<p>Accurate measurements from sensors measuring the vehicle's lateral behavior are vital in todays vehicle dynamic control systems such as the Electronic Stability Program (ESP). This thesis concerns accurate plausibilisation of two of these sensors, namely the yaw rate sensor and the lateral acceleration sensor. The estimation is based on Kalman filtering and culminates in the use of a 2 degree-of-freedom nonlinear two-track model describing the vehicle lateral dynamics. The unknown and time-varying cornering stiffnesses are adapted while the unknown yaw moment of inertia is estimated. The Kalman filter transforms the measured signals into a sequence of residuals that are then investigated with the aid of various change detection methods such as the CuSum algorithm. An investigation into the area of adaptive thresholding has also been made.</p><p>The change detection methods investigated successfully detects faults in both the yaw rate and the lateral acceleration sensor. It it also shown that adaptive thresholding can be used to improve the diagnosis system. All of the results have been evaluated on-line in a prototype vehicle with real-time fault injection.</p>

No description available.

Wind tunnel studies of the wake behind model wind turbines with one, two and three blades have been made in order to get a better understanding of wake development as well as the possibility to predict the power output from downstream turbines working in the wake of an upstream one. Both two-component hot-wire anemometry and particle image velocimetry (PIV) have been used to map the flow field downstream as well as upstream the turbine. All three velocity components were measured both for the turbine rotor normal to the oncoming flow as well as with the turbine inclined to the free stream direction (the yaw angle was varied from 0 to 30 degrees). The measurements showed, as expected, a wake rotation in the opposite direction to that of the turbine. A yawed turbine is found to clearly deflect the wake flow to the side showing the potential of controlling the wake position by yawing the turbine. The power output of a yawed turbine was found to depend strongly on the rotor. The possibility to use active wake control by yawing an upstream turbine was evaluated and was shown to have a potential to increase the power output significantly for certain configurations. An unexpected feature of the flow was that spectra from the time signals showed the appearance of a low frequency fluctuation both in the wake and in the flow outside. This fluctuation was found both with and without free stream turbulence and also with a yawed turbine. The non-dimensional frequency (Strouhal number) was independent of the freestream velocity and turbulence level but increases with the yaw angle. However the low frequency fluctuations were only observed when the tip speed ratio was high. Porous discs have been used to compare the meandering frequencies and the cause in wind turbines seems to be related to the blade rotational frequency. It is hypothesized that the observed meandering of wakes in field measurements is due to this shedding. / QC 20101018

In this thesis we investigate the problem of designing a control system for a modern bicycle so that the bicycle is stable and follows a path. We propose a multi-loop control architecture, where each loop is systematically designed using linear control techniques. The proposed strategy guarantees that the bicycle asymptotically converges to paths of constant curvature. A key advantage of our approach is that by using linear techniques analysis and controller design are relatively simple. We base our control design on the nonlinear (corrected) Whipple model, which has been previously verified for correctness and experimentally validated. The equations of motion for the nonlinear model are very complicated, and would take many pages to explicitly state. They also have no known closed form solution. To enable analysis of the model we linearize it about a trajectory such that the bicycle is upright and travelling straight ahead. This linearization allows us to arrive at a parameterized linear time-invariant state-space representation of the bicycle dynamics, suitable for analysis and control design. The inner-loop control consists of a forward-speed controller as well as a lean and steer controller. To keep the bicycle at a constant forward speed, we develop a high-bandwidth proportional controller that uses a torque along the axis of the rear wheel of the bicycle to keep the angular velocity of the rear wheel at a constant setpoint. To stabilize the bicycle at this forward speed, lean torque and steer torque are treated as the control signals. We design a state-feedback controller and augment integrators to the output feedback of the lean angle and steer angle to provide perfect steady-state tracking. To arrive at the gains for state feedback, linear-quadratic regulator methods are used. When following a constant-curvature path, a vehicle has a constant yaw rate. Using this knowledge, we begin designing the outer-loop path-following control by finding a map that converts a yaw rate into appropriate lean angle and steer angle references for the inner loop. After the map is completed, system identification is performed by applying a yaw-rate reference to the map and analyzing the response of the bicycle. Using the linear approximation obtained, a classical feedback controller for yaw-rate tracking is designed. In addition to yaw-rate control, to track a path the yaw angle of the bicycle must match that of the path and the bicycle must physically be on the path. To analyze these conditions a linear approximation for the distance between the bicycle to the path is found, enabling construction of a linear approximation of the entire system. We then find that by passing the signal for the difference in yaw rate and the distance through separate controllers, summing their output, and subtracting from the reference yaw rate of the path, the bicycle converges to the path. After developing the general design procedure, the final part of the thesis shows a step by step design example and demonstrates the results of applying the proposed control architecture to the nonlinear bicycle model. We highlight some problems that can arise when the bicycle is started far from the path. To overcome these problems we develop the concept of a virtual path, which is a path that when followed returns the bicycle to the actual path. We also recognize that, in practice, typical paths do not have constant curvature, so we construct more practical paths by joining straight line segments and circular arc segments, representing a practical path similar to a path that would be encountered when biking through a series of rural roads. Finally, we finish the design example by demonstrating the performance of the control architecture on such a path. From these simulations we show that using the suggested controller design that the bicycle will converge to a constant curvature path. Additionally with using the controllers we develop that in the absence of disturbance the bicycle will stay within the intended traffic lane when travelling on a typical rural road.

The purpose of this project is to continue the work on a vehicle model developed in ADAMS/Car and applied with the concept of ACM (Autonomous Corner Module). The project is divided up in two parts. The objective of the first part is to setup a co-simulation environment between ADAMS/Car and MATLAB/Simulink, and evaluate the vehicle model. In the second part a yaw controller is developed using only the rear wheel steering possibilities. The controller will be evaluated when it is applied on the vehicle model. The approach is to develop two models, one simpler in MATLAB/Simulink and one more complex in ADAMS/Car, and verify that they show similar behavior. The models will then be linearized and the control design will be based on the most appropriate linear model. Most of the work has been developing and evaluating the two vehicle models in ADAMS/Car and MATLAB/Simulink. The result was a working co-simulation environment where an evaluation of two different controllers was made. Due to linearization of the ADAMS model was nsuccessful, the controllers were based on the simpler linear Simulink model. Both controllers show similar results. Tests on the ADAMS model showed that it is hard to control both the yaw rate and body slip only by rear wheel steering.

Accurate measurements from sensors measuring the vehicle's lateral behavior are vital in todays vehicle dynamic control systems such as the Electronic Stability Program (ESP). This thesis concerns accurate plausibilisation of two of these sensors, namely the yaw rate sensor and the lateral acceleration sensor. The estimation is based on Kalman filtering and culminates in the use of a 2 degree-of-freedom nonlinear two-track model describing the vehicle lateral dynamics. The unknown and time-varying cornering stiffnesses are adapted while the unknown yaw moment of inertia is estimated. The Kalman filter transforms the measured signals into a sequence of residuals that are then investigated with the aid of various change detection methods such as the CuSum algorithm. An investigation into the area of adaptive thresholding has also been made. The change detection methods investigated successfully detects faults in both the yaw rate and the lateral acceleration sensor. It it also shown that adaptive thresholding can be used to improve the diagnosis system. All of the results have been evaluated on-line in a prototype vehicle with real-time fault injection.

No description available.

<p>Wind tunnel studies of the wake behind a model wind turbine have been made in order to get a better understanding of wake development as well as the possibility to predict the power output from downstream turbines working in the wake of an upstream one. Both two-component hot-wire anemometry as well as particle image velocimetry (PIV) have been used to map the flow field. All three velocity components were measured both for the turbine rotor normal to the oncoming flow as well as with the turbine inclined to the free stream direction (the yaw angle was varied from 0 to 30 degrees). The measurements showed, as expected, a wake rotation in the opposite direction to that of the turbine. A yawed turbine is found to clearly deflect the wake flow to the side showing the potential of controlling the wake position by yawing the turbine. The power output of a yawed turbine was found to vary nearly as the square of the cosine of the yaw angle. The possibility to use active wake control by yawing an upstream turbine was evaluated and was shown to have a potential to increase the power output significantly for certain configurations. An unexpected feature of the flow was that spectra from the time signals showed the appearance of a low frequency fluctuation both in the wake and in the flow outside. This fluctuation was found both with and without free stream turbulence and also with a yawed turbine. The non-dimensional frequency (Strouhal number) was independent of the free-stream velocity and turbulence level but increases with the yaw angle. However the low frequency fluctuations were only observed when the tip speed ratio (or equivalently the drag coefficient) was high. This is in agreement with the idea that the turbine shed structures as a bluff body. It is hypothesized that the observed meandering of wakes in field measurements is due to this shedding.</p>

<p>Wind tunnel studies of the wake behind model wind turbines with one, two and three blades have been made in order to get a better understanding of wake development as well as the possibility to predict the power output from downstream turbines working in the wake of an upstream one. Both two-component hot-wire anemometry and particle image velocimetry (PIV) have been used to map the flow field downstream as well as upstream the turbine. All three velocity components were measured both for the turbine rotor normal to the oncoming flow as well as with the turbine inclined to the free stream direction (the yaw angle was varied from 0 to 30 degrees). The measurements showed, as expected, a wake rotation in the opposite direction to that of the turbine. A yawed turbine is found to clearly deflect the wake flow to the side showing the potential of controlling the wake position by yawing the turbine. The power output of a yawed turbine was found to depend strongly on the rotor. The possibility to use active wake control by yawing an upstream turbine was evaluated and was shown to have a potential to increase the power output significantly for certain configurations. An unexpected feature of the flow was that spectra from the time signals showed the appearance of a low frequency fluctuation both in the wake and in the flow outside. This fluctuation was found both with and without free stream turbulence and also with a yawed turbine. The non-dimensional frequency (Strouhal number) was independent of the freestream velocity and turbulence level but increases with the yaw angle. However the low frequency fluctuations were only observed when the tip speed ratio was high. Porous discs have been used to compare the meandering frequencies and the cause in wind turbines seems to be related to the blade rotational frequency. It is hypothesized that the observed meandering of wakes in field measurements is due to this shedding.</p>

<p>The purpose of this project is to continue the work on a vehicle model developed in ADAMS/Car and applied with the concept of ACM (Autonomous Corner Module). The project is divided up in two parts. The objective of the first part is to setup a co-simulation environment between ADAMS/Car and MATLAB/Simulink, and evaluate the vehicle model. In the second part a yaw controller is developed using only the rear wheel steering possibilities. The controller will be evaluated when it is applied on the vehicle model. </p><p>The approach is to develop two models, one simpler in MATLAB/Simulink and one more complex in ADAMS/Car, and verify that they show similar behavior. The models will then be linearized and the control design will be based on the most appropriate linear model. Most of the work has been developing and evaluating the two vehicle models in ADAMS/Car and MATLAB/Simulink. </p><p>The result was a working co-simulation environment where an evaluation of two different controllers was made. Due to linearization of the ADAMS model was nsuccessful, the controllers were based on the simpler linear Simulink model. Both controllers show similar results. Tests on the ADAMS model showed that it is hard to control both the yaw rate and body slip only by rear wheel steering.</p>