A Computationally Efficient Path Following Control Strategy of Autonomous Electric Vehicles with Yaw Motion Stabilization

his paper proposes a computationally efficient path following control strategy of autonomous electric vehicles (AEVs) with yaw motion stabilization. First, the nonlinear control-oriented model including path following model, single track vehicle model, and Magic Formula tire model, are constructed. To handle the stability constraints with ease, the nonlinear model predictive control (NMPC) technique is applied for path following issue. Here NMPC control problem is reasonably established with the constraints of vehicle sideslip angle, yaw rate, steering angle, lateral position error, and Lyapunov stability. To mitigate the online calculation burden, the continuation/ generalized minimal residual (C/GMRES) algorithm is adopted. The deadzone penalty functions are employed for handling the inequality constraints and holding the smoothness of solution. Moreover, the varying predictive duration is utilized in this paper so as to fast gain the good initial solution by numerical algorithm. Finally, the simulation validations are carried out, which yields that the proposed strategy can achieve desirable path following and vehicle stability efficacy, while greatly reducing the computational burden compared with the NMPC controllers by active set algorithm or interior point algorithm

Climbing and Walking Robots

With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information

Climbing and Walking Robots

Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study

Optimal handling characteristics for electric vehicles with torque vectoring.

Torque vectoring by virtue of independent electric motors is the focus of an increasing number of studies as electric vehicles gain prominence as the chosen direction for the automotive industry. Building on active yaw control systems developed over the past decades, torque vectoring benefits from the high-responsiveness and controllability of the electric motor actuator. Furthermore, and especially in the case of vehicles equipped with one independent motor per wheel, the overall performance envelope of the vehicle is significantly improved, as well as the ability to actively shape the vehicle handling. Much attention has been focussed on controller development and control allocation aspects of torque vectoring controllers, but little on the appropriate yaw rate reference. Optimal control studies have been successfully used to mimic the expert driver in both minimum-time circuit racing and high-sideslip rally driving, and can offer insight into how to optimally tune active chassis control systems, such as torque vectoring yaw control. The main aim of this thesis was to investigate the optimal handling characteristics of an electric vehicle with four independent electric motors at the limits of performance. A TV controller was first developed for a prototype sportscar with 4 independent motors, employing a model-based design process that encompassed real-time software in the loop testing. Real-world track testing demonstrated the controller was able to successfully modify the handling characteristic of the vehicle in both understeer and oversteer directions, achieving good controller performance in steady-state and transient manoeuvres. The limit performance of the TV-controlled vehicle was subsequently investigated in the simulation domain. Numerical techniques were used to solve optimal control problems for a single-track vehicle model with linear tyres and an external yaw moment term representing the overall yaw moment arising from the difference in torques at each wheel. For a U-turn manoeuvre, it was shown that torque vectoring significantly lowers manoeuvre time in comparison with the vehicle without TV active, and that modifying the passive understeer gradient does not affect manoeuvre time. The system dynamics were reformulated to include a feedback torque vectoring controller. The target yaw rate reference was varied and it was found that the manoeuvre time was highly sensitive to the yaw rate reference. For minimising laptime, the target understeer gradient should be set to the passive understeer gradient value. The methodology was repeated for a higher fidelity model including nonlinear tyres and lateral load transfer, and found that when the torque vectoring controller was included in the system dynamics, the manoeuvre time showed little sensitivity to the target understeer gradient. Following the contradictory results of the optimal control problems, the vehicle models were investigated next. Time optimal yaw rate gain surfaces were generated from further minimum-time optimal control problems. Open-loop manoeuvres investigating effects of tyre model, lateral load transfer and torque vectoring generation mechanism found that tyre modelling was the dominant differentiator and tyre nonlinearity is an essential modelling consideration. Optimal control techniques have been used for high sideslip manoeuvring for conventional vehicles but no studies have explored the effects of torque vectoring on agility. In the final chapter, an aggressive turn-around manoeuvre was simulated and it was found that torque vectoring can significantly increase agility and reduce the space taken for an aggressive turn-around manoeuvre. Reducing yaw inertia increased agility, as well as increasing longitudinal slips limits. A critique of agility metrics in this context was given.PhD in Transport System

Integrated Vehicle Stability and Power Management Controls for Electric Vehicles

An integrated vehicle controller is presented for electric vehicles using independently driven wheel motors. This topology takes an optimal control approach to enhancing a vehicle's performance, stability, and energy consumption metrics simultaneously in a unified software structure. The logical output of this algorithm is a set of re-distributed wheel torques, to create torque vectoring for stability-focused yaw rate tracking, and longitudinal biasing to modify motor load for energy savings. A real-time numerical approach to solving the optimization problem is also presented, and shown to offer benefits over a closed form analytic approach. In this, solution constraints are used to link considerations such as nonlinear motor limits, tire friction envelopes, and lower-level traction control loops. To test the efficacy of this control structure, two vehicle test platforms were constructed as retrofits of production gas SUVs for electric drive. For this, the component layout is given, followed by an explanation of the software code structure as performed in a Simulink/Carsim/dSpace environment. Results from these platforms are given, with experimental and simulation data for traction control, yaw performance tracking and drive cycle power consumption. Proven performance over a variety of maneuvers and surface conditions further demonstrate the controller's stability and suitability for mass production.1 yea

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

Reconfigurable Integrated Vehicle Stability Control Using Optimal Control Techniques

The motivation for the development of vehicle stability control systems comes from the fact that vehicle dynamic behavior in unfavorable driving conditions such as low road-tire adhesion and high speed differs greatly from its nominal behavior. Due to this unexpected behavior, a driver may not be successful in controlling the vehicle in challenging driving situations based only on her/his everyday driving experience. Several noteworthy research works have been conducted on stability control systems over the last two decades to prevent car accidents due to human error. Most of the resultant stability controllers contain individual modules, where each perform a particular task such as yaw tracking, sideslip control, or wheel slip control. These design requirements may contradict each other in some driving scenarios. In such situations, inconsistent control actions can be generated with individual modules. The development of a stability controller that can satisfy diverse and often contradictory requirements is a great challenge. In general, transferring a control structure from one vehicle to another with a different drivetrain layout and actuation system configuration requires remarkable rectifications and repetition of tuning processes from the beginning to achieve a similar performance. This can be considered to be a serious drawback for car manufacturing companies since it results in extra effort, time, and expenses in redesigning and retuning the controller. In this thesis, an integrated controller with a modular structure has been designed to concurrently provide control of the vehicle chassis (yaw rate and sideslip control) and wheel stability (wheel slip ratio control). The proposed control structure incorporates longitudinal and lateral vehicle dynamics to decide on a unified control action. This control action is an outcome of solving an optimization problem that considers all the control objectives in a single cost function, so integrated wheel and vehicle stability is guaranteed. Moreover, according to the particular modular design of the proposed control structure, it can be easily reconfigured to work with different drivetrain layouts such as all-wheel-drive, front-wheel-drive, and rear-wheel-drive, as well as various actuators such as torque vectoring, differential braking, and active steering systems. The high-level control module provides a Center of Gravity (CG) based error analysis and determines the required longitudinal forces and yaw moment adjustments. The low-level control module utilizes this information to allocate control actions optimally at each vehicle corner (wheel) through a single or multi-actuator regime. In order to consider the effect of the actuator dynamics, a mathematical description of the auction system is included in distribution objective function. Therefore, a legitimate control performance is promised in situations requiring shifting from one configuration to another with minimal modifications. The performance of the proposed modular control structure is examined in simulations with a high-fidelity model of an electric GM Equinox vehicle. The high-fidelity model has been developed and provided by GM and the use of the model is to reduce the number of labor-intensive vehicle test and is to test extreme and dangerous driving conditions. Several driving scenarios with severe steering and throttle commands, then, are designed to evaluate the capability of the proposed control structure in integrated longitudinal and lateral vehicle stabilization on slippery road condition. Experimental tests also have been performed with two different electric vehicles for real-time implementation as well as validation purposes. The observations verified the performance qualifications of the proposed control structure to preserve integrated wheel and vehicle chassis stability in all track tests

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