<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>

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.

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.

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.

No description available.

The main aim of this research project is to extend theories of four-wheel-steering as developed by J. Ackermann to include an individually steered four-wheel steering system for passenger vehicles. Ackermann’s theories, including theories available in this subject area, dwell much on vehicle system dynamics developed from what is called single track model and some call it a bicycle model. In the bicycle model, the front two wheels are bundled together. Similarly, the rear wheels are bundled together. The problem with this is that it assumes two front wheels or two rear wheels to be under the same road, vehicle and operating conditions. The reality on the ground and experiments that are conducted are to the contrary. Therefore this study discusses vehicle disturbance rejection through robust decoupling of yaw and lateral motions of the passenger vehicle. A mathematical model was developed and simulated using Matlab R2008b. The model was developed in such a way that conditions can be easily changed and simulated. The model responded well to variations in road and vehicle conditions. Focus was in the ability of the vehicle to reject external disturbances. To generate yaw moment during braking, the brake on the left front wheel was disconnected. This was done because lateral wind generators, as used by Ackermann, were not available. The results from both simulations and experiments show disturbance rejection in the steady state. Copyright / Dissertation (MSc)--University of Pretoria, 2010. / Mechanical and Aeronautical Engineering / unrestricted

It is possible to obtain information about the stability conditions of a vehicle by observing and comparing existing signals involved in the rotational motion of the vehicle around the vertical axis. Accurate information about the current state of a vehicle is critical for the development and function of new active safety features in a vehicle. Therefore, the goal of this thesis is to create a new signal based on already existing signals from the vehicle electronic control unit for detecting understeering and oversteering of a vehicle. The signal should consider all the factors that affect the evaluation of the vehicle´s stability conditions. The results show that the developed signal can, in certain conditions, detect understeering and oversteering. Issues arise in situations such as banked curves or low-mu surfaces. In those cases, the signal is not fully able to describe the vehicle behavior.

This diploma thesis deals with the possibilities of determining the influence of electronic stability systems on the chassis of the vehicle driving dynamics. In the introductory section is made theoretical analysis of road vehicle dynamics. Further description is made of some stabilization systems and situations and how to solve them by using these systems. Chapter 6.2.1 describes the methodology of practical experiment, which can determine influence of the stability system of the vehicle chassis on driving dynamics. The next chapter describes an experiment conducted and interpreted the measured values. The penultimate chapter is a simulation of this experiment using simulation software Virtual Crash. The last chapter is an evaluation of the experiment and compares the results with simulation programs using the same input conditions. The conclusion summarizes the results of this work.

Die komplexen Strukturen von MEMS-Drehratensensoren führen immer wieder zu Herausforderungen bei der Systembeschreibung. Die zunehmende Miniaturisierung der Bauteile steigert den Einfluss von mechanischen Nichtlinearitäten und AVT-Einflüssen. Daher sind ein tiefer gehendes Verständnis dieser Effekte und verbesserte Simulationsmethoden zur effizienten Entwicklung neuer Sensoren von großer Bedeutung. In dieser Arbeit wird die TPWL-Methode, ein Ansatz für ein transientes nichtlineares ROM, vorgestellt und erfolgreich auf MEMS-Drehratensensoren angewendet. Im Fokus der Untersuchungen stehen die Implementierung der Methode und die Zeitersparnis gegenüber FE-Simulationen - diese beträgt bis zu 3 Größenordnungen. Weiterhin finden sich Untersuchungen der ROM-Daten, mit einem Schwerpunkt auf deren Interpretation, in den Ausführungen. Hierdurch werden Limitierungen, Rahmenbedingungen und Aussagekraft der Methodik aufgezeigt. Diese Erkenntnisse ermöglichen es, zukünftige Simulationen durch geeignet gewählte Parameter und Trainingsdaten effektiv aufzusetzen. Es werden TPWL-Ansätze auf Basis von POD und modaler Superposition verglichen, um systematische Vorteile der POD zu erklären. Die Validierung der Modelle erfolgt qualitativ sowie mit Messungen, analytischen und FE-Rechnungen. Bestehende Ansätze zur Simulation von AVT-Einflüssen, mit einem Schwerpunkt auf mechanischen Stresswirkpfaden, auf MEMS-Drehratensensoren werden untersucht und erweitert. Als Basis für Package- und statische Struktursimulationen dienen FE-Modelle und für die transiente Systemsimulation ein ROM. Es stehen Verständnis und Analyse der Wirkpfade im Vordergrund. Die resultierenden Erkenntnisse werden erfolgreich in die Modelle eingebracht. Ein einfacher, dennoch aussagekräftiger Ansatz zur Abschätzung des Drehraten-Offsets gestresster Sensoren wird vorgestellt. Zudem wird ein vielversprechendes neuartiges FE-Modell zur Simulation von Die-attach- und Lötsimulationen hergeleitet. Oberflächen- und Signalmessungen von durch eine Leiterplattenbiegung gestressten Sensoren dienen zur Validierung. Die vorgestellten Modelle werden erfolgreich validiert und können zukünftig zur Optimierung des Entwicklungsprozesses von MEMS-Drehratensensoren verwendet werden.:Abkürzungen und Symbole I. Einführung, Grundlagen und Methoden 1. Einleitung 1.1. Hintergrund und aktuelle Entwicklung 1.2. Motivation und Zielsetzung der Arbeit 1.3. Struktur der Arbeit 2. Grundlagen MEMS 2.1. Definition der Mikrosystemtechnik 2.2. Technologie und Aufbau von MEMS Bausteinen 2.3. Funktionsprinzipien und physikalischen Grundlagen von MEMS-Gyroskopen 3. Rechenmodelle für mechanische Systeme 3.1. Analytische Rechnungen mithilfe der Balkentheorie 3.2. Finite-Elemente-Methode 3.3. Ordnungsreduktionsverfahren 3.4. Ordnungsreduzierte Systemmodelle in der Signalflusssimulation II. Mechanische Nichtlinearitäten 4. Nichtlinearitäten in MEMS-Gyroskopen 4.1. Einleitung und Motivation 4.2. Gegenüberstellung nichtlinearer Effekte und deren Einflüsse auf MEMS-Gyroskope 4.3. Konzepte zur Vermeidung von Stress-Stiffening und deren Grenzen 5. Methoden zur Simulation mechanischer Nichtlinearitäten 5.1. Nichtlineare Effekte in der FE-Rechnung 5.2. Konzept der Trajectory Piecewise Linearization 5.3. Werkzeuge zur Implementierung eines TPWL-Verfahrens in die Systemsimulation 5.4. Generierung einer ordnungsreduzierten TPWL-Simulation von Drehratensensoren 6. Die Trajectory Piecewise Linearization in der Praxis 6.1. Beidseitig eingespannter Biegebalken in der TPWL mit POD 6.2. Die TPWL anhand eines perforierten Einmassenschwingers 6.3. Untersuchung einer stark nichtlinearen Sensorgeometrie III. Einfluss von mechanischem Stress durch die Aufbau- und Verbindungstechnik auf Sensoren und Sensor-Packages 7. Messungen und Simulationen in der AVT 7.1. Einleitung und Motivation 7.2. Einfluss von mechanischem Stress auf die Sensorgeometrie 7.3. Schema einer Stresssimulation 7.4. Experimentelles Setup 7.5. Viskoelastische Eigenschaften in Experiment und Simulation 8. FE-Package Simulationen 8.1. Annahmen 8.2. Struktur und Inhalt einer FE-Package-Simulation 8.3. CAD-Modellierung und Vernetzung 8.4. Prozesssimulationen 8.5. Biegesimulation 8.6. Validierung durch Weißlichtinterferometrie 9. FE-Modelle von MEMS Strukturen 9.1. Transfer des AVT Stresses aus den Package Simulationen 9.2. Stresseinfluss auf Eigenfrequenzen 10.Berücksichtigung von AVT-Einflüssen in Signalflusssimulationen 10.1. Signalflussmodelle mit AVT-Einfluss 10.2. Sensormoden und Dämpfungsmatrix 10.3. Validierung der Modelle anhand des Closed-Loop Systems 10.4. Simulation des Dreikanalsensors IV. Abschluss 11.Zusammenfassung 11.1. Mechanische Nichtlinearitäten 11.2. Einfluss der Aufbau- und Verbindungstechnik 12.Fazit und Ausblick V. Anhang A. Faktoren der Newmark-Integration B. Einfluss der Samplingrate auf die Schwingungsfrequenz in einer transienten FE-Simulation C. Ergebnisstabellen zu Kapitel 6.1 D. Einseitig eingespannter Biegebalken mit Streckbiegung D.1. Aufbau des Systems D.2. Systemtraining D.3. Systemsimulation und Auswertung D.4. Fazit E. Modenabbildungen zu Kapitel 6.2 F. Vergleich von TPWL und linearer Ordnungsreduktion mit nichtlinearen Kräften G. Modellbeispiel Schwingungsform H. Mathematische Ergänzungen I. Einfluss von Prozessparametern Quellenangaben Tabellenverzeichnis Abbildungsverzeichnis Danksagung Versicherung Thesen / The complex structures of MEMS yaw-rate sensors continuously lead to challenges in their system description. The continuing miniaturization of the components increases the effects of mechanical nonlinearities and packaging influences. Therefore, a deeper understanding of these effects and improved simulation methods are of great importance for the efficient development of new sensors. In this work the TPWL-method, an approach for a transient nonlinear ROM, is introduced and successfully applied to MEMS yaw-rate sensors. The focal points of the study, are the implementation of the method, and the time savings compared to FE-simulations; which are up to 3 magnitudes. Furthermore, the analysis of the ROM-data with a focus on its interpretation is included. This highlights limits, boundary conditions and the informative value of the method. These insights enable the future set up of simulations effectively with appropriately chosen parameters and training data. TPWL-approaches with POD and modal superposition are compared to highlight systematic advantages of the POD. The validation of the models is realized qualitatively as well as with measurements, analytical and FE-calculations. Existing approaches for the simulation of packaging influences with a focal point on mechanical stress root causes are studied and extended. As a baseline for package and static structure simulations FE-models are used, and for transient system simulations a ROM is used. Understanding and analysis of the root causes stand in the foreground. The resulting insights are successfully implemented into the models. A simple but significant approach for an estimation of the yaw-rate offset of stressed sensors is introduced. Additionally, a promising and new FE-model for the simulation of die attach and solder simulations is derived. Surface and signal measurements of sensors, stressed by the bending of a printed circuit board, serve for validation. The introduced models were validated successfully and can be used in the future to optimize the development process of MEMS yaw-rate sensors.:Abkürzungen und Symbole I. Einführung, Grundlagen und Methoden 1. Einleitung 1.1. Hintergrund und aktuelle Entwicklung 1.2. Motivation und Zielsetzung der Arbeit 1.3. Struktur der Arbeit 2. Grundlagen MEMS 2.1. Definition der Mikrosystemtechnik 2.2. Technologie und Aufbau von MEMS Bausteinen 2.3. Funktionsprinzipien und physikalischen Grundlagen von MEMS-Gyroskopen 3. Rechenmodelle für mechanische Systeme 3.1. Analytische Rechnungen mithilfe der Balkentheorie 3.2. Finite-Elemente-Methode 3.3. Ordnungsreduktionsverfahren 3.4. Ordnungsreduzierte Systemmodelle in der Signalflusssimulation II. Mechanische Nichtlinearitäten 4. Nichtlinearitäten in MEMS-Gyroskopen 4.1. Einleitung und Motivation 4.2. Gegenüberstellung nichtlinearer Effekte und deren Einflüsse auf MEMS-Gyroskope 4.3. Konzepte zur Vermeidung von Stress-Stiffening und deren Grenzen 5. Methoden zur Simulation mechanischer Nichtlinearitäten 5.1. Nichtlineare Effekte in der FE-Rechnung 5.2. Konzept der Trajectory Piecewise Linearization 5.3. Werkzeuge zur Implementierung eines TPWL-Verfahrens in die Systemsimulation 5.4. Generierung einer ordnungsreduzierten TPWL-Simulation von Drehratensensoren 6. Die Trajectory Piecewise Linearization in der Praxis 6.1. Beidseitig eingespannter Biegebalken in der TPWL mit POD 6.2. Die TPWL anhand eines perforierten Einmassenschwingers 6.3. Untersuchung einer stark nichtlinearen Sensorgeometrie III. Einfluss von mechanischem Stress durch die Aufbau- und Verbindungstechnik auf Sensoren und Sensor-Packages 7. Messungen und Simulationen in der AVT 7.1. Einleitung und Motivation 7.2. Einfluss von mechanischem Stress auf die Sensorgeometrie 7.3. Schema einer Stresssimulation 7.4. Experimentelles Setup 7.5. Viskoelastische Eigenschaften in Experiment und Simulation 8. FE-Package Simulationen 8.1. Annahmen 8.2. Struktur und Inhalt einer FE-Package-Simulation 8.3. CAD-Modellierung und Vernetzung 8.4. Prozesssimulationen 8.5. Biegesimulation 8.6. Validierung durch Weißlichtinterferometrie 9. FE-Modelle von MEMS Strukturen 9.1. Transfer des AVT Stresses aus den Package Simulationen 9.2. Stresseinfluss auf Eigenfrequenzen 10.Berücksichtigung von AVT-Einflüssen in Signalflusssimulationen 10.1. Signalflussmodelle mit AVT-Einfluss 10.2. Sensormoden und Dämpfungsmatrix 10.3. Validierung der Modelle anhand des Closed-Loop Systems 10.4. Simulation des Dreikanalsensors IV. Abschluss 11.Zusammenfassung 11.1. Mechanische Nichtlinearitäten 11.2. Einfluss der Aufbau- und Verbindungstechnik 12.Fazit und Ausblick V. Anhang A. Faktoren der Newmark-Integration B. Einfluss der Samplingrate auf die Schwingungsfrequenz in einer transienten FE-Simulation C. Ergebnisstabellen zu Kapitel 6.1 D. Einseitig eingespannter Biegebalken mit Streckbiegung D.1. Aufbau des Systems D.2. Systemtraining D.3. Systemsimulation und Auswertung D.4. Fazit E. Modenabbildungen zu Kapitel 6.2 F. Vergleich von TPWL und linearer Ordnungsreduktion mit nichtlinearen Kräften G. Modellbeispiel Schwingungsform H. Mathematische Ergänzungen I. Einfluss von Prozessparametern Quellenangaben Tabellenverzeichnis Abbildungsverzeichnis Danksagung Versicherung Thesen