Deliang Liang

A Fast Analytical Model for an Integrated Switched Reluctance Starter/Generator

This paper presents a fast analytical modeling method for an integrated switched reluctance starter/generator (SRS/G). This method extends the basic theory of the Chi model and utilizes the first five components of Fourier series in expression of current-dependent arctangent function to express the whole flux linkage model of SRS/G, which could be built with only nine data points at five positions. Then the electromagnetic torque is further calculated from the proposed flux linkage model. The accuracy of the model is verified via comparison with measured flux linkage and torque data. Afterward, the details of simulation model for an integrated 6/4 SRS/G system are presented and the dynamic performances at starting-up and power generating states are predicted. Finally, more experimental results such as phase currents, output dc voltages at different operations and torque-speed characteristics for a 6/4 SRS/G based on a DSP drive platform are also presented to verify the accuracy and rapidity of the proposed method.

Stochastic Coordination of Plug-In Electric Vehicles and Wind Turbines in Microgrid: A Model Predictive Control Approach

To realize the synergy between plug-in electric vehicles (PEVs) and wind power, this paper presents a hierarchical stochastic control scheme for the coordination of PEV charging and wind power in a microgrid. This scheme consists of two layers. Based on the non-Gaussian wind power predictive distributions, an upper layer stochastic predictive controller coordinates the operation of PEV aggregator and wind turbine. The computed power references are sent to the lower layer PEV and wind controllers for execution. The PEV controller optimally allots the aggregated charging power to individual PEVs. The wind controller regulates the power output of wind turbine. In this way, a power balance between supply and demand in a microgrid is achieved. The main feature of this scheme is that it incorporates the non-Gaussian uncertainty and partially dispatchability of wind power, as well as the PEV uncertainty. Numerical results show the effectiveness of the proposed scheme.

Coordinated Predictive Control of DFIG-Based Wind-Battery Hybrid Systems: Using Non-Gaussian Wind Power Predictive Distributions

To improve the wind energy dispatchability in the presence of non-Gaussian wind power uncertainties, this paper presents a stochastic coordinated control scheme for the doubly-fed-induction-generator-based wind-battery hybrid systems (WBHS). The proposed control scheme has a two-layer structure. Based on the non-Gaussian distributional wind power forecasts, an upper layer stochastic predictive controller coordinates the operation of wind and battery subsystems. The computed power references are passed to the lower layer wind and battery controllers for execution. This way, the combined power output of WBHS is brought to the desired dispatch levels. The salient feature of the proposed scheme is that it optimizes the control actions over the non-Gaussian wind power predictive distributions, thus handling the non-Gaussian uncertainties in wind power. The simulation results on actual wind data demonstrate the effectiveness of the proposed scheme.

A complete model characterization of dual three-phase permanent magnet brushless machine for electromechanical servoactuation

This paper looks at the requirements and challenges of designing the Dual Three-Phase Permanent Magnet Brushless Machine (DTPPMBLM) for the driven electromechanical servoactuator (EMA) for aerospace applications. The main goals of the design are a high level of actuator integration in order to minimize weight and volume, fault tolerance, and high reliability. This paper addresses the modeling problem associated with DTPPMBLM with uniform air gaps that operate in a range where magnetic saturation may exist. The mathematical model includes the effects of reluctance variations as well as magnetic saturation to guarantee proper modeling of the system. An experimental procedure is developed and implemented in a laboratory environment to identify the electromagnetic characteristics of the DTPPMBLM in the presence of magnetic saturation. It is demonstrated that the modeling problem associated with this class of the DTPPMBLM can be formulated in terms of mathematically modeling a set of multidimensional surfaces corresponding to the electromagnetic torque function and the flux linkages associated with the machine phase windings. The accuracy of the mathematical model constructed by the developed method is checked against experimental measurements.

Distributed Coordination of Multiple PMSGs in an Islanded DC Microgrid for Load Sharing

For wind-powered dc microgrids working auto-nomously, the available wind generation may be greater than the load demand, and hence, may cause supply–demand imbalance. To address this issue, this paper presents a new distributed load sharing control scheme, which coordinates the operation of multiple permanent magnet synchronous generators (PMSGs) in a dc microgrid. This scheme has a two-layer structure. Based on the distributed model predictive control approach, the upper layer controllers cooperatively optimize the operation of parallel-connected buck converters, which serve as the interfaces between PMSGs and microgrid bus. The optimized power references are sent to the lower layer wind generator controllers for execution. This way, the optimal load sharing among multiple PMSGs is achieved. The salient feature of the proposed scheme is that it optimizes the control actions in a distributed manner, which ensures that multiple PMSGs cooperate, rather than compete, with each other in achieving system-wide objectives. Simulation results verify the effectiveness of the proposed scheme.

Research on loss reduction of dual active bridge converter over wide load range for solid state transformer application

This paper presents the design of new highfrequency transformer isolated bidirectional dc-dc converter modules connected in module-cascaded solid state transformer (SST). A phase-shift dual active bridge (DAB) converter is employed to achieve high-frequency galvanic isolation, bidirectional power flow, and zero voltage switching (ZVS) of all switching devices, which leads to low switching losses even with high-frequency operation. Bidirectional DC-DC converter is crucial to the power transmission in SST. The proposed DAB converter consists of two three-leg bridges and a high-frequency transformer with winding shunting taps. Furthermore, the commutation inductance connected in series with the transformer in the conventional DAB converter is integrated into the transformer windings, thus, enjoying smaller volume and higher power density. By changing the number of primary winding turns, leakage inductance, which is the key parameter in the energy transfer process of DAB converter, can be adjusted on a large scale, enabling the possibility of reducing loss over wide load range. Additionally, time-sharing circuit topology and operation mode are adopted to adapt to the output power by detecting the output current as the feedback. As a result, the efficiency at both light and heavy load can be significantly improved compared with the conventional DAB converter, and, therefore, high efficiency over wide load range and high power density can be achieved. Besides, the additional bridge arm structure along with a flexible control scheme provides possible high-level fault tolerance. Finally, the simulation results on a 2-kW DAB converter module switching at 10kHz are presented to validate the theoretical analysis.

Fault-tolerant performances of switched reluctance machine and doubly salient permanent magnet machine in starter/generator system

The reliability of aeronautic starter/generator system is very important to the safety of aircraft. This paper investigates a starter/generator system with one dual-channel switched reluctance starter/generator and one dual-channel doubly salient permanent magnet starter/generator. By analyzing the mathematic models of two starter-generators considering magnetically coupling between channels and phases, a Matlab/Simulink model is built. To achieve fault-tolerant operations, a speed closed-loop control strategy and a voltage closed-loop control strategy are proposed for motor mode and generator mode, respectively. The dynamic performance of two starter/generators under normal and open-circuit fault conditions are analyzed and compared. Using the proposed approach, the simulated performances are shown to provide reference for further research.

Calculation of flux linkages of the dual-redundancy permanent magnet brushless machine from magnetic circuit model to finite element analysis

Different from the conventional dual-redundancy permanent magnet brushless machine (DRPMBLM), the windings of the novel DRPMBLM were placed in opposite series and driven by two independent sets of power electronic circuits. Thereby an electrical driven system with dual control channels was formed, and a fault tolerated operation mode could be used in this system for high reliability. On the bases of analysing the structure and principle of DRPMBLM, the mathematical model of the magnetic equivalent circuits in each channel winding for DRPMBLM was constructed, and the air gap flux and back electromotive force and the flux matrix which consists of several permeances were derived. The practicability of this model was increased because the effects of the magnetic circuit of yoke flux paths and the nonlinear magnetic saturation were included. The validity of the mathematical model is verified by the results of the finite element analysis.

Preparation of BiFeO3 solution and its movement effects controlled by electrical field

This paper demonstrated our discovery of the movement effect of BiFeO3 nanoparticles in solution by strong electrical polarization. First, BiFeO3 nanoparticles were prepared by ball milling and characterized by SEM. Then, the preparation of BiFeO3 solution was finished. BiFeO3 nanoparticles are found to move in solution due to electrical field. The movement velocity of BiFeO3 nanoparticles, which is about 10 μm·s−1, is influenced and controlled by the applied electrical field. The concentration of BiFeO3 solution and the nanoparticle sizes also have effects on its movement properties. The movement of BiFeO3 nanoparticles in solution is induced by strong polarization, and BiFeO3 nanoparticles have net negative electric charges because of the electrostatic force between BiFeO3 nanoparticles and the negative ions in water resolver.

Finite-Control-Set Model Predictive Control for DFIG Wind Turbines

This paper presents a time efficient finite-control-set model predictive control (FCS-MPC) scheme for the doubly fed induction generator system. In this scheme, the switching states of the rotor side converter are directly taken as control inputs. This way, the optimized control action can be directly applied to the converter. Compared with the existing FCS-MPC approaches, the salient feature of the proposed scheme is the reduction of the computation time. By introducing a set of augmented decision variables, the original intractable binary quadratic programming problem in FCS-MPC can be analytically transformed to a binary linear programming problem, which can be solved efficiently. By this means, the computation time of the proposed scheme is much less than that of the existing schemes. This reduction in computation time enables FCS-MPC with longer prediction horizons, thus yielding better control performance.Note to Practitioners—This paper was motivated by the problem of improving the control performance for the doubly fed induction generator (DFIG). Because of its advantages, such as high energy efficiency, low acoustic noise, variable speed operation, and reduced converter rating, DFIG has emerged as a promising solution for the wind power generation. However, existing DFIG controllers have limitations, such as difficult to tune the parameters, inefficient to handle constraints, and do not consider the discrete operation of the power converters. To overcome these limitations, this paper proposes a new DFIG control scheme based on finite-control-set model predictive control (FCS-MPC), which has the abilities of online optimal control, explicitly handling constraints, and directly generating the switching signals for the power converters. A computationally efficient algorithm is proposed to reformulate the FCS-MPC problem as a linear program, thereby significantly reducing the computational efforts and rendering the proposed scheme more practical for implementation. Simulation results validate the effectiveness of the proposed control scheme. This scheme can be implemented in the field-programmable gate array, which will be our future work.