TY - GEN
T1 - An Efficient Method to Evaluate the Influence of Additional Air Gaps on the Cogging Torque for the PM Machines with Modular Stator
AU - Zhao, Yue
AU - Yang, Yongxi
AU - Zhang, Chengning
AU - Zhang, Shuo
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Due to the uncertainties in the manufacturing process, additional air gaps (AAGs) between different stator segments in the modular stator motors are inevitable, which might deteriorate the cogging torque performance. To evaluate the influences of the uncertainties, a mass of finite element analysis (FEA) on designs featuring different uncertain combinations is always required. The correspondingly high computational cost is the biggest obstacle to uncertainties analysis and robust design. To solve this problem, an approach based on the worst-uncertain-combination-analysis (WUCA) method is proposed to theoretically find the possible worst-case under uncertainties. With the help of the WUCA approach, the influence of AAG uncertainties on the cogging torque could be estimated by only at most two specific combinations, while hundreds of uncertain comparisons are usually required if the conventional approach is adopted. The efficacy of the proposed method is verified by FEA results for different pole/slot configurations, indicating its high potential to reduce the high computational burden for robust optimization.
AB - Due to the uncertainties in the manufacturing process, additional air gaps (AAGs) between different stator segments in the modular stator motors are inevitable, which might deteriorate the cogging torque performance. To evaluate the influences of the uncertainties, a mass of finite element analysis (FEA) on designs featuring different uncertain combinations is always required. The correspondingly high computational cost is the biggest obstacle to uncertainties analysis and robust design. To solve this problem, an approach based on the worst-uncertain-combination-analysis (WUCA) method is proposed to theoretically find the possible worst-case under uncertainties. With the help of the WUCA approach, the influence of AAG uncertainties on the cogging torque could be estimated by only at most two specific combinations, while hundreds of uncertain comparisons are usually required if the conventional approach is adopted. The efficacy of the proposed method is verified by FEA results for different pole/slot configurations, indicating its high potential to reduce the high computational burden for robust optimization.
KW - additional airgaps
KW - cogging torque
KW - uncertainties
KW - worst-case uncertain combination analysis (WUCA)
UR - http://www.scopus.com/inward/record.url?scp=85182942681&partnerID=8YFLogxK
U2 - 10.1109/ECCE53617.2023.10362134
DO - 10.1109/ECCE53617.2023.10362134
M3 - Conference contribution
AN - SCOPUS:85182942681
T3 - 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023
SP - 4552
EP - 4557
BT - 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023
Y2 - 29 October 2023 through 2 November 2023
ER -