Nonlinear energy harvesting from base excitation in automotive applications

Energy harvesting is an emerging technological field, aiming, among others, to harvest kinetic energy from mechanical oscillations and converting the same to useful electrical energy. Usually, the reclaimed energy is quite small, acquired by lightweight devices which can be positioned in confined spaces and do not significantly add to the system mass and inertia. This potential use is in line with the vehicular powertrain development principle of high output power- to-light weight ratio as this concept has progressively led to increasing vibratory energy. These devices would potentially supply a few mW of power, which can typically power automotive sensors, potentially reducing the ever-increasing vehicle wiring network. A multitude of such devices positioned strategically can recover some of the vibratory energy of a plethora of vibration phenomena. The paper outlines some of these phenomena and proposes the use of a magnetic translational harvester. A preliminary study based on an experimental set up and a devised non-linear model show good potential across a range of frequencies, typical of engine order vibration at engine idling condition. However, the potential exists for both the optimisation of the demonstrated observer and increased energy recovery for suitable location(s) in the powertrain system

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

Tire-Road Friction Estimation Using Slip-based Observers

In order to improve the security of the vehicles, the car industry focuses more and more on Active Safety. The objective is to introduce embedded electronic control systems to detect dangerous conditions, warn the driver and, in emergency situations, even take actions to avoid crash or at least reduce the violence of the impact. The tire-road friction coefficient which defines the maximum traction and braking capacities is very useful information for both the driver and electronic devices like ABS, ESP, roll-over prevention or collision mitigation. Unfortunately such a coefficient cannot be directly measured and has to be estimated from other available data. This thesis reviews the main directions followed by researchers around the world and then focuses on slip-based methods. The methods proposed in a few papers are implemented, compared and commented. Then some original solutions are proposed. First, a hybrid observer has been developed with the idea to classify roads into a few categories. The principle is very interesting and the implementation brings out many problems to take into consideration and some attempts of solutions.Secondly, a force observer and a tire friction model are combined. This natural approach works well in simulations

Design of an Elastic Actuation System for a Gait-Assistive Active Orthosis for Incomplete Spinal Cord Injured Subjects

A spinal cord injury severely reduces the quality of life of affected people. Following the injury, limitations of the ability to move may occur due to the disruption of the motor and sensory functions of the nervous system depending on the severity of the lesion. An active stance-control knee-ankle-foot orthosis was developed and tested in earlier works to aid incomplete SCI subjects by increasing their mobility and independence. This thesis aims at the incorporation of elastic actuation into the active orthosis to utilise advantages of the compliant system regarding efficiency and human-robot interaction as well as the reproduction of the phyisological compliance of the human joints. Therefore, a model-based procedure is adapted to the design of an elastic actuation system for a gait-assisitve active orthosis. A determination of the optimal structure and parameters is undertaken via optimisation of models representing compliant actuators with increasing level of detail. The minimisation of the energy calculated from the positive amount of power or from the absolute power of the actuator generating one human-like gait cycle yields an optimal series stiffness, which is similar to the physiological stiffness of the human knee during the stance phase. Including efficiency factors for components, especially the consideration of the electric model of an electric motor yields additional information. A human-like gait cycle contains high torque and low velocities in the stance phase and lower torque combined with high velocities during the swing. Hence, the efficiency of an electric motor with a gear unit is only high in one of the phases. This yields a conceptual design of a series elastic actuator with locking of the actuator position during the stance phase. The locked position combined with the series compliance allows a reproduction of the characteristics of the human gait cycle during the stance phase. Unlocking the actuator position for the swing phase enables the selection of an optimal gear ratio to maximise the recuperable energy. To evaluate the developed concept, a laboratory specimen based on an electric motor, a harmonic drive gearbox, a torsional series spring and an electromagnetic brake is designed and appropriate components are selected. A control strategy, based on impedance control, is investigated and extended with a finite state machine to activate the locking mechanism. The control scheme and the laboratory specimen are implemented at a test bench, modelling the foot and shank as a pendulum articulated at the knee. An identification of parameters yields high and nonlinear friction as a problem of the system, which reduces the energy efficiency of the system and requires appropriate compensation. A comparison between direct and elastic actuation shows similar results for both systems at the test bench, showing that the increased complexity due to the second degree of freedom and the elastic behaviour of the actuator is treated properly. The final proof of concept requires the implementation at the active orthosis to emulate uncertainties and variations occurring during the human gait

Electric Vehicle Efficient Power and Propulsion Systems

Vehicle electrification has been identified as one of the main technology trends in this second decade of the 21st century. Nearly 10% of global car sales in 2021 were electric, and this figure would be 50% by 2030 to reduce the oil import dependency and transport emissions in line with countries’ climate goals. This book addresses the efficient power and propulsion systems which cover essential topics for research and development on EVs, HEVs and fuel cell electric vehicles (FCEV), including: Energy storage systems (battery, fuel cell, supercapacitors, and their hybrid systems); Power electronics devices and converters; Electric machine drive control, optimization, and design; Energy system advanced management methods Primarily intended for professionals and advanced students who are working on EV/HEV/FCEV power and propulsion systems, this edited book surveys state of the art novel control/optimization techniques for different components, as well as for vehicle as a whole system. New readers may also find valuable information on the structure and methodologies in such an interdisciplinary field. Contributed by experienced authors from different research laboratory around the world, these 11 chapters provide balanced materials from theorical background to methodologies and practical implementation to deal with various issues of this challenging technology. This reprint encourages researchers working in this field to stay actualized on the latest developments on electric vehicle efficient power and propulsion systems, for road and rail, both manned and unmanned vehicles

Robust adaptive control of switched systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.Includes bibliographical references (leaves 141-149).In this thesis, robust adaptive controllers are developed for classes of switched nonlinear systems. Switched systems are those governed by differential equations, which undergo vector field switching due to sudden changes in model characteristics. Such systems arise in many applications such as mechanical systems with contacts, electrical systems with switches, and thermal-fluidic systems with valves and phase changes. The presented controllers guarantee system stability, under typical adaptive control assumptions, for systems with piecewise differentiable bounded parameters and piecewise continuous disturbances without requiring a priori knowledge on such parameters or disturbances. The effect of plant variation and switching is reduced to piecewise continuous and impulsive inputs acting on a Bounded Input Bounded State (BIBS) stable closed loop system. This, in turn, provides a separation between the robust stability and robust performance control problems. The developed methodology provides clear guidelines for steady-state and transient performance optimization and allows for parameter scheduling and multiple model controller adjustment techniques to be utilized with no stability concerns. The results are illustrated for various systems including contact-based robotic manipulation and Atomic Force Microscope (AFM) based nano-manipulation.by Khalid El Rifai.Ph.D