The principle of braking in road vehicles involves the conversion of kinetic energy into heat. This high energy conversion therefore demands an appropriate rate of heat dissipation if a reasonable temperature and performance stability are to be maintained. While the design, construction, and location features severely limit the heat dissipation function of the friction brake, electromagnetic brakes work in a relatively cool condition and avoid problems that friction brakes face by using a totally different working principle and installation location. By using the electromagnetic brake as supplementary retardation equipment, the friction brakes can be used less frequently and therefore practically never reach high temperatures. The brake linings thus have a longer life span, and the potential "brake fade" problem can be avoided. It is apparent that the electromagnetic brake is an essential complement to the safe braking of heavy vehicles. In this thesis, a new mathematical model for electromagnetic brakes is proposed to describe their static characteristics (angular speed versus brake torque). The performance of the new mathematical model is better than the other three models available in the literature in a least-square sense. Compared with old models that treat reluctance as a constant, our model treats reluctance as a function of speed. In this way, the model represents more precisely the aggregate effect of all side effects such as degree of saturation of the iron in the magnet, demagnetizing effects, and air gap. The software program written in Matlab can be used to code different brake characteristics (both static and dynamic) and evaluate their performance in different road scenarios. A controller is designed that achieves wheel-slip control for vehicle motion. The objective of this brake control system is to keep the wheel slip at an ideal value so that the tire can still generate lateral and steering forces as well as shorter stopping distances. In order to control the wheel slip, vehicle system dynamic equations are given in terms of wheel slip. The system shows the nonlinearities and uncertainties. Hence, a nonlinear control strategy based on sliding mode, which is a standard approach to tackle the parametric and modeling uncertainties of a nonlinear system, is chosen for slip control. Due to its robustness properties, the sliding mode controller can solve two major difficulties involved in the design of a braking control algorithm: 1) the vehicle system is highly nonlinear with time-varying parameters and uncertainties; 2) the performance of the system depends strongly on the knowledge of the tire/road surface condition. A nominal vehicle system model is simulated in software and a sliding mode controller is designed to maintain the wheel slip at a given value. The brake control system has desired performance in the simulation. It can be proven from this study that the electromagnetic brake is effective supplementary retardation equipment. The application and control of electromagnetic brakes might be integrated with the design of vehicles and their friction braking systems so that an ideal match of the complementary benefits of both systems might be obtained to increase safety to a maximum while reducing vehicle operating costs to a minimum. / Master of Science

Traction efficiency of tractors barely reaches 50 % in field operations. On the other hand, modern trends in agriculture show growth of the global tractor markets and at the same time increased demands for greenhouse gas emission reduction as well as energy efficiency due to increasing fuel costs. Engine power of farm tractors is growing at 1.8 kW per year reaching today about 500 kW for the highest traction class machines. The problem of effective use of energy has become crucial. Existing slip control approaches for tractors do not fulfil this requirement due to fixed reference set-point. The present work suggests an optimal control scheme based on set-point optimization and on assessment of soil conditions, namely, wheel-ground parameter identification using fuzzy-logic-assisted adaptive unscented Kalman filter.

Wheel slip is a common problem in planetary rover exploration tasks. During the current Mars Exploration Rover (MER) mission, the Spirit rover almost became trapped on a dune because of wheel slip. As rover missions on harsh terrains expand in scope, mission success will depend not only on rover safety, but also alacrity in task completion. Speed combined with exploration of varied and difficult terrains, the risk of slip increases dramatically. We first characterize slip performance of a rover on harsh terrains by implementing a novel High Fidelity Traversability Analysis (HFTA) algorithm in order to provide slip prediction and detection capabilities to a planetary rover. The algorithm, utilizing path and energy cost functions in conjunction with simulated navigation, allows a rover to select the best path through any given terrain by predicting high slip paths. Integrated software allows the rover to then accurately follow a designated path while compensating for slippage, and reach intended goals independent of the terrain over which it is traversing. The algorithm was verified using ROAMS, a high fidelity simulation package, at 3.5x real time speed. We propose an adaptive path following algorithm as well as a human-trained neural network to traverse multiple harsh terrains using slip as an advantage. On a near-real-time system, and at rover speeds 15 times the current average speed of the Mars Exploration Rovers, we show that the adaptive algorithm traverses paths in less time than a standard path follower. We also train a standard back-propagation neural network, using human and path following data from a near-real-time system. The neural network demonstrates it ability to traverse new paths on multiple terrains and utilize slip to minimize time and path error.

Recently, mostly due to global warming concerns and high oil prices, electric vehicles have attracted a great deal of interest as an elegant solution to environmental and energy problems. In addition to the fact that electric vehicles have no tailpipe emissions and are more efficient than internal combustion engine vehicles, they represent more versatile platforms on which to apply advanced motion control techniques, since motor torque and speed can be generated and controlled quickly and precisely. The chassis control systems developed today are distinguished by the way the individual subsystems work in order to provide vehicle stability and control. However, the optimum driving dynamics can only be achieved when the tire forces on all wheels and in all three directions can be influenced and controlled precisely. This level of control requires that the vehicle is equipped with various chassis control systems that are integrated and networked together. Drive-by-wire electric vehicles with in-wheel motors provide the ideal platform for developing the required control system in such a situation. The focus of this thesis is to develop effective control strategies to improve driving dynamics and safety based on the philosophy of individually monitoring and controlling the tire forces on each wheel. A two-passenger electric all-wheel-drive urban vehicle (AUTO21EV) with four direct-drive in-wheel motors and an active steering system is designed and developed in this work. Based on this platform, an advanced fuzzy slip control system, a genetic fuzzy yaw moment controller, an advanced torque vectoring controller, and a genetic fuzzy active steering controller are developed, and the performance and effectiveness of each is evaluated using some standard test maneuvers. Finally, these control systems are integrated with each other by taking advantage of the strengths of each chassis control system and by distributing the required control effort between the in-wheel motors and the active steering system. The performance and effectiveness of the integrated control approach is evaluated and compared to the individual stability control systems, again based on some predefined standard test maneuvers.

Recently, mostly due to global warming concerns and high oil prices, electric vehicles have attracted a great deal of interest as an elegant solution to environmental and energy problems. In addition to the fact that electric vehicles have no tailpipe emissions and are more efficient than internal combustion engine vehicles, they represent more versatile platforms on which to apply advanced motion control techniques, since motor torque and speed can be generated and controlled quickly and precisely. The chassis control systems developed today are distinguished by the way the individual subsystems work in order to provide vehicle stability and control. However, the optimum driving dynamics can only be achieved when the tire forces on all wheels and in all three directions can be influenced and controlled precisely. This level of control requires that the vehicle is equipped with various chassis control systems that are integrated and networked together. Drive-by-wire electric vehicles with in-wheel motors provide the ideal platform for developing the required control system in such a situation. The focus of this thesis is to develop effective control strategies to improve driving dynamics and safety based on the philosophy of individually monitoring and controlling the tire forces on each wheel. A two-passenger electric all-wheel-drive urban vehicle (AUTO21EV) with four direct-drive in-wheel motors and an active steering system is designed and developed in this work. Based on this platform, an advanced fuzzy slip control system, a genetic fuzzy yaw moment controller, an advanced torque vectoring controller, and a genetic fuzzy active steering controller are developed, and the performance and effectiveness of each is evaluated using some standard test maneuvers. Finally, these control systems are integrated with each other by taking advantage of the strengths of each chassis control system and by distributing the required control effort between the in-wheel motors and the active steering system. The performance and effectiveness of the integrated control approach is evaluated and compared to the individual stability control systems, again based on some predefined standard test maneuvers.

Traction efficiency of tractors barely reaches 50 % in field operations. On the other hand, modern trends in agriculture show growth of the global tractor markets and at the same time increased demands for greenhouse gas emission reduction as well as energy efficiency due to increasing fuel costs. Engine power of farm tractors is growing at 1.8 kW per year reaching today about 500 kW for the highest traction class machines. The problem of effective use of energy has become crucial. Existing slip control approaches for tractors do not fulfil this requirement due to fixed reference set-point. The present work suggests an optimal control scheme based on set-point optimization and on assessment of soil conditions, namely, wheel-ground parameter identification using fuzzy-logic-assisted adaptive unscented Kalman filter.:List of figures VIII List of tables IX Keywords XI List of abbreviations XII List of mathematical symbols XIII Indices XV 1 Introduction 1 1.1 Problem description and challenges 1 1.1.1 Development of agricultural industry 1 1.1.2 Power flows and energy efficiency of a farm tractor 2 1.2 Motivation 9 1.3 Purpose and approach 12 1.3.1 Purpose and goals 12 1.3.2 Brief description of methodology 14 1.3.2.1 Drive torque feedback 14 1.3.2.2 Measurement signals 15 1.3.2.3 Identification of traction parameters 15 1.3.2.4 Definition of optimal slip 15 1.4 Outline 16 2 State of the art in traction management and parameter estimation 17 2.1 Slip control for farm tractors 17 2.2 Acquisition of drive torque feedback 23 2.3 Tire-ground parameter estimation 25 2.3.1 Kalman filter 25 2.3.2 Extended Kalman filter 27 2.3.3 Unscented Kalman filter 27 2.3.4 Adaptation algorithms for Kalman filter 29 3 Modelling vehicle dynamics for traction control 31 3.1 Tire-soil interaction 31 3.1.1 Forces in wheel-ground contact 32 3.1.1.1 Vertical force 32 3.1.1.2 Tire-ground surface geometry 34 3.1.2 Longitudinal force 36 3.1.3 Zero-slip condition 37 3.1.3.1 Soil shear stress 38 3.1.3.2 Rolling resistance 39 3.2 Vehicle body and wheels 40 3.2.1 Short description of Multi-Body-Simulation 40 3.2.2 Vehicle body and wheel models 42 3.2.3 Wheel structure 43 3.3 Stochastic input signals 45 3.3.1 Influence of trend and low-frequency components 47 3.3.2 Modelling stochastic signals 49 3.4 Further components and general view of tractor model 53 3.4.1 Generator, intermediate circuit, electrical motors and braking resistor 53 3.4.2 Diesel engine 55 4 Identification of traction parameters 56 4.1 Description of identification approaches 56 4.2 Vehicle model 58 4.2.1 Vehicle longitudinal dynamics 58 4.2.2 Wheel rotational dynamics 59 4.2.3 Tire dynamic rolling radius and inner rolling resistance coefficient 60 4.2.4 Whole model 61 4.3 Static methods of parameter identification 63 4.4 Adaptation mechanism of the unscented Kalman filter 63 4.5 Fuzzy supervisor for the adaptive unscented Kalman filter 66 4.5.1 Structure of the fuzzy supervisor 67 4.5.2 Stability analysis of the adaptive unscented Kalman filter with the fuzzy supervisor 69 5 Optimal slip control 73 5.1 Approaches for slip control by means of traction control system 73 5.1.1 Feedback compensation law 73 5.1.2 Sliding mode control 74 5.1.3 Funnel control 77 5.1.4 Lyapunov-Candidate-Function-based control, other approaches and choice of algorithm 78 5.2 General description of optimal slip control algorithm 79 5.3 Estimation of traction force characteristic curves 82 5.4 Optimal slip set-point computation 85 6 Verification of identification and optimal slip control systems 91 6.1 Simulation results 91 6.1.1 Identification of traction parameters 91 6.1.1.1 Comparison of extended Kalman filter and unscented Kalman filter 92 6.1.1.2 Comparison of ordinary and adaptive unscented Kalman filters 96 6.1.1.3 Comparison of the adaptive unscented Kalman filter with the fuzzy supervisor and static methods 99 6.1.1.4 Description of soil conditions 100 6.1.1.5 Identification of traction parameters under changing soil conditions 101 6.1.2 Approximation of characteristic curves 102 6.1.3 Slip control with reference of 10% 103 6.1.4 Comparison of operating with fixed and optimal slip reference 104 6.2 Experimental verification 108 6.2.1 Setup and description of the experiments 108 6.2.2 Virtual slip control without load machine 109 6.2.3 Virtual slip control with load machine 113 7 Summary, conclusions and future challenges 122 7.1 Summary of results and discussion 122 7.2 Contributions of the dissertation 123 7.3 Future challenges 123 Bibliography 125 A Measurement systems 137 A.1 Measurement of vehicle velocity 137 A.2 Measurement of wheel speed 138 A.3 Measurement or estimation of wheel vertical load 139 A.4 Measurement of draft force 140 A.5 Further possible measurement systems 141 B Basic probability theoretical notions 142 B.1 Brief description of the theory of stochastic processes 142 B.2 Properties of stochastic signals 144 B.3 Bayesian filtering 145 C Modelling stochastic draft force and field microprofile 147 D Approximation of kappa-curves 152 E Simulation parameters 156

In this thesis project, brake performance of heavy vehicles is improved by the development of new wheel-based functions for a longitudinal slip control braking system using novel Fast Acting Braking Valves (FABVs). To achieve this goal, Volvo Trucks' vehicle dynamics model has been extended to incorporate the FABV system. After validating the updated model with experimental data, a slip-slope based recursive least squares friction estimation algorithm has been implemented. Using information about the tire-road friction coefifcient, the sliding mode slip controller has been made adaptive to different road surfaces by implementing a friction dependent reference slip signal and switching gain for the sliding mode controller. This switching gain is further optimized by means of a novel on-line optimization algorithm. Simulations show that the on-line friction estimation converges close to the reference friction level within one second for hard braking. Furthermore, using this information for the optimized controller has resulted in reduction of braking distance on most road surfaces of up to 20 percent, as well as in most cases a reduction in air usage.

Active vehicle safety systems for road vehicles play an important role in accident prevention. In recent years, rapid developments have been observed in this area with advancing technology and electronic control systems. Active yaw control is one of these subjects, which aims to control the vehicle in case of any impending spinning or plowing during rapid and/or sharp maneuver. In addition to the development of these systems, integration and cooperation of these independent control mechanisms constitutes the current trend in active vehicle safety systems design. In this thesis, design methodology and simulation results of an active yaw control system for two axle road vehicles have been presented. Main objective of the yaw control system is to estimate the desired yaw behavior of the vehicle according to the demand of the driver and track this desired behavior accurately. The design procedure follows a progressive method, which first aims to design the yaw control scheme without regarding any other stability parameters, followed by the development of the designed control scheme via taking other stability parameters such vehicle sideslip angle into consideration. A two degree of freedom vehicle model (commonly known as &ldquo / Bicycle Model&rdquo / ) is employed to model the desired vehicle behavior. The design of the controller is based on Fuzzy Logic Control, which has proved itself useful for complex nonlinear design problems. Afterwards, the proposed yaw controller has been modified in order to limit the vehicle sideslip angle as well. Integration of the designed active yaw control system with other safety systems such as Anti-Lock Braking System (ABS) and Traction Control System (TCS) is another subject of this study. A fuzzy logic based wheel slip controller has also been included in the study in order to integrate two different independent active systems to each other, which, in fact, is a general design approach for real life applications. This integration actually aims to initiate and develop the integration procedure of the active yaw control system with the (ABS). An eight degree of freedom detailed vehicle model with nonlinear tire model is utilized to represent the real vehicle in order to ensure the validity of the results. The simulation is held in MATLAB/Simulink environment, which has provided versatile design and simulation capabilities for this study. Wide-ranging simulations include various maneuvers with different road conditions have been performed in order to demonstrate the performance of the proposed controller.

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Vehicle Dynamics Control (VDC) systems (also known as Active Chassis systems) are mechatronic systems developed for improving vehicle comfort, handling and/or stability. Traditionally, most of these systems have been individually developed and manufactured by various suppliers and utilised by automotive manufacturers. These decentralised control systems usually improve one aspect of vehicle performance and in some cases even worsen some other features of the vehicle. Although the benefit of the stand-alone VDC systems has been proven, however, by increasing the number of the active systems in vehicles, the importance of controlling them in a coordinated and integrated manner to reduce the system complexity, eliminate the possible conflicts as well as expand the system operational envelope, has become predominant. The subject of Integrated Vehicle Dynamics Control (IVDC) for improving the overall vehicle performance in the existence of several VDC active systems has recently become the topic of many research and development activities in both academia and industries Several approaches have been proposed for integration of vehicle control systems, which range from the simple and obvious solution of networking the sensors, actuators and processors signals through different protocols like CAN or FlexRay, to some sort of complicated multi-layered, multi-variable control architectures. In fact, development of an integrated control system is a challenging multidisciplinary task and should be able to reduce the complexity, increase the flexibility and improve the overall performance of the vehicle. The aim of this thesis is to develop a low-cost control scheme for integration of Electric Power-Assisted Steering (EPAS) system with Enhanced Stability Program (ESP) system to improve driver comfort as well as vehicle safety. In this dissertation, a systematic approach toward a modular, flexible and reconfigurable control architecture for integrated vehicle dynamics control systems is proposed which can be implemented in real time environment with low computational cost. The proposed control architecture, so named “Integrated Vehicle Control System (IVCS)”, is customised for integration of EPAS and ESP control systems. IVCS architecture consists of three cascade control loops, including high-level vehicle control, low-level (steering torque and brake slip) control and smart actuator (EPAS and EHB) control systems. The controllers are designed based on Youla parameterisation (closed-loop shaping) method. A fast, adaptive and reconfigurable control allocation scheme is proposed to coordinate the control of EPAS and ESP systems. An integrated ESP & ESP HiL/RCP system including the real EPAS and Electro Hydraulic Brake (EHB) smart actuators integrated with a virtual vehicle model (using CarMaker/HiL®) with driver in the loop capability is designed and utilised as a rapid control development platform to verify and validate the developed control systems in real time environment. Integrated Vehicle Dynamic Control is one of the most promising and challenging research and development topics. A general architecture and control logic of the IVDC system based on a modular and reconfigurable control allocation scheme for redundant systems is presented in this research. The proposed fault tolerant configuration is applicable for not only integrated control of EPAS and ESP system but also for integration of other types of the vehicle active systems which could be the subject of future works.