Single-Loop Coordinated Speed Control of Dual PMSM Systems Considering Load Sharing

The multiphase and multilevel motor drives have attracted more and more attention during the last decade since they offered advantages of high-power rating, lower voltage and current stresses in semiconductor switches, higher fault-tolerant ability, compared to the conventional two-level three-phase drives. This paper presents a model predictive current control (MPC) for a T-type three-level inverters fed dual three-phase permanent magnet synchronous motor (PMSM) drives. The key is to propose new space voltage vector synthesis method for voltage vector candidates in MPC scheme of the T-type three-level inverters fed dual three-phase PMSM drives. The proposed scheme can alleviate the computation burden of MPC and suppress the current harmonics induced from inherent property of dual three-phase PMSM. The experimental results are given to verify the validation of the proposed scheme.

To address the issue of speed synchronization deterioration in dual permanent magnet synchronous motor (PMSM) systems under uncertain disturbances, this study proposes a power-law-enhanced nonsingular fast terminal sliding mode (NFTSM) control strategy and introduces an innovative reaching law. This synchronization architecture embeds the enhanced sliding mode algorithm within a cross-coupled control framework, where the redesigned reaching law is specifically tailored to optimize steady-state operating characteristics. For individual motor regulation, an improved deadbeat predictive current control (DPCC) method incorporating a super-twisting sliding mode observer (STSMO) resolves inherent one-step delay limitations and parameter model discrepancies. This observer architecture converts discontinuous control variables into higher-order sliding surface derivatives, significantly mitigating the characteristic chattering phenomenon prevalent in classical first-order sliding mode implementations. The STSMO also adopts a predictive current substitution method to eliminate time-delay effects. Comprehensive simulation analysis shows that compared to traditional PI control, there are significant improvements in three operational aspects: system anti-interference capability, speed trajectory tracking accuracy, and inter-motor synchronization consistency.

In this study, a novel mode l of a Hybrid Electric Vehicle (HEV) based off the 2016 Chevy Volt is implemented and examined. The study will also examine the operation of the modified Series Parallel Hybrid Electric Vehicle (SPHEV) and modeled powertrain components contained within. The 2016 Chevy Volt has six unique modes of operation; however, the dual Permanent Magnet Synchronous Motor (PMSM) EV drive as well as the application of regenerative braking is the area of focus for this initial study. In these modes of interest we will examine the following characteristic outputs of our model: Current in/out of Battery, DC converter low voltage side current, state of charge (SOC) of the battery, Voltage at Both sides of DC-DC converter, Vehicle Torque vs Vehicle Speed and power loss through the DC-DC converter. Observing the simulation results conducted in PSIM10 HEV Design Suite we can support the functionality of the model.

Precise speed synchronization control of dual-motor and multimotor systems is essential in specific industrial applications. This article studies an improved data-driven speed synchronization predictive control (DSSPC) scheme of dual permanent magnet synchronous motors (PMSMs) powered by a five-leg inverter. Based on characteristic modeling theory, an equivalent first-order model is established for current prediction without motor parameter dependence. An improved model predictive control (MPC) with duty cycle adjustment is proposed, considering the switching constraint from the common leg. A new global cost function is formulated for the selection of optimal voltage vectors (VVs) of dual PMSMs. Moreover, a current reference compensation method is introduced to replace the traditional cross-coupling control with constant gain. It can quickly eliminate the synchronization error between dual PMSMs against disturbances. An extensive comparison with experimental tests is conducted between the proposed DSSPC scheme and the existing advanced approaches. The results prove that the proposed DSSPC strategy concurrently mitigates speed synchronization error and tracking error effectively, and with higher robustness against parameter mismatches and external disturbance.

In this paper, the five-leg inverter-dual permanent magnet synchronous motor system is taken as the research object. To solve the problem of large steady-state speed fluctuation when applying the traditional model predictive control strategy, based on the mathematical models of the five-leg inverter and the dual permanent magnet synchronous motor, the causes of the fluctuation are analyzed, and then an improved model predictive control algorithm with error feedback is proposed. The algorithm makes full use of the high-speed operation ability of modern digital processor, and introduces the prediction value of error feedback correction model, so that the rolling optimization is not only based on the model, but also makes full use of the actual value of the feedback state variables. At the same time, the second-order Euler discrete method is used to further improve the model progress. Simulation and experimental results show that the model predictive control strategy with error feedback can effectively improve the steady-state speed control performance of the system while maintaining the dynamic performance of the original system and the decoupling control effect of the two motors.

Multi-phase permanent magnet synchronous motors (PMSM) are widely used in electric vehicles owing to their merits such as high efficiency, high precision and high reliability. This paper presents a novel dual measurement vector injection method (DMVIM) for dual three-phase PMSM using two hall-effect DC link current sensors. The principle of phase current reconstruction method is described as well as the basic driving system of dual three-phase PMSM. The mathematical model of dual three-phase PMSM is established. Then, the DMVIM is presented in detail and the reference voltage vector trajectories of the two windings are analyzed. Furthermore, since the extra voltage vectors are introduced with this method, the compensation algorithms of DMVIM are proposed to modify the reconstruction errors. Both the simulation results and the experimental results validate the proposed DMVIM as well as its compensation algorithms.

This paper presented a vector controlled drives of permanent Magnet Synchronous Motor (PMSM) by using Proportional-Integral (PI) Speed controller based dSPACE implementation. The concept of vector control is applied to PMSM to obtain linear dynamics similar to that of a DC motor. The model consist of two control loops, hysteresis current controller is used for inner loop current control and PI controller for outer loop speed control. PI speed controller selected due to simplicity compare to fuzzy, neutral etc. to make sure dSPACE DS1103 successfully implemented. The PMSM vector control algorithm for a theoretical basic has been verified by experimental results and created a rapid control prototype environment by using MATLAB/ Simulink and the DS1103 DSP of dSPACE.

To solve the problems of slow response speed of the permanent magnet synchronous motor (PMSM) system when the external interference occurs and the poor anti-interference ability, this paper proposes a double model predictive control (MPC) strategy for PMSM to control speed and current. To be specific, firstly, the mathematical model of PMSM is established under the two-phase synchronous rotation coordinate system. Secondly, we propose the double MPC strategy where MPC controller is used in the speed outer loop and deadbeat prediction controller is used in the current inner loop. Finally, By comparing the traditional control strategy (speed outer loop PI controller and current inner loop deadbeat prediction controller) with the double MPC strategy, the simulation results show that the double MPC has no overshot, better steady-state performance, faster dynamic response and stronger anti-load disturbance capability, which proves the effectiveness of the proposed strategy.

A new instantaneous torque-control strategy is presented for high-performance control of a permanent magnet (PM) synchronous motor. In order to deal with the torque pulsating problem of a PM synchronous motor in a low-speed region, new torque estimation and control techniques are proposed. The linkage flux of a PM synchronous motor is estimated using a model reference adaptive system technique, and the developed torque is instantaneously controlled by the proposed torque controller combining a variable structure control (VSC) with a space-vector pulse-width modulation (PWM). The proposed control provides the advantage of reducing the torque pulsation caused by the nonsinusoidal flux distribution. This control strategy is applied to the high-torque PM synchronous motor drive system for direct-drive applications and implemented by using a software of the digital signal processor (DSP) TMS320C30. The simulations and experiments are carried out for this system, and the results demonstrate the effectiveness of the proposed control.

This chapter describes the sliding-mode control of permanent magnet synchronous motor (PMSM) servo systems. The typical structure of the systems consists of the position, velocity, and current control loops. The design of three controllers, position controller, speed controller, and current controller, and a filter in speed loop has been described respectively, aimed at reaching high-performances of PMSM servo systems, such as fast response, strong robustness, and high precision. The digitization of terminal sliding-mode (TSM) controllers of PMSM servo system has been discussed for the purpose of practical implementation.

The field-oriented control (FOC) strategy of a permanent magnet synchronous motor (PMSM) in a simplified form is based on PI-type controllers. In addition to their low complexity (an advantage for real-time implementation), these controllers also provide limited performance due to the nonlinear character of the description equations of the PMSM model under the usual conditions of a relatively wide variation in the load torque and the high dynamics of the PMSM speed reference. Moreover, a number of significant improvements in the performance of PMSM control systems, also based on the FOC control strategy, are obtained if the controller of the speed control loop uses sliding mode control (SMC), and if the controllers for the inner control loops of id and iq currents are of the synergetic type. Furthermore, using such a control structure, very good performance of the PMSM control system is also obtained under conditions of parametric uncertainties and significant variations in the combined rotor-load moment of inertia and the load resistance. To improve the performance of the PMSM control system without using controllers having a more complicated mathematical description, the advantages provided by reinforcement learning (RL) for process control can also be used. This technique does not require the exact knowledge of the mathematical model of the controlled system or the type of uncertainties. The improvement in the performance of the PMSM control system based on the FOC-type strategy, both when using simple PI-type controllers or in the case of complex SMC or synergetic-type controllers, is achieved using the RL based on the Deep Deterministic Policy Gradient (DDPG). This improvement is obtained by using the correction signals provided by a trained reinforcement learning agent, which is added to the control signals ud, uq, and iqref. A speed observer is also implemented for estimating the PMSM rotor speed. The PMSM control structures are presented using the FOC-type strategy, both in the case of simple PI-type controllers and complex SMC or synergetic-type controllers, and numerical simulations performed in the MATLAB/Simulink environment show the improvements in the performance of the PMSM control system, even under conditions of parametric uncertainties, by using the RL-DDPG.

To address the issue of reduced motion accuracy in tracked sandblasting robots caused by nonlinear slippage on steel grit-covered hard surfaces, a hierarchical control framework combining model and data learning is proposed to enhance dual-motor coordination precision and terrain disturbance suppression capability. The inner layer employs a slip-mode control-cross-coupling (SMC-CCC) algorithm, combined with a novel composite approach law, to simultaneously optimize motor tracking error and synchronization error. The outer layer employs a coupled simulation of multi-body dynamics and discrete element method (MBD-DEM) to generate high-fidelity data, which trains a radial basis function neural network (RBFNN) to predict and compensate in real time for slip disturbances caused by track-ground interactions. The standard deviation of dual permanent magnet synchronous motor synchronous error decreased to 1.12, while the standard deviation of tracking error dropped to 7.86. After RBFNN compensation, vehicle lateral deviation was reduced to 70.08 mm—a 92.28% decrease compared to the uncontrolled condition—with slip rate stabilizing between 20% and 25%. In summary, the proposed hierarchical framework effectively addresses motion instability issues beneath steel grit surfaces: SMC-CCC ensures motor coordination precision, while RBFNN achieves adaptive compensation for nonlinear slippage based on MBD-DEM data, providing a viable solution for high-precision motion control in complex terrain.

The doubly fed differential linear active disturbance rejection control (DLADRC) in the speed loop control of permanent magnet synchronous motor (PMSM) produces observation time lag due to the bandwidth impact, which leads to the problem of slower dynamic response and poorer disturbance rejection performance of the system. To solve this problem, a speed controller of PMSM based on series lead correction DLADRC (SLC‐DLADRC) is investigated in this paper. Firstly, the speed loop of PMSM is modeled and the traditional LADRC is reconstructed to obtain DLADRC to improve the control performance of the system. Based on DLADRC, a phase lead correction unit is introduced, and a feedback differential extended state observer based on series lead correction (SLC‐DLESO) is investigated for observing the total disturbance of the system to further improve the system's anti‐disturbance performance. Then, the estimation error analysis of the studied SLC‐DLESO is performed and its stability performance is proved. The stability analysis of the SLC‐DLADRC control strategy is conducted using the Nyquist stability criterion. Finally, MATLAB/Simulink simulation and DSPACE semi‐physical platform are used to verify the effectiveness of the control strategy. Theoretical analyses and experimental results show that, without changing the bandwidth, SLC‐DLADRC not only improves the observation time lag problem but also extends the estimation range of the total disturbance. In the speed loop control of PMSM, the control strategy provides better dynamic response performance and anti‐disturbance under various operating conditions compared to the conventional LADRC and DLADRC.

To improve the dynamic response and disturbance rejection performance of a permanent magnet synchronous motor (PMSM) speed control system, this paper designs a speed control strategy of PMSM based on super-twisting sliding mode corrected differential linear active disturbance rejection (STSM-CDLADRC). First, the speed loop model of a permanent magnet synchronous motor based on traditional LADRC is established. Second, the observer of LADRC is reconstructed according to the principle of error control, and the differential linear extended state observer (DLESO) is obtained. Then, to solve the observation hysteresis problem existing in the DLESO, the phase lead correction unit is introduced, and a corrected DLESO is designed (CDLESO); on this basis, the feedback rate in LADRC is also improved by using the super-twisting sliding mode control algorithm to design the super-twisting sliding mode linear state error feedback rate (STSM-LSEF), which improves the dynamic response performance of the system. Finally, the effectiveness and feasibility of the designed control strategy are verified by MATLAB/Simulink simulation and an experimental platform, and the results show that in the speed control system of the PMSM, the strategy effectively improves the dynamic response performance and anti-disturbance performance of the system.

With the rapid development of power electronic technology and the permanent magnet industry, Permanent Magnet Synchronous Motor (PMSM) is widely used in high-tech industries such as aerospace and transportation with excellent performance. However, PMSM is a time-varying system with multiple variables and strong coupling, making its control strategy rather complex. It is becoming increasingly important to improve the control strategy. Addressing the issues of easy saturation, poor robustness in PI controllers, and the inconvenience of injecting third-harmonic from the outside into the three-phase three-leg topology to enhance torque density, which leads to insufficient control precision in the PMSM servo system, a nonlinear active disturbance rejection controller (NLADRC) is proposed as the control strategy for the third-harmonic injection-based field-oriented control (FOC). Compared to the PMSM servo system without the injection of third-harmonic, the proposed system exhibits better disturbance rejection capability and higher torque density. Through simulations of the PMSM servo system with the injection of third-harmonic, the proposed control strategy is verified to have good response speed and control performance.