• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.468-477
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• 2007

The DTC of voltage source inverter-fed PMSMs is based on hysteresis controllers of torque and flux. It has several advantages, namely, elimination of the mandatory rotor position sensor, less computation time, and rapid torque response. In addition, the stator resistance is the only parameter, which should be known, and no reference frame transformation is required. The DTC theory has achieved great success in the control of induction motors. However, for the control of PMSM drives proposed a few years ago, there are many basic theoretical problems that must be clarified. This paper describes an investigation into the effect of the zero voltage space vectors in the DTC system and points out that if using it rationally, not only can the DTC of the PMSM drive be driven successfully, but torque and flux ripples are reduced and overall performance of the system is improved. The implementation of DTC in PMSM drives is described and the switching tables specific for an interior PMSM are derived. The conventional eight voltage-vector switching table, which is namely used in the DTC of induction motors does not seem to regulate the torque and stator flux in a PMSM well when the motor operates at low speed. Modelling and simulation studies have both revealed that a six voltage-vector switching table is more appropriate for PMSM drives at low speed. In addition, the sources of difficulties, namely, the error in the detection of the initial rotor position, the variation of stator resistance, and the offsets in measurements are analysed and discussed.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.224-234
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• 2008

Multi-phase machines can be used in variable speed drives. Their applications include electric ship propulsion, 'more-electric aircraft' and traction applications, electric vehicles, and hybrid electric vehicles. Multi-phase machines enable independent control of a few numbers of machines that are connected in series in a particular manner with their supply being fed from a single voltage source inverter(VSI). The idea was first implemented for a five-phase series-connected two-motor drive system, but is now applicable to any number of phases more than or equal to five-phase. The number of series-connected machines is a function of the phase number of VSI. Theoretical and simulation studies have already been reported for number of multi-phase multi-motor drive configurations of series-connection type. Variable speed induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. To replace the sensor, information concerning the rotor speed is extracted from measured stator currents and voltages at motor terminals. Open-loop estimators or closed-loop observers are used for this purpose. They differ with respect to accuracy, robustness, and sensitivity against model parameter variations. This paper analyses operation of an MRAS estimator based sensorless control of a vector controlled series-connected two-motor five-phase drive system with current control in the stationary reference frame. Results, obtained with fixed-voltage, fixed-frequency supply, and hysteresis current control are presented for various operating conditions on the basis of simulation results. The purpose of this paper is to report the first ever simulation results on a sensorless control of a five-phase two-motor series-connected drive system. The operating principle is given followed by a description of the sensorless technique.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.4
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• pp.411-419
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• 2005

In this paper, a sliding mode observer for solar array current estimation in the photovoltaic power generation system is presented. The solar array current estimation Information is obtained from the sliding mode observer and fed into the maximum power point tracker to update the reference voltage. The parameter values such as inverter dc link capacitances cm be changed up to 50$\%$ from their nominal values and the linear observer can't estimate the correct state values under the parameter variations and noisy environments. The configuration of sliding mode observer is simple, but it shows the robust tracking performance against parameter variations and modeling uncertainties. In this paper, the method for constructing the sliding mode observer using equivalent control input is presented and the convergence of the proposed observer is verified by the Lyapunov method. The mathematical modeling and the experimental results verify the validity of the proposed method.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.408-411
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• 2009

In this paper, conventional PI, fuzzy neural network(FNN) and adaptive teaming mechanism(ALM)-FNN for rotor field oriented controlled(RFOC) induction motor are studied comparatively. The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. Comparative study of PI, FNN and ALM-FNN are carried out from various aspects which is dynamic performance, steady-state accuracy, parameter robustness and complementation etc. To have a clear view of the three techniques, a RFOC system based on a three level neutral point clamped inverter-fed induction motor drive is established in this paper. Each of the three control technique: PI, FNN and ALM-FNN, are used in the outer loops for rotor speed. The merit and drawbacks of each method are summarized in the conclusion part, which may a guideline for industry application.