Zhao Xin, Dongqin Xiong, Teng Yun, et al. Optimal design of linear switched reluctance motor for sea wave power generation[J]. Global Energy Interconnection, 2022, 5(4): 434-447.
DOI:
Zhao Xin, Dongqin Xiong, Teng Yun, et al. Optimal design of linear switched reluctance motor for sea wave power generation[J]. Global Energy Interconnection, 2022, 5(4): 434-447. DOI: 10.1016/j.gloei.2022.08.009.
Optimal design of linear switched reluctance motor for sea wave power generation
The switchless reluctance motor’s non-permanent magnet structure design ensures its high reliability in the marine environment; thus
it is a feasible solution for the generator of a sea wave power generation system. However
the corresponding thrust density and efficiency remain insufficient. This study focused on a new type of flat linear switched reluctance motor (LSRM)
using the finite element software to establish a structural model
and optimized the design with the goal of improving the efficiency and energy density. The entropy method was adopted for sensitivity stratification to objectively select weights to avoid the influence of subjectively selected different proportional weights on the optimization results. Based on the entropy method
the sensitivity of different structural parameters was stratified
and the simulated annealing algorithm
response surface method
and single parameter scanning method were combined for optimization. Finally
the optimal structural size parameters of the motor were determined. Based on the two-dimensional finite element method
to simulate the electromagnetic performance of the reluctance motor under different operating conditions
such as thrust
loss
and efficiency
changes in motor performance before and after optimization were compared to verify the high power generation efficiency and energy density of the optimized linear motor.
Optimized design and energy management of a hybrid electric traction substation integrating photovoltaic generation and storage systems: case study of the Moroccan railway network
Advancing electric vehicle ecosystems: a survey of generative artificial intelligence and distributed machine learning applications
Empowering the grid: A comprehensive review of vehicle-to-grid technology, digital twins, and intelligent energy systems
A context-driven dynamic modeling method for ultra-short-term wind power forecasting
Optimal scheduling of renewable energy system based on probabilistic power balance under dynamic frequency security