In this paper, power electronic transformer (PET)-based railway traction systems are comprehensively reviewed according to the unique application features and requirements. By comparing PET and conventional line frequency transformer (LFT)-based systems, their pros and cons are summarized. By further reviewing all kinds of PET-based designs from the early concepts to the latest ones in the order of their publication dates, the developing trends are highlighted. By synthetically considering the requirements and the state of the art, the key challenges and opportunities are identified and discussed. It shows that although PET-based systems are still developing and far from mature, they are already superior to LFT-based systems in terms of system weight, efficiency, and functionalities especially for 15-kV/16.7-Hz applications. With the advancements on wide bandgap power devices, medium frequency transformers, and converters, PET systems will be even more promising and available for all types of railway tractions in the near future.

Online parameter estimation of permanent magnet synchronous machines is critical for improving their control performance and operational reliability. This paper provides an overview of the recent achievements of online parameter estimation of PMSMs with examples. The critical issues in parameter estimation are firstly analysed, especially the rank-deficient issue and inverter nonlinearities. Then, the state-of-the-art online parameter estimation modelling techniques are reviewed and assessed. Finally, some typical applications and examples are outlined, e.g. estimation of mechanical parameters, improvement of sensored and sensorless control performance, thermal condition monitoring, and fault diagnosis, together with future research trends.

This paper proposes a novel scheme for the identification of the whole flux linkage map of permanent magnet synchronous machines (PMSMs), by which the map of dq-axis flux linkages at different load or saturation conditions can be identified by the minimization of a proposed estimation model. The proposed method works on a conventional three-phase inverter based vector control system and the immune clonal based quantum genetic algorithm (ICQGA) is employed for the global searching of minimal point. Besides, it is also noteworthy that the influence of uncertain inverter nonlinearity and circuit resistance are cancelled during the modeling process. The proposed method is subsequently tested on two PMSMs and shows quite good performance compared with the finite element prediction results.

This paper proposes a novel hybrid-magnetic-circuit variable flux memory machine (HMC-VFMM) by combining series and parallel hybrid magnet structures. Thus, the synergies of wide flux regulation range in parallel type and excellent on-load demagnetization withstand capability in series type can be simultaneously obtained with the proposed HMC design. Meanwhile, two sets of the permanent magnets (PMs) with high coercive force (HCF) and low coercive force (LCF), i.e. NdFeB and AlNiCo PMs, are employed to achieve high torque density and energy-efficient magnetization state (MS) adjustment. The topologies and tradeoffs of traditional parallel and series VFMMs are addressed first. In addition, the structure evolution, features and operating principle of the proposed HMC-VFMM are described, respectively. A simplified equivalent magnetic circuit is modelled to reveal the performance improvement of the machine. Then, the design improvements with q-axis barriers are presented to elevate the LCF PM working point for preventing the on-load demagnetizing effect, while maintaining the torque capability. The electromagnetic characteristics of the HMC design are investigated and compared with the parallel/series counterparts. Finally, the experiments have been carried out to validate the finite element (FE) analyses.