Sequential Parts Analysis Using Local Optimization Method for Hybrid Excitation Flux Switching Generator
The Hybrid Excitation Flux Switching Generator (HEFSG) has gained significant popularity in recent times owing to its relatively simple remarkably efficient topology. To optimize the performance of the generator, recent advancements and emerging patterns in mathematical modeling and software simulat...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
OICC Press
2024-04-01
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| Series: | Majlesi Journal of Electrical Engineering |
| Subjects: | |
| Online Access: | https://oiccpress.com/mjee/article/view/5056 |
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| Summary: | The Hybrid Excitation Flux Switching Generator (HEFSG) has gained significant popularity in recent times owing to its relatively simple remarkably efficient topology. To optimize the performance of the generator, recent advancements and emerging patterns in mathematical modeling and software simulation, along with the utilization of optimization techniques, have facilitated the development of a novel methodology for electrical machine design. This study investigates the configuration and optimization of a Hybrid Excitation Flux Switching Generator, focusing on the rotor, armature coil, and field excitation. The optimization process involves multiple sequences for each component, employing the Local Optimization Method as an iterative approach to determine the optimal sequence that yields the highest output efficiency. Through the investigation of six rotor sequences, two armature coil sequences, and two field excitation coil sequences, a detailed optimization process was conducted. Consequently, the final output voltage of the HEFSG gains a 1.10% increment of voltage compared to the initial outcomes. Several sequences have influenced the output voltage performance of the generator during the optimization process. Therefore, modifications to the design of the arrangement contribute to the expansion of the operational range of the generator.
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| ISSN: | 2345-377X 2345-3796 |