An Improved Torque Density Synchronous Reluctance Machine With a Combined Star–Delta Winding Layout

2018 ◽  
Vol 33 (3) ◽  
pp. 1015-1024 ◽  
Author(s):  
Mohamed Nabil Fathy Ibrahim ◽  
Ayman S. Abdel-Khalik ◽  
Essam M. Rashad ◽  
Peter Sergeant
Keyword(s):  
Synchronous Reluctance Machine ◽  
Torque Density ◽  
Reluctance Machine

scholarly journals Optimized design of a high-power-density PM-assisted synchronous reluctance machine with ferrite magnets for electric vehicles

2017 ◽  
Vol 66 (2) ◽  
pp. 279-293 ◽  
Author(s):  
Xiping Liu ◽  
Ya Li ◽  
Zhangqi Liu ◽  
Tao Ling ◽  
Zhenhua Luo
Keyword(s):  
Power Density ◽  
High Power ◽  
High Efficiency ◽  
Torque Ripple ◽  
Optimized Design ◽  
High Power Density ◽  
Element Analysis ◽  
Synchronous Reluctance Machine ◽  
Torque Density ◽  
Reluctance Machine

AbstractThis paper proposes a permanent magnet (PM)-assisted synchronous reluctance machine (PMASynRM) using ferrite magnets with the same power density as rareearth PM synchronous motors employed in Toyota Prius 2010. A suitable rotor structure for high torque density and high power density is discussed with respect to the demagnetization of ferrite magnets, mechanical strength and torque ripple. Some electromagnetic characteristics including torque, output power, loss and efficiency are calculated by 2-D finite element analysis (FEA). The analysis results show that a high power density and high efficiency of PMASynRM are obtained by using ferrite magnets.

scholarly journals Smart Collaborative Performance-Induced Parameter Identification Algorithms for Synchronous Reluctance Machine Magnetic Model

2021 ◽  
Vol 13 (8) ◽  
pp. 4379
Author(s):  
Linjie Ren ◽  
Guobin Lin ◽  
Yuanzhe Zhao ◽  
Zhiming Liao
Keyword(s):  
Low Cost ◽  
Parameter Extraction ◽  
Synchronous Reluctance Machine ◽  
Fitness Evaluation ◽  
Reluctance Machine ◽  
Candidate Solution ◽  
Collaborative Performance ◽  
Magnetic Model ◽  
Quantitative Results ◽  
Cost Characteristics

In rail transit traction, due to the remarkable energy-saving and low-cost characteristics, synchronous reluctance motors (SynRM) may be a potential substitute for traditional AC motors. However, in the parameter extraction of SynRM nonlinear magnetic model, the accuracy and robustness of the metaheuristic algorithm is restricted by the excessive dependence on fitness evaluation. In this paper, a novel probability-driven smart collaborative performance (SCP) is defined to quantify the comprehensive contribution of candidate solution in current population. With the quantitative results of SCP as feedback in-formation, an algorithm updating mechanism with improved evolutionary quality is established. The allocation of computing resources induced by SCP achieves a good balance between exploration and exploitation. Comprehensive experiment results demonstrate better effectiveness of SCP-induced algorithms to the proposed synchronous reluctance machine magnetic model. Accuracy and robustness of the proposed algorithms are ranked first in the comparison result statistics with other well-known algorithms.

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