Component-Level Optimization of Hybrid Excitation Synchronous Machines for a Specified Hybridization Ratio Using NSGA-II

Optimal Design of a Low-Cost Sae Ja2954 Compliant Wpt System Using Nsga Ii

“…The NSGA-II algorithm has been selected because it is the most widely used and cited multi-objective algorithm in the literature (Ma, Zhang, Sun, Liu, & Shan, 2023;Verma, Pant, & Snásel, 2021) with good results. Specifically, this algorithm has been used, in its basic, modified or hybridised version, to solve multiple problems in all types of electrical engineering applications, both in optimal asset location and design and even in the determination of control parameters, such as, for example: in Shahryari, Shayeghi, and Moradzadeh (2018) is used to decide the optimal placement of D-STACOMS in a distributed generation power grid, in Zhang et al (2019) for the optimal design of a hybrid solar-wind-battery power generation system to supply the power demand of DC facilities and AC cooling equipment of a mobile base station on a small remote island, Wang, Li, Ding, Cheng, and Buja (2023) proposes a parallel DC power system planning method as a demand-side management method to maximise stability gain, economic benefits and RES penetration, In Heydari et al (2023) an intelligent photovoltaic power output forecasting (PV-OP) model is developed, in Blažek, Prokop, Misak, Kedron, and Pergl (2023) the power consumption in home microgrids with V2G is optimised, in Abid, Ahshan, Al-Abri, Al-Badi, and Albadi (2023) a simultaneous optimal solution technique for distributed renewable generation and the sizing and placement of virtual synchronous generators in distribution grids is proposed, in Balasubramanian et al (2023) it is used for the optimal design of the permanent magnet inner motor of an EV, Ranjan and Mishra (2015) uses it for the optimal design of a three-phase squirrel cage asynchronous motor, in Mohammadi, Trovão, and Antunes (2020) it optimises the design of a hybrid synchronous excitation machine for electric vehicles, depending on the hybridisation ratio and minimising the material cost, in Ding, Yang, and Xiong (2021) it is used for the optimal design of a traction transformer for high-speed trains, in Abunike, Okoro, and Davidson (2021), El-Nemr, Afifi, Rezk, and Ibrahim (2021) a three-phase four-pole switched reluctance motor (SRM) is optimally designed, in Liu, Wei, Cai, and Yuan (2020) proposes an optimal design method for the 315 kVA three-phase amorphous metal distribution transformer, in Xu, Zhu, Zhang, Zhang, and Quan (2021) proposes the optimal design of a dual-stator linear rotating permanent magnet generator (DSLRPM) with Halbach PM array for marine energy harvesting, in Pan and Fang (2022) uses the algorithm to find the optimal solution to the combination of structural parameters and obtain the optimal efficiency of a permanent magnet arc motor with hybrid dualstator excitation, in Wang, Han, Chen, Song, and Yuan (2022), the volume and ...…”

Optimal-Setting for Ore and Water Feeding in Grinding Process Based on Improved Case-Based Reasoning

“…The case-based reasoning process is mainly divided into four basic steps: (1) case retrieval in which, by a series of searching and similarity calculations, the most similar case with the current problem is found in the case base; (2) case reuse, which compares the differences between the source case and the target case. Then, the solution case recognized by the user is submitted to the user, and the election of its application is observed; (3) case revision in which the solution strategy is adjusted by combining the elect of the case reuse and the current issue to fit the current problem; and (4) case storage in which the current issue is resolved and stored in the case database for future use [28]. In the CBR process, case retrieval is the core of CBR technology, which directly determines the decision-making speed and accuracy.…”

“…However the commonly used CBR assigns weights through expert experience, which is generally qualitative rather than quantitative. To address the above issues, this paper used NSGA-II which has been used in industrial production [26][27][28] for multiobjective optimization of weights based on historical cases.…”

Modern Hybrid Excited Electric Machines

“…It was also found that one of the analyzed configurations almost eliminates the PM flux. Similar construction of the machine is shown in [37]. On the other hand, in [38] the authors presented simulation studies of a machine with an excitation flux in both, radial and axial direction, while the rotor is similar to a rotor of a flux-switching machine.…”