Online ISSN
1751-8679
Print ISSN
1751-8660
IET Electric Power Applications
Volume 6, Issue 2, February 2012
Volumes & issues:
Volume 6, Issue 2
February 2012
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- Author(s): F.-J. Lin ; Y.-C. Hung ; J.-C. Hwang ; I.-P. Chang ; M.-T. Tsai
- Source: IET Electric Power Applications, Volume 6, Issue 2, p. 47 –61
- DOI: 10.1049/iet-epa.2011.0153
- Type: Article
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A digital signal processor (DSP)-based probabilistic fuzzy neural network (PFNN) control is proposed in this study to control an in-wheel motor drive using a six-phase permanent magnet synchronous motor (PMSM) for light electric vehicle (LEV). First, the dynamics of LEV and in-wheel motor drive system with lumped uncertainty are described in detail. Then, a feedback linearisation control is designed to control the in-wheel motor drive system. Moreover, a non-linear disturbance observer (NDO) is applied to estimate the lumped uncertainty for the designed feedback linearisation control. However, the system response is degraded by the existed observer error. In order to achieve the required control performance of LEV, the PFNN control is developed for the control of the in-wheel motor drive system. The network structure and its on-line learning algorithm using delta adaptation law of the PFNN are derived. Moreover, a 32-bit fixed-point DSP, TMS320F2812, is adopted for the implementation of the proposed intelligent controlled drive system. Finally, some experimental results are illustrated to show the validity of the proposed PFNN control for in-wheel motor drive system. - Author(s): T.-Y. Chou ; T.-H. Liu ; T.-T. Cheng
- Source: IET Electric Power Applications, Volume 6, Issue 2, p. 62 –72
- DOI: 10.1049/iet-epa.2011.0108
- Type: Article
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62
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This study proposes a new sensorless speed control system for a micro-permanent magnet synchronous motor. Owing to the special characteristics of the micro-permanent magnet synchronous motor, a new rotor position estimator is proposed here. First, by detecting the three-phase zero-current crossing points, a low-resolution of the current position can be detected. Next, by using a Proportional Integral (PI) state estimator, the resolution of the current position can be obviously improved. After that, the deviation voltage between the ideal d-axis voltage and the estimated d-axis voltage is computed to compensate the estimated rotor position. By using the estimated rotor position, the proposed sensorless closed-loop control system, which has good performance including fast transient responses, good load disturbance responses and good tracking responses, can be realised. A digital signal processor, TMS320F28335, is used as a control centre to execute the rotor position estimating algorithm and control algorithm. Experimental results show that the sensorless micro-permanent magnet synchronous motor control system can provide a wide adjustable speed range from 5 to 40 000 r/min with satisfactory performance, which is better than the micro-permanent magnet synchronous motor using an attached 64 pulses/revolution encoder. - Author(s): H. Wang ; Y. Wang ; X. Liu ; J.-W. Ahn
- Source: IET Electric Power Applications, Volume 6, Issue 2, p. 73 –81
- DOI: 10.1049/iet-epa.2010.0229
- Type: Article
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73
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This study presents a novel bearingless switched reluctance motor (SRM) with decoupled torque and suspending stator poles. Different from the conventional bearingless SRM, the suspending poles of the proposed bearingless SRM are separated from the phase torque poles. Perpendicularly placed suspending poles are designed to produce a continuous radial force for rotor bearing. Owing to independently placed suspending and torque poles, the produced suspending force has excellent linearity according to rotor position and independent characteristics of the torque current. The control of air gap is easier than the conventional one from the linear and independent characteristics. In order to verify the proposed structure, the mathematic model for the suspending force is derived. Finite element analysis is also employed to compare with expressions for the suspending force. A prototype motor is designed and manufactured to verify the proposed bearingless structure. - Author(s): A. Weinläder ; W. Wu ; S. Tenbohlen ; Z. Wang
- Source: IET Electric Power Applications, Volume 6, Issue 2, p. 82 –90
- DOI: 10.1049/iet-epa.2011.0122
- Type: Article
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82
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In the context of thermal performance and thermal design, it is of significance to predict the magnitude and the location of the ‘hot-spot’ temperature inside a power transformer. In an attempt to accurately predict this hot-spot in an oil-immersed transformer, various numerical modelling approaches have been developed for calculating the cooling oil flow distribution, which are generally categorised as either ‘network models’ or the methods that incorporate forms of computational fluid dynamics (CFD). In network modelling, the complex pattern of oil ducts and passes in a winding is approximated with a matrix of simple hydraulic channels, where analytical expressions are then applied to describe oil flow and heat transfer phenomena. On the other hand, CFD models often adopt discretisations of much higher fineness, which can be expected to offer a higher order of accuracy but also comes with a large increase in the required computational resources. In order to compare both modelling approaches, the network model implementation TEFLOW and a commercial CFD package, ANSYS-CFX, were applied on a typical ‘zigzag’ oil channel arrangement of a disc-type winding to predict oil flow distribution and disc temperatures; experiments on hydraulic models have also been performed to validate the models. The principle work of this study is then comparing the results and concluding recommendations to industrial practices. - Author(s): S. Roy and L. Umanand
- Source: IET Electric Power Applications, Volume 6, Issue 2, p. 91 –100
- DOI: 10.1049/iet-epa.2010.0294
- Type: Article
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91
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This study presents a novel magnetic arm-switch-based integrated magnetic circuit for a three-phase series–shunt compensated uninterruptible power supply (UPS). The magnetic circuit acts as a common interacting field for a number of energy ports, viz., series inverter, shunt inverter, grid and load. The magnetic arm-switching technique ensures equivalent series or shunt connection between the inverters. In normal grid mode (stabiliser mode), the series inverter is used for series voltage correction and the shunt one for current correction. The inverters and the load are effectively connected in parallel when the grid power is not available. These inverters are then used to share the load power. The operation of the inverters in parallel is ensured by the magnetic arm-switching technique. This study also includes modelling of the magnetic circuit. A graphical technique called bond graph is used to model the system. In this model, the magnetic circuit is represented in terms of gyrator–capacitors. Therefore the model is also termed as gyrator–capacitor model. The model is used to extract the dynamic equations that are used to simulate the system using MATLAB/SIMULINK. This study also discusses a synchronously rotating reference frame-based control technique that is used for the control of the series and shunt inverters in different operating modes. Finally, the gyrator–capacitor model is validated by comparing the simulated and experimental results. - Author(s): H.-T. Tseng and J.-F. Chen
- Source: IET Electric Power Applications, Volume 6, Issue 2, p. 101 –110
- DOI: 10.1049/iet-epa.2011.0151
- Type: Article
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p.
101
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When a transformer is initially energised, its iron core is driven into saturation, which will result in high-amplitude magnetising inrush current. For lessening this transient phenomenon, a voltage compensation-type inrush current limiter (VCT-ICL) is presented in this study. The VCT-ICL can automatically insert high impedance to restrain the sudden change in line current. After completing the restriction of inrush current, the VCT-ICL freewheels, and acts as a short circuit. Thus, other than performing the restriction, the VCT-ICL has a negligible effect in the circuit and the transformer seems to connect directly with the voltage source. When a load is connected at the secondary side of the transformer, to adjust the magnitude of DC reactor current so that it is equal to or higher than the peak of line current, there is almost no distortion to the load voltage and current waveforms during the steady state. A 5 kVA single-phase power transformer is used as an example to demonstrate the performance of the proposed limiter. According to the simulated and experimental results, the feasibility of the VCT-ICL has been verified. Moreover, increasing the insulation levels of the related components in the proposed limiter allows it to be applied in high-voltage distribution transformers. - Author(s): R. Zhong ; Y.B. Wang ; Y.Z. Xu
- Source: IET Electric Power Applications, Volume 6, Issue 2, p. 111 –121
- DOI: 10.1049/iet-epa.2011.0092
- Type: Article
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p.
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Neural network (NN) has been applied as rotor position estimator in switched reluctance motor (SRM) whose characteristic is highly non-linear. However, conventional two inputs back propagate (BP) NN based rotor position estimator is not appropriate for real-time application in high speed operations because of its considerable computational time consumption in its hidden layer. In this study, an improved BP NN with inductance input pretreatment for the rotor position estimator of SRM is proposed. It achieves 75.44% computational burden reduction while staying at the same accuracy as the conventional one. Moreover, with the pretreatment, the NN can output the angle of full electrical period of the SRM operation. Training data includes rotor position, flux-linage which is acquired by finite element analysis (FEA) and phase current Sensorless control algorithm is also described. Simulations and experiments are performed based on a 12/8 SRM. The results are compared with conventional method. The effectiveness of the proposed sensorless estimator and control strategy are testified under low speed, high speed and sudden loading change operations. - Author(s): S. Wu ; Y. Wang ; S. Cheng
- Source: IET Electric Power Applications, Volume 6, Issue 2, p. 122 –132
- DOI: 10.1049/iet-epa.2011.0210
- Type: Article
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An advanced joint optimal reset control (ORC) scheme based on linear principle is proposed for current controls and uncertainties estimations in permanent magnet synchronous motor (PMSM). The joint ORC consists of ORC current controllers and ORC uncertainty observers. It has been proved that the optimal reset law (ORL) of ORC can be obtained by solving algebraic Riccati equations. Based on the ORC theory, the system stability is guaranteed. Owing to the fast convergence of the ORC uncertainty observers, real-time feed-forward compensations of uncertainty terms can be employed in the ORC current control loops to eliminate the uncertainty effects. The joint ORC control scheme can achieve fast dynamic response during the transient process and robustness against uncertainties in the controls of PMSM. Moreover, ORC is as simple and reliable as baseline linear controllers owing to its linear design principle. The proposed ORC is implemented in both simulations and experiments. The performance comparisons and analysis of proportional-integral (PI) controllers, sliding mode controllers (SMC) and the proposed joint ORC are given which show the effectiveness of the joint ORC current control scheme. - Author(s): H.V. Khang and A. Arkkio
- Source: IET Electric Power Applications, Volume 6, Issue 2, p. 133 –142
- DOI: 10.1049/iet-epa.2010.0256
- Type: Article
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133
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A triple-cage circuit of a deep-bar induction motor is numerically identified in the time domain. The parameters are estimated either in the transient state or in the steady state by using a curve-fitting technique. The data used for estimation were obtained from finite-element analysis and measurements using a 37 kW induction motor. The accurate parameters allow the circuit model to well represent the operating motor or predict the performance of the motor. The goodness and limitations of the method are also discussed.
Digital signal processor-based probabilistic fuzzy neural network control of in-wheel motor drive for light electric vehicle
Sensorless micro-permanent magnet synchronous motor control system with a wide adjustable speed range
Design of novel bearingless switched reluctance motor
Prediction of the oil flow distribution in oil-immersed transformer windings by network modelling and computational fluid dynamics
Magnetic arm-switch-based three-phase series–shunt compensated quality AC power supply
Voltage compensation-type inrush current limiter for reducing power transformer inrush current
Position sensorless control of switched reluctance motors based on improved neural network
Optimal reset control design for current control and uncertainties estimation in permanent magnet synchronous
Parameter estimation for a deep-bar induction motor
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