Iet Electric Power Applications最新文献

Linear machines (LMs) have become excellent candidates for linear motion applications due to their abilities of generating thrust without any transmissions, and have been widely adopted in transportation, industries etc. Among the numerous control methods of LM drive systems, finite control set model predictive control (FCS-MPC) method has been given special attention due to its clear concept, fast response performance, and ability to handle constrained multivariate non-linear control problems. It is widely used to improve the performance and efficiency of overall LM drive systems. Firstly, based on the three elements of FCS-MPC, the advantages and shortcomings of the FCS-MPC method in applications are fully investigated. The research status in FCS-MPC has been summarised, such as multistep MPC, parameters robustness improvement, fast optimisation, and multi-vector MPC. Then, the key issues in FCS-MPC such as delay compensation, parameters design, and stability analysis are discussed, and their typical research methods and current research status are explained. Finally, the future development trends of FCS-MPC in LM drive systems are discussed.

Recently, the development trend of large capacity generator has gradually shifted from electrical excitation generator to permanent magnet generator (PMG). As a result, the large capacity high-speed permanent magnet generator (HSPMG) with high power density and high efficiency have received widespread attention. This paper aims to analyse the loss optimization of novel large capacity HSPMG under multi-operating conditions. In terms of the parameter requirements, a 2.5 MW and 7000 rpm HSPMG is designed. To verify the accuracy of simulation model and the rationality of generator design, the output characteristics of large capacity HSPMG which has been combined with prototype experimental data are calculated under both no-load and load conditions. Based on the load power characteristics of large capacity HSPMG, the optimization range of the magnetization angle under multi-operating conditions is explored. By analysing the no-load back electromotive force (EMF) and loss characteristics of large capacity HSPMG, the optimal magnetization angle that corresponds to the minimum loss under three conditions is obtained. The correctness of the analysis and optimization method is verified by comparing the loss distribution and electromagnetic results before and after the optimization. The research results provide a reference for the multi-operating characteristics analysis and loss optimization of large capacity HSPMG.

Due to the increasing variety of converters in more electric aircraft (MEA), the stability of the MEA power system has become a critical issue that receives wide concerns. As the primary power source for MEA, the wound rotor synchronous machine (WRSM) greatly affects the stability of the whole power system, and therefore accurate modelling of the WRSM serves as the basis for the analysis of system characteristics and even stability. Nevertheless, the complex structure and coupling of WRSM bring great challenges to small-signal modelling methods. This paper introduces a novel method to model the WRSM in a modular and cascaded manner. Instead of deriving the complex transfer function, the proposed method uses a dual port to model each component. By connecting the dual port of each component from the rear stage to the front stage in a cascaded way, a dual-port network can be built to describe the external impedance characteristics of the WRSM. Kirchhoff law can be applied to calculate the impedance by circumventing the complicated decoupling process. The proposed dual-port network model has been validated on a hardware-in-loop platform. Furthermore, the output impedance characteristics of the AC port has also been analysed with the proposed model.

As aircraft electrification advances, permanent magnet synchronous motors (PMSMs) require higher power density and efficiency, but optimisation is hindered by high computational costs and resource consumption. To address this, the paper proposes a multi-objective optimisation method based on adaptive sampling radial basis function (ASRBF). The ASRBF algorithm adaptively adds sample points by estimating expected improvements at prediction points, enabling the surrogate model to rapidly approximate the global optimum while significantly reducing function evaluations. It integrates optimisation objectives and constraints using probabilistic improvement techniques, enhancing robustness and convergence speed by avoiding excessive exploration of invalid regions. Mathematical test functions validate ASRBF's excellent performance in handling complex objective domains. Applied to high-speed PMSM with hollow conductors, it aims to minimise AC losses while maximising slot fill factor and heat dissipation, resulting in a 15% reduction in losses and an increase in conductor heat dissipation area and slot fill factor, at one-thousandth of the cost of the full factorial optimisation method. The ASRBF algorithm efficiently constructs surrogate models for multi-dimensional, multi-objective, non-linear, and constrained problems, providing a powerful tool for comprehensive performance optimisation of complex systems such as motors.

Direct drive permanent magnet (PM) motors have become a very attractive choice for electric vehicles. Generally, PM motors are divided into PM synchronous motors (PMSMs) and PM flux-modulated motors (PMFMMs). High torque density is the main requirement of direct drive motors, therefore, the structure of conventional PM motors is modified to boost the torque. Increasing the number of poles is a structural modification to achieve high torque density in PMSMs; however, a large number of poles affects motor characteristics such as power factor, flux weakening, losses, and efficiency. The other way to have high torque is to use PMFMMs, which have a high intrinsic torque density. This paper first compares the performance of PMSMs with different number of poles. Then the performance of PMFMMs and PMSMs are compared to show their differences. The performance of PMFMMs with different teeth modulators and magnetic gear ratios are predicted to show their effects upon its performance. The simulation results using finite elements method|finite element method (FEM) are presented, and finally, a PMFMM with 36 slots and 40 poles as case study is subjected to an experimental test and its results are compared with FEM.

The cover image is based on the article Comparison of permanent magnet synchronous machine and permanent magnet flux-modulated machine in direct drive considering number of rotor poles by Saeed Abareshi et al., https://doi.org/10.1049/elp2.12500.

In the past decade, model predictive control (MPC) has been widely used in AC motor drives. Although a series of improved MPC strategies have been proposed, researchers are still seeking more effective solutions for different application backgrounds and application requirements to achieve the goals such as algorithm simplification, weighting factor design, parameter robustness enhancement, current/torque ripple suppression, and so on. In this paper, aiming at the above problems, the MPC strategy and its optimisation technology for AC motor drive system are comprehensively reviewed. Firstly, this paper introduces the classical MPC technology with the permanent magnet synchronous motor drive system fed by two-level voltage source inverter as the control object. Secondly, this paper introduces and discusses the existing MPC optimisation methods from the aspects of current/torque ripple suppression, algorithm simplification, weight factor design and parameter robustness enhancement. Finally, based on the current industrial development requirements for AC motor drive systems and the research status of MPC optimisation methods in the existing literature, the current challenges and future trends of MPC technology are discussed.