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.

<p>This master’s degree project includes the construction, implementation and the theory of function of the traction control system NTRAC, a traction control system designed to increase performance. A closer functionality study of the more common safety-designed traction control systems has been executed. As a result of this study different techniques in decreasing engine torque has been concluded. NTRAC uses a fuel-cutting method to decrease the torque. The risks and consequences by this, as well as different solutions, are in detail discussed in the report.</p><p>One of the main design purposes with NTRAC was to be able to adapt it easily to different vehicles. To evaluate this ability NTRAC has been implemented into two test vehicles, most different to each other by means of physical measurements. As an outcome of this evaluation, a number of mathematical models have been derived and implemented in numerical MATLAB programs. Two models are explained in the report and are included in MATLABfiles as appendix three and four at the end of the report.</p><p>The first model describes the dependency between the action of decrease in torque and the relative remaining degree of efficiency and the report explains why this does not show a linear dependency. The friction between the tire and the road surface plays a crucial part in the theory behind traction control and the report describes in detail how traditional traction control systems are designed to make compromises, in wheel spin tolerances, and thus not uses the maximum amount of traction. To increase performance traction control systems continuously have to optimise this amount and also minimise its fluctuations. Wheels travel with different speeds when cornering, thus the traction control system has to compensate for this, and the second mathematical model in the report describes this in detail.</p><p>Finally an increase in performance is verified through the usage of NTRAC in the formula car KTHR2. During an international competition in the summer of 05, at Bounthingsthorp proving grounds, Leicestershire, England, under perfect weather conditions, a time-saving of nine percentage where registered at acceleration tests from 0 to 75 meters. </p>

<div>Traction control (TC) systems have become quite common in on-road passenger vehicles in recent years. However, for vehicles in other applications, they are not as widely available.</div><div>This work presents a methodology for the proper design and implementation of a traction control system for heavy duty off-road machines, using a wheel loader as a reference vehicle.</div><div><br></div><div><div>A simulation model was developed, using standard vehicle dynamics constructs, including equations of motion and a description of the distribution of weight between the axles for different operating conditions. This model contains considerations for resistive forces acting on the machine implement, such as that generated by a work pile. The simulation also incorporates a detailed representation of the slip-friction characteristics between the vehicle tires and the road surface. One objective of this research was to model this interaction accurately, because the system traction behavior is dependent on it. Therefore, a series of tests was run using a state estimator to generate data on the slip-friction relationship at various ground conditions, and the results were incorporated into the simulation model. The dynamics of the machine braking system pressure were also modeled to give a more accurate description of the system response. The result is a mathematical model capable of accurately reproducing the behavior of the real-world system.</div></div><div><br></div><div><div>One of the primary goals of this work was the description of the traction control strategy itself, which should work as effectively and efficiently as possible. Several different aspects of the system were taken into consideration in generating this control structure. First, a relatively simple controller based on a PID control law was created. This controller was updated to account for peculiarities of the traction control system, as well as aspects like time delay. From there, more advanced controllers were created to address certain aspects of the system in greater detail. First, a self-tuning controller based on real-time optimization strategies was developed, to allow the controller to quickly adapt to changes in ground condition. Then, different nonlinear controllers were synthesized which were designed to address the theoretical behavior of the system. All of these controllers were simulated using the system model and then some were run in experiments to show their potential for improving system performance. To improve system efficiency, the machine drivetrain itself was also examined to develop a more efficient control algorithm. By designing a more efficient methodology, traction control congurations which had previously seen increases in fuel consumption of 16% were now able to actually reduce fuel usage by 2.6%.</div></div><div><br></div><div><div>Another main goal of this work was the development of a prototype system capable of implementing the formulated control strategies. The reference machine was modied so that the brakes could be controlled electronically and independently for implementation of the TC system. The vehicle was instrumented using a wide array of sensors, and estimation methodologies for accurately determining vehicle speed and implement forces were designed. The velocity estimator designed in this work is more accurate and more reliable than an industry standard sensor, which is important for traction control implementation. The implement force estimate was also quite accurate, achieving payload estimate errors of less than 2.5%, comparable to commercially-available measurement systems. This setup allowed for tests to be accurately compared, to assess the traction control performance.</div></div><div><br></div><div><div>With the objective of performing experiments on the traction control system, many tests were run to assess its capabilities in various situations. These tests included experiments for characterizing the vehicle behavior so that the simulation model could be updated to accurately reflect the physical machine performance. Another task for the experimental work was the generation of useful metrics for quantifying traction control performance. Laboratory experiments which were very controlled and repeatable were also run for generating data to improve the system model and for comparing traction control performance results side-byside. The test metrics proposed for these experiments provided for accurate, repeatable comparisons of pushing force, tire wear, and brake consumption. For each of these tests, the traction control system saw an increase in pushing force of at least 10% when compared with the stock machine, with certain operating conditions showing increases as high as 60%. Furthermore, every test case showed a decrease in wheel slip of at least 45% (up to 73% for some cases), which translates into increased tire longevity.</div></div><div><br></div><div><div>Other tests were conducted in the eld, designed to mimic the real-world operating conditions of the wheel loader. Various performance comparisons were made for different congurations in which traction control could provide potential benets. These included parameters for comparing overall vehicle performance in a typical truck loading cycle, such as tire wear, fuel consumption, and material moved per load. Initial results for this testing showed a positive result in terms of wheel slip reduction, but other performance parameters such as fuel consumption were negatively impacted. Therefore, the control structure was reexamined extensively and new methods were added to improve those results. The final control implementation saw a 12% reduction in tire slip, while also reducing fuel consumption by 2.6% compared to the stock system. These results show signicant potential for traction control as a technology for maximizing the performance output of construction machines.</div></div>

This thesis contains the design and simulation test results for the implementation of a new all-wheel drive (AWD) torque vectoring (TV) control system. A separate algorithm using standard control methods is included in this study for a comparison. The proposed controller was designed to be applied to an AWD independent drive electric vehicle, however the main concepts can be re-purposed for other vehicle drive train configurations. The purpose of the control system is to assist the driver in achieving a desired vehicle trajectory whilst also maintaining stability and control of the vehicle. This is accomplished by measuring various real time parameters of the vehicle and using this information as feedback for the control system to act on. The focus of this thesis resides on the controller. Hence, this study assumes perfect observation of feedback parameters, therefore some uncertainties are not accounted for. Using feedback parameters, the control system will manage wheel slip whilst simultaneously generating a torque around the center of gravity of the vehicle by applying a torque differential between the left and right wheels. The proposed TV algorithm is simulated in MATLAB/Simulink along with another separate TV algorithm for comparison. Both algorithms are comprised of two main parts: a slip ratio controller applied to each wheel individually and stability controller that manages yaw rate and side slip of the vehicle. The new algorithm leverages the super twisting algorithm for the slip ratio controller and uses a fusion of a linear quadratic regulator with the integral term of a super twisting algorithm to implement the yaw rate and side slip controller. The other algorithm used for comparison derives its implementation for the slip ratio controller and yaw rate and side slip controllers from simple and standard first order sliding mode control methods. Both control algorithms were tested in three different main tests: anti-lock braking, sine dwell (SD) steering, and constant steering angle (CSA) tests. To increase the comprehensive nature of the study, the SD and CSA tests were simulated at 3 speeds (30,50, and 80 mph) and the steering angle parameter was varied from 2 to 24 degrees in increments of 2. The result of this study proves that the proposed controller is a feasible option for use in theory. Simulated results show advantages and disadvantages of the new controller with respect to the standard comparison controller. Both controllers are also shown to provide positive impacts on the vehicle response under most test conditions.

Active safety systems for road vehicles make a crucial preventive contribution to road safety. In recent years, technological developments and the increasing demand for road safety have resulted in the integration and cooperation of these individual active safety systems. Traction control system (TCS) is one of these individual systems, which is capable of inhibiting wheel-spin during acceleration of the vehicle on slippery surfaces. In this thesis, design methodology and simulation results of a traction control system for four wheeled road vehicles are presented. The objective of the TCS controller is basically to improve directional stability, steer-ability and acceleration performance of vehicle by controlling the wheel slip during acceleration. In this study, the designed traction control system based on fuzzy logic is composed of an engine torque controller and a slip controller. Reference wheel slip values were estimated from the longitudinal acceleration data of the vehicle. Engine torque controller determines the throttle opening angle corresponding to the desired wheel torque, which is determined by a slip controller to track the reference slip signals. The wheel torques delivered by the engine are compensated by brake torques according to the desired wheel torque determined by the slip controller. Performance of the TCS controller was analyzed through several simulations held in MATLAB/Simulink for different road conditions during straight line acceleration and combined acceleration and steering. For simulations, an 8 DOF nonlinear vehicle model with nonlinear tires and a 2 DOF nonlinear engine model were built.

Tato práce se zabývá návrhem a realizací palubní elektroniky experimentálního vozidla Car4, dále pak základní programovou výbavou řídicí jednotky a Hardware In the Loop simulačním ověřením funkčnosti řídicí jednotky.

This thesis evaluates different controllers for traction control on an electric forklift truck and has been done in cooperation with Toyota Material Handling Manufacturing Sweden. The need for a traction control system has increased with the introduction of lithium-ion batteries replacing the older lead-acid batteries, reducing the battery weight and therefore the downward force on the driving wheel increasing the risk for slip. The forklift truck was modelled using Simulink and validated by experiment. Different possible control strategies were investigated and three were chosen for implementation in simulation. These were controllers based on Model Following Control, Maximum Transmissible Torque Estimation and Sliding Mode Control. Model Following Control makes use of a nominal model to compare actual wheel speed values with nominal wheel speed values to determine if slip is occurring, Maximum Transmissible Torque Estimation makes use of a closed-loop disturbance observer to compute the maximum transmissible torque possible without inducing slip and using it as a limitation on the input signal, and Sliding Mode Control uses different functions to \say{slide} along a sliding surface to stay around a specific slip value. All three controller types were developed both as speed controlled and torque controlled. All of the controllers could reduce slip heavily in simulation. The Maximum Transmissible Torque Estimation controller reduced slip the most and kept oscillations at a minimum, but was not as responsive as the others to driver commands. The conclusion was that the controller of choice would depend on the working environment of the forklift truck. In a low friction environment where slip is expected to occur often, the Maximum Transmissible Torque Estimation controller is advisable, while the other two would be a better choice for environment with low slip occurrence. The use of torque control, while often better with regards to decreasing slip, could not be advised due to a perceived increase in implementation cost.

Development of electric vehicles is motivated by global concerns over the need for environmental protection. In addition to its zero-emission characteristics, an electric propulsion system enables high performance torque control that may be used to maximize vehicle performance obtained from energy-efficient, low rolling resistance tires typically associated with degraded road-holding ability. A simultaneous plant/controller optimization is performed on an electric vehicle traction control system with respect to conflicting energy use and performance objectives. Due to system nonlinearities, an iterative simulation-based optimization approach is proposed using a system model and a genetic algorithm (GA) to guide search space exploration. The system model consists of: a drive cycle with a constant driver torque request and a step change in coefficient of friction, a single-wheel longitudinal vehicle model, a tire model described using the Magic Formula and a constant rolling resistance, and an adhesion gradient fuzzy logic traction controller. Optimization is defined in terms of the all at once variable selection of: either a performance oriented or low rolling resistance tire, the shape of a fuzzy logic controller membership function, and a set of fuzzy logic controller rule base conclusions. A mixed encoding, multi-chromosomal GA is implemented to represent the variables, respectively, as a binary string, a real-valued number, and a novel rule base encoding based on the definition of a partially ordered set (poset) by delta inclusion. Simultaneous optimization results indicate that, under straight-line acceleration and unless energy concerns are completely neglected, low rolling resistance tires should be incorporated in a traction control system design since the energy saving benefits outweigh the associated degradation in road-holding ability. The results also indicate that the proposed novel encoding enables the efficient representation of a fix-sized fuzzy logic rule base within a GA.

Development of electric vehicles is motivated by global concerns over the need for environmental protection. In addition to its zero-emission characteristics, an electric propulsion system enables high performance torque control that may be used to maximize vehicle performance obtained from energy-efficient, low rolling resistance tires typically associated with degraded road-holding ability. A simultaneous plant/controller optimization is performed on an electric vehicle traction control system with respect to conflicting energy use and performance objectives. Due to system nonlinearities, an iterative simulation-based optimization approach is proposed using a system model and a genetic algorithm (GA) to guide search space exploration. The system model consists of: a drive cycle with a constant driver torque request and a step change in coefficient of friction, a single-wheel longitudinal vehicle model, a tire model described using the Magic Formula and a constant rolling resistance, and an adhesion gradient fuzzy logic traction controller. Optimization is defined in terms of the all at once variable selection of: either a performance oriented or low rolling resistance tire, the shape of a fuzzy logic controller membership function, and a set of fuzzy logic controller rule base conclusions. A mixed encoding, multi-chromosomal GA is implemented to represent the variables, respectively, as a binary string, a real-valued number, and a novel rule base encoding based on the definition of a partially ordered set (poset) by delta inclusion. Simultaneous optimization results indicate that, under straight-line acceleration and unless energy concerns are completely neglected, low rolling resistance tires should be incorporated in a traction control system design since the energy saving benefits outweigh the associated degradation in road-holding ability. The results also indicate that the proposed novel encoding enables the efficient representation of a fix-sized fuzzy logic rule base within a GA.

This thesis presents a proposal of newly designed concept for travel hydraulic circuit of vibratory single drum roller ASC 110. The maximum machine gradeability was chosen as the main parameter for hydraulic circuit proposal. After selecting the new hydraulic travel concept, suitable hydraulic components have been selected. Length and local losses for two different machine speeds were calculated for sufficient hydraulic circuit design. Hydraulic losses have also been calculated for use in different climatic conditions. A new machine cooling concept has also been proposed. Heating and cooling curves of hydraulic circuit were calculated. For the purpose of comparing gradeability and energy balance of the newly designed travel concept compared to the existing one currently in mass production, both machines were fitted with measuring points. On both machines were measured for example, pressure, flow and temperature in each hydraulic circuit branch and others. From the time dependencies of the above-mentioned parameters it was possible to determine the energy efficiency of the newly designed concept. To assess the maximum gradeability, the slope of the hill was measured. Comparing the two machines, it has been found that the two hydraulic circuit solution has significantly improved traction properties in demanding machine applications, especially when driving uphill and downhill. This concept also affects less fuel consumption and places less demand on the hydraulic oil cooler due to its energy efficiency.