Framework for Analytical-based Digital Twin Development of Electric Drives Using Slotless PM Machines
Doctoral thesis
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Date
2023Metadata
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- Institutt for elkraftteknikk [2482]
Abstract
This Ph.D. thesis investigates and develops analytical models and techniques to build the foundation for the digital twin development of electric drives using slotless permanent magnet (PM) machines. The idea is to rely on analytical models’ intrinsic computational efficiency to meet the digital twins’ fundamental requirement.
Despite the required multi-disciplinarity hidden behind the development of the digital replica of an electrical drive, this research is limited to developing a generalized electromagnetic model of inverter-driven slotless machines. To implement a generally applicable model using accurate state-of-the-art (SotA) modeling techniques, several challenges were highlighted during implementation. Therefore, the focuswas on ensuring the uttermost reproducibility of the proposed modeling techniques. Nevertheless, the presented models can offer a sound tool in the design phase of inverter-driven slotless machines, thus highlighting a promising potential for digital twin development.
The analytical electromagnetic models of slotless PM machines are based on solutions to Maxwell’s equation through Fourier series decomposition. These models give a noteworthy balance between accuracy and computational time, making them a desirable solution for design and analysis purposes and digital twin implementation.
The different formulations allow for magneto-static and magneto-quasi-static modeling. The resulting field formulations have been heavily exploited throughout the research, giving a solid foundation for design purposes. The magnetostatic field formulation, in particular, is employed to estimate torque, inductance, and induced voltage.
The same formulation is also employed for iron loss estimate in the stator core by using four different laminations’ loss models with the support of experimental measurements; moreover, an improved optimization algorithm includes the possibility of accounting for magnet demagnetization. On the other hand, the magneto-quasi-static formulations were investigated to calculate the induced eddy currents in the magnets.
Every field formulation has been thoroughly validated through FEA to ensure the best accuracy achievable by the analytical models. The same validation step highlighted some significant flaws in the mathematical expressions if directly implemented as executable code causing accuracy reduction due to numerical inaccuracies. These numerical challenges are fully addressed in this work, and the field formulations show to deliver results with the same accuracy as FEA. In support of future development around these modeling techniques, all the implemented programs and algorithms are made available as complementary accessories to the presented work.
Has parts
Paper 1. Leandro, Matteo; Nøland, Jonas Kristiansen. An Approach for Optimal Pre-Conditioning of the Analytical Field Solution of Slotless PM Machines. IEEE Access 2021 ;Volum 9. s. 36748-3676 https://doi.org/10.1109/ACCESS.2021.3062769 This work is licensed under a Creative Commons Attribution 4.0 License. CC BYPaper 2: Leandro, Matteo; Elloumi, Nada; Tessarolo, Alberto; Nøland, Jonas Kristiansen. Analytical Iron Loss Evaluation in the Stator Yoke of Slotless Surface-Mounted PM Machines. IEEE transactions on industry applications 2022 ;Volum PP.(99) https://doi.org/10.1109/TIA.2022.3171528
Paper 3: Leandro, Matteo; Nøland, Jonas Kristiansen. Analytical PM Eddy Currents Loss Evaluations in Inverter-Fed Slotless Machines Induced by SVM Control Using Polar Coordinates Formulations. IEEE transactions on energy conversion 2023 ;Volum PP.(99) https://doi.org/10.1109/TEC.2023.3294807
Paper 4: Leandro, Matteo; Bianchi, Nicola; Molinas Cabrera, Maria Marta; Ummaneni, Ravindra Babu. Low Inductance Effects on Electric Drives using Slotless Permanent Magnet Motors: A Framework for Performance Analysis. I: 2019 IEEE International Electric Machines & Drives Conference (IEMDC). s. 1099-1105 https://doi.org/10.1109/IEMDC.2019.8785241
Paper 5: Elloumi, Nada; Leandro, Matteo; Nøland, Jonas Kristiansen; Tessarolo, Alberto. Stator Core Flux Density Analytical Determination in Slotless Machines. I: Proceedings 2020 International Conference on Electrical Machines (ICEM). s. 345-351 https://doi.org/10.1109/ICEM49940.2020.9270749
Paper 6: Leandro, Matteo; Nada, Elloumi; Tessarolo, Alberto; Nøland, Jonas Kristiansen. Analytical-Based Iron Loss Assessment in the SPM Slotless Machine Stator Core. I: Proceedings 2020 International Conference on Electrical Machines (ICEM). s. 772-778 https://doi.org/10.1109/ICEM49940.2020.9270766.
Paper 7: Leandro, Matteo; Nøland, Jonas Kristiansen. A Penalty-Based PSO Algorithm for Demagnetization Risk-Free Design of Slotless Halbach PM Machines. I: 25th International Conference on Electrical Machines (ICEM). IEEE conference proceedings 2022 s. 276-281 https://doi.org/10.1109/ICEM51905.2022.9910651