Vehicle dynamics virtual sensing and advanced motion control for highly skilled autonomous vehicles

This dissertation is aimed at elucidating the path towards the development of a future generation of highly-skilled autonomous vehicles (HSAV). In brief, it is envisaged that future HSAVs will be able to exhibit advanced driving skills to maintain the vehicle within stable limits in spite of the driving conditions (limits of handling) or environmental adversities (e.g. low manoeuvrability surfaces). Current research lines on intelligent systems indicate that such advanced driving behaviour may be realised by means of expert systems capable of monitoring the current vehicle states, learning the road friction conditions, and adapting their behaviour depending on the identified situation. Such adaptation skills are often exhibited by professional motorsport drivers, who fine-tune their driving behaviour depending on the road geometry or tyre-friction characteristics. On this basis, expert systems incorporating advanced driving functions inspired by the techniques seen on highly-skilled drivers (e.g. high body slip control) are proposed to extend the operating region of autonomous vehicles and achieve high-level automation (e.g. manoeuvrability enhancement on low-adherence surfaces). Specifically, two major research topics are covered in detail in this dissertation to conceive these expert systems: vehicle dynamics virtual sensing and advanced motion control. With regards to the former, a comprehensive research is undertaken to propose virtual sensors able to estimate the vehicle planar motion states and learn the road friction characteristics from readily available measurements. In what concerns motion control, systems to mimic advanced driving skills and achieve robust path-following ability are pursued. An optimal coordinated action of different chassis subsystems (e.g. steering and individual torque control) is sought by the adoption of a centralised multi-actuated system framework. The virtual sensors developed in this work are validated experimentally with the Vehicle-Based Objective Tyre Testing (VBOTT) research testbed of JAGUAR LAND ROVER and the advanced motion control functions with the Multi-Actuated Ground Vehicle “DevBot” of ARRIVAL and ROBORACE.Diese Dissertation soll den Weg zur Entwicklung einer zukünftigen Generation hochqualifizierter autonomer Fahrzeuge (HSAV) aufzeigen. Kurz gesagt, es ist beabsichtigt, dass zukünftige HSAVs fortgeschrittene Fahrfähigkeiten aufweisen können, um das Fahrzeug trotz der Fahrbedingungen (Grenzen des Fahrverhaltens) oder Umgebungsbedingungen (z. B. Oberflächen mit geringer Manövrierfähigkeit) in stabilen Grenzen zu halten. Aktuelle Forschungslinien zu intelligenten Systemen weisen darauf hin, dass ein solches fortschrittliches Fahrverhalten mit Hilfe von Expertensystemen realisiert werden kann, die in der Lage sind, die aktuellen Fahrzeugzustände zu überwachen, die Straßenreibungsbedingungen kennenzulernen und ihr Verhalten in Abhängigkeit von der ermittelten Situation anzupassen. Solche Anpassungsfähigkeiten werden häufig von professionellen Motorsportfahrern gezeigt, die ihr Fahrverhalten in Abhängigkeit von der Straßengeometrie oder den Reifenreibungsmerkmalen abstimmen. Auf dieser Grundlage werden Expertensysteme mit fortschrittlichen Fahrfunktionen vorgeschlagen, die auf den Techniken hochqualifizierter Fahrer basieren (z. B. hohe Schlupfregelung), um den Betriebsbereich autonomer Fahrzeuge zu erweitern und eine Automatisierung auf hohem Niveau zu erreichen (z. B. Verbesserung der Manövrierfähigkeit auf niedrigem Niveau) -haftende Oberflächen). Um diese Expertensysteme zu konzipieren, werden zwei große Forschungsthemen in dieser Dissertation ausführlich behandelt: Fahrdynamik-virtuelle Wahrnehmung und fortschrittliche Bewegungssteuerung. In Bezug auf erstere wird eine umfassende Forschung durchgeführt, um virtuelle Sensoren vorzuschlagen, die in der Lage sind, die Bewegungszustände der Fahrzeugebenen abzuschätzen und die Straßenreibungseigenschaften aus leicht verfügbaren Messungen kennenzulernen. In Bezug auf die Bewegungssteuerung werden Systeme zur Nachahmung fortgeschrittener Fahrfähigkeiten und zum Erzielen einer robusten Wegfolgefähigkeit angestrebt. Eine optimale koordinierte Wirkung verschiedener Fahrgestellsubsysteme (z. B. Lenkung und individuelle Drehmomentsteuerung) wird durch die Annahme eines zentralisierten, mehrfach betätigten Systemrahmens angestrebt. Die in dieser Arbeit entwickelten virtuellen Sensoren wurden experimentell mit dem Vehicle-Based Objective Tyre Testing (VBOTT) - Prüfstand von JAGUAR LAND ROVER und den fortschrittlichen Bewegungssteuerungsfunktionen mit dem mehrfach betätigten Bodenfahrzeug ”DevBot” von ARRIVAL und ROBORACE validiert

Lateral dynamics vehicle model: an analysis on different approaches with increasing level of model complexity

This thesis presents an analysis on different approaches with increasing level of model complexity with respect to lateral vehicle dynamics. In recent years, there has been an increasing interest in developing accurate and reliable models for lateral vehicle dynamics, in order to improve vehicle stability and control. The analysis begins with a review of the existing literature on lateral vehicle dynamics, and the differ- ent mathematical and physical modeling approaches that have been proposed. These include linear and nonlinear models, as well as more complex models that take into account factors such as tire dynamics and suspension dynamics, among others, that are not detailed in this study. Next, the thesis presents a comparative analysis of the different approaches based on machine learn- ing, using both simulation and experimental data from scientific literature. The analysis focuses on the accuracy and predictive power of the different deep learning models, as well as their computa- tional efficiency and ease of implementation. The results of the analysis indicate that while more complex models can provide more accurate pre- dictions of lateral vehicle dynamics, they also require significantly more computational resources and can be more difficult to implement. Therefore, the results of several publications indicate that deep learning models can provide highly accurate predictions for lateral vehicle dynamics, and can be trained with relatively small datasets. Overall, this study provides a comprehensive analysis on the use of machine learning techniques to develop competitive and high performance controllers for lateral vehicle dynamics and state estima- tion, highlighting the potential contribution in autonomous driving and vehicle stability and control that these methods will allow to achieve in the next decade

Numerical design of vehicles with optimal straight line stability on undulating road surfaces

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A state-of-the-art review on torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains

© 2019, Levrotto and Bella. All rights reserved. Electric vehicles are the future of private passenger transportation. However, there are still several technological barriers that hinder the large scale adoption of electric vehicles. In particular, their limited autonomy motivates studies on methods for improving the energy efficiency of electric vehicles so as to make them more attractive to the market. This paper provides a concise review on the current state-of-the-art of torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains (FEVIADs). Starting from the operating principles, which include the "control allocation" problem, the peculiarities of each proposed solution are illustrated. All the existing techniques are categorized based on a selection of parameters deemed relevant to provide a comprehensive overview and understanding of the topic. Finally, future concerns and research perspectives for FEVIAD are discussed

Ride and handling assessment of vehicles using four-post rig testing and simulation

The tuning of production road car suspension parameters in the development stage of a vehicle can be a lengthy and expensive procedure and commonly relies on the subjective judgements of test drivers to assess various aspects of ride and handling. The work in this thesis aims to create a testing and tuning technique using four-post rig testing and vehicle simulation to significantly reduce the amount of physical and subjective testing required within the development stage. A four-post rig testing technique is developed using modal sine sweep inputs to acquire the response of the vehicle in the heave, pitch, roll and warp modes of excitation. An analysis and parameter estimation method is developed based on four-post data and a 7 degree-of-freedom model, with four-post test data used to validate the parameter estimation and vehicle model simultaneously, obtaining satisfactory results in all but the roll mode of excitation. The BS 6841 [1] discomfort acceleration weightings are applied to the modal responses, with road input PSDs representative of standardised roads and driving cycles used to produce a comfort index value for a tested vehicle or setup. A novel performance index is created to estimate grip loss due to static and dynamic tyre properties for each axle, which allows the prediction of road input effects on the total grip and balance of the vehicle, as well as a driver requirement of steering input. MATLAB code is constructed for the parameter estimation procedure and for three general user interfaces to assist with the testing, tuning and benchmarking procedure. An objective-subjective validation exercise is carried out using a single vehicle with four different component setups which are tested on the four-post rig to determine comfort and performance index values, as well as recording the subjective assessments of three test drivers on two drive routes in the UK and Germany. The results show fair to good correlation for comfort measures but generally poor correlation to the performance index, mostly because of large variations between the drivers’ subjective assessment criteria

Tyre models for vehicle handling analysis under steady-state and transient manoeuvres

The work presented in this thesis is devoted to the study of mechanism of tyre force generation and its influence on handling dynamics of ground vehicles. The main part of the work involves the development of tyre models for use under steady-state and transient operating conditions. The general capability of these models is assessedin a full vehicle simulation environment. The interaction between tyre and vehicle dynamics is critically evaluated and the observed vehicle behaviour is related to the inherent characteristics of different tyre models. In the field of steady-state tyre modelling, two versions of a numerical tyre model are developed. The modelling procedure is carried out in accordance with the viscoelastic properties of rubber, which influence the mechanical properties of the tyre structure and play a significant role in the determination of friction in the tyre contact patch. Whilst the initial simple version of the tyre model assumes a parabolic pressure distribution along the contact, a later more elaborate model employs a numerical method for the calculation of the actual normal pressure distribution. The changes in the pressure distribution as a result of variations in the rolling velocity and normal load influence mainly the levels of self-aligning moment, whilst the force characteristics remain practically unaffected. The adoption of a velocity dependent friction law explains the force generating behaviour of tyres at high sliding velocities. The analysis is extended to the area of transient tyre behaviour with the development of a tyre model appropriate for the study of transient friction force generation within the contact patch. The model incorporates viscoelasticity and inertial contributions, and incorporates a numerical stick-slip law. These characteristics are combined together for the successful simulation of transient friction force generation. The methodologies developed for the modelling of transient friction and steady-state tyre force generation are combined and further extended in order to create a generic transient tyre model. This final model incorporates a discretised flexible viscoelastic belt with inertia and a separate fully-dynamic discretised tread, also with inertia and damping, for the simulation of actual prevailing conditions in the contact patch. The generic tyre model appears to be capable of performing under a variety of operating conditions, including periodic excitations and transient inputs which extend to the non-linear range of tyre behaviour. For the evaluation of the influence of the aforementioned tyre models on the handling responses of a vehicle, a comprehensive vehicle model is developed, appropriate for use in handling simulations. The two versions of the steady-state models and the generic transient model are interfaced with the vehicle model, and the response of the vehicle to a step-steer manoeuvre is compared with that obtained using the Magic Formula tyre model. The comparison between the responses is facilitated by the definition of a new measure, defined as the non-dimensional yaw impulse. It is found that the transience involved in tyre behaviour may largely affect the response of a vehicle to a prescribed input

Modeling of the interaction of rigid wheels with dry granular media

We analyze the capabilities of various recently developed techniques, namely Resistive Force Theory (RFT) and continuum plasticity implemented with the Material Point Method (MPM), in capturing dynamics of wheel--dry granular media interactions. We compare results to more conventionally accepted methods of modeling wheel locomotion. While RFT is an empirical force model for arbitrarily-shaped bodies moving through granular media, MPM-based continuum modeling allows the simulation of full granular flow and stress fields. RFT allows for rapid evaluation of interaction forces on arbitrary shaped intruders based on a local surface stress formulation depending on depth, orientation, and movement of surface elements. We perform forced-slip experiments for three different wheel types and three different granular materials, and results are compared with RFT, continuum modeling, and a traditional terramechanics semi-empirical method. Results show that for the range of inputs considered, RFT can be reliably used to predict rigid wheel granular media interactions with accuracy exceeding that of traditional terramechanics methodology in several circumstances. Results also indicate that plasticity-based continuum modeling provides an accurate tool for wheel-soil interaction while providing more information to study the physical processes giving rise to resistive stresses in granular media

Adaptive Robust Vehicle Motion Control for Future Over-Actuated Vehicles

International audienceMany challenges still need to be overcome in the context of autonomous vehicles. These vehicles would be over-actuated and are expected to perform coupled maneuvers. In this paper, we first discuss the development of a global coupled vehicle model, and then we outline the control strategy that we believe should be applied in the context of over-actuated vehicles. A gain-scheduled H ∞ controller and an optimization-based Control Allocation algorithms are proposed. High-fidelity co-simulation results show the efficiency of the proposed control logic and the new possibilities that could offer. We expect that both car manufacturers and equipment suppliers would join forces to develop and standardize the proposed control architecture for future passenger cars