Finite-control-set model predictive current control (FCS-MPCC) always has large steady-state fluctuation and computational burden. In this paper, a novel FCS-MPCC without a modulator to drive permanent magnet synchronous hub motors (PMSHMs), which combines virtual vectors expansion scheme and duty cycle control was proposed. The lack of a modulator reduces the complexity of the control system. The virtual vectors are synthesized by using active vectors, which improve the accuracy of voltage selection, and further improve PMSHM's steady-state performance and reduce current harmonics. The duty cycle control uses a zero vector to obtain better steady-state performance. However, the duty cycle of the virtual vectors is limited by the synthesis method, and further analysis is needed. A new calculation process is proposed to reduce the amount of calculation. The deadbeat principle is used to get reference voltage which determines sectors. Then, the best voltage vector in the selected sector is determined by the predetermined cost function. The traditional MPCC and the duty cycle MPCC (DCMPCC) are used as a comparison item to compare with the proposed method to illustrate its effectiveness. Results confirm that improved MPCC has good steady-state performance while maintaining a fast dynamic response.

Improved Finite-Control-Set Model Predictive Control With Virtual Vectors for PMSHM Drives

Permanent magnet synchronous motors (PMSMs) have been widely employed in the industry. Finite-control-set model predictive control (FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the holistic PMSM drive systems. Based on the three elements of model predictive control, this paper provides an overview of the superiority of the FCS-MPC control scheme and its shortcomings in current applications. The problems of parameter mismatch, computational burden, and unfixed switching frequency are summarized. Moreover, other performance improvement schemes, such as the multi-vector application strategy, delay compensation scheme, and weight factor adjustment, are reviewed. Finally, future trends in this field is discussed, and several promising research topics are highlighted.

Finite-Control-Set Model Predictive Control of Permanent Magnet Synchronous Motor Drive Systems—An Overview

This article represents modified model reference adaptive system (MRAS) method for speed sensorless control of interior permanent magnet synchronous motor (IPMSM), which can estimate rotor speed and position information. To suppress the adverse effect of parameter variation on control performance, the stator resistance and the permanent magnet flux linkage are estimated and continuously updated in reference and adjustable model. Then, proportional-integral (PI) controller parameters of speed adaptive law obtained by MRAS are optimized by gray wolf optimization (GWO) algorithm. To get the smallest possible speed following error and reference current error, the objective function is designed with discretized rotor speed error and current error as variables. The simulation results show the better performance of rotor speed estimation is obtained with GWO algorithm. 

Speed Sensorless Control for IPMSMs Using a Modified MRAS With Gray Wolf Optimization Algorithm

Permanent magnet synchronous motors (PMSMs) have been widely employed in the industry. Finite-control-set model predictive control (FCS-MPC), as an advanced control scheme, has been developed and applied to improve the performance and efficiency of the holistic PMSM drive systems. Based on the three elements of model predictive control, this paper provides an overview of the superiority of the FCS-MPC control scheme and its shortcomings in current applications. The problems of parameter mismatch, computational burden, and unfixed switching frequency are summarized. Moreover, other performance improvement schemes, such as the multi-vector application strategy, delay compensation scheme, and weight factor adjustment, are reviewed. Finally, future trends in this field is discussed, and several promising research topics are highlighted. 

This article presents a new scheme to extract the rotor position angle of interior permanent magnet synchronous motors using a high-frequency signal injection method with an iterative strategy. An iterative strategy based on the binary principle is proposed to reduce the computational burden using discrete rotor position angles. These discrete rotor position angles are obtained from the angle space, which is divided into several separate sectors and employed to calculate the defined cost function that generates the optimal rotor position angle. With the number of iterations increasing, the accuracy of the iterative search strategy will increase geometrically. Finally, a series of experimental tests have been carried out to compare the performances of the proposed and the conventional low-speed sensorless methods. Experimental results have verified the effectiveness of the proposed low-speed sensorless scheme.

Finite Position Control of Interior Permanent Magnet Synchronous Motors at Low Speed

As an efficient control strategy, model predictive current control (MPCC) has rapid response and simple calculation. This article proposes an improved MPCC scheme for permanent-magnet synchronous hub motor (PMSHM) drives. The mentioned control scheme uses the parameter values at the last moment to obtain the back electromotive force (EMF) and utilizes the obtained back EMF to obtain the predicted current value at the next moment. In the actual application of the motor, to enhance the robustness of the control system, a sliding mode controller is used to replace the conventional proportional-integral (PI) speed loop, and a finite position phase-locked loop based on the dichotomy is added to achieve sensorless speed control and provide an accurate rotor position angle. To improve the steady-state performance, the method of duty cycle is introduced, and the null vector and the actual vector are used together in the same control cycle. The simulation and experimental results both show the effectiveness of the proposed MPCC scheme, and the steady-state performance of MPCC is greatly improved compared with traditional MPCC.

Speed Sensorless Model Predictive Current Control Based on Finite Position Set for PMSHM Drives

The invention discloses a tracking control method for an extension vehicle speed self-adaptive change trajectory of an intelligent automobile. The method includes the following steps: step S1. establishing a two-degree-of-freedom transverse dynamic model; step S2. establishing a longitudinal kinematics model; step S3. establishing a three-degree-of-freedom longitudinal and transverse coupling dynamic model, and a preview deviation expression; step S4. designing an upper layer extension controller; step S5. designing a lower layer transverse deviation tracking controller; step S6. establishinga speed self-adaptive driving expert knowledge base; and step S7. designing a lower layer speed extension controller. A longitudinal speed self-adaptive driving expert knowledge base and the extensioncontroller are added in trajectory tracking control of the control method, the trajectory tracking accuracy of the intelligent automobile is improved when the intelligent automobile passes through complex roads, and the efficiency, safety and comfortableness of vehicles during cornering are improved.

Tracking control method for extension vehicle speed self-adaptive change trajectory of intelligent automobile

A hydro-mechanical hybrid transmission device and a control method thereof, including an input shaft 1, a split mechanism 2, a hydraulic transmission assembly 3, a mechanical transmission assembly 4, a convergence mechanism 5, and an output shaft 6. The input shaft is connected, through the split mechanism, to the hydraulic transmission assembly and the mechanical transmission assembly that are connected in parallel. The hydraulic transmission assembly and the mechanical transmission assembly are each connected to the output shaft through the convergence mechanism. The split and convergence mechanisms are planetary gear systems and the hydraulic transmission assembly comprises a unidirectional variable pump 33 and a unidirectional quantitative motor 35.

Zhen Zhu

Papers

Speed Sensorless Model Predictive Current Control Based on Finite Position Set for PMSHM Drives

Tracking control method for extension vehicle speed self-adaptive change trajectory of intelligent automobile

Hydro-mechanical hybrid transmission device and control method thereof