Examensarbeten för masterexamen


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  • Post
    Implementation of a latency controller in an 8-DOF driving simulator: A Latency controller based on the Otto-Smith predictor, with a model developed using System Identification
    (2023) Hägglund, Alexander; Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper; Chalmers University of Technology / Department of Mechanics and Maritime Sciences; Bruzelius, Fredrik; Saparia, Smit; Kharazzi, Sogol
    In all driving simulators delays will be present. These delays are in all parts of the system. Delays in the driving simulator have according to previous studies both effects on the driving performance and the risk of experience simulator sickness. This thesis focused on the acceleration in the Motion System, and no other delays were investigated. The aim was to investigate the accelerations in Sim IV with an IMU and use the IMU-data to develop a dynamic model of the longitudinal dynamics of the XY-table. This model should then be used to better control the acceleration against the Motion Cueing reference. The controller is partially an Otto-Smith predictor. The result of this thesis is a lowered acceleration latency with both synthetic and driving data as input. More tests with actual driving need to be done for evaluating if the controller has an impact on the driver’s experience. This controller was implemented for longitudinal dynamics with the XY-table, in the future it could be implemented for the other seven degrees of freedom.
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    Modelling and control of active power steering systems for heavy trucks
    (2023) Ashok Kumar, Sharath Chandra; Erikmats, Emil; Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper; Chalmers University of Technology / Department of Mechanics and Maritime Sciences; Jacobson, Bengt; Kulcsár, Balázs Adam; Marzbanrad, Alireza
    Transportation via trucks constitutes an important part of the logistics chain. Today’s trucks can take a front axle load of approximately 8 tonnes. To be able to maneuver at high front axle loads, the driver needs assistance from additional power sources. The additional power can be provided through different sources in different steering topologies: Hydraulic Power Steering (HPS), Electric Power Steering (EPS) or Electro-Hydraulic Power Steering (EHPS), where HPS and EHPS are more common today. Some benefits of EPS over the other two are reduced energy consumption, improved autonomous drivability, and the absence of hydraulic oils which can contaminate soil, groundwater and seawater. However, hydraulics are faster than electromechanical systems. This thesis aims to see if acceptable steering performance can be achieved with EPS and compare it to EHPS by modelling, designing controllers and simulating the complete vehicle-driver-ground systems. The version of EHPS chosen was a Volvo Dynamic Steering-like (VDS-like) topology. The mechanical systems were mainly modeled using tools in Dymola but also in MATLAB, Simulink, and TruckMaker for Simulink (TM4SL) environment. The Dymola model of the VDS-like model was validated by comparing it to Volvo’s steering black box model at Chalmers. The control was developed in MATLAB and Simulink, where PID controller was selected for the motor and the outer control scheme being H2 for energy optimization. The mechanical system, the motor model, and the controllers were then connected in TM4SL. Evaluation on TruckMaker was conducted by simulating two scenarios namely, path following in a figure of eight and in a wheel lock scenario. The models of the two steering systems developed were found to be acceptable while the designed boost for the EPS system also performed supportively. The controller however did not produce the anticipated behaviour.
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    Optical Load Detection: Load Weighing for Construction Machines using Stereo Vision and Convolutional Neural Networks
    (2022) Stråhle, Daniel; Wingård Olsson, Kevin; Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper; Chalmers University of Technology / Department of Mechanics and Maritime Sciences; Forsberg, Peter; Andreasson, Mathias
    Accurate excavation monitoring is important for the handling of materials within the construction industry. Modern construction machines provide built-in systems for weighing handled goods. In this thesis, an alternative optical weighing system is developed and implemented for an excavator and a wheel loader. The optical system detects and provides the volume and weight of the handled material through fill-factor estimation. The methodology is based on depth data and images captured by a stereo camera, mounted on the machines. By using a region-based convolutional neural network (CNN), localization of material and fill-factor estimation are managed jointly. Material classification is also proved to be possible using gathered images and a simple CNN. By combining the fill-factor and information about the material, weight is obtained. Evaluations reveal that the system measures fill-factor to mean absolute percentage errors (MAPE), relative to the maximum capacity of the excavator and the wheel loader, of 3.3 % and 3.0 % respectively.
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    Gas Turbine’s share in the future electricity system, under the effect of EU ETS policies. A Modeling of the future energy transition, considering CO2 reduction policies by European ETS
    (2023) Rahmanpour, Mohammad; Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper; Chalmers University of Technology / Department of Mechanics and Maritime Sciences; Grahn, Maria; Farabi, Hadi
    Power generation plays a significant role in global warming, as it is a primary source responsible for emitting a substantial amount of harmful greenhouse gas (GHG) pollutants into the atmosphere, and this topic presents a critical and concerning problem on a global scale [1]. As part of implemented actions against global warming, the European Emission Trading System (EU ETS) is a functioning mechanism managing European emission reduction policies [2]. On the other hand, using gas turbines (GT) in power generation, specifically with natural gas, has been a well established method for converting fuel to electricity. The primary objective of this study is to identify the future share of gas turbine application in the electricity production market(considering the SGT-800 gas turbine, a mid-range Siemens Energy product) under the effect of EU ETS possible scenarios. In addition, possible sustainable solutions for gas turbine applications, specifically hydrogen (H2) as a carbon-free fuel and carbon capture system (CCS), are under consideration. By modeling various potential scenarios and analyzing the outcomes and trends, the study will shed light on how gas turbine market share and competitiveness might be affected in the future. Emission CAP, carbon cost, and Net Zero target year represent EU ETS policies. In addition to EU ETS measures, some techno-economical items have been considered, consisting of power generation modes for gas turbines (simple and combined cycles), which determines the efficiency of electrical generation plants, investment and operation costs, available carbon storage capacities, and different shares of renewable energy systems (RES) in electricity production. The cost of fuels and phasing out old technologies (nuclear and fossil fuels including coal and oil) [3] will be considered technical parameters and, simultaneously, could be complementary policies in different scenarios. The global energy transition (GET) model generates the solutions with the lowest cost for future electricity mix under various technology assumptions and CO2 emission constraints. Results revealed a significant role of emission CAP, in parallel with a proper carbon cost. At the same time, CO2 storage capacity and penetration of RES in the electricity market also have considerable effectson gas turbine application. Based on different scenario outcomes, hydrogen(H2) as a carbon-freefuel for GT and CO2-capturing technology in power plants are effective solutions for integrating gas turbine-based power plants in a more sustainable future energy system.
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    Design parameter optimization of Electric Drive Units. A regression based optimization of PMSM geometrical design parameters and final drive ratio
    (2023) Panyam, Adithya Ram; Panguluru, Chanakya; Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper; Chalmers University of Technology / Department of Mechanics and Maritime Sciences; Sedarsky, David; Velmurugan, Dhinesh
    Permanent magnet synchronous machines (PMSM) are widely used for propulsion system in electric vehicles due to their high efficiency, high torque density, excellent dynamic response and control, and reliability. Significant investments are being made to fund research on improving their efficiency, torque capabilities to enhance overall vehicle performance and driving range. To appropriately determine the size and specifications of the motor for a specific powertrain requirement, numerous geometric, electric, and mechanical parameters need to be considered. In this study, we present a method to optimize certain selected design parameters of the PMSM to improve the performance of the powertrain. The focus of this study is on the geometrical design parameters of the PMSM, while also considering the final drive ratio, to imrprove the performance of the overall powertrain. By employing orthogonal design of experiments, simulations are conducted with predefined levels of these parameters to generate a dataset used for training regression models. Two types of regression models, linear and Gaussian process, are considered and compared. The study reveals that Gaussian process regression provides more accurate predictions for the selected output variables. Subsequently, the Gaussian process regression model is used for optimizing the design parameters. The optimization process incorporates cost functions defined for particular application, such as efficiency optimization for Passenger variant and performance optimization for Performance variant.