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When accelerating, traction from the tyres is necessary to move the vehicle forward. If too much torque is applied to the wheels of the vehicle, the tyres will start to spin and thereby the traction will decrease. This can occur when the driver of the vehicle applies to much throttle, but can be controlled with a traction control system that prevent the tyres from spinning and keeps the tyres at maximum traction to increase acceleration. In Formula Student competitions, every tenths of a second gained is vital and a traction control could help the driver to find these tenths of a second during acceleration. The purpose of this bachelor thesis was to design a slip ratio based traction control for the KTH Formula Student car DeV17 with focus on the acceleration event from standing start. A problem with standing start is the launch of the acceleration which were investigated along with a PID-controller. The model was developed in MATLAB's SIMULINK and simulated with IPG CarMaker. Small improvements in acceleration time were seen with the PID-controller but the launch did not see any improvements.

<p>För att ett fordon ska kunna bromsa, accelerera och svänga är friktion mellan däcken och vägen ett måste. Vid för mycket gaspådrag under en acceleration kan det hända att hjulen förlorar fäste och börjar spinna loss, något som leder till både försämrad kontroll över fordonet och att däcken slits ut i förtid. Traction controlsystemet förhindrar hjulen från att spinna loss och försöker maximera friktionen.</p><p>Målet med detta examensarbete är att utvärdera olika reglerprinciper samt att undersöka olika möjligheter för att reglera friktionen mellan däck och väg. Det är ett svårt reglerproblem, dels på grund av dess olinjäritet, dels på grund av det faktum att friktionen är en okänd parameter.</p><p>För att kunna undersöka olika reglermöjligheter har en modell över hjuldynamiken och en modell över drivlinan tagits fram i Matlabs simuleringsprogram Simulink. Därutöver har tre regulatorer designats: en fuzzy-regulator, en fuzzy-P-regulator och en PI-regulator. Regulatorerna utvärderades i tre tester som bland annat testade deras robusthet.</p><p>Fuzzy-regulatorn och fuzzy-P-regulatorn lyckades reglera systemet bra. PI-regulatorn gjorde däremot inte ett tillfredsställande jobb, mest på grund av dess behov av ett börvärde.</p> / <p>Traction is necessary for a vehicle to be able to brake, accelerate and turn. When pushing the accelerator pedal too hard during an acceleration, the wheel can loose traction and start spinning, which leads to a worsen vehicle control and also wears out the tyres faster. The traction control system prevents the wheels from spinning and tries to make the tyres maintain maximum traction.</p><p>The purpose of this master’s thesis is to evaluate different control methods and to investigate possible ways to control the traction. This is a difficult control problem due to its nonlinearity and the fact that the friction is an unknown parameter.</p><p>For the investigation, a model of the wheel dynamics and a model of the powertrain have been developed in Matlab’s simulation program Simulink. Furthermore, three different controllers have been designed; a fuzzy controller, a fuzzy-P controller and a PI controller. The controllers were evaluated in three test cycles that among others tested their robustness.</p><p>The fuzzy controller and the fuzzy-P controller managed to control the system very well. The PI controller, however, did not work satisfactory, mainly because of its need of a desired value.</p>

The thesis investigates control system integration in ADAMS and the thesis presents appropriate knowledge related to the topic as multi body system, acting forces between road and wheels, equation of motion regarding to the haulers, traction control system and differential locks. The emphasis of the thesis is to implement and test the automatic traction control (ATC) for the hauler into ADAMS and Simulink models. The ATC models are based on certain requirements provided by Volvo Construction Equipment. As expected, results indicate that the ATC model operates during simulation for various road conditions. Nevertheless, the ATC model includes a few defects which are observed in results. The significant achievement of the thesis is a great collaboration between ADAMS and Simulink model.

För att ett fordon ska kunna bromsa, accelerera och svänga är friktion mellan däcken och vägen ett måste. Vid för mycket gaspådrag under en acceleration kan det hända att hjulen förlorar fäste och börjar spinna loss, något som leder till både försämrad kontroll över fordonet och att däcken slits ut i förtid. Traction controlsystemet förhindrar hjulen från att spinna loss och försöker maximera friktionen. Målet med detta examensarbete är att utvärdera olika reglerprinciper samt att undersöka olika möjligheter för att reglera friktionen mellan däck och väg. Det är ett svårt reglerproblem, dels på grund av dess olinjäritet, dels på grund av det faktum att friktionen är en okänd parameter. För att kunna undersöka olika reglermöjligheter har en modell över hjuldynamiken och en modell över drivlinan tagits fram i Matlabs simuleringsprogram Simulink. Därutöver har tre regulatorer designats: en fuzzy-regulator, en fuzzy-P-regulator och en PI-regulator. Regulatorerna utvärderades i tre tester som bland annat testade deras robusthet. Fuzzy-regulatorn och fuzzy-P-regulatorn lyckades reglera systemet bra. PI-regulatorn gjorde däremot inte ett tillfredsställande jobb, mest på grund av dess behov av ett börvärde. / Traction is necessary for a vehicle to be able to brake, accelerate and turn. When pushing the accelerator pedal too hard during an acceleration, the wheel can loose traction and start spinning, which leads to a worsen vehicle control and also wears out the tyres faster. The traction control system prevents the wheels from spinning and tries to make the tyres maintain maximum traction. The purpose of this master’s thesis is to evaluate different control methods and to investigate possible ways to control the traction. This is a difficult control problem due to its nonlinearity and the fact that the friction is an unknown parameter. For the investigation, a model of the wheel dynamics and a model of the powertrain have been developed in Matlab’s simulation program Simulink. Furthermore, three different controllers have been designed; a fuzzy controller, a fuzzy-P controller and a PI controller. The controllers were evaluated in three test cycles that among others tested their robustness. The fuzzy controller and the fuzzy-P controller managed to control the system very well. The PI controller, however, did not work satisfactory, mainly because of its need of a desired value.

This thesis evaluates an electric vehicle with four independently-controlled in-wheel electric motors. The electric vehicle investigated in this work requires a main con- troller that not only coordinates with each individual motor drive controller, but is also needed to distribute torque and power to each in-wheel motor. The controller adjusts the speed of each motor to the driving conditions according to the require- ments and emulates the behavior of a mechanical di erential. Then, in addition to the electronic di erential controller, a simple yet robust control strategy for maximiz- ing traction force between tire and road is developed and presented. Moreover, the controller continuously senses the yaw rate and prevents over- and under-steering by adjusting the torque on the right or left wheels. Simulation and experimental results validate the proposed strategy.

Modern hybrid electric and pure electric vehicles are highly dependent on control algorithms to provide seamless safe and reliable operation under any driving condition, regardless of driver behavior. Three unique and independently operating supervisory control algorithms are introduced to improve reliability and vehicle performance on a series-hybrid electric vehicle with an all-wheel drive all-electric drivetrain. All three algorithms dynamically control or limit the amount of torque that can be delivered to the wheels through an all-electric drivetrain, consisting of two independently controlled brushless-direct current (BLDC) electric machines. Each algorithm was developed and validated following a standard iterative engineering development process which places a heavy emphasis on modeling and simulation to validate the algorithms before they are tested on the physical system. A comparison of simulated and in-vehicle test results is presented, emphasizing the importance of modeling and simulation in the design process.

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[pt] Em terrenos acidentados é crítico para robôs móveis manter uma adequada tração nas rodas, pois um excessivo deslizamento das mesmas pode fazer o robô capotar ou desviar da rota desejada. Também, se uma força excessiva é aplicada sobre uma região do terreno, pode levar o mesmo a ceder deixando as rodas presas. Para se evitar os problemas acima citados e ainda otimizar o consumo de energia em terrenos planos, a presente dissertação desenvolveu um controle de tração para terrenos acidentados com o intuito de aplicá- lo ao Robô Ambiental Híbrido (RAH) da Petrobrás. O RAH é um robô móvel anfíbio que está em fase de desenvolvimento no Laboratório de Robótica do CENPES (Petrobras), que poderá ser comandado por um operador ou se deslocar autonomamente. Esse robô faz parte do projeto Cognitus, braço tecnológico do projeto Piatam (Potenciais Impactos e Riscos Ambientais da Indústria de Óleo e Gás na Amazônia), e será aplicado na monitoração e coleta de dados do meio ambiente de dois gasodutos da Petrobrás na região Amazônica, o gasoduto Urucu (AM)- Porto Velho (RO) e o gasoduto Coari (AM) - Manaus (AM). A técnica de controle de tração de veículos robóticos em terrenos acidentados desenvolvida visa controlar a velocidade ao mesmo tempo em que garante a estabilidade dinâmica, não deslizamento das rodas, evita a saturação dos motores, e em certas condições ainda permite minimizar a potência requerida através do conhecimento dos ângulos de contato entre as rodas e o terreno. Foram feitas duas modelagens independentes, uma considerando a suspensão do robô flexível e a outra considerando o veículo robótico como um corpo rígido, sendo ambas para o caso plano (2D).Foram realizadas simulações em terrenos suaves e acidentados, as quais comprovaram a eficácia das técnicas de controle propostas. / [en] Abstract Silva, Alexandre F. Barral Silva; Meggiolaro, Marco Antonio. Traction Control to Mobile Robotic Systems in Rough Terrain. Rio de Janeiro, 2004. 194 p. MSc. Thesis - Departamento de Engenharia Mecânica, Pontifícia Universidade Católica do Rio de Janeiro. In rough terrain it is critical for mobile robots to maintain adequate wheel traction, because excessive sliding could cause the robot to roll over or deviate from its intended path. Also, if an excessive force is applied onto the terrain, the soil may fail and trap the robot wheels. To avoid these problems, and also minimize the power consumption on even terrain, the present work develops a rough terrain traction control to be applied to the Hybrid Environmental Robot (HER) from Petrobras. The HER is an amphibious mobile robot developed by the Robotics Laboratory from CENPES (Petrobras). It can be commanded by an operator or autonomously. This robot is part of the Cognitus Project, technological branch of the Piatam project (Potential Impacts and Environmental Risks of the Oil and Gas Industry in the Amazon). It will be used for monitoring and environmental data collecting along two gas pipelines in the Amazon region, the Urucu (AM) - Porto Velho (RO) and the Coari (AM) - Manaus (AM). The developed traction control of robotic vehicles in rough terrain aims to control the speed at the same time that it guarantees dynamic stability, no slip of the wheels, prevents motor saturation, and under certain conditions it may also allow for the minimization of the required power. This control needs the knowledge of the current state of the robot, including the contact angles between its wheels and the terrain. Two independent 2D models have been proposed, one including the suspension compliance and one considering the robotic vehicle as a rigid body. Simulations have been performed in even and rough terrains, proving the effectiveness of the proposed control techniques.

Human expert drivers have the unique ability to build complex perceptive models using correlated sensory inputs and outputs. In the case of longitudinal vehicle traction, this work will show a direct correlation in longitudinal acceleration to throttle input in a controlled laboratory environment. In fact, human experts have the ability to control a vehicle at or near the performance limits, with respect to vehicle traction, without direct knowledge of the vehicle states; speed, slip or tractive force. Traditional algorithms such as PID, full state feedback, and even sliding mode control have been very successful at handling low level tasks where the physics of the dynamic system are known and stationary. The ability to learn and adapt to changing environmental conditions, as well as develop perceptive models based on stimulus-response data, provides expert human drivers with significant advantages. When it comes to bandwidth, accuracy, and repeatability, automatic control systems have clear advantages over humans; however, most high performance control systems lack many of the unique abilities of a human expert. The underlying motivation for this work is that there are advantages to framing the traction control problem in a manner that more closely resembles how a human expert drives a vehicle. The fundamental idea is the belief that humans have a unique ability to adapt to uncertain environments that are both temporal and spatially varying. In this work, a novel approach to traction control is developed using an anthropomimetic control synthesis strategy. The proposed anthropomimetic traction control algorithm operates on the same correlated input signals that a human expert driver would in order to maximize traction. A gradient ascent approach is at the heart of the proposed anthropomimetic control algorithm, and a real-time implementation is described using linear operator techniques, even though the tire-ground interface is highly non-linear. Performance of the proposed anthropomimetic traction control algorithm is demonstrated using both a longitudinal traction case study and a combined mode traction case study, in which longitudinal and lateral accelerations are maximized simultaneously. The approach presented in this research should be considered as a first step in the development of a truly anthropomimetic solution, where an advanced control algorithm has been designed to be responsive to the same limited input signals that a human expert would rely on, with the objective of maximizing traction. This work establishes the foundation for a general framework for an anthropomimetic control algorithm that is capable of learning and adapting to an uncertain, time varying environment. The algorithms developed in this work are well suited for efficient real time control in ground vehicles in a variety of applications from a driver assist technology to fully autonomous applications. / Ph. D.