Anwen Shen

An LTCL Filter for Three-Phase Grid-Connected Converters

This paper presents a new high-order filter for three-phase grid-connected voltage source converters (VSCs) named the inductor-trap-capacitor-inductor (LTCL) filter, in which multiple LC trap filters are inserted in parallel with the branch of the capacitor in the traditional LCL filter to compose multiple series resonant circuits at the selected frequencies. Particularly, the LTCL filter can attenuate the harmonic currents around the multiples of switching frequencies and guarantee -60 dB/decade attenuation in the high-frequency band, leading to a decrease of the total inductance and volume. Furthermore, within half of the switching frequency range, an LTCL -filter-based grid-connected VSC has almost the same frequency-response characteristic as that with the traditional LCL filter. That is to say, the LTCL filter does not bring any extra control difficulties. The basic parameter selection criteria and the parameter design procedure of the LTCL filter are introduced. Moreover, the sensitivity analysis of the LTCL filter is analyzed and discussed in detail. The comparative analysis and discussion considering the LCL filter, the LLCL filter, the multituned traps filter, and the proposed LTCL filter, have been presented and evaluated through the experiments on a 65-kW three-phase grid-connected VSC prototype.

PMSM Sensorless Control by Injecting HF Pulsating Carrier Signal Into Estimated Fixed-Frequency Rotating Reference Frame

For permanent-magnet synchronous machines (PMSMs) sensorless control, the widely employed high-frequency (HF) pulsating carrier signal injection method is based on tracking the rotor saliency. It may face the problems of long convergence time, potential start-up failure, and limited system stability. Different from the conventional schemes, the proposed strategy is a direct estimation method. In which, a HF pulsating carrier voltage is injected into the estimated fixed-frequency rotating reference frame other than the estimated synchronous reference frame (SRF). With this approach, spatial saliency tracking observer, which is necessary in the conventional sensorless control, is removed to simplify the control structure and improve the system stability. Furthermore, the rotor position information is directly obtained from the response of injected HF pulsating carrier signal, which can avoid potential convergence failure of tracking observer. In addition, the compensation of system delays existing in the proposed sensorless control strategy is deduced to improve the accuracy of rotor position estimation. For magnetic polarity detection, a new method which has the advantages of high signal-to-noise ratio and low vibration is also investigated. Finally, the experimental results on a PMSM indicate that the rotor position with good steady state and dynamic performance can be obtained accurately with the proposed sensorless control strategy.

ANN Based on IncCond Algorithm for MPP Tracker

In photovoltaic (PV) generation systems, to get the maximum of the solar output power is the essential part to raise the efficiency of the whole system. A new Artificial Neural Network (ANN) based algorithm for Maximum Power Point Tracking (MPPT) has been proposed in this work. By using the duty ratio data generated from the finest results of the traditional Incremental Conductance (IncCond) method as the neural network training data, and building the DC-DC boost tracker to test it in Saber simulation software, the simulation results are shown to clarity the effectiveness of the proposed method.

Multi-parameter estimation of non-salient pole permanent magnet synchronous machines by using evolutionary algorithms

This paper describes how to apply evolutionary algorithms (EA) for multi-parameter estimation of non-salient pole permanent magnet synchronous machines (PMSM). The encoding of estimated parameters is firstly described and the design of a penalty function associated with a proposed error analysis for PMSM multi-parameter estimation is then introduced. The PMSM stator winding resistance, dq-axis inductances and rotor flux linkage can be estimated by maximizing the proposed penalty function through evolutionary algorithms such as immune clonal algorithm (ICA), quantum genetic algorithm (QGA) and genetic algorithm (GA). The experimental results show that the proposed strategy has good convergence in simultaneously estimating winding resistance, dq-axis inductances and rotor flux linkage. In addition, the convergence speed of ICA in estimation is compared with GA and QGA, which verifies that the ICA has better performances in global searching. The ability of proposed method for tracking the parameter variation is verified by winding resistance step change and temperature variation experiments at last.

Influence of inverter nonlinearity on parameter estimation in permanent magnet synchronous machines

This paper investigates the influence of inverter nonlinearity on the parameter estimation in permanent magnet synchronous machines (PMSM). An estimator based on model reference adaptive system (MRAS) is firstly described for simultaneously estimating the stator winding resistance and rotor flux linkage, together with injection of a pulse of id<0 which is required for activating the estimation of stator winding resistance. Then the MRAS estimator with/without the inverter nonlinearity compensation is applied to a prototype surface-mounted PMSM for experimental investigation. It shows that at low speed the inverter nonlinearity compensation has significant influence on both the rotor flux linkage and winding resistance estimation, while at high speed it has only significant influence on the winding resistance estimation but negligible influence on the rotor flux linkage estimation.

Detection and reduction of middle frequency resonance for industrial servo

A novel method for middle frequency resonance detection and reduction is proposed for industrial servo system. Defects of traditional resonance reduction method based on adaptive notch filter in middle frequency range are analyzed and summarized as the difference between the resonance frequency and the oscillation frequency. A self-tuning low-pass filter is introduced in the speed feedback path, whose corner frequency is determined by FFT results and several self-tuning rules. With the proposed method the effective range of the adaptive filter is extended across the middle frequency range. Simulation and Experiment results show that the frequency detection is accurate and resonances during the speed steady states and dynamics are successfully reduced.

Systematic Design of the Hybrid Damping Method for Three-Phase Inverters With High-Order Filters

High-order filters (HO-filters) such as LCL-LC-filters have recently drawn attention to their small size and better attenuation to switching harmonics than LCL -filters for three-phase inverter grid interfaces. Hybrid damping that combines passive damping and active damping is an effective method to suppress HO-filter resonances. However, due to the high-order characteristic of the system, the tuning procedure for the parameters of hybrid damping is complicated. Hence, an equivalent circuit analysis method is proposed in this paper to accurately simplify the model of the HO-filter. Based on this, a systematic step-by-step design method for HO-filter-type grid-connected inverters with hybrid damping has been proposed. The passive losses, effects of equivalent series resistances (ESRs) and robustness against grid impedance variation have been studied. Compared with existing design procedures, the proposed method makes the hybrid damping more reliable by locating appropriate position for closed-loop resonant poles. Experimental results verify the proposed systematic design procedure.

Initial rotor position estimation and sliding preventing for elevators with surface-mounted PMSMs

Improved methods of initial rotor position estimation and sliding prevention are presented in this paper for elevators with surface-mounted permanent magnet synchronous machines (SPMSMs). In contrast to most of the existing literature, in this paper, estimation errors caused by stator resistance and dead time are analysed in detail. The improved estimation method can reduce the errors greatly without dead-time compensations and knowledge of motor parameters. Besides, an observer-based feedforward compensation of load torque is introduced to elevator applications to prevent sliding during the starting process. Since the torque observer is widely used in other motor applications, we focus on the impact caused by the change in inertia. Finally, a series of experiments are performed on a testing system with two 13.4 kW SPMSMs and drivers to illustrate the effectiveness and improvement of the method.

An Improved Phase Disposition SPWM Strategy for Cascaded Multilevel Inverter

The Carrier Phase Shifted (CPS) strategy is conventional for cascaded multilevel inverter, because it can naturally ensure all cascaded cells to output balanced power. However, in point of spectra of the output line voltage, CPS is suboptimal to Phase Disposition (PD) strategy, because the latter can not naturally ensure power balance. This paper presents an improved PD strategy, inspiration from the disposition of CPS strategy triangle carriers. Just reconstructing the triangle carriers of PD strategy, it can not only reserve the waveform quality of the line voltage to be optimal, but also naturally ensure the output power of each cascaded cells to be balanced.

Research of a self-tuning algorithm for industrial micro-grid power conversion

With more and more attention on the grid current harmonic in recent years, many control schemes of the Pulse Width Modulation Voltage Source Converter PWM-VSC have been investigated. Conventional PI controller has limitations in sensitivity subject to load and system parameter variation. Even the stability of the system can be threatened under a large and sudden load change. In this paper, the practical situation of a VSC for industrial Micro Grid MG is considered and an Artificial Neural Network ANN based control method is employed to solve the problem. Meanwhile, an online parameter tuning algorithm is introduced for its advantage of self-tuning and system character identification. The proposed control scheme is verified through simulation and prototype experiment. The experiment is performed to demonstrate the advantages of the proposed controller under different situations.