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.

The lumped-parameter thermal network (LPTN) has been widely used in the thermal analysis for electrical machines. Nevertheless, since the thermal resistances are defined based on the 1-dimensional heat transfer equation, it will cause misestimation of the average temperatures when the thermal model extends to 2-dimensions or 3-dimensions. In this paper, a hybrid thermal model utilizing the synergies of LPTN and 2-D analytical thermal models is developed to address this issue and to predict accurate critical temperatures, especially average and maximum temperatures of the active- and end-windings. The 2-D analytical thermal models are obtained by solving the Poisson's equations with the Dirichlet boundary conditions extracted from the LPTN. The derived analytical solutions are expressed as Fourier series, which can be further simplified by utilizing the first term only to represent average and maximum temperatures with sufficient accuracy and short computation time. The hybrid thermal model is applied to a totally enclosed forced convection permanent magnet synchronous machine and validated by numerical techniques and experiments.

Permanent magnet (PM) machines have been extensively used for various applications. Nevertheless, thermal effect, particularly hotspot temperature, not only severely restricts power/torque density but also leads to deteriorations in electromagnetic performance, service life, and reliability. Starting with foundations of PM machines and heat transfer mechanisms, this paper reviews the development of thermal analysis methods over the last thirty years and the state-of-the-art research achievements, and the hotspot temperatures of winding and PM are particularly evaluated. In the overview, various machine losses and cooling techniques are first introduced, which are the essential reasons for temperature rise and the most straightforward way to remove the generated heat. Afterwards, the mainstream thermal analysis techniques, i.e., numerical techniques, lumped-parameter thermal model, and hybrid thermal models, as well as the online electrical parameter-based and thermal model-based temperature monitoring techniques, are reviewed and assessed in depth. In addition, this paper also reviews the analytical thermal modelling methods for winding and PM. Finally, future research trends are highlighted.

The low-order lumped parameter thermal models (LPTMs) are one of the most competitive online approaches to estimate the critical temperatures in electrical machines. Firstly, this paper explores the correlation between the conventional high-order and low-order LPTMs and then presents some critical modelling guidelines of low-order LPTM together with an improved four-order LPTM. Secondly, a simple dynamic quasi-linear model (DQM) is proposed to define convection thermal resistances, which can be used in both conventional high-order and low-order LPTMs. The application of DQM can improve the estimation accuracy by indirectly introducing more degrees of freedom, which is especially beneficial for the magnet temperature estimation in the low-order LPTM due to its highly abstract rotor thermal modelling. Finally, a prototype permanent magnet synchronous machine is used for experimental validation under different operation profiles.

This paper proposes an improved position-offset based parameter estimation (POPE) method for permanent magnet synchronous machines. In the proposed method, dq -axis inductances and permanent magnet flux linkage can be estimated simultaneously based on three machine states corresponding to injections of zero, positive, and negative position offsets. The guideline is also provided for selecting appropriate amplitude of injected position offset. Compared with the conventional POPE methods, the proposed method has two distinguished advantages, i.e., (a) the influence of inverter nonlinearity can be fully eliminated and (b) the proposed method can be applied under both constant and variable speed operations. The effectiveness of the proposed parameter estimation method is verified by simulations and experiments.

This paper presents a hybrid analytical thermal model by utilizing the synergies of the lumped-parameter thermal model (LPTM) and the analytical thermal model to estimate the 3-dimensional (3-D) permanent magnet (PM) temperature distribution as well as the hotspot for surface-mounted PM synchronous machines (SPMSMs). The hybrid analytical thermal model is firstly developed based on 2-dimensional analytical models in radial-circumferential and radial-axial planes, and then extended to three dimensions, in which the uneven distributions of PM eddy current loss are taken into account. The analytical solutions are obtained by solving the Poisson's equations under the Dirichlet and the convection boundary conditions, which are extracted from the synergized LPTM. The proposed hybrid thermal model is applied to a totally enclosed SPMSM and validated by the 3-D electromagnetic-thermal coupled finite element method and experiments.