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Adjustments in vehicle height and attitude under high-speed steering, emergency obstacle avoidance, and obstacle crossing can significantly improve the safety, mobility, and passing ability of a vehicle. At present, air and hydraulic suspensions are generally used for vehicle body height adjustment, both of which have problems of slow response and complex structures. In this study, a novel method of vehicle body height adjustment based on active suspension with a permanent magnet synchronous linear motor (PMSLM) is proposed. First, active suspension and PMSLM models are established. Then, the vehicle body height controller is designed by hierarchical control, where the upper layer uses PI control to make the vehicle body height track the desired vehicle body height and calculate the desired control force, whereas the lower layer uses the finite control set model predictive current control to make the linear motor track the desired suspension control force. For motor control, the cost function is constructed based on the minimum tracking error between the reference and predicted currents. The forward Euler discrete method is used to deduce the current prediction model for the linear motor. The simulation tests under different road classes and vehicle speeds prove that the active suspension with the PMSLM can effectively adjust the vehicle body height and has a fast response, simple structure, and does not affect ride comfort. The proposed method provides a new concept for short-term vehicle body height adjustments under specific working conditions. [ABSTRACT FROM AUTHOR]

In this paper, the enhanced nonlinear magnetic model of the low voltage interior permanent magnet synchronous machine (IPMSM) is developed using the frozen permeability (FP) technique in finite element analysis (FEA) FEMM 4.2 software. The magnetic model is derived by obtaining flux saturation maps for a wide range of dq stator currents. Furthermore, the FEA FP technique accounts for the corresponding offset in the flux maps due to the excitation of the permanent magnets, and well as for fitting the coefficients for the curve-fitting procedure. In order to demonstrate the usefulness of the proposed magnetic model, a nonlinear control strategy based on the maximum torque per ampere (MTPA) optimal algorithm for IPMSM is employed. The magnetic model and the MTPA control strategy are validated through a variety of computer simulations based on FEMM 4.2 and MATLAB R2023a software, as well as on a real IPMSM electric vehicle (EV) traction drive experimental setup. [ABSTRACT FROM AUTHOR]

The accurate identification of permanent magnet synchronous motor (PMSM) parameters is the foundation for high-performance driving in predictive control systems. The traditional PMSM multi-parameter identification method suffers from insufficient rank of the identification equation and is prone to getting stuck in local optimal solutions. This article combines the bacterial foraging optimization algorithm (BFOA) to establish a built-in PMSM predictive control parameter compensation model. Firstly, we analyzed the reasons why the distortion of PMSM motor parameters affects the actual speed and calculated the deviation of d-axis and q-axis currents caused by the distortion. Secondly, parameter compensation was applied to the prediction model, and BFOA was combined to optimize the compensation parameters. This algorithm does not use the traditional voltage equation as the fitness function but instead uses a brand-new set of four equations for parameter iteration optimization. The optimized compensation parameters can reduce current deviation and improve the robustness of the PMSM predictive control system. The proposed model can cover four kinds of motor distortion parameters, including stator resistance, D-axis inductance, Q-axis inductance, and permanent magnet flux linkage. Finally, the traditional PMSM predictive control model is compared with the predictive control model combined with BFOA. The simulation results show that the dynamic and static performance of the compensated system is improved when single or multiple parameters are distorted. [ABSTRACT FROM AUTHOR]

Maximum torque per ampere (MTPA) control of internal permanent magnet synchronous motors (IPMSM) has become integral to high-efficiency motor drives. To minimize the influence of the traditional model-based analytical solution method on the MTPA control strategy due to the parameter variations during the motor operation, an online search MTPA method without model-based fractional-order extremum seeking control (FO-ESC) is proposed. Compared with the traditional integer-order ESC method, the Oustaloup approximation-based fractional-order calculus provides additional factors and possibilities for optimizing controller parameters to improve control performance. At the same time, the proposed approach does not require machine parameters and is thus not influenced by machine and drive nonlinearities. Simulation results show that the proposed method can ensure robust MTPA control under different loading conditions in real-time and improve the system's dynamic response speed and steady-state accuracy. [ABSTRACT FROM AUTHOR]

In order to reduce the convergence time of permanent magnet linear synchronous motor (PMLSM) and improve the robustness of system, a fixed‐time fractional order nonsingular terminal sliding mode control (FTFONTSMC) strategy is designed to realize the rapidity and accuracy of PMLSM position tracking response. Firstly, an improved fixed‐time terminal sliding mode (FTTSM) reaching law is proposed to reduce the time of convergence. Secondly, due to the uncertainty of the disturbance in PMLSM system, an exponential convergent disturbance observer (DO) is designed to observe the disturbance. Further, finite time stability of the control system is proved by Lyapunov stability theory. Finally, the above control algorithm is applied to PMLSM, and the proposed control method's effectiveness and superiority are validated by comparing with existing control methods. [ABSTRACT FROM AUTHOR]

Demagnetization in permanent magnet synchronous motor (PMSM), caused by high temperature or inverse magnetic field, may increase loss and torque ripple, and even degrade the system stability in severe cases. On-line detection can identify the incipient demagnetization of permanent magnets (PMs), as well as providing reference for subsequent fault-tolerant control, so as to avoid further demagnetization. Therefore, an on-line demagnetization detection method is proposed in this paper by using flux observer. First, an observer is established in the three-phase stationary reference frame by taking the stator currents and the amplitudes of the fundamental and harmonic components of flux as state variables. Then, three demagnetization indexes are presented to evaluate the properties of PMs based on the observed flux information. The proposed method can directly track the amplitude of harmonic flux and evaluate the severity of the demagnetization more comprehensively. Simulation and experimental results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The finite control set model predictive torque control (FCS-MPTC) selects the optimal voltage vector (VV) by the composite cost function composed of torque and flux error, which makes it have a faster dynamic response than conventional control methods. However, the prediction state error caused by machine parameter mismatch and the difficulty in setting the weight factor in the composite cost function seriously restrict the popularization and application of FCS-MPTC. In this paper, a model-free parallel predictive torque control (MF-PPTC) based on an ultra-local (UL) model is proposed to solve above problems. The UL model replaces the machine mathematical model without any machine parameters and only uses the input and output of the system, which greatly improves the robustness of the control system. The nonlinear extended state observer proposed for the unknown part of the system has fast convergence and improves the dynamic performance of the system. In addition, the conventional parallel predictive control structure is optimized to reduce the dynamic adjustment process during the selection of optimal voltage vector. Simulation and experimental comparison between the conventional PPTC and the proposed MF-PPTC verified the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a sensorless model predictive torque control strategy based on an adaptive Takagi–Sugeno (T–S) fuzzy model for the design of a six–phase permanent magnet synchronous generator (PMSG)–based hydrokinetic turbine systems (PMSG-HTs), which not only provides clean electric energy and stable energy-conversion efficiency, but also improves the reliability and robustness of the electricity supply. An adaptive T–S fuzzy model is first formed to characterize the nonlinear system of the PMSG before a model predictive torque controller based on the T–S fuzzy model for the PMSG system is employed to indirectly control the stator current and the stator flux magnitude, which improves the performance in terms of anti–disturbance, and achieves maximum hydropower tracking. Finally, we consider two types of tidal current, namely the mixed semidiurnal tidal current and the northwest European shelf tidal current. The simulation results demonstrate that the proposed control strategy can significantly improve the voltage–support capacity, while ensuring the stable operation of the PMSG in hydrokinetic turbine systems, especially under uneven tidal current speed conditions. [ABSTRACT FROM AUTHOR]

This work addresses the problem of mitigating the effects of the cogging torque in permanent magnet synchronous motors, particularly brushless motors, which is a main issue in precision electric drive applications. In this work, a method for mitigating the effects of the cogging torque is proposed, based on the use of a nonlinear automatic control technique known as feedback linearization that is ideal for underactuated dynamic systems. The aim of this work is to present an alternative to classic solutions based on the physical modification of the electrical machine to try to suppress the natural interaction between the permanent magnets and the teeth of the stator slots. Such modifications of electric machines are often expensive because they require customized procedures, while the proposed method does not require any modification of the electric drive. With respect to other algorithmic-based solutions for cogging torque reduction, the proposed control technique is scalable to different motor parameters, deterministic, and robust, and hence easy to use and verify for safety-critical applications. As an application case example, the work reports the reduction of the oscillations for the angular position control of a permanent magnet synchronous motor vs. classic PI (proportional-integrative) cascaded control. Moreover, the proposed algorithm is suitable to be implemented in low-cost embedded control units. [ABSTRACT FROM AUTHOR]

This paper discusses nonlinear controller structure design for a synchronous reluctance motor (SynRM). The SynRM is represented with a nonlinear dynamic model. All presented nonlinearities of the SynRM are respected in the controller design procedure. A nonlinear controller policy is used for a SynRM positing system. The nonlinear controller design is based on the chattering alleviation technique for the super-twisted algorithm (STA). The alleviation technique assumes the presence of a fast parasitic dynamic, or fast, actuator. Based on the motor structure, the STA controller is designed only for the mechanical subsystem, where the electrical part presents the parasitic dynamic, and is taken in to account in the chattering suppression procedure. Chattering rejection is based on the STA describing function and harmonic balance equation. The approach allows determination of fast oscillation parameters, such as amplitude and frequency of oscillation. The conditions for the controller parameters' selection are derived with regard to the given oscillation parameters. The derived conditions cover the stability analysis for the STA controller, as well as the stability condition for current controllers and chattering amplitude minimization. The result is confirmed with an example. [ABSTRACT FROM AUTHOR]

This paper presents a robust current tracking controller for permanent magnet synchronous motors (PMSMs) with a performance recovery property for electric power steering (EPS) applications. The contributions of this work are twofold. First, a disturbance observer (DOB) is designed to compensate the disturbances arising from the model–plant mismatches while reducing the closed-loop sensitivity. Second, a current controller is designed to improve the current tracking performance in the frequency domain by assigning the performance recovery property to the closed-loop system. The closed-loop performance is verified through simulations and experiments using a 500 W PMSM connected to an EPS system. [ABSTRACT FROM AUTHOR]