基于最小铜耗和最大转矩的双三相永磁电机单相缺相折衷容错控制

多相电机缺相后仍具有额外的自由度与灵活性，可以在实现无扰运行的同时提高系统性能。传统容错控制策略或是最小化电机定子铜耗或是最大化转矩输出能力，无法同时兼顾电机驱动系统的运行效率与带载能力。为此，本文通过分析容错运行时不同控制方式下的容错性能，提出基于最小铜耗和最大转矩的折衷容错控制策略。为减少缺相前后控制框架的改变，基于正常解耦矢量控制实现对缺相电机的容错控制。通过在谐波平面注入特定的基波平面电流分量，实现了电机缺相后的无扰运行。为实现所提容错控制策略，额外引入权重系数权衡电机驱动系统产生的定子铜耗与转矩输出能力。通过分析权重系数对容错性能的影响，得出结论：相比最小铜耗控制方式，所提容错控制策略带载能力更强；相比最大转矩制方式，所提容错控制策略运行效率更高，即所提容错控制策略在提高带载能力的同时实现效率最优。最后，双三相永磁同步电机的实验验证了所提容错控制策略的准确性及有效性。     

飞机主动侧杆系统用双三相永磁同步电机的设计与转矩性能分析

针对主动侧杆系统的运行需求，本文设计了一款双三相永磁同步电机，介绍了该种电机的基本结构和优点，分析了极槽配合和裂比两大关键参数的设计方法，研究了在空间限制下电机尺寸设计策略，分析了关键参数对电机性能的影响，对比了参数变化时电机转矩、转矩脉动的变化趋势，研究了电机的优化方向和参数，确定了电机的结构尺寸、绕组分布等参数。通过仿真验证了理论设计的正确性。所设计的电机输出转矩符合设计需求，转距脉动较小，不会为操纵杆手柄带来震荡的问题。电机单余度工作情况下，仍然可以达到额定转距的输出需求，保证了系统的安全性。     

Surrogate role of machine learning in motor-drive optimization for more-electric aircraft applications

Motor drives form an essential part of the electric compressors, pumps, braking and actuation systems in the More-Electric Aircraft (MEA). In this paper, the application of Machine Learning (ML) in motor-drive design and optimization process is investigated. The general idea of using ML is to train surrogate models for the optimization. This training process is based on sample data collected from detailed simulation or experiment of motor drives. However, the Surrogate Role (SR) of ML may vary for different applications. This paper first introduces the principles of ML and then proposes two SRs (direct mapping approach and correction approach) of the ML in a motor-drive optimization process. Two different cases are given for the method comparison and validation of ML SRs. The first case is using the sample data from experiments to train the ML surrogate models. For the second case, the joint-simulation data is utilized for a multi-objective motor-drive optimization problem. It is found that both surrogate roles of ML can provide a good mapping model for the cases and in the second case, three feasible design schemes of ML are proposed and validated for the two SRs. Regarding the time consumption in optimizaiton, the proposed ML models can give one motor-drive design point up to 0.044 s while it takes more than 1.5 mins for the used simulation-based models.     

Design and analysis of a novel hybrid cooling method of high-speed high-power permanent magnet assisted synchronous reluctance starter/generator in aviation applications

To improve the heat dissipation performance, this paper proposes a novel hybrid cooling method for high-speed high-power Permanent Magnet assisted Synchronous Reluctance Starter/Generator (PMaSynR S/G) in aerospace applications. The hybrid cooling structure with oil circulation in the housing, oil spray at winding ends and rotor end surface is firstly proposed for the PMaSynR S/G. Then the accurate loss calculation of the PMaSynR S/G is proposed, which includes air gap friction loss under oil spray cooling, copper loss, stator and rotor core loss, permanent magnet eddy current loss and bearing loss. The parameter sensitivity analysis of the hybrid cooling structure is proposed, while the equivalent thermal network model of the PMaSynR S/G is established considering the uneven spraying at the winding ends. Finally, the effectiveness of the proposed hybrid cooling method is demonstrated on a 40 kW/24000 r/min PMaSynR S/G experimental platform.