Semi-active suspension systems has become an increasingly popular alternative to the passive suspensions in recent time. By varying the spring stiffness and damping coefficient in the system, different characteristics can be achieved depending on driver preferability and road disturbances. The difference in damping coefficient will however lead to a trade-off between comfort and road holding,which means that in order to improve one of the areas, performance in the other will need to be reduced. This trade-off will also be different depending on the underlying road disturbances. This thesis is conducted on behalf of Volvo Cars, who are looking for a strategy in order to analyze the trade-off for different ISO classified roads which has been done through a literature study, theoretical analysis and comparison of control methods for different roads. A skyhook based controller was built with added modifications in order to reduce the jerk in the vehicle. Tests with the controller were carried out on a quarter car model as well as a full car model in IPG Carmaker. The simulations with the quarter car model showed that the controllerimproved the peak jerk values as well as the comfort, compared to both skyhook control and passive suspension. The full car simulations consisted of test runs on four roads, all with different road profiles and frequency content. For each road, tests were conducted with two different damper control methods as well as with a varying spring stiffness.The tested damper control methods were force gain control, which modulates the force request from the skyhook controller, as well as rate limitation control, which modulates the rate at which current is applied to the damper. The results showed that the trade-off between road holding and comfort appeared differently when the road profile changed. All results were compared to Janeway’s comfort criterion in order to validate the comfort of the vehicle. The outcome of the thesis was a strategy that involved various tuning for the semi-active damper and air suspension depending on the primary and secondary ride nature of the road. More specifically, a stiff damping is preferred during general primary ride conditions and a soft damping is preferred during general secondary ride conditions. For cases when the low frequency disturbances are small, the trade-off will be small and comfort can be improved with little to no cost of road holding. When the high frequency disturbances increase in amplitude, the damper should be tuned depending on preferability. For improved road holding ability, a stiff damping is preferred and for improved comfort, a soft damping is preferred. A soft spring will, for most cases, be preferred in terms of both road holding and comfort.

In the last decades, the development of self-driving vehicles has rapidly increased. Improvements in algorithms, as well as sensor and computing hardware have led to self-driving technologies becoming a reality. It is a technology with the potential to radically change how society interacts with transportation. One crucial part of a self-driving vehicle is control schemes that can safely control the vehicle during evasive maneuvers. This work investigates the modeling and lateral control of tractor-trailer vehicles during aggressive maneuvers. Models of various complexity are used, ranging from simple kinematic models to complex dynamic models, which model tire slip and suspension dynamics. The models are evaluated in simulations using TruckMaker, which is a high fidelity vehicle simulator. Several lateral controllers are proposed based on Model predictive control (MPC) and linear-quadratic (LQ) control techniques. The controllers use different complex prediction models and are designed to minimize the path-following error with respect to a geometric reference path. Their performance is evaluated on double lane change maneuvers of various lengths and with different longitudinal speeds. Additionally, the controllers' robustness against changes in trailer mass, weight distribution, and road traction is investigated. Extensive simulations show that dynamic prediction models are necessary to keep the control errors small when performing maneuvers that result in large lateral accelerations. Furthermore, to safely control the tractor-trailer vehicle during high speeds, it is a necessity to include a model of the trailer dynamics. The simulation study also shows that the proposed LQ controllers have trouble to evenly balance tractor and trailer deviation from the path, while the MPC controllers handle it much better. Additionally, a method for approximately weighting the trailer deviation is shown to improve the performance of both the LQ and MPC controllers. Finally, it is concluded that an MPC controller with a dynamic tractor-trailer model is robust against model errors, and can become even more robust by tuning the controller weights conservatively.

This thesis is providing an insight into the verification of a quasi-static simulation model based on the estimation of fuel consumption using machine learning methods. Traditional verification using real test data is not always available. Therefore, a methodology consisting of verification analysis based on estimation methods was developed together with an improving process of a quasi-static simulation model. The modelling of the simulation model mainly consists of designing and implementing a gear selection strategy together with the gearbox itself for a dual clutch transmission dedicated to hybrid application. The purpose of the simulation model is to replicate the fuel consumption behaviour of vehicle data provided from performed tests. To verify the simulation results, a so-called ranking model is developed. The ranking model estimates a fuel consumption reference for each time step of the WLTC homologation drive cycle using multiple linear regression. The results of the simulation model are verified, and a scoring system is used to indicate the performance of the simulation model, based on the correlation between estimated- and simulated data of the fuel consumption. The results show that multiple linear regression can be an appropriate approach to use as verification of simulation models. The normalised cross-correlation power is also examined and turns out to be a useful measure for correlation be-tween signals including a lag. The developed ranking model is a fast first step of evaluating a new vehicle configuration concept.

Vehicle Platooning has emerged in recent years as a promising method to reducethe fuel consumption of heavy trucks in long-distance transportation. Platoon-ing lowers the fuel consumption by forming strings of vehicles driving very closebehind each other, thus reducing the air drag. However, in order to form aplatoon, vehicles have to follow a common route. As vehicles are scattered overa road network, some sort of high-level coordination and route planning is re-quired to unlock the full potential of this technique. In this thesis, we evaluatevarious methods to minimize the total fuel consumption of a large-scale systemby guiding vehicles to fuel-ecient paths.We develop a comprehensive mathematical formulation of the problem andpresent a global solution approach to the problem. The approach is implementedand the investigation of the fuel reduction potential shows promising results.However, an exponential increase in computational complexity makes it unsuitedfor problems involving more than 20 trucks, even on small road networks.As a consequence, we then promote a locally distributed approach whichis able to eciently solve large problems. We implement such a distributedalgorithm and run large simulations on a model of the German autobahn roadnetwork. Results show that signicant savings can be achieved for even a fewhundred vehicles. We also investigate the in uence of the number of trucks onthe total fuel savings and examine the eect of limiting the maximum traveltime of trucks.

Truck suspension technology has traditionally comprised more or less passive elements that possibly are adjusted slowly compared to the suspension dynamics. In attempts to overcome the inherent comfort-handling trade off, departures from fully passive designs have been made in the past. Fully active suspensions have successfully been implemented in private cars but have gained little ground in the truck industry because of their large energy consumption and high cost. Semi-active suspensions take a middle-ground with lower performance potential but also with considerably lower power requirements and cost of implementation. Effective controller design for a semi-active suspension includes consideration of the passivity constraints imposed on the control force. In this thesis an optimisation algorithm was written in MATLAB in a way that allows for embedded code-generation and was then used for designing a Model Predictive Controller (MPC) with switched passivity constraints. The resulting controller was tested on a 3D truck-trailer model and evaluated, together with other controllers as well as the passive system against both comfort and handling metrics. Non-convexity generally makes an MPC less useful for high sampling rates but with a switched linear approximation of the passivity constraints the resulting controller was shown to still be effective.

This thesis focuses on control of nonholonomic system with particular reference to the unicycle-like robots. These are common examples of WMRs (Wheeled Mobile Robots), increasingly present in industrial and service robotics, particularly when exible motion capabilities are required. The major objective of this study is to solve the regulation problem for the unicycle model while guaranteeing prescribed performance. Dierent controllers based on either polar coordinates or time-varying laws are proposed. The main contribution is the combination of the standard control laws (both with polar coordinates and time-varying laws) that allow to achieve posture regulation for the unicycle model, with the prescribed performance control technique that imposes time-varying constraints to the system coordinates. The study also illustrates two dierent approaches to bind linear or angular coordinates, one based on a particular error transformation, and the other arising from a specific potential function. Simulations conrm the eectiveness of the proposed solutions.

This thesis investigates the resistive losses incurred in returning a power network to a synchronous state following a transient stability event, or in maintaining this state in the presence of persistent stochastic disturbances. We quantify these transient power losses, the so-called “Price of Synchrony”, using the squared H2 norm of a linear system of generator and load dynamics subject to distributed disturbances. We first consider a large network of synchronous generators and use the classical machine model to form a system with coupled second order swing equations. We then extend this model to explicitly include dynamics of loads and asynchronous generators, which represent solar and wind power plants. These elements are modeled as frequency-dependent power injections (extractions), and the resulting system is one of coupled firstand second order dynamics. In both cases, the disturbance inputs represent power fluctuations due to transient stability events or the inherent variability of loads and intermittent energy sources. The network structure is captured through a weighted graph Laplacian of the network admittance. In order to simplify the analysis for both models, we use the concept of grounded graph Laplacians to obtain an asymptotically stable reduced system. We then evaluate the transient losses in the reduced system and show that this system’s H2 norm is in fact equivalent to the H2 norm of the original system. Furthermore we show that although the transient behaviours of the first order, second order or mixed dynamical systems are in general fundamentally different, for same-sized networks they may all have the same H2 norm if the damping coefficients are uniform. The H2 norms for both system models are shown to be a function of transmission line and generator properties and to scale with the network size. These transient losses do not, however, depend on the network connectivity. This is in contrast to related power system stability notions that predict better synchronous stability properties for highly connected networks. The equivalence of the norms for different order systems indicate that renewable energy sources will not increase transient power losses if their controllers can be adjusted to match the dampings of existing synchronous generators. However, since the losses scale linearly with the number of generators, our results also demonstrate that increased amounts of distributed generation in low-voltage grids will lead to larger transient losses, and that this effect cannot be alleviated by increasing the network connectivity.

This thesis focuses on a model predictive control scheme which allows organizing the power production of power plants in a decentralized fashion. That way a less computationally demanding control scheme can be applied to control the frequency at each power plant without a governing, high level controller for the whole power grid. The main contribution was to develop a communication scheme between power plants that can be applied in a competitive environment like the energy market. Most established schemes for decentralized power production require giving away a mathematical representation of a plant to all its neighbors. However, the developed control scheme only requires informing the neighboring power plants the expected future evolution of the power networks voltage angle. This is information which is more efficiently communicated by power plant operators. Additionally, this simplification does not only yield a notable reduction in communicated data but also reduces the computational complexity of the control problem for a single power plant. The aforementioned control scheme was applied to a network consisting of several different plants for each of which a model was developed. The modeled plants range from conventionally generated plants like hydro-, gas- or wind power plants to more modern converter coupled plants like photovoltaic installations. The plants were modeled such that energy buffers - in the form of aggregated Electric Vehicle Batteries - can be taken into account. For the power plants and the energy transfer between them, linear time-invariant models were augmented with linear matrix inequalities. These represent physical bounds which the model has to regard in order to have a realistic system evolution ie, maximal power line capacities or limiting power plant production capabilities. Proofs are given which indicate necessary properties of the developed algorithm to ensure nominal or robust stability. Simulations were carried out which verified the conditions obtained from the proofs. Also by simulation, the obtained control scheme was compared with a centralized approach, amongst others. Considering the developments towards a Smart Grid one can say that a power production which is organized in a decentralized way reduces the computational effort greatly with a tolerable loss of performance. This statement is backed up with results from the simulations. The findings also indicate that the addition of buffers is very beneficial regarding disturbance rejection in the power grid.

This work presents an improved variant of the Direct Torque Control (DTC) for a Permanent Magnet Synchronous Motor (PMSM). The improved DTC use a higher number of voltage space vectors by introducing a kind of Space Vector Modulation technique. The higher number of space vectors are tabulated in more precise switch tables which also take the emf induced in the stator windings into account. The emf voltage significantly affect the motor behavior from a given space vector. It is discussed how the switch tables are constructed. Experiments from the classical and improved DTC are compared and show that the torque, flux linkage and stator current ripples are significantly decreased with the improved DTC.

Simulations of simulink models using Kalman filters are often very time-consuming. This problem depends mainly on the fact that the Kalman correction has to be performed at each sample instance through the whole simulation. The goal for this thesis work is to reduce that time-consumption for the filtering part (the integration partis treated in a complementary report) of a simulation. Furthermore a Matlab routine to perform parameter tuning and finally a graphical user interface is developed. The filtering part of the simulation in this thesis is based on an Extended Kalman Filter (EKF). The time optimization of this filter considers searching for the possibility to replace the today’s existing Matlab functions that is used to perform the filtering calculations. Examples of such functions are routines for linearization and integration. To decrease the time-consumption, we have also developed a routine to make it possible to convert a simulink model to a state-space description. This conversion makes it possible to avoid a lot of time-consuming calls to the simulink model. In this case it is the built-in functions in Matlab that causes the large time-consumption. The main time-consuming parts in the filter are the built-in routines for linearization (linmod) and the numerical method that is used to calculate the prediction error (riccatiequation). By creating new routines to solve these problems, the total time-consumption for the filtering part is reduced by approximately a factor of eighteen. As a final step the time optimized Kalman filter and the time optimized integration (treated in a complementary report) are brought together in a time efficient routine for simulation. This final routine for simulation may further be used to perform a time efficient simulation, but also to form a routine, which can be used to estimate unknown parameters in a simulink model. Using the time optimized parts of the simulation routine will make it possible to reduce the execution time for a filtering simulation by approximately a factor of ten. Three kinds of models are used to confirm that the different element of the Kalman filter and the new developed routines work properly. These models consist of one fermentation system that describes a biological process, and two different tank systems that describe the level and the torrent of water in several water tanks. / Vid filtrerande simulering av simulinkmodeller är tidsåtgången i dagsläget mycket påtaglig, mest beroende på att kalmankorrigeringen måste appliceras i varje samplingspunkt. Målet med detta examensarbete är att minska tidsåtgången som för närvarande råder för den filtrerande delen (den integrerande delen av simuleringen behandlas i en komplimenterande rapport) av en simulering. Utöver detta utvecklas även en Matlab-rutin för parametersökning samt ett enkelt grafiskt användargränssnitt som underlättar användandet av utvecklade rutiner. Den filtrerande delen av simuleringen består i detta examensarbete av ett s.k. utvidgat kalmanfilter, EKF (Extended Kalman Filter). Tidsoptimeringen av detta filter bygger på att undersöka och eventuellt ersätta de inbyggda Matlabfunktioner som i dagsläget måste användas för att genomföra en sådan filtrering. Exempel på sådana är funktioner för linjarisering och integrering. För att minska tidsåtgången utvecklas även en rutin för konvertering av simulinkmodeller till en s.k. tillståndsbeskrivning. Detta medför bl.a. att tidsödande anrop till simulinkmodellen kan undvikas. De i Matlab inbyggda funktioner som i detta fall står för den största delen av den påtagliga tidsåtgången är linmod för linjarisering samt en inbyggd numerisk metod för att beräkna prediktionsfelets varians (riccati-ekvationen). Genom att skapa nya metoder för att lösa dessa problem, har tidsåtgången för att utföra den filtrerande delen av simuleringen reducerats med en faktor 18. I ett slutskede sammanfogas sedan det tidsoptimerade kalmanfiltret med en tidsoptimerad rutin för integrering (behandlas i en komplimenterande rapport) till en komplett simuleringsrutin. Denna simuleringsrutin kan sedan användas för tidseffektiva simuleringar av simulinkmodeller, men utnyttjas även som grundstomme vid utveckling av parametersökningsrutinen. Den sammanfogade simuleringsrutinen har med hjälp av de två tidsoptimerade delarna för kalmanfiltrering och integrering medfört att tidsåtgången för att genomföra en filtrerande simulering reducerats med ungefär en faktor 10. För att testa de olika momenten och de utvecklade rutinerna används tre olika modeller. Dessa modeller består av ett fermatorsystem som beskriver en biologisk tillväxtprocess samt två olika tanksystem som beskriver flöden och nivåer i det aktuella systemets vattentankar.