In this work we reproduce driving techniques to mimic expert race drivers and obtain the open-loop control signals that may be used by auto-pilot agents driving autonomous ground wheeled vehicles. Race drivers operate their vehicles at the limits of the acceleration envelope. An accurate characterization of the acceleration capacity of the vehicle is required. Understanding and reproduction of such complex maneuvers also require a physics-based mathematical description of the vehicle dynamics. While most of the modeling issues of ground-vehicles/automobiles are already well established in the literature, lack of understanding of the physics associated with friction generation results in ad-hoc approaches to tire friction modeling. In this work we revisit this aspect of the overall vehicle modeling and develop a tire friction model that provides physical interpretation of the tire forces. The new model is free of those singularities at low vehicle speed and wheel angular rate that are inherent in the widely used empirical static models. In addition, the dynamic nature of the tire model proposed herein allows the study of dynamic effects such as transients and hysteresis. The trajectory-planning problem for an autonomous ground wheeled vehicle is formulated in an optimal control framework aiming to minimize the time of travel and maximize the use of the available acceleration capacity. The first approach to solve the optimal control problem is using numerical techniques. Numerical optimization allows incorporation of a vehicle model of high fidelity and generates realistic solutions. Such an optimization scheme provides an ideal platform to study the limit operation of the vehicle, which would not be possible via straightforward simulation. In this work we emphasize the importance of online applicability of the proposed methodologies. This underlines the need for optimal solutions that require little computational cost and are able to incorporate real, unpredictable environments. A semi-analytic methodology is developed to generate the optimal velocity profile for minimum time travel along a prescribed path. The semi-analytic nature ensures minimal computational cost while a receding horizon implementation allows application of the methodology in uncertain environments. Extensions to increase fidelity of the vehicle model are finally provided.

The goal of this thesis is to develop an active front steering(AFS) control system which can apply to ordinary vehicle. This AFS control system stabilizes the driving vehicle and reduces the possibility of rollover. This thesis uses magic formula tire model and constructs a vehicle model with eight degrees of freedom to study the dynamic behavior of the real driving vehicle. This thesis constructs a vehicle model with three degrees of freedom and eight degree of freedom, compare with two vehicle model, we adopt eight vehicle model in this thesis. The advantages of PI controller are low cost and easy to modify, so this thesis adopts PI controller as the control strategy. This study uses four simulate methods and compares the simulated results to develop the AFS control system which can apply to ordinary vehicle.

Tires serve as important components of wheeled vehicles and their analytical modeling has drawn the attention of many researches in the past decades. A high-resolution finite element (FE) tire model contains detailed structural and material characteristics of a tire that exhibit degrees-of-freedom (DoF) in the order of 10⁵ or greater. However, such high-resolution models in their full detail are not practically applicable in multibody dynamic analysis of vehicles and a reduction in their order becomes necessary. In this research different formulations to construct condensed FE tire models suitable for multibody simulations are developed and their characteristics are discussed. In addition, two new and novel forms of substructuring are presented that aim at isolating the contact region of a tire without the need for keeping the boundary DoF which otherwise remain in the reduced system in the standard substructuring procedures. The new substructuring methods provide a great tool in constructing condensed FE tire models with much less total number of DoF compared to cases where a standard substructuring is used. In order to increase the computational efficiency of the condensed FE tire models even further, the possibility of model condensation in the contact region is studied. This research also addresses the applicability of available friction models into the condensed FE tire models. Different formulations of a condensed tire model presented in this research are used to construct several computational models. These models are utilized to simulate certain scenarios and the results are discussed.

The suspension system of a vehicle is conventionally designed such that the spring-damper element is configured in the vertical direction, and the longitudinal connection between the vehicle chassis and wheels is always very stiff compared to the vertical one. This mechanism can isolate vibrations and absorb shocks efficiently in the vertical direction but cannot attenuate the longitudinal impacts caused by road obstacles. In order to overcome such a limitation, a planar suspension system (PSS) is proposed. This novel vehicle suspension system has a longitudinal spring-damper strut between the vehicle chassis and wheel. The dynamic performance, including ride comfort, pitch dynamics, handling characteristics and total dynamic behaviour, of a mid-size passenger vehicle equipped with such planar suspension systems is thoroughly investigated and compared with those of a conventional vehicle. To facilitate this investigation, various number of vehicle models are developed considering the relative longitudinal motions of wheels with respect to the chassis. A 4-DOF quarter-car model is used to conduct a preliminary study of the ride quality, and a pitch plane half-car model is employed to investigate the pitch dynamics in both the frequency and time domain. A 5-DOF yaw plane single-track half-car model along with a pitch plane half-car model is proposed to carry out the handling performance study, and also an 18-DOF full-car model is used to perform total dynamics study. In addition to these mathematical models, virtual full-car models are constructed in Adams/car to validate the proposed mathematical models. For the sake of prediction of the tire-ground interaction force, a radial-spring tire model is modified by adding the tire damping to generate the road excitation forces due to road disturbances in the vertical and longitudinal directions. A dynamic 2D tire friction model based on the LuGre friction theory is modified to simulate the dynamic frictional interaction in the tire-ground contact pitch. The ride quality of a PSS vehicle is evaluated in accordance with the ISO 2631 and compared with that of a conventional vehicle. It is shown that the PSS system exhibits good potential to attenuate the impact and isolate the vibration due to road excitations in both the vertical and longitudinal directions, resulting in improved vehicles’ ride and comfort quality. The relatively soft longitudinal strut can absorb the longitudinal impact and, therefore, can protect the components. The investigation of handling performance including the steady-state handling characteristics, transient and frequency responses in various scenarios demonstrates that the PSS vehicle is directionally stable and generally has comparable handling behaviour to a similar conventional vehicle. The application of PSS in vehicles can enhance the understeer trend, i.e. the understeer becomes more understeer, neutral steer becomes slightly understeer, and oversteer becomes less oversteer. The total dynamic behaviour combining the bounce, pitch, roll and the longitudinal dynamics under various scenarios such as differential brake-in-turn and asymmetric obstacle traversing was thoroughly investigated. Simulation results illustrate that the PSS vehicle has a relatively small roll angle in a turning manoeuvre. In some cases such as passing road potholes, the PSS vehicle has a better directional stability.

Diploma thesis is devoted to tractor cabin's suspension. First part of the work consists of the overview of used suspension designs and their various modifications. Next, law requirements for roll-over protective structure are described. Subsequently, the suspension design for small-sized tractor is explored. Law compliance is revised via ROPS procedure simulation using finite element method. In the last part of the work, virtual prototype of agricultural tractor in Multi-body environment is built and it is used for studying the dynamic characteristics of proposed cabin suspension design.

Considering the more and more important issues concerning the climate changes and the global warming, the automotive industry is paying more and more attention to vehicle concepts with full electric or partly electric propulsion systems. The introduction of electric power sources allow the designers to implement more advanced motion control systems in vehicle, such as active suspensions. An example of this concept is the Autonomous corner module (ACM), designed by S. Zetterström. The ACM is a modular based suspension system that includes all features of wheel control, such as control of steering, wheel torque and camber individually, using electric actuators. With a good control strategy it is believed that is it possible to reduce the fuel consumption and/or increase the handling properties of the vehicle. In particular, camber angle has a significant effect on vehicle handling. However, very few efforts have been done in order to analyse its effects on tire dissipated energy. The aim of this study is to develop a new tire model, having as starting point the simple Brush Tire model, in order to analyse the tire behaviour, in terms of forces generated and energy dissipated, for different dynamic situations. In order to reach this scope, the characteristic equations of the rubber material are implemented in a 3D Multi-Line brush tire model. In this way the energy dissipated, thus the rolling resistance force, can be studied and analysed, considering also the tire geometry. From the results of this work it is possible to assert that the angular parameters (e.g. camber angle) affect the power losses in rolling tires, as well as the tire geometry influences their rolling resistance. Thus, using a good control strategy, it is possible to reduce the power losses in tires.

Due to a recent number of undesired rollovers in the field for the studied vehicle, rollover mitigation strategies have been investigated and developed. This research begins with the study of the tire, as it is the single component on the vehicle responsible for generating all of the non-inertial forces to direct the motion of the vehicle. Tire force and moment behavior has been researched extensively and several accurate tire models exist. However, not much research has been performed on off-road tire models. This research develops an off-road tire model for the studied vehicle by first using data from rolling road testing to develop a Pacejka Magic Formula tire model and then extending it to off-road surfaces through the use of scaling factors. The scaling factors are multipliers in the Magic Formula that describe how different aspects of the force and moment curves scale when the tire is driven on different surfaces. Scaling factors for dirt and gravel driving surfaces were obtained by using an existing portable tire test rig to perform force and moment tests on a passenger tire driven on these surfaces. The off-road tire model was then used as a basis for developing control algorithms to prevent vehicle rollover on off-road terrain. Specifically, a direct yaw control (DYC) algorithm based on Lyapunov direct method and an emergency roll control (ERC) algorithm based on a rollover coefficient were developed. Emergency evasive maneuvers were performed in a simulation environment on the studied vehicle driven on dry asphalt, dirt, and gravel for the controlled and uncontrolled cases. Results show that the proposed control algorithms significantly improve vehicle stability and prevent rollover on a variety of driving surfaces. / Master of Science

Forklifts are commonly perceived as simple machines that are not representative of modern technology. However, a deeper analysis uncovers their inherent complexity and sophistication. This project aims to develop a tire model for indoor forklifts with sufficient accuracy that it can replace the need for physical tests and significant calibration, thereby shortening development time and decreasing costs. This report is part of a Master's thesis work on modeling shocks generated when driving over obstacles with a forklift. The project is conducted in collaboration with Linköping University and Toyota Material Handling Manufacturing Sweden. Various methods for modeling tire behavior, along with different contact types, have been explored and tested, primarily focusing on the Fiala tire model. Developing a tire model that accurately captures all aspects of driving over obstacles is a challenging endeavor. Despite several challenges, the findings presented in this report suggest that, with additional time, it is possible to develop a model that effectively simulates shocks across various speeds and obstacle heights.

Doctor of Philosophy / The control systems installed in modern vehicles lack crucial information regarding the interaction between the tires and the road surface. This knowledge gap significantly impacts the safety and control of the vehicle. Thus, to address this issue, this research introduces a novel fusion approach to estimate friction at the tire-road contact interface. This hybrid fusion friction estimation algorithm employs techniques like signal processing and machine learning, backed up by information from various vehicle and tire dynamics models, to develop algorithms that estimate the level of friction between the tire and the road. This fusion approach enables more precise estimations of the friction coefficient in both normal driving situations and scenarios involving sudden changes in speed or road conditions. Therefore, this research aids in enhancing vehicle safety and control by providing improved information about such tire-road interactions.

Tires, being the only component of the vehicle in contact with the road surface, are responsible for generating the forces for maintaining the vehicle pose, orientation and stability of the vehicle. Additionally, the on-board advanced chassis control systems require estimation of these tire-road interaction properties for their operation. Extraction of these properties becomes extremely important in handling limit maneuvers such as Double Lane Change (DLC) and cornering wherein the lateral force transfer is dependent upon these computations. This research focuses on the development of a high-fidelity vehicle-tire model and control algorithm framework for vehicle trajectory tracking for vehicles operating in this limit handling regime. This combined vehicle-tire model places an emphasis on the lateral dynamics of the vehicle by integrating the effects of relaxation length on the contact patch force generation. The vertical dynamics of the vehicle have also been analyzed, and a novel double damper has been mathematically modeled and experimentally validated. Different control algorithms, both classical and machine learning-based, have been developed for optimizing this vertical dynamics model. Experimental data has been collected by instrumenting a vehicle with in-tire accelerometers, IMU, GPS, and encoders for slalom and lane change maneuvers. Different state estimation techniques have been developed to predict the vehicle side slip angle, tire slip angle, and normal load to further assist the developed vehicle-tire model. To make the entire framework more robust, Machine Learning algorithms have been developed to classify between different levels of tire wear. The effect of tire tread wear on the pneumatic trail of the tire has been further evaluated, which affects the aligning moment and lateral force generation. Finally, a Model Predictive Control (MPC) framework has been developed to compare the performance between the conventional vehicle models and the developed vehicle models in tracking a reference trajectory. / Doctor of Philosophy / In our rapidly advancing world, self-driving or autonomous vehicles are no longer a vision of the future but a reality of today. As we grow more reliant on these vehicles, ensuring their safety and reliability becomes increasingly critical. Unlike traditional vehicles, self-driving cars operate without human intervention. Consequently, the onus of passenger and pedestrian safety falls squarely on the vehicle's control systems. The efficiency and effectiveness of these control systems are pivotal in preventing accidents and ensuring a smooth ride. One vital aspect of these control systems lies in understanding the tires' behavior, the only parts of the vehicle that are in contact with the road surface. A tire's interaction with the road surface significantly impacts the vehicle's handling and stability. Information such as how much of the tire is in contact with the road, the forces and moments generated at this contact point, becomes valuable for optimizing the vehicle's performance. This is particularly crucial when a vehicle is turning or cornering, where the forces developed between the tires and the road are key to maintaining control and stability. In this research, a framework has been designed to improve the vehicle performance, primarily by improving the modeling of tire lag dynamics. This refers to the delay or 'lag' between a change in tire conditions (such as pressure, wear, and temperature) and the corresponding change in tire behavior. In addition, in this research a vertical dynamics model of the vehicle has also been developed incorporated with a novel double damper suspension system. To complete the entire framework, the effect of tire wear over time and how this affects its performance and safety characteristics has also been examined. By estimating and understanding this wear, we can predict how it will affect the dynamic properties of the tire, thus improving the reliability and efficiency of our autonomous vehicles. The last piece of this framework comprises the development of an MPC controller to track a reference trajectory and evaluate the performance of the developed model.