this problem is solved using non smooth optimization.Such approach ensures the absence of pessimism, but requires an appropriate initialization and a parsimonious controller structure, because it does not ensure convergence toward the global optimum. The proposed methodology was validated in simulation and experimentally. It allows a precise evaluation and comparison of achievable performances according to the constraints on available measures and means of action.

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Many control algorithms for ABS systems have been proposed in the literature since the introduction of this equipment by Bosch in 1978. In general, one can divide these control algorithms into two different types: those based on a regulation logic with wheel acceleration thresholds that are used by most commercial ABS systems; and those based on wheel slip control that are preferred in the large majority of academic algorithms. Each approach has its pros and cons [Shida 2010]. Oversimplifying, one can say that the strength of the first ones is their robustness; while that of the latter ones their short braking distances (on dry grounds) and their absence of limit cycles. At the midpoint of this industry/academy dichotomy, based on the concept of extended braking stiffness (XBS), a quite different class of ABS control strategies has been proposed by several researchers (see, e.g., [Sugai 1999] and [Ono 2003]). This concept combines the advantages from both the industrial and academic approaches. Nevertheless, since the slope of the tyre characteristic is not directly measurable, it introduces the question of real-time XBS estimation. The first part of this thesis is devoted to the study of this estimation problem and to a generalization of the proposed technique to a larger class of systems. From the technological point of view, the design of ABS control systems is highly dependent on the ABS system characteristics and actuator performance. Current ABS control algorithms on passenger cars, for instance the Bosch ABS algorithm, are based on heuristics that are deeply associated to the hydraulic nature of the actuator. An interesting observation is that they seem to work properly only in the presence of a specific delay coming from the hydraulic actuation [Gerard 2012]. For brake systems that have different delays compared to those of hydraulic actuators, like electric in-wheel motors (with a smaller delay) or pneumatic trailer brakes (with a bigger delay), they might be no longer suitable [Miller 2013]. Therefore, adapting standard ABS algorithms to other advanced actuators becomes an imperative goal in the automobile industry. This goal can be reached by the compensation of the delays induced by actuators. The second part of this thesis is focused on this issue, and to the generalization of the proposed technique to a particular class of nonlinear systems. Throughout this thesis, we employ two different linearization techniques: the linearization of the error dynamics in the construction of model-based observers [Krener 1983] and the linearization based on restricted state feedback [Brockett 1979]. The former is one of the simplest ways to build an observer for dynamical systems with output and to analyze its convergence. The main idea is to transform the original nonlinear system via a coordinate change to a special form that admits an observer with a linear error dynamics and thus the observer gains can be easily computed to ensure the observer convergence. The latter is a classical method to control nonlinear systems by converting them into a controllable linear state equation via the cancellation of their nonlinearities. It is worth mentioning that existing results for observer design by error linearization in the literature are only applied to the case of regular time scalings ([Guay 2002] and [Respondek 2004]). The thesis shows how to extend them to the case of singular time scalings. Besides, the thesis combines the classical state feedback linearization with a new method for the input delay compensation to resolve the output tracking problem for restricted feedback linearizable systems with input delays.