Performance Evaluation of Two-Vector-Based Model Predictive Current Control of PMSM Drives

Conventional model predictive current control(MPCC)applies only one vector during one control period,which produces large torque and flux ripples and high current harmonics in permanent magnet synchronous motor(PMSM)drives.Recently MPCC with duty cycle control has been proposed to improve the steady state performance by applying one non-zero vector and one null vector during one control period.However,the prior method requires lots of calculations and predictions to find the optimal voltage vectors and calculate their respective duration.Different from prior enumeration-based MPCC,this paper proposes an efficient two-vector MPCC by applying two arbitrary voltage vectors during one control period.The reference voltage vector is firstly calculated based on the principle of deadbeat current control.Two optimal vectors and their duration are then obtained in a very efficient way,which does not require the calculation of current slopes in prior MPCC methods.The proposed method is compared to the state-of-the-art predictive control methods,including conventional MPCC,MPCC with duty cycle control,deadbeat control with space vector modulation(SVM)and modulated model predictive control(M2PC).Both simulation and experimental results prove that the proposed method achieves better steady state performance than conventional MPCC with or without duty cycle and the dynamic response is not degraded.Under the condition of insufficient dc bus voltage,the proposed method outperforms deadbeat control and M2PC by presenting even higher speed range and less torque ripples.

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

Deadbeat predictive current control(DPCC)has been widely applied in permanent magnet synchronous motor(PMSM)drives due to its fast dynamic response and good steady-state performance.However,the control accuracy of DPCC is dependent on the machine parameters’accuracy.In practical applications,the machine parameters may vary with working conditions due to temperature,saturation,skin effect,and so on.As a result,the performance of DPCC may degrade when there are parameter mismatches between the actual value and the one used in the controller.To solve the problem of parameter dependence for DPCC,this study proposes an improved model-free predictive current control method for PMSM drives.The accurate model of the PMSM is replaced by a first-order ultra-local model.This model is dynamically updated by online estimation of the gain of the input voltage and the other parts describing the system dynamics.After obtaining this ultra-local model from the information on the measured stator currents and applied stator voltages in past control periods,the reference voltage value can be calculated based on the principle of DPCC,which is subsequently synthesized by space vector modulation(SVM).This method is compared with conventional DPCC and field-oriented control(FOC),and its superiority is verified by the presented experimental results.

Simulation on model predictive control for PMSM drive system based on double extended state observer

A novel double extended state observer(DESO)based on model predictive torque control(MPTC)strategy is developed for three-phase permanent magnet synchronous motor(PMSM)drive system without current sensor.In general,to achieve high-precision control,two-phase current sensors are necessary for successful implementation of MPTC.For this purpose,two ESOs are used to estimate q-axis current and stator resistance respectively,and then based on this,d-axis current is estimated.Moreover,to reduce torque and flux ripple and to improve the performance of the torque and speed,MPTC strategy is designed.The simulation results validate the feasibility and effectiveness of the proposed scheme.

Double ESOs-based field-oriented control for PMSM drive system with current sensorless

A novel double extended state observers(ESOs)-based field-oriented control(FOC)strategy is developed for three-phase permanent magnet synchronous motor(PMSM)drive systems without any phase current sensor.In principle,two current sensors are essential parts of the drive system for implementation of the feedback to achieve high accuracy control.For this purpose,the double ESOs are created to provide feedback stator currents instead of actual current sensors.The first one of the double ESOs is designed to estimate the benchmark value of q-axis stator current,which is a primary premise;While the second is designed to estimate real-time stator currents of d-axis and q-axis simultaneously.The resultant double ESOs can rapidly and accurately give estimation of the actual currents of a-axis,b-axis and c-axis,and the synthesized double ESOs-based FOC strategy for PMSM drive system without any current sensors has satisfactory control performance and strong robustness.Numerical experiments validate the feasibility and effectiveness of the proposed scheme.