Search Results (4)

Subject to magnetic saturation, temperature rise, and other factors, the electrical parameters of permanent magnet synchronous motors (PMSMs) in marine electric propulsion systems exhibit time-varying characteristics. Existing parameter identification algorithms fail to fully satisfy the requirements of high-performance PMSM control systems in terms of accuracy, response speed, and robustness. To address these limitations, this paper introduces multi-innovation theory and proposes a novel multi-innovation extended Kalman filter (MIEKF) for the identification of key electrical parameters of PMSMs, including stator resistance, d-axis inductance, q-axis inductance, and permanent magnet flux linkage. Firstly, the extended Kalman filter (EKF) algorithm is applied to linearize the nonlinear system, enhancing the EKF’s applicability for parameter identification in highly nonlinear PMSM systems. Subsequently, multi-innovation theory is incorporated into the EKF framework to construct the MIEKF algorithm, which utilizes historical state data through iterative updates to improve the identification accuracy and dynamic response speed. An MIEKF-based PMSM parameter identification model is then established to achieve online multi-parameter identification. Finally, a StarSim RCP MT1050-based experimental platform for online PMSM parameter identification is implemented to validate the effectiveness and superiority of the proposed MIEKF algorithm under three operational conditions: no-load, speed variation, and load variation. Experimental results demonstrate that (1) across three distinct operating conditions, compared to forget factor recursive least squares (FFRLS) and the EKF, the MIEKF exhibits smaller fluctuation amplitudes, shorter fluctuation durations, mean values closest to calibrated references, and minimal deviation rates and root mean square errors in identification results; (2) under the load increase condition, the EKF shows significantly increased deviation rates while the MIEKF maintains high identification accuracy and demonstrates enhanced anti-interference ability. This research has achieved a comprehensive improvement in parameter identification accuracy, dynamic response speed, convergence effect, and anti-interference performance, providing an electrical parameter identification method characterized by high accuracy, rapid dynamic response, and strong robustness for high-performance control of PMSMs in marine electric propulsion systems. Full article

Machines with highly saturated magnetic circuits are utilized to maximize drive efficiency. However, their control is non-trivial due to highly non-linear characteristics, and therefore, an accurate parameter identification procedure is crucial. This paper presents and validates a comprehensive flux linkage identification procedure. Several steps needed for accurate parameter identification and their influence on the estimation results are described. The impact of all main parts of the electrical drive, i.e., dead times introduced between switching off and switching on the power transistors, phase delay from the current low-pass filters, delay from the control system, and misalignment of the $d–$axis angle due to the machine asymmetries is considered and partially eliminated. An improved identification procedure with the look-up table-based dead time compensation and estimation of equivalent circuit resistance is applied to estimate the parameters of the highly saturated PMSM traction machine from the fourth generation of the Toyota Prius, and the obtained results are compared with a Finite Element Method-based model of this machine. Finally, dynamic test results are conducted to prove the proposed approach’s accuracy. Full article

Permanent magnet synchronous machines (PMSMs) have garnered increasing interest because of their advantages such as high efficiency, high power density, wide speed range, and fast dynamics. They have been employed recently in several industrial applications including robotics and electric vehicles (EVs). However, PMSMs have highly nonlinear magnetic characteristics, especially interior PMSMs, due to the existence of reluctance torque. Nonlinearity complicates not only machine modeling but also control algorithms. An accurate machine model is the key aspect for the prediction of machine performance as well as the development of a high-performance control algorithm. Hence, this paper presents an accurate modelling method for PMSMs. The proposed model method is applicable for all PMSMs, even multiphase machines. This paper considers a fractional slot concentrated winding 12/10 interior PMSM (IPMSM) for this study to demonstrate the effect of magnetic saturation and special harmonics. The developed model considers accurately the magnetic saturation, mutual coupling, spatial harmonics, and iron loss effects. It utilizes finite element analysis (FEA) to estimate the precise magnetic characteristics of IPMSM. The finite element model is calibrated precisely using experimental measurements. The iron losses are estimated within the simulation model as d- and q-axes current components. The model accuracy is validated experimentally based on a 12/10 IPMSM prototype. Full article

Interior Permanent Magnet Synchronous Machine (IPMSM) are high torque density machines that usually work under heavy load conditions, becoming magnetically saturated. To obtain properly their performance, this paper presents a node mapping criterion that ensure accurate results when calculating the performance of a highly saturated IPMSM via a novel magnetic reluctance network approach. For this purpose, a Magnetic Circuit Model (MCM) with variable discretization levels for the different geometrical domains is developed. The proposed MCM caters to V-shaped IPMSMs with variable magnet depth and angle between magnets. Its structure allows static and dynamic time stepping simulations to be performed by taking into account complex phenomena such as magnetic saturation, cross-coupling saturation effect and stator slotting effect. The results of the proposed model are compared to those obtained by Finite Element Method (FEM) for a number of IPMSMs obtaining excellent results. Finally, its accuracy is validated comparing the calculated performance with experimental results on a real prototype. Full article