Deadbeat Predictive Current Control Research Articles

Output current harmonic analysis and suppression method for PMSM drive system with modular multilevel converter

AbstractAiming at the output current distortion problem in the low frequency operation of permanent magnet synchronous motor (PMSM) drive system of modular multilevel converter (MMC), the essential relationship between the output current distortion and the injected components is analyzed in this paper. A current harmonic suppression method combining feedforward and feedback compensation is proposed. Firstly, the feedback control method is applied to transform the MMC three‐phase output current into the dq rotating coordinate system at fundamental frequency ω. The harmonics of the AC terms to be suppressed are filtered out. The dominant fundamental frequency component turned into the DC term is retained. Then combined with feedforward control, the control performance of the system is improved. Secondly, the deadbeat predictive current control is improved by introducing an integral link in it. System disturbances caused by parameter changes can be compensated in real time. The design of the control system is simplified and the static error is reduced. Meanwhile, the system has the advantages of small torque pulsation and fast speed response. Finally, the PMSM drive system model of the 11‐level MMC is built in MATLAB/Simulink. The correctness and effectiveness of the proposed suppression method are verified.

An Improved Model-Free Active Disturbance Rejection Deadbeat Predictive Current Control Method of PMSM Based on Data-Driven

This article proposes an improved model-free active disturbance rejection deadbeat predictive current control(ADRDPCC) method for permanent magnet synchronous motor (PMSM) used in more electric aircraft (MEA) based on the data driven method, which is used to solve the parameter mismatch problem of deadbeat predictive current control (DPCC) and improve the performance of PMSM control system. DPCC model applied to the current loop of the MEA motor is established as the main control strategy of the system. The principle of active disturbance rejection control is combined with DPCC, and the ADRDPCC structure is formed to optimize the control strategy. A specific extended state observer (ESO) of ADRDPCC is designed to track the internal disturbance caused by parameter mismatch and the external disturbance in real time. DPCC is used as the control law of the ADRDPCC structure to predict the current and output the reference voltage based on the observation of ESO. A deep reinforcement learning model based on ADRDPCC is designed and trained based on the data-driven method. The trained model can compensate and optimize ADRDPCC based on the disturbance observed by ESO and the observed control state of PMSM. The simulated and experimental results show the superiority of the proposed method.

A Robust DPCC for IPMSM Based on a Full Parameter Identification Method

This paper proposes a robust deadbeat predictive current control (DPCC) method for the interior permanent magnet synchronous motor (IPMSM) based on a full parameter identification method. The DPCC method is innovatively combined with the high frequency (HF) currents injection method, which can observe inductances, flux linkage, and resistance values of the IPMSM online. After the parameter identification results are obtained, the initial crude parameters are replaced by the identification values in the DPCC method to enhance the robustness of the IPMSM control system. Moreover, a novel online accuracy verification method for parameter identification results is proposed to judge the error estimation level. The proposed method extracts the high bandwidth and the high parameter sensitivity characteristic of the DPCC method. The online identification and verification of IPMSM parameters are proceeded subsequently while achieving robust control of the IPMSM with the DPCC method. Finally, the proposed method is experimentally demonstrated with a 1.5kW motor. The experimental results show that the IPMSM with the proposed method can still work well even in the situation of severe initial parameters mismatch.

Fault-tolerant control strategy of six-phase permanent magnet synchronous motor based on deadbeat current prediction.

The fault-tolerant control after phase loss is crucial in the studies of the six-phase permanent magnet synchronous motor (PMSM), and the one phase loss is the most frequent phase loss fault. To improve the system instability caused by nonlinear and time-varying perturbations of inductance parameters in a double-Y phase shifted 30° six-phase PMSM, an improved deadbeat predictive current fault-tolerant control (DPC-FTC) method is proposed in this study. The transformation matrix after single-phase open-phase is first reduced and reconstructed, and the reduced-dimensional voltage equation is derived. Based on this equation, the deadbeat current predictive control is then used to predict the expected voltage using the current feedback value and the reference value, so as to shorten the response time and improve the overall control effect. The voltage equation after parameter perturbation is rewritten, and the current discrete transfer function under constant expected voltage before and after parameter perturbation is calculated. Afterwards, to further improve the low stability of fault-tolerant control after phase loss, which is caused by the inductance parameter perturbation of the control system, the weight coefficient is introduced in order to enhance the deadbeat predictive current control so that it splits and optimizes the direct-quadrature axis current. The stability of the system is then analyzed. By changing the weight coefficient, the fault-tolerant control system has a wider stable working range. Finally, the simulation model and experimental platform are completed. The results show that the improved DPC-FTC method improves the permissible inductor parameter uptake range by a factor of 1/β, reduces the current static difference by 32.05% and 46.02% when the inductor parameter is mismatched by a factor of 2, reduces the current oscillation and effectively reduces the sensitivity of system stability to inductor parameter uptake.

Parameter Robust Deadbeat Predictive Current Control for Open-Winding Surface Permanent Magnet Synchronous Motor Drives

Deadbeat predictive current control (DPCC) of open-winding surface permanent magnet synchronous motor (OW-SPMSM) has excellent dynamic and steady-state performance, but it depends heavily on the accuracy of motor model parameters (resistance, inductance, and flux linkage). To eliminate the influence of parameter mismatch and retain the fast dynamic performance of the traditional DPCC, a parameter robust DPCC for OW-SPMSM drives is proposed in this paper. Firstly, the incremental prediction model of OW-SPMSM is introduced which eliminates the flux linkage parameters in traditional DPCC. Secondly, the parameter sensitivity analysis shows that the mismatch of resistance parameter hardly affects the current prediction errors of incremental prediction model, which are mainly caused by the mismatch of inductance parameters. Finally, to extract the actual inductance information, an inductance extraction strategy is proposed. Experimental results show that the current control performance of the proposed robust DPCC is not influenced by any motor parameter mismatch, which always has smaller current tracking errors and total harmonic distortion (THD) than traditional DPCC. Moreover, compared with the existing robust DPCC with observers, the proposed DPCC has better dynamic response performance.

An Improved Robust Deadbeat Predictive Current Control for the Consequent-Pole Hybrid Excitation Motor

This paper proposes an improved robust deadbeat predictive current control (DPCC) to optimize the current loop control performance of the hybrid excitation motor (HEM) drive system, which is a multi-variable and strongly coupled system. First, the topology and mathematical model of a consequent-pole hybrid excitation machine (CPHEM) are introduced. In order to optimize the current performance of HEM drive system, a DPCC strategy is proposed, followed by a proposed stability analysis method for parameter mismatch. In addition, a robust deadbeat predictive current control (RDPCC) based on extended state observer (ESO) is proposed to suppress the effects of parameter mismatch in DPCC. Furthermore, in the predictive control of HEMs, the divergence of current prediction is caused by certain combinations of controller parameters, which is not resolved by RDPCC. To deal with this issue, the estimation equations of the virtual parameter are introduced into the current prediction of RDPCC. Finally, the effectiveness of proposed control strategy is verified in experiments.

An Improved Modulation Strategy With Torque Ripple Suppression Method for OEW-PMSM Drives With Common DC Bus

The open-end winding permanent magnet synchronous machine drive with common dc bus has zero sequence loop, which inevitably generates the zero sequence current (ZSC). Due to the existence of the third harmonic flux linkage, ZSC causes the zero sequence torque and augments the torque ripple. In this paper, an improved modulation strategy with torque ripple suppression method is presented. Firstly, to reduce the computation burden, a modified alternate sub-hexagonal center pulsewidth modulation (ASHCPWM) strategy is designed. The switching duration time of two inverters can be obtained by the projection of voltage vector on the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">abc</i> coordinate frame. Secondly, a ZSC suppression method based on the time compensation coefficient is adopted for the modified modulation strategy, which can restrain ZSC and reduce torque ripple. Thirdly, to further reduce torque ripple, a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis current injection method is employed in the control scheme. Finally, three methods are presented in simulation and experiments for comparison, namely the deadbeat predictive current control (DPCC) method with conventional ASHCPWM, the DPCC method with sample-averaged zero-sequence current elimination PWM, and the proposed DPCC method with modified ASHCPWM and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis current injection. The results test the effectiveness of the proposed method.

An Improved Deadbeat Predictive Current Control of PMSM Drives Based on the Ultra-local Model

An Improved Deadbeat Predictive Current Control of PMSM Drives Based on the Ultra-local Model

Gaussian Noise Suppression in Deadbeat Predictive Current Control of Permanent Magnet Synchronous Motors Based on Augmented Fading Kalman Filter

Gaussian Noise Suppression in Deadbeat Predictive Current Control of Permanent Magnet Synchronous Motors Based on Augmented Fading Kalman Filter

Parameter-Free Ultralocal Model-Based Deadbeat Predictive Current Control for PMVMs Using Finite-Time Gradient Method

Traditional ultra-local model based predictive current control (UL-PCC) method has strong robustness on current control, however, the UL-PCC still rely on inductance to design the controller gain which really deteriorate its robustness on parameter. To solve it, a parameter free ultra-local model based deadbeat predictive current control (PF-DPCC) method using finite-time gradient method (FGM) is proposed in this paper for permanent magnet vernier motor (PMVM) drives. The UL-PCC is firstly modified considering rotor speed without any extra parameter. Then, the impact of initial controller gain on robustness is analyzed and an extreme low duty-cycle current signal which has negligible impact on current is injected to estimate the controller gain of PF-DPCC adaptively on the basis of the deadbeat concept and the FGM. Hence, all motor parameters are not required in advance and the initial controller gain can be set as 1 directly. Then, the robustness can be effectively improved and the dependence on initial value of controller gain can be eliminated. Finally, the effectiveness and the correctness of the proposed PF-DPCC are experimentally verified on a 400 W PMVM drive platform.

Static-Errorless Deadbeat Predictive Current Control for PMSM Current Harmonics Suppression Based on Vector Resonant Controller

The traditional deadbeat predictive current control (DPCC) is sensitive to the unmodeled disturbances in permanent magnet synchronous motor (PMSM) drives, including alternating current (AC) and direct current (DC) disturbances, which can lead to intolerable current deviations, especially the current harmonics caused by the AC disturbance. To address the problem, a static-errorless DPCC is proposed for the current loop of PMSM drives. In the studied scheme, a vector resonant controller is used in parallel with the control law of the DPCC to compensate for the AC disturbance, while an extended state observer is used to compensate for the DC disturbance. Thus, the studied scheme is robust to both the AC and DC disturbances. The stability of the proposed scheme is systematically analyzed by the Jury criterion, while the parameter tuning is discussed in detail based on the stability analysis. Compared with the traditional DPCC, the studied scheme can effectively eliminate the current deviations to achieve static-errorless current control in PMSM drives. Finally, the effectiveness of the proposed scheme is validated on a 2.2-kW PMSM platform.

Harmonic Current Suppression for Dual Three-Phase PMSM Based on Deadbeat Control and Disturbance Observer

Harmonic currents always exist in a dual three-phase permanent magnet synchronous machine due to the inverter nonlinearity, nonsinusoidal back-electromotive force, and external disturbances. This article proposes a deadbeat predictive harmonic current control (DPHCC) method to suppress the harmonic currents. The DPHCC method can directly calculate the harmonic control voltage based on the sampled harmonic currents and the machine model. Thus, the steady-state and transient-state performance of harmonic current control can be improved. Further, a disturbance observer is designed to avoid the influence of inaccurate machine parameters and other unmodeled disturbances. The observer is designed based on discrete-time sliding mode theory and an improved sliding mode reaching law. The stability of the observer has been analyzed, and the value range of the observer parameters has been determined theoretically. Finally, experimental results have been presented to verify the effectiveness of harmonic current suppression for the proposed control system.

Variable Switching Frequency Deadbeat Predictive Current Control for PMSM with High-Speed and Low-Carrier Ratio

The predictive current control method of permanent magnet synchronous motor has the advantages of fast dynamic response and easy digital implementation, so more attention has been paid to it. When the motor operates in a high-speed condition, the switching frequency is relatively low, the carrier ratio is low, and the rotor angle varies greatly within a control cycle, resulting in a large error in the traditional liner approximation prediction model and inaccuracy of the voltage control quantity calculation, which leads to the deterioration of the predictive current control effect. At the same time, the output harmonic of the three-phase current increases, which affects the stable operation of the motor. In this paper, we study the causes of the large errors in the prediction model based on the traditional linear approximation and phase current fluctuation of the permanent magnet synchronous motor under high speed and low carrier-ratio conditions. Based on the improvement of the prediction model and modulation, a new control strategy of variable switching frequency deadbeat predictive current control is proposed. The control method proposed in this paper improves the dynamic and steady-state performance of the motor, under the condition that the carrier ratio does not increase and reduces the fluctuation of the output current of the motor. Finally, the effectiveness and superiority of the proposed method are verified by an experiment.

A Bidirectional Onboard Charger With Multistep Constant Current Charging Capability

This article realizes a bidirectional onboard charger (OBC) for light electric vehicles (LEVs), with multistep-constant-current (MSCC) charging capability. In this MSCC charging operation, the battery current is reduced during the peak-load hours and resumes the rated charging operation amid the off-peak load hours. Since this MSCC operation is a wide load range operation, the controllers of the front-end converter (FEC) and back-end converter are modified. In this context, a Hermite polynomial-derived functional link neural network (H-FLNN)-based deadbeat predictive current controller (DPCC) is introduced to improve the performance of the FEC of the OBC. Moreover, the HFLNN-based DPCC for the FEC regulates the grid current quality during MSCC and distinct operating conditions such as grid voltage sag and swell, distorted grid voltage, and the presence of dc offset error in the measured grid voltage. A laboratory prototype of a 1.1-kW rating is developed to verify the efficacy of the H-FLNN DPCC to keep the grid current power quality (PQ) within the International Electrotechnical Commission (IEC)-61000-3-2 standard throughout the operation. Moreover, the effectiveness of the design is verified amid the grid voltage sag and swell and distinct operating conditions. The experimental analysis depicts that the rated efficiency of the developed laboratory prototype is 90.18% and the analytical power density is 64.16 W/in3. Furthermore, the vehicle to grid (V2G) operation validates the satisfactory design of OBC for bidirectional operation. At last, the comparison of the presented system with existing systems is given to summarize the advantages of the presented system over the existing systems.

Robust deadbeat predictive current control of induction motor drives with improved steady state performance

AbstractConventional deadbeat predictive current control (DBPCC) based on space vector modulation (SVM) shows quick dynamic responses and a good steady‐state performance in induction motor (IM) drives. However, the motor parameters change during operation due to temperature and saturation changes, leading to inaccurate reference voltage vectors and a degraded performance. Furthermore, conventional DBPCC uses a fixed vector sequence of 0127 over the entire speed range, which results in large current harmonics at high modulation indices. To address the above issues, this paper proposes a robust deadbeat predictive current control (RDBPCC) for IM drives. Based on an ultra‐local model, the proposed method updates the input voltage gain and unknown system components online according to the voltage and current of the previous two control cycles. Because the final control expression contains only the measured stator current and voltage values, the model shows a strong robustness. The steady‐state performance is significantly improved by selecting the optimal vector sequence according to the modulation index based on the principle of current harmonic minimization. The experimental results confirm that, compared with conventional vector control and conventional DBPCC, the proposed method achieves a strong parameter robustness and reduces the current total harmonic distortion (THD) by more than 10% and 20% at high‐modulation indices.

Sliding-Mode-Based Deadbeat Predictive Current Control for PMSM Drives

Deadbeat predictive current control (DPCC) has become a research hotspot for permanent magnet synchronous motor (PMSM) drive systems due to its advantages of short dynamic response time and superior current tracking performance. However, the speed controller in traditional deadbeat current control usually consists of a linear proportional-integral (PI) controller, which cannot quickly limit uncertain disturbances from internal or external sources. Moreover, DPCC is more sensitive to model parameters. In order to reduce the parameter sensitivity of the DPCC method and improve the fast-limiting disturbance capability of the speed controller, a sliding-mode-based deadbeat predictive control method is presented in this article. First, the traditional DPCC is introduced; then, a variable-speed sliding-mode reaching law is designed, and a sliding-mode speed controller is developed using this law to improve the antidisturbance capability of the speed controller. Moreover, in order to suppress the negative impact of the parameter mismatches on the control performance, the parameter mismatches are considered when building the system model, and a sliding-mode-based deadbeat current controller based on the same sliding-mode reaching law as the speed controller is presented. Finally, the experimental results show that the proposed method has a better control performance.

A New Model-Free Deadbeat Predictive Current Control for PMSM Using Parameter-Free Luenberger Disturbance Observer

Deadbeat predictive current control (DPCC) has been widely used in the field of permanent magnet synchronous motor current control due to its fast dynamic response, good current followability, and a small amount of calculation. However, the accuracy of its predictive model depends heavily on the accuracy of motor parameters. When the motor parameters are mismatched due to temperature changes and magnetic saturation during operation, the robustness of its control is greatly reduced. Based on the above reasons, model-free deadbeat predictive current control with Luenberger disturbance observer (MFDPCC-LDO) method is proposed in this article. This method uses the LDO without motor parameters to estimate the total disturbance of the system, then calculates the predictive control voltage combined with the ultralocal model, and performs delay compensation. It only needs the input and output of the system and the determination of three control parameters, and it is not affected by motor parameter mismatch, and internal and external interference. The simulation and experimental results verify the effectiveness of the improved MFDPCC + LDO method.

Predictive Current Control of Sensorless Linear Permanent Magnet Synchronous Motor

In the vector control system of a tubular oscillating permanent magnet synchronous linear motor, it is difficult to obtain accurate feedback information from the conventional mechanical sensors under bad and complex working conditions. This paper presents a new predictive current control designed to estimate the speed of the tubular oscillation permanent magnet synchronous linear motor. It implements two control techniques: The first technique is using the sliding-mode observer’s speed observer for speed estimation. The second is to design a deadbeat predictive current control to replace the PI regulator in the conventional current loop; it solves the difficulties of global optimization and PI parameter setting. The simulation and experimental results show that this method gives a good dynamic performance.

Modified Deadbeat Predictive Current Control Method for Single-Phase AC–DC PFC Converter in EV Charging System

In a single-phase charging system of electric vehicles, the current control performance of the single-phase ac–dc factor correction (PFC) converter with a deadbeat predictive current control (DPCC) method is affected by the distorted grid voltage, parameter dependence, and control delay. To tackle these problems, a modified DPCC method is proposed in this article. By introducing a phase adjustment parameter <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">θ</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> , which can be directly calculated according to the required power factor, into the grid voltage feedforward of the current loop, an improved input current control performance with lower harmonic components and higher power factor can be achieved when the converter operates at unity power factor. At the same time, compared with the traditional method, a reactive power compensation function is added in the modified DPCC and a deadtime compensation method is adopted in the modulation. Finally, a 7.8-kW single-phase PFC converter prototype is built to verify the feasibility and effectiveness of the proposed control method.

Transient Performance Improvement of Deadbeat Predictive Current Control of High-Speed Surface-Mounted PMSM Drives by Online Inductance Identification

This article presents an analytical derivation of transient performance deterioration for high-speed surface-mounted permanent magnet synchronous machine (SPMSM) drives under parameter mismatches, with an advanced deadbeat predictive current control (DBPCC), which exhibits fast dynamics and strong robustness with disturbances rejection. All the influential factors, including permanent magnet flux linkage and inductance mismatches, inverter nonlinearity, and speeds are taken into account in the analysis. It is shown that the transient performance with the advanced DBPCC is only dependent on inductance accuracy. Large transient overshoot and cross-coupling in the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -axis currents at high speeds arise due to inductance mismatch. Based on the understanding gained through the analysis, a novel inductance identification method is also proposed in this article, which significantly improves the transient performance of high-speed SPMSM drives. The proposed online inductance identification method does not require signal injection, is nonintrusive, and can be easily implemented. By integrating the proposed method with the advanced DBPCC, the close-to-ideal deadbeat control can be achieved for high-speed SPMSM drives even in the presence of parameter mismatch and inverter nonlinearity. Both the analysis and proposed method have been validated experimentally on a prototype high-speed (30 000 r/min) SPMSM drive under various conditions.