Smart Traction Control Systems for Electric Vehicles Using Acoustic Road-type Estimation

The application of traction control systems (TCS) for electric vehicles (EV) has great potential due to easy implementation of torque control with direct-drive motors. However, the control system usually requires road-tire friction and slip-ratio values, which must be estimated. While it is not possible to obtain the first one directly, the estimation of latter value requires accurate measurements of chassis and wheel velocity. In addition, existing TCS structures are often designed without considering the robustness and energy efficiency of torque control. In this work, both problems are addressed with a smart TCS design having an integrated acoustic road-type estimation (ARTE) unit. This unit enables the road-type recognition and this information is used to retrieve the correct look-up table between friction coefficient and slip-ratio. The estimation of the friction coefficient helps the system to update the necessary input torque. The ARTE unit utilizes machine learning, mapping the acoustic feature inputs to road-type as output. In this study, three existing TCS for EVs are examined with and without the integrated ARTE unit. The results show significant performance improvement with ARTE, reducing the slip ratio by 75% while saving energy via reduction of applied torque and increasing the robustness of the TCS.Comment: Accepted to be published by IEEE Trans. on Intelligent Vehicles, 22 Jan 201

A multisensing setup for the intelligent tire monitoring

The present paper offers the chance to experimentally measure, for the first time, the internal tire strain by optical fiber sensors during the tire rolling in real operating conditions. The phenomena that take place during the tire rolling are in fact far from being completely understood. Despite several models available in the technical literature, there is not a correspondently large set of experimental observations. The paper includes the detailed description of the new multi-sensing technology for an ongoing vehicle measurement, which the research group has developed in the context of the project OPTYRE. The experimental apparatus is mainly based on the use of optical fibers with embedded Fiber Bragg Gratings sensors for the acquisition of the circumferential tire strain. Other sensors are also installed on the tire, such as a phonic wheel, a uniaxial accelerometer, and a dynamic temperature sensor. The acquired information is used as input variables in dedicated algorithms that allow the identification of key parameters, such as the dynamic contact patch, instantaneous dissipation and instantaneous grip. The OPTYRE project brings a contribution into the field of experimental grip monitoring of wheeled vehicles, with implications both on passive and active safety characteristics of cars and motorbikes

Tien ja renkaan välisen kitkapotentiaalin arviointi inertia-anturin mittausten perusteella alhaisen kitkan olosuhteissa

Electronic driver aids have become commonplace in passenger cars in the last two decades. These systems improve safety by attempting to prevent the vehicle from exceeding the limits of its handling and becoming unstable. Those limits are largely defined by the tire-road friction potential. Consequently, the friction potential is one of the variables used in the control logics of these systems. Thus, by estimating the potential, the effectiveness of electronic driver aids can be significantly improved. The purpose of this thesis is to develop and test the accuracy of a novel friction estimation algorithm that uses the accelerations and yaw, pitch, and roll rates of the vehicle measured with an inertial sensor as its basis. The algorithm was designed to account for the effects of inclination and banking, as they influence the acceleration capabilities of the vehicle and the acceleration measurements. Three different versions of the algorithm were created so that the effects of compensating for inclination and bank angle could be assessed. Additionally, the algorithm was designed in such a way that it should be able to estimate the friction potential accurately in start maneuvers where the steering angle is high. The single-track model was incorporated into the algorithm for this purpose. The algorithm must also detect when the vehicle is on the limits of its handling, as it is only then that the measured friction coefficient is equal to the friction potential. The algorithm accomplishes this by monitoring the states of the driver aids. The algorithm was tested with simulations and experimental tests. The research vehicle was modelled in simulation software, including the most significant electronic driver aids. A variety of acceleration, braking, and cornering maneuvers were performed in order to test the capabilities of the algorithm on roads with varying inclinations and bank angles. The tests focused on low-friction conditions, as friction estimation is at its most beneficial in such circumstances. The results show that this novel algorithm is capable of estimating the friction potential accurately in most acceleration, braking, and cornering situations on inclined, banked, and level roads. However, the results also indicate that accounting for the inclination and the bank angle makes little difference in the friction estimation. The algorithm calculates the tire-road forces largely based on the longitudinal and lateral acceleration measurements of the inertial sensor, which contain a component of gravitational acceleration if the road is not level. Thus, the effects of inclination and bank angle get mostly compensated even in the versions that were not specifically designed to account for them. The results also show that the friction potential estimation produced by the single-track model in high steering angle start maneuvers contains significant error due to the two front tires producing forces in different directions in such situations.Elektronisista ajoavuista on tullut yleisiä henkilöautoissa viimeisten kahden vuosikymmenen aikana. Nämä järjestelmät parantavat turvallisuutta yrittämällä estää autoa ylittämästä suorituskykyrajojaan, jolloin auto muuttuu epästabiiliksi. Kyseiset rajat perustuvat laajalti renkaan ja tien väliseen kitkapotentiaaliin. Kitkapotentiaali on siksi yksi niistä muuttujista, joita nämä järjestelmät käyttävät ohjauslogiikoissaan. Täten ajoapujen toimintaa voidaan tehostaa merkittävästi estimoimalla kitkapotentiaalia. Tämän opinnäytetyön tarkoituksena on luoda uudenlainen kitkaestimointialgoritmi, jonka toiminta perustuu inertia-anturilla mitattaviin auton kiihtyvyyksiin ja kallistumis-, nyökkimis- ja pystykiertymänopeuksiin, ja tutkia sen tarkkuutta. Algoritmi suunniteltiin huomioimaan tien nousu- ja sivuttaiskulmien vaikutus, sillä ne vaikuttavat auton kiihtyvyysrajoihin ja mitattuihin kiihtyvyyslukemiin. Algoritmista luotiin kolme eri versiota, jotta tien kulmien kompensoinnin vaikutusta voitaisiin arvioida. Lisäksi algoritmi suunniteltiin siten, että sen pitäisi kyetä arvioimaan kitkapotentiaalia tarkasti myös sellaisissa liikkeellelähtötilanteissa, joissa ohjauskulma on suuri. Kaksipyörämalli sisällytettiin algoritmiin tätä tarkoitusta varten. Algoritmin on myös kyettävä havaitsemaan, milloin auto on lähellä suorituskykyrajojaan, koska arvioitu kitkakerroin on lähellä kitkapotentiaalia vain silloin. Algoritmi toteuttaa tämän tarkkailemalla ajoapujen tiloja. Algoritmia testattiin simulaatioiden ja koeautolla tehtävien testien avulla. Koeauto ja sen merkittävimmät ajoavut mallinnettiin simulaatio-ohjelmistossa. Monenlaisia kiihdytys-, jarrutus- ja kaarreajoliikkeitä suoritettiin algoritmin kykyjen tutkimiseksi erilaisia kallistuksia sisältävillä teillä. Testit keskittyivät alhaisen kitkan olosuhteisiin, sillä kitkaestimoinnista on eniten hyötyä juuri sellaisissa oloissa. Tulokset näyttävät, että luotu algoritmi kykenee arvioimaan kitkapotentiaalia tarkasti useimmissa kiihdytys-, jarrutus- ja kaarreajotilanteissa mäkisillä, kallistetuilla ja tasaisilla teillä. Tulokset kuitenkin myös osoittavat, että nousu- ja sivuttaiskulman huomiointi algoritmissa tuottaa vain pienen eron kitkaestimoinnissa. Algoritmi laskee rengasvoimat perustuen enimmäkseen inertia-anturin pitkittäis- ja sivuttaiskiihtyvyysmittauksiin, jotka sisältävät putoamiskiihtyvyyskomponentin, mikäli tie ei ole tasainen. Täten nousu- ja sivuttaiskulmien vaikutus kompensoituu enimmäkseen pois niissäkin algoritmiversioissa, joita ei erityisesti suunniteltu huomioimaan kyseisiä kulmia. Tulokset näyttävät myös, että kaksipyörämallin tuottama kitkapotentiaaliarvio suuren ohjauskulman liikkeellelähtötilanteissa sisältää merkittävästi virhettä johtuen siitä, että etupyörät tuottavat tällöin voimaa eri suuntiin

Design of a Smart Tire Sensor System

A research project is conducted that involves the design of a smart tire sensor system that can determine six tire outputs, including tire longitudinal force, tire lateral force, tire vertical force, tire aligning moment, tire / road friction coefficient and tire air inflation pressure. All of these quantities are estimated using in-tire deformation sensors. The rationale for conducting the smart tire research project is that its results have the potential to improve ground vehicle safety. The objectives of the research project are to identify the quantity and types of sensors required, determine the sensor locations and orientations in the tire, develop post-processing methods for the raw sensor output and confirm correct operation of the sensor system, which involves prototyping and physical testing. Strain is predicted in the tire inner liner as part of a tire finite element analysis study. The tire finite element model is used to calculate strain (inputs) and tire forces (outputs) for use in artificial neural networks. Results from the radial basis function networks studied are excellent, with calculated tire forces within 1% and tire aligning moment within 1%. The conclusion is that radial basis function networks can likely be used effectively for analysis of strain sensor measurements in the smart tire sensor system. Further studies using virtual strain show that the system should have two in-tire strain sensors located near one another at the outside sidewall, with one oriented longitudinally and the other oriented radially, along with an angular position sensor. Commercially available piezoelectric deformation sensors are installed in this layout, along with a rotary encoder, in a smart tire physical prototype. On-road data collected during physical testing are used with radial basis function neural networks to estimate the three orthogonal tire forces and the tire aligning moment. The networks are found capable of predicting the correct trends in the tire force data over several testing events. While the smart tire sensor system in its current state of development is not production-ready, the research project has resulted in new scientific knowledge that will be the foundation of future smart tire work. Contributions include the identification of in-tire sensor quantity, locations and orientations, confirmation that an angular position measurement is necessary and the determination of the artificial neural network architecture. The most significant remaining smart tire technical hurdle is the identification of a sufficiently durable strain sensor for in-tire use. If this strain sensor can be found, the next steps will include validation of the non-force tire estimates and studies of temperature effects, wireless data transmission and energy harvesting for a battery free design. Despite these outstanding concerns, the results of the smart tire research project show that the concept is feasible and further work is justified.1 yea

Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics 2015

This volume contains the full papers accepted for presentation at the ECCOMAS Thematic Conference on Multibody Dynamics 2015 held in the Barcelona School of Industrial Engineering, Universitat Politècnica de Catalunya, on June 29 - July 2, 2015. The ECCOMAS Thematic Conference on Multibody Dynamics is an international meeting held once every two years in a European country. Continuing the very successful series of past conferences that have been organized in Lisbon (2003), Madrid (2005), Milan (2007), Warsaw (2009), Brussels (2011) and Zagreb (2013); this edition will once again serve as a meeting point for the international researchers, scientists and experts from academia, research laboratories and industry working in the area of multibody dynamics. Applications are related to many fields of contemporary engineering, such as vehicle and railway systems, aeronautical and space vehicles, robotic manipulators, mechatronic and autonomous systems, smart structures, biomechanical systems and nanotechnologies. The topics of the conference include, but are not restricted to: ● Formulations and Numerical Methods ● Efficient Methods and Real-Time Applications ● Flexible Multibody Dynamics ● Contact Dynamics and Constraints ● Multiphysics and Coupled Problems ● Control and Optimization ● Software Development and Computer Technology ● Aerospace and Maritime Applications ● Biomechanics ● Railroad Vehicle Dynamics ● Road Vehicle Dynamics ● Robotics ● Benchmark ProblemsPostprint (published version

Advances in Robotics, Automation and Control

The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man

Advanced Sensing and Control for Connected and Automated Vehicles

Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs

Recent Advances and Future Trends in Pavement Engineering

This Special Issue “Recent Advances and Future Trends in Pavement Engineering” was proposed and organized to present recent developments in the field of innovative pavement materials and engineering. The 12 articles and state-of-the-art reviews highlighted in this editorial are related to different aspects of pavement engineering, from recycled asphalt pavements to alkali-activated materials, from hot mix asphalt concrete to porous asphalt concrete, from interface bonding to modal analysis, and from destructive testing to non-destructive pavement monitoring by using fiber optics sensors. This Special Issue partly provides an overview of current innovative pavement engineering ideas that have the potential to be implemented in industry in the future, covering some recent developments

Multibody dynamics 2015

This volume contains the full papers accepted for presentation at the ECCOMAS Thematic Conference on Multibody Dynamics 2015 held in the Barcelona School of Industrial Engineering, Universitat Politècnica de Catalunya, on June 29 - July 2, 2015. The ECCOMAS Thematic Conference on Multibody Dynamics is an international meeting held once every two years in a European country. Continuing the very successful series of past conferences that have been organized in Lisbon (2003), Madrid (2005), Milan (2007), Warsaw (2009), Brussels (2011) and Zagreb (2013); this edition will once again serve as a meeting point for the international researchers, scientists and experts from academia, research laboratories and industry working in the area of multibody dynamics. Applications are related to many fields of contemporary engineering, such as vehicle and railway systems, aeronautical and space vehicles, robotic manipulators, mechatronic and autonomous systems, smart structures, biomechanical systems and nanotechnologies. The topics of the conference include, but are not restricted to: Formulations and Numerical Methods, Efficient Methods and Real-Time Applications, Flexible Multibody Dynamics, Contact Dynamics and Constraints, Multiphysics and Coupled Problems, Control and Optimization, Software Development and Computer Technology, Aerospace and Maritime Applications, Biomechanics, Railroad Vehicle Dynamics, Road Vehicle Dynamics, Robotics, Benchmark Problems. The conference is organized by the Department of Mechanical Engineering of the Universitat Politècnica de Catalunya (UPC) in Barcelona. The organizers would like to thank the authors for submitting their contributions, the keynote lecturers for accepting the invitation and for the quality of their talks, the awards and scientific committees for their support to the organization of the conference, and finally the topic organizers for reviewing all extended abstracts and selecting the awards nominees.Postprint (published version

Diseño de un sistema de detección del deslizamiento lateral para neumáticos instrumentados mediante extensometría

Mención Internacional en el título de doctorLos neumáticos han sido siempre un área de interés tanto para la sociedad como para la industria automovilística. Como los únicos elementos que mantienen el contacto entre el vehículo y la calzada, los neumáticos son un factor clave en el rendimiento, confort, consumo de combustible y seguridad de los vehículos. Aunque las prestaciones de los neumáticos actuales son adecuadas para la gran mayoría de situaciones, éstos son sólo elementos pasivos que no asisten activamente a los conductores o a los sistemas de control de los vehículos para mejorar la experiencia de conducción y la seguridad del tráfico. Debido a las características no lineales del contacto neumático-calzada, es difícil aplicar la fuerza exacta al pedal para detener el vehículo en la mínima distancia sin bloquear las ruedas ni perder el control del vehículo, que podría resultar en un accidente de tráfico a menos que el control de estabilidad (ESP) o el ABS actúen. Además, la situación podría empeorar si las condiciones de la calzada no son óptimas, como en caso de lluvia o barro donde la fricción varía. La posibilidad de que los neumáticos contribuyan activamente en este tipo de situaciones depende de su capacidad para proporcionar información a conductores y sistemas electrónicos para que intervengan antes de que se produzca un accidente. Estos son algunos de los motivos para desarrollar los denominados “neumáticos inteligentes”, comúnmente definidos como neumáticos instrumentados con sensores que serían capaces de proporcionar información en tiempo real sobre las condiciones de trabajo e interactuar con diferentes sistemas de control del vehículo para mejorar sus prestaciones, así como prevenir a los conductores de potenciales peligros. Sin embargo, para la obtención de información a partir de dichos sensores se deben considerar múltiples obstáculos, como la compatibilidad de los mismos con las características del caucho, la transmisión de datos o temas económicos, pero, sobre todo, el mayor obstáculo es cumplir con las necesidades energéticas de los componentes electrónicos. El potencial y las dificultades para su desarrollo hacen de los neumáticos inteligentes uno de los más prometedores y ambiciosos campos de investigación para ingenieros e investigadores. Los sistemas de monitorización de la presión del neumático (TPMS) fueron introducidos en 2002, siendo los primeros sistemas producidos y desarrollados en masa. Aunque fueron un gran logro, el potencial del neumático inteligente es aún mayor; tendría el objetivo final de monitorizar en tiempo real las fuerzas en el contacto neumático-calzada, el coeficiente de fricción, la condición de la calzada, etc. De este modo, el vehículo tendría un sistema de seguridad activo con información fiable sobre las condiciones de trabajo del neumático. En esta Tesis Doctoral se presenta un método de estimación de las condiciones de trabajo de un neumático instrumentado mediante extensometría y el coeficiente de adherencia lateral solicitado en el contacto neumático-calzada, detectando el deslizamiento lateral del mismo. Se han llevado a cabo una serie de ensayos mediante bandas extensométricas y un banco de pruebas de neumáticos. Estos equipos se eligieron para medir la deformación del neumático bajo condiciones dinámicas, que podrían ayudar a introducir sistemas de neumáticos inteligentes en un futuro próximo. Los ensayos se centran en analizar la influencia de la presión de inflado, la fuerza vertical, el ángulo de deriva y el ángulo de caída en los valores máximos de deformación y la medida de fuerza lateral para establecer cómo estos parámetros están relacionados. Los datos experimentales se han utilizado para estimar condiciones de trabajo mediante lógica difusa, desarrollando un sistema de detección del deslizamiento basado en un modelo experimental del comportamiento de la fuerza lateral. Los resultados de los ensayos y de las simulaciones confirman la viabilidad de las bandas extensométricas y del modelo computacional propuesto para resolver las características no lineales de los parámetros del neumático, convirtiendo éste en un sistema de seguridad activo.Tires have always been an area of interest for society and the automotive industry as well. As the only part that keeps the contact between the vehicle chassis and the road, they are a key factor on performance, comfort, fuel consumption and safety of vehicles. Despite the fact that current tires perform well in a huge variety of situations, they are just passive elements that do not contribute actively to driver or vehicle control systems to improve the driving experience and traffic safety. Due to the non-linear tire-road contact features, it is difficult to apply the exact braking force to stop the vehicle for the minimum distance without locking the wheels and, as a consequence, losing control of the vehicle which may result in a traffic accident unless Electronic Stability Control (ESC) or Anti-Lock Braking System (ABS) take action. Moreover, the situation may be even worse if unsuitable road conditions are considered, like wet or muddy surfaces where friction changes. The possibility of tires to take active part in this sort of situations is subject to its potential to provide information for drivers and active control systems to intervene before a crash occurs. These are some of the reasons to develop the so-called “intelligent tires”. They are usually define as tires equipped with sensors that would be able to monitor and provide information in real time about tire working conditions and interact with different vehicle dynamics control systems to improve their performance as well as warning the driver of potential hazards. However, in order to get information from sensors equipped in tires many obstacles must be overcame, such as the compatibility of the sensors with tire rubber properties, data transmission or economic issues, but above all the main obstacle is to meet the power requirements of all the electronic components. The prospects and difficulties of intelligent tires them in one of the most promising and ambitious research fields for researchers and automotive engineers. Concerning intelligent tires’ developments, the Tire Pressure Monitoring Systems (TPMS) were introduce in 2002, these being the first such systems introduced in the automotive market. Although they were a great achievement, intelligent tire technology has bigger prospects than TPMS. The intelligent tire concept would have the final aim of monitoring, in real time, the forces at the tire-road interface, friction coefficient, slip angle, road condition, and tire wear. In this way, the vehicle would have an active safety system provided with reliable information about the tire working conditions. In this Thesis, a strain-based method to estimate tire working conditions, lateral friction coefficient and detect the lateral tire’s slip is presented. A series of experiments by means of a tire equipped with strain sensors on an indoor tire test rig have been carried out. This equipment was selected to measure strain dynamic behaviour based on tire working conditions, which could help to introduce intelligent tire systems in the near future. The tests focused on the influence of pressure, rolling speed, vertical load, slip angle and camber angle on maximum strain values and lateral force measurements to elucidate how tire’s deformation and lateral force are interconnected. The experimental data have been used to estimate some tire working conditions by Fuzzy Logic, developing a tire slip detection system based on an experimental model of the lateral force behaviour to estimate the lateral friction coefficient and detect the tires’ loss of grip. The simulation and test results confirm the feasibility of strain sensors and the proposed computational model to solve the non-linearity characteristics of the tires’ parameters and turn tires into an active safety system.Programa Oficial de Doctorado en Ingeniería Mecánica y de Organización IndustrialPresidente: José Luis San Román García.- Secretario: Fernando Viadero Rueda.- Vocal: Gabriel Cornel Anghelach