Search results for "VDP::Teknologi: 500::Elektrotekniske fag: 540"
showing 10 items of 80 documents
Modeling Stator Winding Inter-Turn Short Circuit Faults in PMSMs including Cross Effects
2020
Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This paper presents a detailed analysis of stator winding inter-turn Short Circuit (ITSC) faults, taking the cross effects in the three phases of a permanent magnet synchronous motor (PMSM) into account by considering insulation degradation resistances. A PMSM with series coils in eac…
Performance evaluation and stability of silicide-based thermoelectric modules
2020
Abstract Long-term studies on thermoelectric generators based on N-type magnesium silicide (Mg2.01Si0.49Sn0.5Sb0.01) and P-type higher manganese silicide (Mn0.98Mo0.02Si1.73Ge0.02) materials are presented, in the operating temperature range of 200 °C–400 °C. Emphasis is put on the performance and reliability of the current collector configuration, especially on the hot side of the module, and on the thermomechanical stresses that are created during operation and lifetime testing as a result of large temperature gradients experienced across the thermoelectric legs. With silver (Ag) paste as contact material, the long term-stability of the uni-couples was carried out on non-metalized legs and…
A Deep Learning-Based Framework for Feature Extraction and Classification of Intrusion Detection in Networks
2022
An intrusion detection system, often known as an IDS, is extremely important for preventing attacks on a network, violating network policies, and gaining unauthorized access to a network. The effectiveness of IDS is highly dependent on data preprocessing techniques and classification models used to enhance accuracy and reduce model training and testing time. For the purpose of anomaly identification, researchers have developed several machine learning and deep learning-based algorithms; nonetheless, accurate anomaly detection with low test and train times remains a challenge. Using a hybrid feature selection approach and a deep neural network- (DNN-) based classifier, the authors of this re…
An Efficient Online/Offline Signcryption Scheme for Internet of Things in Smart Home
2022
The delivery of unified intelligent services is accomplished through a networked environment comprised of a wide array of electronic devices. Through the use of Internet of Things (IoT) technology, smart homes collect data from their surroundings and use it to improve their tenants’ lives. Remote control, real-time monitoring, and a fire alarm are all characteristics of smart home security. Since smart homes hold personally identifying information about their residents, security is critical to ensure their reliability and prevent data breaches. In this paper, a certificateless online/offline signcryption (COOS) technique for IoT-enabled smart homes is proposed. The proposed solution takes a…
Control strategy based on wavelet transform and neural network for hybrid power system
2013
Published version of an article in the journal: Journal of Applied Mathematics. Also available from the publisher at: http://dx.doi.org/10.1155/2013/375840 Open Access This paper deals with an energy management of a hybrid power generation system. The proposed control strategy for the energy management is based on the combination of wavelet transform and neural network arithmetic. The hybrid system in this paper consists of an emulated wind turbine generator, PV panels, DC and AC loads, lithium ion battery, and super capacitor, which are all connected on a DC bus with unified DC voltage. The control strategy is responsible for compensating the difference between the generated power from the…
A Survey on Particle Swarm Optimization for Association Rule Mining
2022
Association rule mining (ARM) is one of the core techniques of data mining to discover potentially valuable association relationships from mixed datasets. In the current research, various heuristic algorithms have been introduced into ARM to address the high computation time of traditional ARM. Although a more detailed review of the heuristic algorithms based on ARM is available, this paper differs from the existing reviews in that we expected it to provide a more comprehensive and multi-faceted survey of emerging research, which could provide a reference for researchers in the field to help them understand the state-of-the-art PSO-based ARM algorithms. In this paper, we review the existing…
Computational Offloading in Mobile Edge with Comprehensive and Energy Efficient Cost Function: A Deep Learning Approach
2021
In mobile edge computing (MEC), partial computational offloading can be intelligently investigated to reduce the energy consumption and service delay of user equipment (UE) by dividing a single task into different components. Some of the components execute locally on the UE while the remaining are offloaded to a mobile edge server (MES). In this paper, we investigate the partial offloading technique in MEC using a supervised deep learning approach. The proposed technique, comprehensive and energy efficient deep learning-based offloading technique (CEDOT), intelligently selects the partial offloading policy and also the size of each component of a task to reduce the service delay and energy …
Performance of a thermoelectric module based on n-type (La0.12Sr0.88)0.95TiO3-δ and p-type Ca3Co4-xO9+δ
2020
Here, we present the performance of a thermoelectric (TE) module consisting of n-type (La0.12Sr0.88)0.95TiO3 and p-type Ca3Co4-xO9+δ materials. The main challenge in this investigation was operation of TE module in different atmosphere conditions, since n-type has its optimum TE-performance at reducing, while p-type at oxidizing conditions. The TE module was exposed to two different atmospheres and demonstrated higher stability in N2 atmosphere than in air. The maximum electrical power output decreased after 40 h when the hot side was exposed to N2 at 600 °C, while only 1 h at 400 °C in ambient air was enough to oxidize (La0.12Sr0.88)0.95TiO3 followed by a reduced electrical power output. T…
Smart Electric Vehicle Charging System : Controlling Multiple Electrical Vehicle Chargers using OCPP to Limit Electricity Demand
2017
Master's thesis Renewable Energy ENE500 - University of Agder 2017 Peak demand is a problem when Electrical Vehicle charging is introduced in the electricity grid. Local limitations like fuses and transformer capacity can rapidly be overloaded if multiple Electrical Vehicles are charging at the same time. This can be solved by shifting these loads in time. This master’s Thesis presents a solution by using the communication protocol OCPP to restrict one or more chargers below a set demand limit. The solution is developed in cooperation with Sharebox [1] and Grønn Kontakt [2], and is in prototype phase at the end of this Master’s Thesis. Testing demonstrates that the prototype can reduce the …
Optimization of Charging Stations on a Route with Electric Buses
2019
Master's thesis Renewable Energy ENE500 - University of Agder 2019 This studyconsiders placement of electric charging stations for a public electric bus system with the intention of minimizing the charging power. This is an optimization problem where fully electric buses with opportunity charging strategy are considered.The developed strategies are proposed for an existing bus route in Oslo city, Norway. Batteryand chargingspecifications were determinedbased on a literature review. Measurements regarding velocity of the bus and altitude of the route were performed. This data where further used to determine the energy needsfor an electric bus. Four cases were formedregarding different batter…