Search Results (591)

For the variable speed variable displacement power unit (VSVDPU), achieving power matching between the permanent magnet synchronous motor (PMSM) and the variable displacement plunger pump (VDPP) is the key to reducing system energy consumption. The control method of adjusting the speed of the PMSM and the displacement of the VDPP is the mainstay of current research and application of the VSVDPU. However, the dynamic properties of the PMSM and VDPP have not been balanced, which affects the control effect of the VSVDPU. This paper proposes a control method of variable speed and variable displacement with low energy consumption and high dynamics. The main idea is based on the efficiency model and dynamic response model of the PMSM and VDPP, and the factors that affect the efficiency and dynamic characteristics of the VSVDPU are analyzed. Guided by the multi-objective optimization algorithm, the optimal combination of speed and displacement under specific working conditions is derived. Simulation and experiment results show that the proposed control method is feasible to improve the efficiency and dynamic characteristics of the VSVDPU. Full article

The Sliding Mode Observer (SMO) is widely used for the sensorless control of Permanent-Magnet Synchronous Motors (PMSMs) due to its simple structure and strong parameter robustness. However, traditional SMOs have a limited speed range and suffer from chattering issues, which affect the accuracy of rotor position estimation. To address these problems, this paper proposes an Adaptive Super-Twisting SMO (AST-SMO) method. First, a fast super-twisting function is designed to resolve the step problem that occurs at the zero-crossing of the traditional sign function. Next, an adaptive-tracking high-order Sliding Mode Observer is constructed to extend the speed range of the SMO. The stability of the system is proven using the Lyapunov theorem. Finally, a sensorless control system for PMSMs is implemented and validated in MATLAB/SIMULINK. The results indicate that, compared to the traditional SMO, the AST-SMO reduces the back EMF THD from 20.03% to 14.2%. Additionally, the rotor estimation error across all speed ranges is less than 0.01. Therefore, AST-SMO offers a higher tracking accuracy, a wider speed range, and effectively suppresses sliding mode chattering and harmonic interference. Full article

To address the issue of system parameter variations during the operation of a maritime light vessel rudder permanent magnet synchronous motor (PMSM), an extended Kalman particle filter (EKPF) algorithm that combines a particle filter (PF) with an extended Kalman filter (EKF) is proposed in this paper. This approach enables the online identification of motor resistance and inductance. For highly nonlinear problems that are challenging for traditional methods such as Kalman filtering, this algorithm is typically a statistical and effective estimation method that usually yields good results. Firstly, a standard linear discrete parameter identification model is established for a PMSM. Secondly, the PF algorithm based on Bayesian state estimation as a foundation for subsequent research is derived. Thirdly, the advantages and limitations of the PF algorithm are analyzed, addressing issues such as sample degeneracy, by integrating it with the Kalman filtering algorithm. Specifically, the EKPF algorithm for online parameter identification is employed. Finally, the identification model within MATLAB/Simulink is constructed and the simulation studies are executed to ascertain the viability of our suggested algorithm. The outcomes from these simulations indicate that the proposed EKPF algorithm identifies resistance and inductance values both swiftly and precisely, markedly boosting the robustness and enhancing the control efficacy of the PMSM. Full article

Common-mode voltage (CMV) leads to the shaft voltage and shaft current by coupling the capacitor network in the permanent magnet synchronous machine (PMSM), which affects the reliability of the whole motor drive system. Based on the low-CMV modulation strategy for the PMSM drive system, this paper proposed an improved near-state pulse-width modulation (NSPWM) on switching loss. First, the generation mechanism for the switching signals of NSPWM was analyzed, and it was observed that there exists one phase of switches in an inactive state for every sector. Then, to reduce the switching loss of the NSPWM, this paper proposed an improved NSPWM modulation strategy based on power factor angle to adjust switching action, which ensures the switching tubes that have the biggest conduction current have no switching action. In addition, the switching loss analytic formula of the NSPWM was derived to prove the correctness of the proposed method for optimizing switching loss. Finally, the proposed modulation strategy was carried out in the simulation and experimental platform. Under the premise of good steady and dynamic performance, the results show that the proposed modulation strategy has less switching loss. Full article

This study investigates the impact of temperature variations on the torque capacity of shrink-fit junctions in water-jacketed permanent magnet synchronous motors. Focusing on both baseline and improved designs; torque capacities were evaluated across a temperature range from −40 °C to 120 °C under different material conditions: Least material condition, nominal, and maximum material condition. The baseline design exhibited torque capacities from 7648 Nm to 9032 Nm at −40 °C, decreasing significantly to 549 Nm to 1533 Nm at 120 °C. The improved design showed enhanced performance, with torque capacities ranging from 8055 Nm to 9247 Nm at −40 °C and from 842 Nm to 1618 Nm at 120 °C. The maximum improvement was observed at 120 °C for least material conditions, with a 55.4% increase, and the minimum improvement at −40 °C for maximum material conditions, with a 2.4% increase. Our findings demonstrate a significant increase in torque capacity by up to 20% under varied thermal conditions. These results underscore the effectiveness of design modifications in enhancing thermal stability and torque capacity, making the improved design a more reliable choice for high-performance applications subject to significant thermal fluctuations. This research highlights the critical role of material selection, thermal management, and precise design adjustments in optimizing the performance and reliability of permanent magnet synchronous motors. Full article

In order to reduce the use of wheel angular velocity sensors and improve the estimation accuracy and robustness of the tire–road friction coefficient (TRFC) in non-Gaussian noise environments, this paper proposes a sensorless control-based distributed drive electric vehicle TRFC estimation algorithm using a permanent magnet synchronous motor (PMSM). The algorithm replaces the wheel angular velocity signal with the rotor speed signal obtained from the sensorless control of the PMSM. Firstly, a seven-degree-of-freedom vehicle dynamics model and a mathematical model of the PMSM are established, and the maximum correntropy singular value decomposition generalized high-degree cubature Kalman filter algorithm (MCSVDGHCKF) is derived. Secondly, a sensorless control system of a PMSM based on the MCSVDGHCKF algorithm is established to estimate the rotor speed and position of the PMSM, and its effectiveness is verified. Finally, the feasibility of the algorithm for TRFC estimation in non-Gaussian noise is demonstrated through simulation experiments, the Root Mean Square Error (RMSE) of TRFC estimates for the right front wheel and the left rear wheel were reduced by at least 41.36% and 40.63%, respectively. The results show that the MCSVDGHCKF has a higher accuracy and stronger robustness compared to the maximum correntropy high-degree cubature Kalman filter (MCHCKF), singular value decomposition generalized high-degree cubature Kalman filter (SVDGHCKF), and high-degree cubature Kalman filter (HCKF). Full article

Finite-set model predictive control (FS-MPC) is an easy and intuitive control technique. However, parametric uncertainties reduce the accuracy of the prediction. Classical MPC requires many calculations; therefore, the calculation time generates a considerable time delay in the actuation. This delay deteriorates the performance of the system and generates a significant current ripple. This paper proposes a finite-set integral sliding modes predictive control (FS-ISMPC) for a permanent magnet synchronous motor (PMSM). The conventional decision function is replaced by an integral sliding cost function, which has several advantages, such as robustness to parameter uncertainties, and convergence in finite time. The proposed decision function does not require the inductance and resistance parameters of the motor. In addition, the proposal includes compensation for the calculation delay of the control vector. The proposed control strategy was compared with traditional predictive control with delay compensation using a real-time hardware-in-the-loop (HIL) simulation. The results obtained from the comparison indicated that the proposed controller has a lower THD and computational burden. Full article

The field of sensorless control of permanent magnet synchronous motor (PMSM) systems has been the subject of extensive research. The accuracy of sensorless controllers depends on the precise estimation of PMSM state quantities, including rotational speed and rotor position. In order to enhance state estimation accuracy, this paper proposes a moving horizon estimator that can be utilized in the sensorless control system of PMSM. Considering the parameter variations observed in PMSM, a nonlinear mathematical model of PMSM is established. A model reference adaptive system (MRAS) is employed to identify parameters such as resistance, inductance, and magnetic chain in real time. This approach can mitigate the impact of parameter fluctuations. Moving horizon estimation (MHE) is an estimation method based on optimization that can directly handle nonlinear system models. In order to eliminate the influence of external interference and improve the robustness of state estimation, a method based on MHE has been designed for PMSM, and a sensorless observer has been established. Considering the traditional MHE with large computation and high memory occupation, the calculation of MHE is optimized by utilizing a Hessian matrix and gradient vector. The speed and position of the PMSM are estimated within constraints during a single-step iteration. The results of the simulation demonstrate that in comparison to the traditional control structure, the estimation error of rotational speed and rotor position can be reduced by utilizing the proposed method. A more accurate estimation can be achieved with good adaptability and computational speed, which can enhance the robustness of the control system of PMSM. Full article

In view of the problem of the low-speed jitter of household lawn mowers driven by a permanent magnet synchronous motor (PMSM) at low speeds and high torque, and the complicated parameters of traditional non-linear active disturbance rejection controllers, a partially optimized linear active disturbance rejection control (LADRC) driving PMSM strategy is proposed. First, the linear extended state observer (LESO), which bears a significant burden in terms of speed and load estimation in active disturbance rejection control, is optimized by reducing its order to improve the anti-disturbance performance of the active disturbance rejection controller within a limited bandwidth. Secondly, the reduced-order parallel linear extended state observer (RPLESO) is obtained by optimizing the parallel structure of the order-reduced LESO, which improves the control precision and robustness of the system. Through a simulation and experimental verification, the optimized LADRC control of the PMSM system is shown to improve the parameter adjustability, speed estimation precision and system robustness. Full article

This paper proposes a novel composite position controller for the field-oriented control (FOC) strategy of permanent-magnet synchronous motor (PMSM) servo systems. The proposed composite position controller integrates a position controller with a disturbance observer, with each designed based on a specific second-order sliding-mode algorithm. Specifically, the continuous twisting algorithm (CTA) is employed to develop the position controller for achieving rotor position tracking, while the modified super-twisting algorithm (STA) is used to construct the disturbance observer for compensating the total disturbance in the rotor position tracking error dynamics to enhance the dynamic performance. Comparative simulation tests, conducted within an FOC strategy of PMSM servo systems, contrast the performance of the CTA-based position controller, the composite position controller using a CTA-based position controller and a standard STA-based disturbance observer, and the proposed composite position controller. The simulation results validate the proposed position controller’s effectiveness and its superiority over comparable position controllers. Full article

With increasing worries about the environment, there is a rising focus on saving energy in various industries. In the e-mobility industry of electric motors, permanent magnet synchronous motors (PMSMs) are widely utilized for saving energy due to their high-efficiency motor technologies. However, challenges like environmental degradation from rare earth development and difficulties in controlling magnetic field fluctuations persist. To address these issues, active research focuses on the wound field synchronous motor (WFSM), known for its ability to regulate field current efficiently across various speeds and operating conditions. Nevertheless, compared with other synchronous motors, the WFSM tends to exhibit relatively lower efficiency and torque density. Because the WFSM involves winding both the rotor and the stator, it results in increased copper and iron losses. In this article, a model that enhances torque density by inserting permanent magnets (PMs) into the rotor of the basic WFSM is proposed. This proposed model bolsters the d axis magnetic flux, thereby enhancing the motor’s overall performance while addressing environmental concerns related to rare-earth materials and potentially reducing manufacturing costs when compared with those of the PMSM. The research methodology involves a comprehensive sensitivity analysis to identify key design variables, followed by sampling using optimal Latin hypercube design (OLHD). A surrogate model is then constructed using the kriging interpolation technique, and the optimization process employs a micro-genetic algorithm (MGA) to derive the optimal model configuration. The algorithm was performed to minimize the use of PMs when the same torque as that of the basic WFSM is present, and to reduce torque ripple. Error assessment is conducted through comparisons with finite element method (FEM) simulations. The optimized permanent-magnet-assisted WFSM (PMa-WFSM) model improved efficiency by 1.08% when it was the same size as the basic WFSM, and the torque ripple decreased by 5.43%. The proposed PMa-WFSM derived from this article is expected to be suitable for use in the e-mobility industry as a replacement for PMSM. Full article

The direct-drive selective compliance assembly robot arm (SCARA) is widely used in high-end manufacturing fields, as it omits the mechanical transmission structures and has the advantages of high positioning accuracy and fast movement speed. However, due to the intensifying dynamic coupling problem of structures in the direct-drive SCARA, the permanent magnet synchronous motors (PMSMs) located at the joints will take on nonstationary loads, which causes excessive internal temperature and reduces the lifetime of PMSMs. To address these issues, the lifetime prediction of PMSMs is studied. The kinematic and dynamic models of the SCARA are established to calculate the torque curve required by the PMSM in specific typical motion tasks. Additionally, considering thermal stress as the main factor affecting lifetime, accelerated degradation tests are conducted on insulation material. Then, the reliability function of the PMSM is formulated based on the accelerated degradation model. Based on the parameters and working conditions of the PMSM, the temperature field distribution is obtained through simulation. The maximum temperature is used as the reference temperature to conduct reliability evaluation and lifetime prediction of the PMSM. The research results show that for a typical point-to-point task, the PMSM can run for 102,623 h while achieving the reliability requirement of 0.99. Full article

In a multi-source permanent magnet synchronous motor (PMSM) drive, three distinct winding structures can be implemented: multi-sector, multi-three-phase, and highly coupled. However, due to variations in the magnetic coupling between windings, their low-frequency DC-link current ripple components differ. This paper presents a method to identify the phenomena associated with each low-frequency harmonic content. Three analytical models are developed for the DC current ripple induced by unbalanced winding, counter-electromotive force (back-EMF) harmonics and aliasing effects, respectively, with the results validated through simulations. Experimental validation is conducted for highly coupled winding drives, demonstrating agreement with the analytical models and simulations. The maximum DC current ripple ratio found in the analytical model, the simulation and the experiments is less than $15\%$, which is deemed acceptable for motor drive applications. Full article

The increasing demand for sustainable development and energy efficiency underscores the importance of optimizing motors in driving the upgrade of energy structures. This paper studies a data-driven approach for the multi-objective optimization of motors designed for scenarios involving multiple variables, objectives, and limited sample sizes and validates its efficacy. Initially, sensitivity analysis is employed to identify potentially influential variables, thus selecting key design parameters. Subsequently, Latin hypercube sampling (LHS) is utilized to select experimental points, ensuring the coverage of the modeled test points across the experimental space to enhance fitting accuracy. Finally, the support vector regression (SVR) algorithm is employed to fit the objective function, in conjunction with multi-objective particle swarm optimization (MOPSO) for solution derivation. The presented method is used to optimize the efficiency, average output torque, and induced electromotive force harmonic distortion rate of a permanent magnet synchronous motor (PMSM). The results show an improvement of approximately 6.80% in average output torque and a significant decrease of about 59.5% in the induced electromotive force harmonic distortion rate, with minimal impact on efficiency. This study offers a pathway for enhancing motor performance, holding practical significance. Full article

Permanent Magnet Synchronous Motors (PMSMs) with high energy efficiency, reliable performance, and a relatively simple structure are widely utilised in various applications. In this paper, a suboptimal controller is proposed for PMSMs without sensors based on the state-dependent Riccati equation (SDRE) technique combined with customised impulsive observers (IOs). Here, the SDRE technique facilitates a pseudo-linearised display of the motor with state-dependent coefficients (SDCs) while preserving all its nonlinear features. Considering the risk of non-available/non-measurable states in the motor due to sensor and instrumentation costs, the SDRE is combined with IOs to estimate the PMSM speed and position states. Customised IOs are proven to be capable of obtaining quality, continuous estimates of the motor states despite the discrete format of the output signals. The simulation results in this work illustrate an accurate state estimation and control mechanism for the speed of the PMSM in the presence of load torque disturbances and reference speed changes. It is clearly shown that the SDRE-IO design is superior compared to the most popular existing regulators in the literature for sensorless speed control. Full article