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Abstract: This Dissertation focuses on the optimization of an Interior Permanent Magnet (IPM) machine for handheld battery-powered tools, aiming to enhance performance and efficiency. The research integrates multi-physics modeling, including electromagnetic Finite Element Method (FEM) and thermal models, to evaluate machine performance under various operating conditions. The performance is evaluated according to selected Key Performance Indicators (KPIs). Further, different control methods, such as Field Oriented Control and Square-Wave Control, impact the performance significantly and are incorporated into the optimization process. Due to the computational challenges of FEM-based performance evaluations in Multi-Objective Optimization (MOO), this work utilizes Artificial Neural Network (ANN)-based meta-models, to accelerate the optimization process while preserving accuracy. The developed meta-models capture nonlinear machine characteristics from the FEM model. These meta-models are then used to evaluate machine performance through a combination of analytical and numerical post-processing methods. Four MOO scenarios are presented, each aimed at optimizing the cross-sectional design of IPM machines, to enhance performance and efficiency while reducing mass and cost. Additionally, these scenarios modify the machine’s electromagnetic behavior, to ensure better alignment with the selected control method. By comparing the optimization process of Scenario 1, which uses direct FEM-based evaluation without time reduction measures, to the approach incorporating Artificial Neural Network based meta-models, the total number of individual FEM evaluations decreased from 2.35×10^9 to 2.03×10^5, without almost any loss of accuracy. This reduced the computation time from 297 years to 9.07 days on our standard desktop computer. The obtained ANN-base meta-models can be used further for other optimizations without the need for additional FEM evaluations. In all four optimization scenarios, the use of meta-models enabled the generation of a Pareto front of the optimal solutions, leading to improved KPIs compared to the reference design. The highest relative improvement occurred in Scenario 1, where the selected optimized machine design achieved a 30% increase in power density compared to the reference design.
Keywords: Interior Permanent Magnet (IPM) Machine, Artificial Neural Network (ANN), Meta-Modeling, Multi-Objective Optimization (MOO), Finite Element Method (FEM), Multi-Physics Modeling, Field Oriented Control (FOC), Square-Wave Control (SWC)
Published in DKUM: 15.05.2025; Views: 0; Downloads: 7
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Abstract: This study investigated the sensitivity of maximum torque per ampere (MTPA) control in synchronous reluctance machines (SynRMs) to angle errors, examining specifically how deviations in the reference control trajectory affected performance. Analytical and numerical methods were employed to analyze this sensitivity systematically, including the impact of magnetic saturation. Two MTPA control implementation schemes were evaluated, with torque and current amplitude as the reference variables, using a template SynRM from the open-source simulation tool SyR-e. The results indicated that performance sensitivity to angle errors was moderately low near the MTPA trajectory, allowing for significant angle deviations with minimal performance loss. Although magnetic saturation increased this sensitivity slightly, reducing the allowable error range by up to 25%, the maximum angle deviation for up to 1% of the performance decrease still corresponded to approximately ±3∘ around the MTPA trajectory. The findings of this study suggest potential for simplifying control implementations, reducing component costs through less precise position determination (sensor-based or sensorless), and achieving additional control objectives such as torque ripple reduction.
Keywords: control angle error, finite element method, MTPA control, sensitivity to performance decrease, suboptimal operation, synchronous reluctance machines
Published in DKUM: 07.02.2025; Views: 0; Downloads: 6
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Abstract: V magistrskem delu je obravnavan razvoj naprave za nanašanje ognjevzdržnega premaza na peščene kalupe, ki se uporabljajo pri proizvodnji centrifugalno litih valjev. Naprava je zasnovana za izboljšanje kakovosti in zanesljivosti proizvodnje valjev, ki so ključni element pri procesih vročega valjanja. Uporaba avtomatiziranega sistema omogoča večjo natančnost pri nanosu premaza in obenem zmanjša potrebo po ročnem delu, kar prispeva k večji varnosti zaposlenih ter manjši možnosti napak, ki so pogosto posledica človeškega faktorja. Poleg tega naprava bistveno pospeši proizvodni proces, saj premazovanje kalupov izvede hitreje kot pri ročnem načinu dela. Naprava vključuje napredne algoritme, ki zaznavajo položaj kalupa in omogočajo natančno prilagajanje gibanja naprave, da se ta samodejno uskladi s položajem kalupa v delovnem območju. Ti algoritmi prav tako omogočajo prilagoditev postopka premazovanja glede na velikost kalupa, kar zagotavlja zaželjene rezultate ne glede na dimenzije kalupa.
Keywords: ognjevzdržni premaz, industrija, centrifugalno liti valji, produktivnost, avtomatizacija
Published in DKUM: 15.01.2025; Views: 0; Downloads: 21
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Abstract: Adequate mathematical description of magnetization curves is indispensable in engineering. The accuracy of the description has a significant impact on the design of electric machines and devices. The aim of this paper was to analyze the capability of Bézier curves systematically, to describe the nonlinear static magnetic properties of non-oriented electrical steels, and to compare this approach versus the established mathematical descriptions. First, analytic functions versus measurements were analyzed. The Bézier curves were then compared systematically with the most adequate analytic functions. Next, the most suitable orders of Bézier curves were determined for the approximation of nonlinear magnetic properties, where the influence of the range of the input measurement dataset on the approximation process was analyzed. Last, the extrapolation capabilities of the Bézier curves and analytic functions were evaluated. The general conclusion is that Bézier curves have adequate flexibility and significant potential for the approximation and extrapolation of nonlinear properties of non-oriented electrical steels.
Keywords: analytical modeling, anhysteretic curve, applied mathematics, Bézier curve, curve fitting, first magnetization curve, major loop, mathematical modeling, non-oriented electrical steel
Published in DKUM: 01.02.2024; Views: 382; Downloads: 27
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Abstract: V diplomskem delu je predstavljeno vodenje asinhronskega stroja s pretvornikom Siemens SINAMICS G120. Najprej sta predstavljeni uporabljena strojna in programska oprema, s pomočjo katerih smo izvedli eksperimentalno analizo. Podrobneje je predstavljen del programskega okolja Siemens Totally Integrated Automation Portal (TIA Portal), ki uporabnikom omogoča nastavljanje pogonskega sklopa. V okviru okolja TIA Portal so predstavljeni postopki za izvedbo vodenja z metodo U/f in za izvedbo vektorskega vodenja, pri čemer je poudarek na avtomatizirani nastavitvi parametrov pretvornika. Predstavljeni rezultati eksperimentalne analize zajemajo primerjavo med odzivi pogonskega sklopa v primeru različnih načinov vodenja, ki jih pretvornik omogoča. Na koncu so podani še napotki za ročno prilagoditev parametrov regulatorja hitrosti za doseganje želene dinamike pogona v primeru vektorskega vodenja.
Keywords: Asinhronski stroj, Siemens Totally Integrated Automation Portal, SINAMICS G120, vektorsko vodenje, vodenje U/f.
Published in DKUM: 13.10.2023; Views: 382; Downloads: 82
Full text (4,86 MB)