Loss minimization DTC electric motor drive system based on adaptive ANN strategy

Yonis M Yonis, Buswig and Sim, Sy Yi and Wahyu, Mulyo Utomo and Goh, Hui Hwang and Chien, Siong Kai and Alvin, John Lim Meng Siang and Nor Aira, Zambri and Kah, Haw Law and Sim, Gia Yi (2020) Loss minimization DTC electric motor drive system based on adaptive ANN strategy. International Journal of Power Electronics and Drive System(IJPEDS), 11 (2). pp. 618-624. ISSN 2088-8694

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Electric motor drive systems (EMDS) have been recognized as one of the most promising motor systems recently due to their low energy consumption and reduced emissions. With only some exceptions, EMDS are the main source for the provision of mechanical energy in industry and accounts for about 60% of global industrial electricity consumption. Large energy efficiency potentials have been identified in EMDS with very short payback time and high-cost effectiveness. Typical, during operation at rated mode, the motor drive able to hold its good efficiencies. However, a motor usually operates out from rated mode in many applications, especially while under light load, it reduced the motor’s efficiency severely. Hence, it is necessary that a conventional drive system to embed with loss minimization strategy to optimize the drive system efficiency over all operation range. Conventionally, the flux value is keeping constantly over the range of operation, where it should be highlighted that for any operating point, the losses could be minimize with the proper adjustment of the flux level to a suitable value at that point. Hence, with the intention to generate an adaptive flux level corresponding to any operating point, especially at light load condition, an online learning Artificial Neural Network (ANN) controller was proposed in this study, to minimize the system losses. The entire proposed strategic drive system would be verified under the MATLAB/Simulink software environment. It is expected that with the proposed online learning Artificial Neural Network controller efficiency optimization algorithm can achieve better energy saving compared with traditional blended strategies

Item Type: Article
Additional Information: Information, Communication and Creative Technology
Uncontrolled Keywords: Adaptive flux control, Efficiency optimization, Loss minimization, Motor drive system, Online ann, UNIMAS, university, Borneo, Malaysia, Sarawak, Kuching, Samarahan, IPTA, education, Universiti Malaysia Sarawak
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Academic Faculties, Institutes and Centres > Faculty of Engineering
Faculties, Institutes, Centres > Faculty of Engineering
Depositing User: Yonis Buswig
Date Deposited: 21 Aug 2020 00:22
Last Modified: 06 Oct 2022 02:43
URI: http://ir.unimas.my/id/eprint/31305

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