Permanent Magnet Synchronous Motor Speed Research Articles

Fuzzy self-tuning fractional order PD permanent magnet synchronous motor speed control based on torque compensation

The permanent magnet synchronous motor control system is characterized by its nonlinear and strongly coupled complexity, presenting significant challenges for control performance optimization. To address these challenges, a Fuzzy adaptive fractional order control strategy based on torque observation compensation is proposed. The parameters of the fractional order controller are optimized real time using fuzzy logic reasoning, in order to enhance the speed of parameters tuning, a graphical design method of the fractional order controller parameters based on frequency domain performance indicators is proposed to obtain the initial values of the fuzzy adaptive fractional order controller parameters graphically and intuitively. Furthermore, a load torque observer is designed to improve the anti interference capability of the system by proportionally converting the observed load torque into compensation current in equal proportion. Simulation and experimental results validate that the proposed strategy demonstrates superior dynamic and static performance, as well as robustness.

Integration of in-wheel motor sensorless systems and hierarchical direct yaw moment control for distributed drive electric vehicles

Ensuring robust and reliable control of distributed vehicles powered by in-wheel motor systems poses a significant challenge due to the harsh operating environments and high costs of such motor systems. Poor motor control, parameter variations, and sensor malfunction under these conditions can compromise the vehicle yaw stability. Integrating permanent magnet synchronous motor (PMSM) sensorless systems with vehicle yaw moment control offers a cost-effective solution for this issue without wheel angular speed sensors while enhancing yaw stability. In this paper, a composite nonlinear feedback sliding mode controller that can enhance the PMSM speed response is proposed. The proposed scheme exhibits a rotor speed overshoot and transient time of only 0.64% and 0.07s, respectively, which are smaller and shorter compared with other methods under motor parameter changes. Subsequently, the key states and tire-road friction coefficients required for vehicle control were estimated using sensorless rotor speeds and unscented Kalman filters, enabling the integration of the PMSM sensorless system with the vehicle yaw moment control. Additionally, a fuzzy adaptive hybrid sliding mode method is presented for yaw moment control enhancement. This method maintained the smallest sideslip angle root mean square error during double lane changes (0.4192 deg) compared with other methods. Analysis results show that different motor controllers and parameter changes significantly affect the vehicle dynamics performance. The proposed integrated scheme is feasible and effectively enhances the yaw moment control via high-performance sensorless PMSM systems.

An Improved Nonlinear Active Disturbance Rejection Controller via Sine Function and Whale Optimization Algorithm for Permanent Magnet Synchronous Motors Speed Control

Permanent magnet synchronous motors (PMSMs) speed control has gained wide application in various fields. Specifically, there is a disadvantage that nonlinear functions in the conventional active disturbance rejection controller (ADRC) is non‐differentiable at the piecewise points. Thus, an improved nonlinear active disturbance rejection controller (NLADRC) for permanent magnet synchronous motor speed control via sine function and whale optimization algorithm (WOA), abbreviated as NLADRC‐sin‐IWOA, is proposed to overcome this drawback. Considering the unsatisfactory control effect caused by the poor active disturbance resisting ability of the traditional PMSM controllers, this paper proposes an improved NLADRC for PMSM, that reconstructs a novel differentiable and smooth nonlinear function, the novel nonlinear function grounded on primitive function by the function of inverse hyperbolic, sine, square functions, and with difference fitting approach; and designs an improved whale optimization algorithm via convergence factor nonlinear decreasing, Gaussian variation and adaptive cross strategies. The experimental results findings show that the improved NLADRC‐sin‐IWOA has the advantages of response fast, small steady‐state error and tiny overshoot. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Robust model-based control and stability analysis of PMSM drive with DC-link voltage and parameter variations

To ensure a stable operation of Permanent Magnet Synchronous Motor (PMSM) drive under both DC link voltage and parameter variations, a robust control technique based on a new dynamic model that includes both drive’s and motor’s specifications is proposed in this paper. In the proposed controller, the first component of the drive’s control law consists of the d-component error of the stator current, and the second one is shaped based on the error in the square value of q-component of the stator current. To further deal with the dynamic alterations of the drive system, compensators are designed to reduce the adverse effects of rotor angular frequency variations and the difference between electrical and load torque errors. Another compensator based on the drive’s output power error is also placed at the q-component of the proposed control law. Moreover, a general operation curve (GOC) for the stator current is introduced to further assess the operation of the PMSM. In the next step, a comprehensive stability analysis verifying the stable operation of both d- and q-components of the stator current is performed using two closed-loop descriptions of the proposed control strategy. Several simulation results in MATLAB/SIMULINK environment are provided to verify the validity of the proposed control technique under various dynamic scenarios. It is worth mentioning that comparative results show that the proposed control technique compared to conventional PI controller has enabled the PMSM speed and torque to reach its 50% and 95% of their desirable values with respectively 42.9% and 28.6% less time. Also, the PMSM speed and torque responses due to proposed control technique have 75% less undershoot compared to conventional PI controller.

Interdisciplinary Education Promotes Scientific Research Innovation: Take the Composite Control of the Permanent Magnet Synchronous Motor as an Example

Intersecting disciplines, as an important trend in the development of modern academic research and education, have exerted a profound and positive influence on scientific research activities. Based on control theory and fractional-order theory, this paper presents a novel approach for the speed regulation of a permanent magnet synchronous motor (PMSM) in the presence of uncertainties and external disturbances. The proposed method is a composite control based on a model-free sliding mode and a fractional-order ultra-local model. The model-free sliding mode is a control strategy that utilizes the sliding mode control methodology without explicitly relying on a mathematical model of the system being controlled. The fractional-order ultra-local model is a mathematical representation of a dynamic system that incorporates the concept of fractional-order derivatives. The core of the controller is a new type of fractional-order fast nonsingular terminal sliding mode surface, which ensures high robustness, quick convergence, while preventing singularity. Moreover, a novel fractional-order nonlinear extended state observer is proposed to estimate both internal and external disturbances of the fractional-order ultra-local model. The stability of the system is analyzed using both the Lyapunov stability theory and the Mittag–Leffler stability theory. The analysis confirms the convergence stability of the closed-loop system under the proposed control scheme. The comparison results indicate that the proposed composite control based on the fractional-order ultra-local model is a promising solution for regulating the speed of PMSMs in the presence of uncertainties and disturbances.

Permanent Magnet Synchronous Motor Speed Control System Based on Fractional Order Integral Sliding Mode Control

Permanent Magnet Synchronous Motor Speed Control System Based on Fractional Order Integral Sliding Mode Control

Parameter fuzzy rectification for sliding mode control of five-phase permanent magnet synchronous motor speed control system

Introduction: Nowadays, five-phase permanent magnet synchronous motors have been widely used in the industrial and transportation fields, and the existing sliding mode control methods for speed control systems can no longer meet the requirements such as fast response and good stability.Methods: In light of the aforementioned considerations, the study initially employs mathematical modeling to elucidate the five-phase permanent magnet synchronous motor. Secondly, on the basis of proportional-integral-derivative sliding mode control, radial basis function and Takagi-Sugeno-Kang fuzzy model are introduced for parameter identification and optimization and regulation. Finally, a new neural network regulation algorithm and speed control strategy are proposed.Results and Discussion: The experimental results demonstrated that the expected parameter optimization rate of the regulation algorithm can reach 90%, and the overshooting amount under small inertia working condition is only 3%, and the adjustment time is 0.02 s. The new control algorithm can be used to control the motor speed with the lowest speed fluctuation and the fastest recovery time. In addition, when affected by the load torque, the motor speed controlled by the new strategy fluctuated the least, with a speed drop of only 1% and the fastest recovery time of 0.02 s. It exhibited the lowest control error of 3.7% and the lowest overshooting amount of 5.9%.Conclusion: In summary, the suggested approach has the potential to significantly enhance the speed control system’s control performance while maintaining strong resilience and anti-interference capabilities. The method has certain guiding significance for the practical application of five-phase permanent magnet synchronous motor speed control system.

Sliding Mode Speed Control for PMSM Based on Model Predictive Current

To enhance the dynamic performance and disturbance rejection capability of the permanent magnet synchronous motor speed control system, a novel speed control method based on a novel sliding mode control (NSMC) and load torque observer is proposed on the basis of model predictive current control (MPCC) with a sliding mode disturbance observer. First, on the basis of MPCC, the influence of parameters such as resistance, inductance, and flux linkage on MPCC is analyzed. To address the aggregated disturbance caused by parameter mismatches, a piecewise square-root switching function sliding mode disturbance observer (SMDO) is designed to enhance the robustness of the parameters. To address the poor dynamic performance and inadequate robustness resulting from the proportional-integral-controller (PI) velocity loop control in the MPCC, a novel NSMC velocity control method is proposed. This method utilizes the hyperbolic sine function and fractional-order integral sliding mode surface, resolving the dilemma faced by traditional slide mode controllers (SMC) in balancing fast response and reduced vibration. Additionally, to enhance the system’s disturbance rejection capability, a sliding mode torque observer (SMTO) is designed to continuously update the observed load torque value into the NSMC controller, achieving speed compensation control. Finally, through comparative experiments among the proportional integral controller (PI), SMC, NSMC, and NSMC + SMTO, the results indicate that the proposed NSMC + SMTO exhibits the best speed response, steady-state characteristics, and disturbance rejection capability.

Observer-Based Suboptimal Controller Design for Permanent Magnet Synchronous Motors: State-Dependent Riccati Equation Controller and Impulsive Observer Approaches

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.

Research on linear/nonlinear active disturbance rejection switching control of PMSM speed servo system

An improved linear/nonlinear active disturbance rejection switching control strategy is proposed to enhance the dynamic response and disturbance suppression capabilities of the permanent magnet synchronous motor (PMSM) speed servo system. Firstly, facilitated by a tracking differentiator, rapid setpoint tracking is achieved without speed overshoot, effectively addressing the inherent conflict between fast system response and overshooting. Secondly, weight factors are introduced into the control law, and a novel switching criterion based on the step function is designed, enabling the system to smoothly transition between operating modes in the presence of disturbances with varying amplitudes. This facilitates accurate estimation and swift compensation for disturbances, thereby enhancing control precision and robustness. Additionally, a frequency domain analysis of the extended state observer is conducted, leading to the formulation of a parameter tuning scheme for the controller. Lastly, simulation tests validate the feasibility and effectiveness of this strategy as a PMSM speed controller. The system exhibits superior dynamic tracking and disturbance suppression performance over a wide speed range.

A Novel reaching law sliding mode control method of PMSM considering iron loss

The loss of motor is ignored in the traditional speed control, while the loss minimization control (LMC) takes the high efficiency of the motor and does not consider the speed performance. Therefore, with the iron loss torque as the bond between efficiency and dynamic performance, this paper presents a sliding mode control method under the loss minimization target to achieve the high efficiency and high dynamic performance of permanent magnet synchronous motor (PMSM). Firstly, a d-axis current compensation method based on Taylor series expansion of virtual power loss (VPL) is proposed to minimize the loss of PMSM. Secondly, to eliminate the influence of iron loss on the speed performance, a PMSM speed tracking model including iron loss is established. Then, an adaptive sliding mode reaching law with disturbance estimation (ASMRLDE) is proposed to avoid energy consumption and the sliding mode chattering of the system caused by excessive sliding mode switch gain by adjusting the speed at which the system state reaches the sliding surface. Finally, the superiority of the proposed sliding mode control method under the loss minimization target in terms of loss minimization and speed control of the motor is proved through multi-condition experiments.

Fixed-Time-Convergent Sliding Mode Control with Sliding Mode Observer for PMSM Speed Regulation.

This paper focuses on the speed control of a permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and external disturbances. Conventional sliding mode control (CSMC) can only converge asymptotically in the infinite domain and will cause unacceptable sliding mode chattering. To improve the performance of the PMSM speed loop in terms of response speed, tracking accuracy, and robustness, a hybrid control strategy for a fixed-time-convergent sliding mode controller (FSMC) with a fixed-time-convergent sliding mode observer (FSMO) is proposed for PMSM speed regulation using the fixed-time control theory. Firstly, the FSMC is proposed to improve the convergence speed and robustness of the speed loop, which can converge to the origin within a fixed time independent of the initial conditions. Then, the FSMO is used as a compensator to further enhance the robustness of the speed loop and attenuate sliding mode chattering. Finally, simulation and experimental results show that the proposed method can effectively improve the dynamic performance and robustness of the PMSM speed control system.

Comparative vector control study on speed of PMSM drive using sensorless and machine learning techniques: review

The main contribution of this review work is to show how various control techniques are used to manage the speed of Permanent Magnet Synchronous Motor (PMSM). The PMSM’s are mostly used in electric vehicles, electric traction and high performance industrial drive applications. In this article conventional sensorless techniques are compared with machine learning techniques such as fuzzy logic, artificial neural network and neuro-fuzzy controllers to control the speed of PMSM drive based on vector control approach. The benefits of machine learning techniques used in sensorless PMSM drive are easy to design, less execution time and fast access speed control. The various controlling techniques used in controller along with its complexity, advantages and drawbacks are discussed in this article. The above mentioned controlling techniques are implemented and simulated by using MATLAB R2019b/Simulink software based on sensorless Model Reference Adaptive System (MRAS) with the help of Field Oriented Control (FOC) strategy of PMSM drive. By comparing the all sensorless controlling techniques in simulation study, it is identified that the combination of neuro-fuzzy controller gives the best speed control performance than other controllers.

Finite time fault estimation and fault‐tolerant control for a class of uncertain nonlinear systems based on cascaded observers

AbstractIn this paper, a finite time fault estimation and fault‐tolerant control method is proposed for a class of uncertain nonlinear systems that have both actuator faults and sensor faults. First, the outputs of the original system pass through the low‐pass filters to obtain the augmented states, and then an augmented system is composed of the states of the low‐pass filters and the original system, so as to realize the conversion of the sensor faults of the original system into partial actuator faults of the augmented system. Next, design state observers to reconstruct the unknown states of the augmented system, and develop extended state observers to estimate the actuator faults and disturbance of the augmented system. Again, the fault‐tolerant controllers are completed based on the backstepping control and the finite time control, and the finite time convergences of the designed observers and controllers are proved by theoretical analyses. Finally, based on a permanent magnet synchronous motor (PMSM) speed system, the simulation research and dSPACE simulated experiment research are conducted to verify the effectiveness of the proposed control method and its feasibility in the actual application.

Permanent magnet synchronous motor inter-turn short circuit diagnosis based on physical-data dual model under oil-drilling environment

Inter-turn Short Circuit (ITSC) faults in Permanent Magnet Synchronous Motor (PMSM) have gained significant attention due to the growing demand for enhanced reliability and safety in actuation systems. This paper presents a adaptive fault diagnosis approach specifically designed for ITSC faults in PMSM used in oil-drilling applications, where sparse actual data and varying speed conditions pose considerable sparse training data and ITSC feature extraction challenges respectively. To address these challenges, we first construct a physical fault model of PMSM-ITSC and establish a simulation experiment platform to replicate downhole environments with high temperatures and rapidly changing PMSM speeds, ensuring a reliable data source for analysis. Subsequently, we propose a novel adaptive peak-to-peak self-finding method (APPS) that leverages frequency-domain prior knowledge to adaptively extract ITSC fault characteristics, even amidst drastic changes in PMSM speed. Furthermore, we introduce the time-sequence efficient moving window self-attention network (EMWSAN) data model for inferring the stator phase winding state, incorporating Half-sandwich and Cascaded windows group attention operations. This approach significantly reduces computational complexity and network parameters compared to traditional self-attention mechanisms. To expedite the fitting process, we apply transfer learning (TL) theory, transferring knowledge from the physical knowledge to the data model, enabling EMWSAN to be trained more efficiently. As a result, our proposed ITSC fault diagnosis scheme achieves an impressive 96.72% classification accuracy, achieving existing state-of-the-art methods.

Research on magnetic-fluid-thermal-stress multi-field bidirectional coupling of high speed permanent magnet synchronous motors

Due to the fact that high speed permanent magnet synchronous motors (HSPMSM) are direct drives instead of using gears, they have technical and economical advantages in many applications. In this paper, a 150 kW, 30,000 r/min HSPMSM was used as research object, for which a magnetic-fluid-thermal-stress multi-field coupling model was developed and solved. Motor losses were obtained from electromagnetic analysis and were applied as heat source. Subsequently, the temperature and fluid distribution were solved according to given heat source characteristics and cooling structure. Based on this, the rotor stress distribution influenced by the temperature load was further obtained. On the other hand, the effect of temperature change on conductor resistivity, permanent magnet remanence, cooling medium thermophysical properties, and loss characteristics, which in turn affect temperature and stress distribution, was considered. The bidirectional coupling of multi-fields was achieved by iterative calculations in the "forward" and "reverse" cycles. The results showed that the hotspot temperature increased by 14.19 % and the tangential stress in permanent magnet increased by 5.28 % compared to the unidirectional coupling. Finally, an experiment platform was built, and tests were conducted. The results showed that the temperature obtained by bidirectional coupling was closer to the experimental result.

Design of PMSM Dual-Loop Control Systems Integrating LADRC and PI Controllers via an Improved PSO Algorithm

This paper is concerned with the design of a dual-loop control system for permanent magnet synchronous motor (PMSM). An improved linear extended state observer (LESO) with excellent estimation capability is employed to develop an improved linear active disturbance rejection control (LADRC) suitable for PMSM speed regulation, achieving outstanding disturbance suppression in PMSM speed control. The use of an internal model control scheme to initialize the parameters of the proportional-integral- (PI-) based current controller simplifies the search space of the control system parameter optimization. An improved particle swarm optimization (PSO) algorithm is applied to optimize the controller parameters, thereby enhancing the overall system performance. Finally, through a series of simulations and experiments, we validate that our proposed controller exhibits superior performance compared to some other control methods.

Research on speed sensorless control strategy of permanent magnet synchronous motor based on fuzzy super-twisting sliding mode observer.

Aiming at the problems of poor adjustment effect, weak anti-disturbance ability, and low robustness of the traditional sliding mode algorithm for permanent magnet synchronous motor speed sensorless, a permanent magnet synchronous motor speed observation method combining super-twisting sliding mode control algorithm and fuzzy control is proposed to accelerate the convergence speed of the system and improve the anti-disturbance ability. Fuzzy rules are used to solve the problem of obtaining the upper bound of the boundary function in the super-twisting algorithm. Moreover, the fuzzy algorithm is used to output the variable sliding mode gain instead of the fixed sliding mode coefficient to improve the system robustness and suppress the jitter. The simulation results show that the overshoot of the control system is 4%, the lag time is not more than 0.003 ms, the speed error is not more than 1%, and the response and adjustment time is not more than 0.02 s. The proposed control strategy improves the tracking accuracy and response speed of the system, suppresses the sliding mode chattering, and enhances the anti-interference ability of the system.

Design of perturbation suppression neural network direct adaptive sliding mode controller for permanent magnet synchronous motor speed regulation system

Design of perturbation suppression neural network direct adaptive sliding mode controller for permanent magnet synchronous motor speed regulation system

Response Analysis and Stator Optimization of Ultrahigh-Speed PMSM for Fuel Cell Electric Air Compressor

For the requirement of the complex dynamic performance for the fuel cell vehicle (FCV), the wide operation range and rapid dynamic response ability are essential to the fuel cell electric air compressor, which are limited by the output torque of the permanent magnet synchronous motor (PMSM) commonly used in FCV. The purpose of this study is to improve the output torque of the stators and its rapid dynamic response capacity of PMSM using the mathematical model, multi-objective optimization and experimental validation. Firstly, a mathematical model of speed regulation response of ultra-high speed PMSM is established, which provides a basis for taguchi legal sub-optimization in this study. Secondly, stator parameters were selected as optimization variables based on Taguchi method, and the optimal combination of optimization variables was selected with the maximum electromagnetic torque, minimum cogging torque, minimum stator copper loss and minimum stator iron loss as optimization objectives. Finally, the effectiveness of the optimization method is verified by simulation analysis and bench test. At the target speed of 110652rpm, 124364rpm and 146876rpm, the overall response times before optimization are 1.9386s, 2.3902s, and 2.7844s. Respectively, the overall response times after optimization are 1.8604s, 2.2856s, and 2.6132s. The speed response time after optimization is 0.0782s, 0.1046s and 0.1712s less than before optimization, respectively.