• Journal of Power Electronics
• /
• v.17 no.4
• /
• pp.1027-1036
• /
• 2017

The brushless doubly-fed induction generator (BDFIG) is a new type of dual stator winding induction generator. In such a generator, both the power winding (PW) and the control winding (CW) are housed in the stator. This paper presents the performance characteristics of a stand-alone BDFIG operation system. A new T-type steady-state model of a BDFIG is proposed. This model is more suitable for the performance analysis of stand-alone BDFIGs than the conventional Π-type steady-state model and the simplified inner core steady-state model. The characteristics of the power flow and CW current are analyzed by detailed mathematical derivations on the basis of the proposed T-type steady-state model. The analysis results are verified by experiments, which are carried out on a prototype BDFIG. The results of the performance analysis contribute to simplifying the control circuit, improving the control performance, and selecting an appropriate BDFIG for actual industrial applications.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.4
• /
• pp.686-692
• /
• 2010

This paper analyzes the effect of the STATCOM on the improvement of the Fault Ride Through (FRT) capability of the fixed speed wind turbines(FSWTs). The steady-state models of the wind farm components, such as induction generator, capacitor bank, and the STATCOM, are developed based on the simplified equivalent circuit. Especially, the STATCOM is modeled as a controllable current source and a method that analytically determines the magnitude of the injection current is developed. For the quasi-steady-state(QSS) analysis, the steady-state model of the generator and STATCOM are merged with the dynamic model of drive train. The QSS simulation with the STATCOM shows that the STATCOM can enhance the FRT performance by improving the $W_r-T_e$ characteristics of the FSWTs.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2008.03a
• /
• pp.187-194
• /
• 2008

Because the types and severities of most engine faults are various and complex, it is not easy that the conventional model based fault detection approach like the GPA(Gas Path Analysis) method can monitor all engine fault conditions. Therefore this study proposed newly a diagnostic algorithm for isolating and diagnosing effectively the faulted components of the smart UAV propulsion system, which has been developed by KARI(Korea Aerospace Research Institute), using the fuzzy logic and the neural network algorithms. A precise performance model should be needed to perform the model-based diagnostics. The based engine performance model was developed using SIMULINK. For the work and mass flow matching between components of the steady-state simulation, the state-flow library was applied. The proposed steady-state performance model can simulate off-design point performance at various flight conditions and part loads, and in order to evaluate the steady-state performance model their simulation results were compared with manufacturer's performance deck data. According to comparison results, it was confirm that the steady-state model well agreed with the deck data within 3% in all flight envelop. The diagnosis procedure of the proposed diagnostic system has the following steps. Firstly after obtaining database of fault patterns through performance simulation, then secondly the diagnostic system was trained by the FFBP networks. Thirdly after analyzing the trend of the measuring parameters due to fault patterns, then fourthly faulted components were isolated using the fuzzy logic. Finally magnitudes of the detected faults were obtained by the trained neural networks. Because the detected faults have almost same as degradation values of the implanted fault pattern, it was confirmed that the proposed diagnostic system can detect well the engine faults.

• Proceedings of the KSME Conference
• /
• 2008.11b
• /
• pp.2070-2075
• /
• 2008

Identification of steady-state is the first step in developing a fault detection and diagnosis (FDD) system. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representing measurements were selected as key features for steady-state detection. The optimized moving window size and the feature thresholds was suggested through startup transient test and no-fault steady-state test. Performance of the steady-state detector was verified during indoor load change test. From the research, the general methodology to design a moving window steady-state detector was provided for vapor compression applications.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2004.03a
• /
• pp.513-520
• /
• 2004

A steady-state/transient performance simulation model was newly developed for the propulsion system of the CRW (Canard Rotor Wing) type UAV (Unmanned Aerial Vehicle) during flight mode transition. The CRW type UAV has a new concept RPV (Remotely Piloted Vehicle) which can fly at two flight modes such as the take-off/landing and low speed forward flight mode using the rotary wing driven by engine bypass exhaust gas and the high speed forward flight mode using the stopped wing and main engine thrust. The propulsion system of the CRW type UAV consists of the main engine system and the duct system. The flight vehicle may generally select a proper type and specific engine with acceptable thrust level to meet the flight mission in the propulsion system design phase. In this study, a turbojet engine with one spool was selected by decision of the vehicle system designer, and the duct system is composed of main duct, rotor duct, master valve, rotor tip-jet nozzles, and variable area main nozzle. In order to establish the safe flight mode transition region of the propulsion system, steady-state and transient performance simulation should be needed. Using this simulation model, the optimal fuel flow schedules were obtained to keep the proper surge margin and the turbine inlet temperature limitation through steady-state and transient performance estimation. Furthermore, these analysis results will be used to the control optimization of the propulsion system, later. In the transient performance model, ICV (Inter-Component Volume) model was used. The performance analysis using the developed models was performed at various flight conditions and fuel flow schedules, and these results could set the safe flight mode transition region to satisfy the turbine inlet temperature overshoot limitation as well as the compressor surge margin. Because the engine performance simulation results without the duct system were well agreed with the engine manufacturer's data and the analysis results using a commercial program, it was confirmed that the validity of the proposed performance model was verified. However, the propulsion system performance model including the duct system will be compared with experimental measuring data, later.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.4 no.2
• /
• pp.209-220
• /
• 1996

In this paper, dynamic performance of 4WD/4WS Electric-driven vehicles is investigated. A coupled dynamic model is introduced for longitudinal, lateral and yawing motion of 4WD/4WS vehicles. Based on the coupled model, dynamic performance is analyzed for steady-state steering, acceleration steering and brake steering, respectively. These non steady-state cornering analysis is important for non-paved road maneuvering, trajectory projection for armored vehicle and future AVCS(Advanced Vehicle Control System) technology. Simulation results are obtained based on a simulink module for the introduced model.

• Journal of the Korean Society for Precision Engineering
• /
• v.22 no.3 s.168
• /
• pp.52-60
• /
• 2005

This paper deals with the position control fur a feed drive system in CNC milling machine, which utilizes a modified error signal for the elimination of steady-state error. A linear time-invariant (LTI) system has consistent properties in response to standard test signal inputs. Those also appear in an error curve acquired from the response. From such properties, constructed is an error model for the position control of the feed drive. And then added is the output of the error model to the current error signal. Consequently the resulting proportional control system brings performance improvement in view of the steady-state error. The effectiveness of the proposed scheme is confirmed through simulations and experiments.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.55 no.11
• /
• pp.483-490
• /
• 2006

When the nonlinearities, such as friction and backlash, are not considered in the controller design, undesirable oscillations can occur in the steady-state response of a control system. This paper deals with a method to reduce oscillations that often appear in the steady-state response of a pendulum system, which is controlled by a state feedback controller based on the linearized system model. With an assumption that the oscillations shown in the steady-state are caused by the Coulomb friction, we improve the performance of stabilization and tracking by estimating and compensating for the Coulomb friction in the pendulum system. Experimental results show that the control performance can be improved sufficiently by the proposed method, when it is applied to an inverted cart pendulum which is a multi-variable unstable system. Furthermore, we could see that the Coulomb friction model used in the estimation of the friction is valid in applying the suggested method.

• Proceedings of the SAREK Conference
• /
• 2008.06a
• /
• pp.282-287
• /
• 2008

Identification of steady-state is the first step in developing a fault detection and diagnosis (FDD) system. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representing measurements were selected as key features for steady-state detection. The optimized moving window size and the feature thresholds was suggested through startup transient test and no-fault steady-state test. Performance of the steady-state detector was verified during indoor load change test. From the research, the general methodology to design a moving window steady-state detector was provided for vapor compression applications.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.34 no.4
• /
• pp.333-339
• /
• 2010

Identification of a steady state is the first step in developing a fault detection and diagnosis (FDD) system of a heat pump. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm, which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representative measurements were selected as key features for steady-state detection. The optimized moving-window size and the feature thresholds were decided on the basis of a startup-transient test and no-fault steady-state test. Performance of the steady-state detector was verified during an indoor load-change test. In this study, a general methodology for designing a moving-window steady-state detector for applications involving vapor compression has been established.