TY - JOUR
T1 - Optimized design of a fault-tolerant 12-slot/10-pole six-phase surface permanent magnet motor with asymmetrical winding configuration for electric vehicles
AU - Mohamed, Mahmoud Y.
AU - Fawzi, Mahmoud
AU - Kalas, Ahmed
AU - Abdel-Khalik, Ayman S.
AU - Ahmed, Shehab
AU - Refaat, Ahmed
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2025/1
Y1 - 2025/1
N2 - This paper presents a comprehensive methodology for optimizing the design of a 12-slot/10-pole permanent magnet (PM) motor with a six-phase winding configuration tailored for electric vehicles (EVs). The design aims to enhance motor performance under both healthy and fault conditions. While the single neutral configuration offers superior torque during faults, it also introduces zero sequence currents and additional space harmonics, which can lead to increased torque ripple that is difficult to control. This study addresses these challenges through innovative machine design optimization. The optimization process begins with sizing equations to establish an initial design. K-means clustering techniques are then employed to identify distinct loading points that accurately represent the full EV driving cycle, effectively minimizing computational power requirements. Following this, the Full Range Minimum Loss (FRML) strategy is applied to determine optimal current profiles across these loading points, significantly reducing copper losses. Finally, a multi-objective optimization approach is utilized to minimize torque ripple, enhance average torque, and optimize machine losses. The results demonstrate substantial improvements in torque and reduced ripple, validated through experiments conducted with a 2 kW lab-scale motor. This integrated approach not only ensures a robust and efficient motor design but also enhances fault tolerance, making it well-suited for advanced EV applications.
AB - This paper presents a comprehensive methodology for optimizing the design of a 12-slot/10-pole permanent magnet (PM) motor with a six-phase winding configuration tailored for electric vehicles (EVs). The design aims to enhance motor performance under both healthy and fault conditions. While the single neutral configuration offers superior torque during faults, it also introduces zero sequence currents and additional space harmonics, which can lead to increased torque ripple that is difficult to control. This study addresses these challenges through innovative machine design optimization. The optimization process begins with sizing equations to establish an initial design. K-means clustering techniques are then employed to identify distinct loading points that accurately represent the full EV driving cycle, effectively minimizing computational power requirements. Following this, the Full Range Minimum Loss (FRML) strategy is applied to determine optimal current profiles across these loading points, significantly reducing copper losses. Finally, a multi-objective optimization approach is utilized to minimize torque ripple, enhance average torque, and optimize machine losses. The results demonstrate substantial improvements in torque and reduced ripple, validated through experiments conducted with a 2 kW lab-scale motor. This integrated approach not only ensures a robust and efficient motor design but also enhances fault tolerance, making it well-suited for advanced EV applications.
KW - Clustering
KW - Electric vehicles (EVs)
KW - Finite element analysis (FEA)
KW - Full range minimum loss
KW - Machine design
KW - Multiphase machines
KW - Optimization
KW - Surface mount synchronous machine
UR - http://www.scopus.com/inward/record.url?scp=85206285347&partnerID=8YFLogxK
U2 - 10.1016/j.aej.2024.10.025
DO - 10.1016/j.aej.2024.10.025
M3 - Article
AN - SCOPUS:85206285347
SN - 1110-0168
VL - 110
SP - 527
EP - 539
JO - Alexandria Engineering Journal
JF - Alexandria Engineering Journal
ER -