For decades vehicle control has been extensively studied to investigate and improve vehicle stability and performance. Such controllers are designed to improve driving safety while the driver is still in control of the vehicle. It is known that human drivers are capable to learn and adapt to their built-in vehicle controller in order to improve their control actions based on their past driving experiences with the same vehicle controller. Although the learning curve varies for different human drivers, it results in a more constructive cooperation between the human driver and the computer-based vehicle controller, leading to globally optimal vehicle stability. The main intent of this research is to develop a novel cooperative interaction model between the human driver and vehicle controller in order to obtain globally optimal vehicle steering and lateral control. Considering the vehicle driver-controller interactions as a common two-player game problem where both players attempt to improve their payoffs, i.e., minimize their objective functions, the Game Theory approach is applied to obtain the optimal driver's steering inputs and controller's corrective yaw moment. Extending this interaction model to include more realistic scenarios, the model is discretized and a road preview model is added to account for the driver's preview-time characteristic. Also, a robust interaction model is developed to stabilize the vehicle performance while taking bounded uncertainty effects in driver's steering behavior into consideration using the Integral Sliding Mode control methodology. For evaluation purposes, a nonlinear vehicle dynamics model is developed that captures nonlinear tire characteristics and includes driver steering controllability and vehicle speed control systems such as cruise control, differential braking, and anti-lock braking systems. A graphical user interface (GUI) is developed in MATLAB to ease the use of the vehicle model and hopefully encourage its widespread application in the future. Simulation results indicate that the proposed cooperative interaction model, which is the end-product of human driver's and vehicle controller's mutual understanding of each other's objective and performance quality, results in more optimal and stable vehicle performance in lateral and yaw motions compared to the existing LQR controllers that tend to independently optimize the driver and vehicle controller inputs. / Ph. D.

Inspired by the recent developments, we studied some recent developments and research trends in intelligent vehicle sensing and control tasks. We emphasize on advanced vehicle motion control techniques and intelligent tires. The main research motivation is to improve drivers/passengers' comfort and safety as well as highway capacity and efficiency.

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The necessity to reduce climate related emissions is driving the electrication of transportation. As well as reducing emissions Electric Vehicles (EV) have the capability of improving traction and vehicle stability. Unlike a conventional vehicle that uses a single Internal Combustion Engine (ICE) to drive one or both axles, an EV can have an electric machine driving each of the wheels independently. This opens up the possibility of using the electric machines as an actuator for traction control. In conventional vehicles the hydraulic brakes together with the ICE are used to actuate traction control. The advantages of electric machines over hydraulic brakes are precise measurable torque, higher bandwidth, bidirectional torque and kinetic energy recovery. A review of the literature shows that a wide range of control methods is used for traction control of EVs. These are mainly focused on control of an individual wheel, with only a minority being advanced to the experimental stage of verication. Integrated approaches to the control of multiple wheels are generally lacking, as well as verication that tests the vehicle's directional stability. A large body of the literature uses the slip ratio of the wheel as the key control variable. A signicant challenge for slip-based traction control is the detection of vehicle velocity together with the calculation of slip around zero vehicle velocity. A traction control method that does not depend upon vehicle velocity detection or slip ratio is Maximum Transmissible Torque Estimation (MTTE), after Yin et al. (2009). In this thesis an MTTE based method is developed for a full size electric vehicle with independently driven rear wheels. The original MTTE method for a single wheel is analysed using a simple quarter vehicle model. The simulation results of Yin et al. (2009) are in general reproducible although a lack of data in the original research prevents a quantitative comparison. A modication is proposed to the rate compensation term. Simulation results show that the proposed modication ensures that the torque demand is delivered to the wheel under normal driving conditions, this includes negative torque demand which is not possible for MTTE, Yin et al. (2009). Enabling negative torque demands means that the proposed traction control is compatible with higher level stability control such as torque vectoring. The performance of the controller is veried through a combination of simulation and vehicle based experiments. Compared with experiments, simulations are fast and inexpensive and can provide greater insight as all of the variables are observable. To simulate the controller a high delity vehicle model is required. To achieve this it is necessary to initially validate the model against experimental data. Simulation verication using a validated vehicle model is lacking in the literature. A full vehicle model is developed for this thesis using Dymola, a multi-body system software tool. The model includes the full suspension geometry of the vehicle. Pacejka's "Magic Formula" is used for the tyre model. The model is validated using Delta Motorsport's E4 coupe. The two Wheel Independent Drive (2WID) MTTE-based traction controller is derived from the equations of motion for the vehicle. This shows that the maximum transmissible torque for one driven wheel is dependent on the friction force of both driven wheels, which has not been shown before. An equal torque strategy is proposed to maintain vehicle directional stability on mixed-μ roads. For verication the 2WID-MTTE controller is simulated on the validated vehicle model described above. The proposed 2WID-MTTE controller is benchmarked against a similar method without the equal torque strategy, termed Independent MTTE, as well as a method combining Direct Yaw Control (DYC) and Independent MTTE. The three controllers are simulated for a vehicle accelerating onto a split-μ road. The results show that the proposed 2WID-MTTE controller prevents the vehicle spinning o the road when compared to Independent MTTE. 2WID-MTTE is found to be as eective as DYC+Independent MTTE but is simpler in design and requires fewer sensors. The proposed 2WID-MTTE controller is also simulated for a vehicle accelerating from a low- to high-μ road. This is done to assess the controller's ability to return to normal operation after a traction event, and because there are no simulations of this type for MTTE control on a high delity vehicle model in the literature. The results show that oscillations in the tyre-road friction force as the wheel transitions across the change in μ somewhat impede the return of the controller's output torque to the torque demand. The 2WID-MTTE controller is implemented on Delta Motorsport's E4 coupe by integrating it into the vehicle's Powertrain Control Module (PCM). This is experimentally tested for the vehicle accelerating across a range of surfaces at the MIRA proving ground. The experimental tests include high- to low-μ, low- to high-μ and split-μ roads. The results for the high- to low-μ road tests show that 2WID-MTTE control prevents the vehicle spinning when compared to no control. Similar to the simulation, the results of the low- to high-μ road experiment show that the controller output torque is also impeded from returning to the demand torque. Observation of the estimated friction force together with the on-board accelerometers conrm that this is due to tyre friction oscillating after the transition. This justies the use of a tyre model with transient dynamics. The proposed 2WID-MTTE controller uses wheel velocity and torque feedback to estimate friction torque. These signals are obtained from the vehicle's motor controllers via a Controlled Area Network (CAN) bus. The 2WID-MTTE controller is benchmarked against Independent MTTE that uses wheel velocity measured directly from the wheel hub sensors and the torque demand to estimate friction torque. The results show that the delays introduced by the CAN bus increase wheel slip for the 2WID-MTTE controller. However, the equal torque strategy means that 2WID-MTTE controller maintains greater vehicle directional stability, which is more important than the pursuit of greater acceleration.

Tyres behave similar to a spring and damper systems smoothing out road irregularities as the tyre rolls. Tyre stiffness and damping characteristics are largely influenced by the tyre pressure. As a result, tyre pressure has an influence on tyre enveloping and ride comfort. To take advantage of the influence of tyre pressure on ride comfort, a pressure controlled tyre was developed to vary the tyre pressure, thus varying the tyre characteristics as the road conditions change to improve ride comfort. Literature exists on TIS (Tyre Inflation Systems) and smart suspension control strategies optimised for ride comfort, which indicate that a pressure controlled tyre can be developed by managing a TIS with a ride comfort controller. A VDG (Vehicle Dynamics Group) test trailer was used to complete this study. The trailer was modelled on three platforms; MATLAB, Cosin and ADAMS View; with the co-simulation managed through Simulink. Three tests were conducted to parametrise and validate the model, namely; pneumatic system parametrisation tests, APG (Aberdeen Proving Ground) bump tests and Belgian paving tests. The pneumatic system parametrisation tests show that the discharge coefficient is approximately 0.07 for choked flow and tappers off to zero for unchoked flow. Also, tests show that the tyre can be inflated from 1.0 bar to 3.0 bar in 8 s and deflated from 3.0 barto 1.0 bar in 13 s. The APG bump tests and Belgian paving tests were conducted to validate the model over discrete obstacles and rough roads, respectively. These tests indicate that the model correlates with the actual trailer. The validated model was used to develop the TIPc (Tyre Inflation Pressure controller), which uses a running RMS control strategy to manage the TIS. The objective of the TIPc is to maintain a NOT uncomfortable ride comfort level. The TIPc achieves this by deflating the tyre to a suitable tyre pressure when the ride comfort level is above NOT uncomfortable. The TIPc is robust to evaluate ride comfort on smooth roads and rough roads, as well as, detecting discrete obstacles. The TIPc ignores discrete obstacles when evaluating ride comfort to determine a suitable tyre pressure to improve ride comfort. The TIPc was able to achieve a 4−7% RCI (Ride Comfort Improvement). / Dissertation (MEng)--University of Pretoria, 2020. / Mechanical and Aeronautical Engineering / MEng / Unrestricted

As vehicle dynamics research delves deeper into better insights in performance, modeling, and vehicle controls, one area remains of utmost importance: tire and road friction forces. The vehicle???s interaction with the road remains the dominant mean of vehicle control. Ultimately, the tire-road interaction will determine the majority of the vehicle???s capabilities and as the understanding of the interface improves, so too can the performance. With more computationally intensive systems being instrumented into modern vehicle systems, one is able to observe a great deal of important vehicle states directly for the remaining vehicle information; excellent estimation techniques are providing the rest of the insights. This study looks at the possible improvements that can be observed by implementing an adaptive dynamic tire model that is physical and flexible enough to permit time varying tire performance. The tire model selected is the Average Lumped LuGre Friction Tire Model, which was originally developed from physical properties of friction and tire systems. The material presented here examines the possibility of an adaptive tire model, which can be implemented on a real-time vehicle platform. The adaptive tire model is just one section of an entire control strategy that is being developed by General Motors in partnership with the University of Waterloo. The approach allows for estimated and measured vehicle information to provide input excitation for the tire model when driven with real-world conditions that enabling tire estimations. The tire model would then provide the controller information indicating the expected tire capacity and compares it with the instantaneous loading. The adaptive tire model has been tested with flat road experimental cases and the results provided reasonable estimates. The experimentation was performed with a fully instrumented research vehicle that used in-wheel force transducers, and later repeated with a completely different non-instrumented fully electric vehicle. The concepts and investigation presented here has initiated the ground work for a real-time implementation of a full adaptive tire model. Further work is still required to evaluate the influence of a range of operating conditions, tire pressure, and of different tire types. However, the findings indicate that this approach can produce reasonable results for the specified conditions examined.

Published Article / Today's industries are based on an automated workplace. These automated workplaces are efficient, reconfigurable and intelligent automated environments. They are filled with technology, robotics, Automated Guided Vehicle (AGV) and, or Unmanned Aerial Vehicles (UAV) etc. For full automation will one need to effectively track an object, unmanned aerial vehicle (UAV) or automated guided vehicle (AGV). Effective tracking of vehicles can be used for control. This could result in less hardware on the craft that leads to a longer battery life, a bigger pay load or more processing power. This system track by using a stationary colour camera placed at an optimal placing in the automated workplace. The vehicle or objects are painted in two colours (colour A and colour B) that are not present in the automated workplace. The images from the camera are hue colour filtered to extract only the object or vehicle. The area, placement in frame and relationship between colour A and B are used for position and determine the orientation of AGV, UAV or object.

The design of the electric platform in military vehicles requires the ability to determine the best combination of power system components that support the desired operational abilities, while minimizing the size, weight, cost, and impact of the overall power system. Because prototypes are both time consuming, rigid, and costly, they have become inadequate for verifying system performance. By using simulations, engineers can best plan for and observe the associations between missions (including modes of operation and system scenarios) and system performance in a dynamic, realistic environment. This thesis proposes a new tool to analyze and design military vehicle platforms: the Advanced Mobile Integrated Power System (AMPS). This tool is useful for design and design verification of military vehicles due to its unique incorporation of mission-specific functionality. It allows the user ease of design with the ability to customize the vehicle power system architecture and components, while permitting full control over source and load input parameters. Simulation of programmed mission sequences allows the user to ensure that the chosen vehicle architecture can provide all of the electrical power and energy needed to support the mission, thus providing adequate design verification. The present thesis includes an introduction to vehicle power systems and an outline of the need for simulation, a description of the AMPS project and vehicle specifications, analytical and numerical models of the simulated vehicle, explanation of the power management system, description of the graphical user interface, and a simulation performed with the AMPS tool.

This thesis describes and evaluates the conversion of a conventional gasoline powered all-terrain vehicle (ATV) to an electric ATV. Preliminary studies are performed to obtain initial power and torque requirements for the vehicle. A detailed simulation model of the mechanical load is written and compared to manufacturer supplied data. The load model is then combined with a comprehensive electronic drive and motor simulation using an electromagnetic transient simulation program (PSCAD). A prototype of the vehicle is constructed by selecting the main components, an electric traction motor, batteries and a custom motor drive, using the simulation results. The results of both the simulation and prototypes are compared and evaluated. / February 2009

The design of the electric platform in military vehicles requires the ability to determine the best combination of power system components that support the desired operational abilities, while minimizing the size, weight, cost, and impact of the overall power system. Because prototypes are both time consuming, rigid, and costly, they have become inadequate for verifying system performance. By using simulations, engineers can best plan for and observe the associations between missions (including modes of operation and system scenarios) and system performance in a dynamic, realistic environment. This thesis proposes a new tool to analyze and design military vehicle platforms: the Advanced Mobile Integrated Power System (AMPS). This tool is useful for design and design verification of military vehicles due to its unique incorporation of mission-specific functionality. It allows the user ease of design with the ability to customize the vehicle power system architecture and components, while permitting full control over source and load input parameters. Simulation of programmed mission sequences allows the user to ensure that the chosen vehicle architecture can provide all of the electrical power and energy needed to support the mission, thus providing adequate design verification. The present thesis includes an introduction to vehicle power systems and an outline of the need for simulation, a description of the AMPS project and vehicle specifications, analytical and numerical models of the simulated vehicle, explanation of the power management system, description of the graphical user interface, and a simulation performed with the AMPS tool.