Phase-locked loop (PLL) is commonly used for three-phase grid-connected inverters to obtain the information of grid synchronization, and PLL dynamics are the key factors for stable operation of the inverters. Under weak grid conditions, the coupling between PLL and grid impedance can result in harmonic resonance, or even instability in the system. In this paper, the effect of PLL dynamics and grid impedance on the stability of three-phase grid-connected inverters is studied with d-q impedance model. Besides, the variable transfer relationship is used to analyze the influence of PLL perturbations on output current under weak grid conditions. To suppress low order harmonics of the network current caused by PLL perturbations under weak grid conditions, a novel feed-forward control method is proposed to compensate PLL perturbations and revise the output impedance, where the operation of the inverter and PLL dynamics have been taken into account in the design process. By analyzing the impedance characteristic of the system, it can be demonstrated that the proposed method can enhance the stability of grid-connected inverters under weak grid conditions and reduce the impact of PLL perturbations on grid-connecting current. The experimental results indicate that the low order harmonics of the network current can be suppressed effectively, which verifies the analysis.

The current loop is the key to realizing high-precision permanent magnet synchronous motor (PMSM) drives. However, the performance of the current loop is deteriorated by the dc and ac disturbances. To deal with the problem, this article proposes a discrete-time repetitive control-based active disturbance rejection control (ADRC) for the current loop. The discrete-time repetitive controller is embedded in the control law of the ADRC and operates in parallel with the discrete-time extended state observer (DESO), which is the core of the ADRC. The repetitive controller is designed to compensate for the ac disturbance, while the DESO is designed to suppress the dc disturbance. The stability and antidisturbance capability of the studied scheme are analyzed theoretically in the discrete-time domain, which can guide the tuning of control parameters. Compared with the existing ADRC-based PMSM control schemes, the studied scheme can suppress the dc and ac disturbances simultaneously, thereby improving dynamic- and steady-state performance of the current loop. Finally, the effectiveness of the studied scheme is validated on a 4.4-kW PMSM drive platform.

High-frequency (HF) signal injection methods have been widely employed in the sensorless control of interior permanent magnet synchronous motor (IPMSM) drives from zero to low speed. However, the control performance will be deteriorated severely when the motor subjects to the disturbance. To cope with this issue, an enhanced linear active disturbance rejection control (LADRC) based HF pulse voltage signal injection method is proposed in this paper. The cascaded extended state observer (ESO) is established to guarantee relatively timely and accurate estimation of the total disturbance. The linear control law is generated to compensate for the total disturbance in a feedforward way, which reduces the plant to approximate a canonical first-order integral. The tracking performance and the stability of the enhanced LADRC are analyzed theoretically. MTPA control is adopted to reduce the estimation burden by making full use of the reluctance torque, which help to further improve the tracking performance of the enhanced LADRC. Finally, the validity of the proposed sensorless control scheme is verified on a 2.2-kW IPMSM drive platform.

The prediction accuracy of short-term load forecast (STLF) depends on prediction model choice and feature selection result. In this paper, a novel random forest (RF)-based feature selection method for STLF is proposed. First, 243 related features were extracted from historical load data and the time information of prediction points to form the original feature set. Subsequently, the original feature set was used to train an RF as the original model. After the training process, the prediction error of the original model on the test set was recorded and the permutation importance (PI) value of each feature was obtained. Then, an improved sequential backward search method was used to select the optimal forecasting feature subset based on the PI value of each feature. Finally, the optimal forecasting feature subset was used to train a new RF model as the final prediction model. Experiments showed that the prediction accuracy of RF trained by the optimal forecasting feature subset was higher than that of the original model and comparative models based on support vector regression and artificial neural network.

Motor parameter identification methods mostly depend on the voltage equations, which leads to the unsatisfactory identification effect at low current and low speed operation. This paper proposes a parameter identification method based on the high frequency (HF) equivalent impedance model of permanent magnet synchronous motor (PMSM) with HF signal injection at both the dq-axes. This method identifies the resistance and the dq-axis inductances offline and online, along with the flux linkage online. In order to improve the identification accuracy, the parameter sensitivity analysis (PSA) based algorithm is proposed to detect the resistance and the flux linkage. Meanwhile, the inverter nonlinearities and the HF influence on parameter identification are compensated effectively. In order not to affect the normal operation of PMSM drives, the selection of the amplitude and the frequency of the injected signal is investigated. The proposed method is validated on a 2.2kW motor and confirmed by finite element analysis (FEA). The experimental results show the good identification effect in different operation conditions.

Wireless power transfer (WPT) has attracted a lot of attention these years due to its convenience, safety, reliability, and weather proof features. First and foremost, the consistency of mutual model and T model of loosely coupled transformer (LCT) was deduced. The application scenarios of these two models were then concluded so as to choose suitable model in circuit analysis. Then, a new WPT compensation topology, which is referred to as LC /S compensation topology and consists of one inductor and two capacitors, is proposed. The constant-current-output (CCOut) characteristic of the newly proposed topology is analyzed in detail on the basis of the discussion about LC and CL resonant tank. The equivalent resistance of the rectifier, filter, and resistor circuit is also analyzed to simplify circuit analysis. Then, the current and voltage stress on each component and the system performance under imperfect resonant condition are studied with the help of MATLAB. The LCT is deliberately designed by the finite element analysis software ANSYS Maxwell as well because the coupling coefficient, primary, and secondary self-inductance have a significant impact on system efficiency, power level, and density. The LCT design approach employed in this paper can be extended to magnetic design of almost all WPT systems. Theoretical analyses are verified by both Pspice simulation and practical experiments. Practical output currents with transient loads show an excellent CCOut characteristic of LC/S compensation topology.