A Fast Space-Vector Modulation Algorithm for Multilevel Three-Phase Converters

 

ABSTRACT:

This paper introduces a general space-vector modulation algorithm for -level three-phase converters. The algorithm is computationally extremely efficient and is independent of the number of converter levels. At the same time, it provides good insight into the operation of multilevel converters.

 KEYWORDS:

  1. Digital control
  2. Pulse width modulation
  3. Space vectors

 SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig.1.Types of multilevel converters.

Fig .2.Classification of multilevel modulations.

 EXPECTED SIMULATION RESULTS:

 Fig.3.Normalized line-to-line PWM voltage waveforms for three, four and five-level converters.

CONCLUSION:

This paper has presented a fast new SVM algorithm for multilevel three-phase converters. The algorithm is general and applicable to converters with any number of levels. In addition, the number of steps required to select the nearest three vectors and compute their duty cycles remains the same regardless of the number of converter levels or the location of the reference vector. In addition, the computational efficiency of this algorithm makes it a useful simulation tool for further study of the properties of multilevel converters.

REFERENCES:

[1] L. M. Tolbert and F. Z. Peng, ―Multilevel converters for large electric drives,‖ in Proc. IEEE APEC’98, vol. 2, 1998, pp. 530–536.

[2] Y. Chen, B. Mwinyiwiwa, Z. Wolanski, and B.-T. Ooi, ―Regulating and equalizing dc capacitance voltages in multilevel statcom,‖ IEEE Trans. Power Delivery, vol. 12, pp. 901–907, Apr. 1997.

[3] J.-S. Lai and F. Z. Peng, ―Multilevel converters—A new breed of power converters,‖ IEEE Trans. Ind. Applicat., vol. 32, pp. 509–517, May/June 1996.

[4] P. M. Bhagwat and V. R. Stefanovic, ―Generalized structure of a multilevel PWM inverter,‖ IEEE Trans. Ind. Applicat., vol. IA-19, pp. 1057–1069, Nov./Dec. 1983.

[5] G. Sinha and T. A. Lipo, ―A four level rectifier-inverter system for drive applications,‖ IEEE Trans. Ind. Applicat., vol. 30, pp. 938–944, July/Aug. 1994.

Power Quality and Power Interruption Enhancement by Universal Power Quality Conditioning System with Storage Device

 

ABSTRACT:

In this paper a novel design of Universal Power Quality Conditioning System (UPQS) is proposed which is composed of the DC/DC converter and the storage device connected to the DC link of UPQS for balancing the voltage interruption. The proposed UPQS can balance the reactive power, harmonic current, voltage sag and swell, voltage unbalance, and the voltage interruption. The performance of proposed system was analyzed through simulations with MATLAB\SIMULINK software. The proposed system can improve the power quality at the common connection point of the non-linear load and the sensitive load.

KEYWORDS:

  1. Universal Power Quality Conditioning System (UPQS)
  2. Voltage interruption
  3. DC/DC converter
  4. Super-capacitor

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 

Fig. 1: Configuration of proposed UPQC with energy storage.

 EXPECTED SIMULATION RESULTS:

                  Fig. 2: Nonlinear load current.

Fig. 3: Active and reactive power consumed by load.

    Fig. 4: Voltage sag compensation. (a) Source voltage. (b) Load voltage.

CONCLUSION:

This paper proposes a new configuration of UPQC that consists of the DC/DC converter and the super capacitors for compensating the voltage interruption. The proposed UPQC can compensate the reactive power, harmonic current, voltage sag and swell, voltage unbalance, and the voltage interruption. The control strategy for the proposed UPQC was derived based on the Synchronous reference frame method. The operation of proposed system was verified through simulations with MATLAB/SIMULINK software. The proposed UPQC has the ultimate capability of improving the power quality at the installation point in the distribution system. The proposed system can replace the UPS, which is effective for the long duration of voltage interruption, because the long duration of voltage interruption is very rare in the present power system.

REFERENCES:

[1]        Akagi, H., Y. Kanazawa and A. Nabae, 2007. Instantaneous reactive power compensator comprising switching devices without energy storage components. IEEE Transactions on Industry Application, 20: 625-630.

[2]        Aredes, M., K. Heumann, E.H. Watanabe, 1998. An universal active power line conditioner. IEEE Transactions on Power Delivery, 13(2): 545-551.

[3]        Aredes, M. and E.H. Watanabe, 1995. New control algorithms for series and shunt three-phase four-wire active power Filters. IEEE Transactions on Power Delivery, 10: 1649-1656.

[4]        Arrillaga, J., M.H.J. Bollen, N.R. Watson, 2000. Power quality following deregulation. Proceedings of the IEEE, 88(2): 246-261.

[5]        Bendre, A., S. Norris, D. Divan, I. Wallace, 2003. New high power DC/DC converter with loss limited switching and lossless secondary clamp. IEEE Transactions on Power Electronics, 18(4):1020-1027.

 

Electric Springs—A New Smart Grid Technology

 

ABSTRACT:

The scientific principle of “mechanical springs” was described by the British physicist Robert Hooke in the 1660’s. Since then, there has not been any further development of the Hooke’s law in the electric regime. In this paper, this technological gap is filled by the development of “electric springs.” The scientific principle, the operating modes, the limitations, and the practical realization of the electric springs are reported. It is discovered that such novel concept has huge potential in stabilizing future power systems with substantial penetration of intermittent renewable energy sources. This concept has been successfully demonstrated in a practical power system setup fed by an ac power source with a fluctuating wind energy source. The electric spring is found to be effective in regulating the mains voltage despite the fluctuation caused by the intermittent nature of wind power. Electric appliances with the electric springs embedded can be turned into a new generation of smart loads, which have their power demand following the power generation profile. It is envisaged that electric springs, when distributed over the power grid, will offer a new form of power system stability solution that is independent of information and communication technology.

KEYWORDS:

  1. Distributed power systems
  2. Smart loads
  3. Stability

 SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig. 1. The experimental setup for the electric spring (with control block diagram).

EXPECTED SIMULATION RESULTS:

 Fig. 2. Measured steady-state electric spring waveforms under “neutral” mode. . Va=4.5vac QES=17.5 var, .[Electric spring voltage is near zero.]

Fig. 3. Measured steady-state electric spring waveforms under “capacitive” mode. Va=97.9vac QES=-349.9 var

Fig. 4. Measured steady-state electric spring waveforms under “inductive” mode. Va=94.3vac QES=348.4 var.

                               

Fig. 5. Measured root-mean-square values of the mains voltage vs, noncritical load voltage vo and electric spring voltage va before and after the electric spring is activated. [Electric spring is programmed for voltage boosting function only.]

Fig. 6. Measured power of the critical load and noncritical loads [Electric spring is programmed for voltage boosting function only.]

Fig. 7. Measured root-mean-square values of the critical load (mains) voltage  vs, noncritical load load voltage vo and electric spring voltage va before and after the electric spring is activated. [Electric spring is programmed for both voltage boosting and suppression functions.]

Fig. 8. Measured power of the critical load and smart load. [Electric spring is programmed for both voltage boosting and suppression functions.].

 CONCLUSION:

The Hooke’s law on mechanical springs has been developed into an electric spring concept with new scientific applications for modern society. The scientific principles, operating modes and limits of the electric spring are explained. An electric spring has been practically tested for both voltage support and suppression, and for shaping load demand (of about 2.5 kW) to follow the fluctuating wind power profile in a 10 kVA power system fed by an ac power source and a wind power simulator. The electric springs can be incorporated into many existing noncritical electric loads such as water heaters and road lighting systems [26] to form a new generation of smart loads that are adaptive to the power grid. If many noncritical loads are equipped with such electric springs and distributed over the power grid, these electric springs (similar to the spring array in Fig. 1) will provide a highly reliable and effective solution for distributed energy storage, voltage regulation and damping functions for future power systems. Such stability measures are also independent of information and communication technology (ICT). This discovery based on the three-century-old Hooke’s law offers a practical solution to the new control paradigm that the load demand should follow the power generation in future power grid with substantial renewable energy sources. Unlike traditional reactive power compensation methods, electric springs offer both reactive power compensation and real power variation in the noncritical loads. With many countries determined to de-carbonize electric power generation for reducing global warming by increasing renewable energy up to 20% of the total electrical power output by 2020 [22]–[25], electric spring is a novel concept that enables human society to use renewable energy as nature provides. The Hooke’s law developed in the 17th century has laid down the foundation for stability control of renewable power systems in the 21st century.

 REFERENCES:

[1] Hooke’s law—Britannica Encyclopedia [Online]. Available:

http://www.britannica.com/EBchecked/topic/271336/Hookes-law

[2] A. M. Wahl, Mechanical Springs, 2nd ed. New York: McGraw-Hill, 1963.

[3] W. S. Slaughter, The Linearized Theory of Elasticity. Boston, MA: Birkhauser, 2002.

[4] K. Symon, Mechanics. ISBN 0-201-07392-7. Reading, MA: Addison- Wesley, Reading,1971.

[5] R. Hooke, De Potentia Restitutiva, or of Spring Explaining the Power of Springing Bodies. London, U.K.: John Martyn, vol. 1678, p. 23.

An Adjustable-Speed PFC Bridgeless Buck Boost Converter-Fed BLDC Motor Drive

 

ABSTRACT

This paper presents a power factor corrected (PFC) bridgeless (BL) buck–boost converter-fed brushless direct current (BLDC) motor drive as a cost-effective solution for low-power applications. An approach of speed control of the BLDC motor by controlling the dc link voltage of the voltage source inverter (VSI) is used with a single voltage sensor. This facilitates the operation of VSI at fundamental frequency switching by using the electronic commutation of the BLDC motor which offers reduced switching losses. A BL configuration of the buck–boost converter is proposed which offers the elimination of the diode bridge rectifier, thus reducing the conduction losses associated with it. A PFC BL buck–boost converter is designed to operate in discontinuous inductor current mode (DICM) to provide an inherent PFC at ac mains. The performance of the proposed drive is evaluated over a wide range of speed control and varying supply voltages (universal ac mains at 90–265 V) with improved power quality at ac mains. The obtained power quality indices are within the acceptable limits of international power quality standards such as the IEC 61000-3-2. The performance of the proposed drive is simulated in MATLAB/Simulink environment, and the obtained results are validated experimentally on a developed prototype of the drive.

KEYWORDS:

  1. Bridgeless (BL) buck–boost converter
  2. Brushless direct current (BLDC) motor
  3. Discontinuous inductor current mode (DICM)
  4. Power factor corrected (PFC)
  5. Power quality.

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

 

Fig. 1. Proposed BLDC motor drive with front-end BL buck–boost converter.

EXPECTED SIMULATION RESULTS:

Fig. 2. Steady-state performance of the proposed BLDC motor drive at rated conditions.

Fig. 3. Harmonic spectra of supply current at rated supply voltage and rated loading on BLDC motor for a dc link voltage of (a) 200 V and (b) 50V.

Fig. 4. Dynamic performance of proposed BLDC motor drive during (a) starting, (b) speed control, and (c) supply voltage variation at rated conditions.

Fig. 5. Harmonic spectra of supply current at rated loading on BLDC motor with dc link voltage as 200 V and supply voltage as (a) 90 V and (b) 270 V.

Fig. 6. Steady-state performance of the proposed BLDC motor drive at rated conditions with dc link voltage as (a) 200 V and (b) 50 V.

CONCLUSION

A PFC BL buck–boost converter-based VSI-fed BLDC motor drive has been proposed targeting low-power applications. A new method of speed control has been utilized by controlling the voltage at dc bus and operating the VSI at fundamental frequency for the electronic commutation of the BLDC motor for reducing the switching losses in VSI. The front-end BL buck–boost converter has been operated in DICM for achieving an inherent power factor correction at ac mains. A satisfactory performance has been achieved for speed control and supply voltage variation with power quality indices within the acceptable limits of IEC 61000-3-2. Moreover, voltage and current stresses on the PFC switch have been evaluated for determining the practical application of the proposed scheme. Finally, an experimental prototype of the proposed drive has been developed to validate the performance of the proposed BLDC motor drive under speed control with improved power quality at ac mains. The proposed scheme has shown satisfactory performance, and it is a recommended solution applicable to low-power BLDC motor drives.

REFERENCES

  • L. Xia, Permanent Magnet Brushless DC Motor Drives and Controls. Hoboken, NJ, USA: Wiley, 2012.
  • Moreno, M. E. Ortuzar, and J. W. Dixon, “Energy-management system for a hybrid electric vehicle, using ultracapacitors and neural networks,” IEEE Trans. Ind. Electron., vol. 53, no. 2, pp. 614–623, Apr. 2006.
  • Chen, C. Chiu, Y. Jhang, Z. Tang, and R. Liang, “A driver for the singlephase brushless dc fan motor with hybrid winding structure,” IEEE Trans. Ind. Electron., vol. 60, no. 10, pp. 4369–4375, Oct. 2013.
  • Huang, A. Goodman, C. Gerada, Y. Fang, and Q. Lu, “A single sided matrix converter drive for a brushless dc motor in aerospace applications,” IEEE Trans. Ind. Electron., vol. 59, no. 9, pp. 3542–3552, Sep. 2012.
  • A. Toliyat and S. Campbell, DSP-Based Electromechanical Motion Control. Boca Raton, FL, USA: CRC Press, 2004..

A Comparison of Soft-Switched DC-to-DC Converters for Electrolyzer Application

 

ABSTRACT:

 An electrolyzer is part of a renewable energy system and generates hydrogen from water electrolysis that is used in fuel cells. A dc-to-dc converter is required to couple the electrolyzer to the system dc bus. This paper presents the design of three soft-switched high-frequency transformer isolated dc-to-dc converters for this application based on the given specifications. It is shown that LCL-type series resonant converter (SRC) with capacitive output filter is suitable for this application. Detailed theoretical and simulation results are presented. Due to the wide variation in input voltage and load current, no converter can maintain zero-voltage switching (ZVS) for the complete operating range. Therefore, a two-stage converter (ZVT boost converter followed by LCL SRC with capacitive output filter) is found suitable for this application. Experimental results are presented for the two-stage approach which shows ZVS for the entire line and load range.

 KEYWORDS:

  1. DC-to-DC converters
  2. Electrolyzer
  3. Renewable energy system (RES)
  4. Resonant converters

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. Block diagram of a typical RES.

EXPECTED SIMULATION RESULTS:

Fig. 2. Calculated and simulated results for LCL SRC with capacitive output filter for Vin = 40V. (a) Vin,min = 40V, Vo = 60V, and Id = 40 A. (b) Vin,min = 40V, Vo = 60V, and Id = 20 A. (c) Vin,min = 40V, Vo = 60V, and Id = 4A.

Fig. 3. Simulated results for LCL SRC with capacitive output filter for different operating conditions. (a) Vin,max = 60V and Vo = 60V at full-load and half-load conditions. (b) Vin = 40V and 60V, Vo = 40V, and Id = 10 A.

Fig. 4. Simulation waveforms for LCL SRC with capacitive output filter at full-load (2.4 kW) with Vin = 40V and Vo = 60V: inverter output voltage vab ; current through resonant tank inductor iLr ; switch currents (iS 1 –iS 4 ); rectifier input voltage (vrectin ); voltage across and current through output rectifier diode DR1 .

Fig. 5. Simulation waveforms of Fig. 13 repeated for LCL SRC with capacitive output filter at 10% load with Vin = 40V and Vo = 60V.

 CONCLUSION:

A comparison of HF transformer isolated, soft-switched, dc to- dc converters for electrolyzer application was presented. An interleaved approach with three cells (of 2.4kWeach) is suitable for the implementation of a 7.2-kW converter. Three major configurations designed and compared are as follows: 1) LCL SRC with capacitive output filter; 2) LCL SRC with inductive output filter; and 3) phase-shifted ZVS PWM full-bridge converter. It has been shown that LCL SRC with capacitive output filter has the desirable features for the present application. Theoretical predictions of the selected configuration have been compared with the SPICE simulation results for the given specifications. It has been shown that none of the converters maintain ZVS for maximum input voltage. However, it is shown that LCL-type SRC with capacitive output filter is the only converter that maintains soft-switching for complete load range at the minimum input voltage while overcoming the drawbacks of inductive output

filter. But the converter requires low value of resonant inductor Lr for low input voltage design. Therefore, it is better to boost the input voltage and then use the LCL SRC with capacitive output filter as a second stage. When this converter is operated with almost fixed input voltage, duty cycle variation required is the least among all the three converters while operating with ZVS for the complete variations in input voltage and load. A ZVT boost converter with the specified input voltage (40–60 V) will generate approximately 100V as the input to the resonant converter for Vo = 60V. Therefore, we have investigated the performance of a ZVT boost converter followed by the LCL SRC with capacitive output filter. It was shown experimentally that the two-stage approach obtained ZVS for all the switches over the complete operating range and also simplified the design of resonant converter.

REFERENCES:

[1] A. P. Bergen, “Integration and dynamics of a renewable regenerative hydrogen fuel cell system,” Ph.D. dissertation, Dept. Mechanical Eng., Univ. Victoria, Victoria, BC, Canada, 2008.

[2] D. Shapiro, J. Duffy, M. Kimble, and M. Pien, “Solar-powered regenerative PEM electrolyzer/fuel cell system,” J. Solar Energy, vol. 79, pp. 544–550, 2005.

[3] F. Barbir, “PEM electrolysis for production of hydrogen from renewable energy sources,” J. Solar Energy, vol. 78, pp. 661–669, 2005.

[4] R. L. Steigerwald, “High-frequency resonant transistor DC-DC converters,” IEEE Trans. Ind. Electron., vol. 31, no. 2, pp. 181–191, May 1984.

[5] R. L. Steigerwald, “A Comparison of half-bridge resonant converter topologies,” IEEE Trans. Power Electron., vol. 3, no. 2, pp. 174–182, Apr. 1988.

 

 

 

Micro Wind Power Generator with Battery Energy Storage for Critical Load

 

ABSTRACT:

In the micro-grid network, it is especially difficult to support the critical load without uninterrupted power supply. The proposed micro-wind energy conversion system with battery energy storage is used to exchange the controllable real and reactive power in the grid and to maintain the power quality norms as per International Electro-Technical Commission IEC- 61400-21 at the point of common coupling. The generated micro wind power can be extracted under varying wind speed and can be stored in the batteries at low power demand hours. In this scheme, inverter control is executed with hysteresis current control mode to achieve the faster dynamic switchover for the support of critical load. The combination of battery storage with micro-wind energy generation system (μWEGS), which will synthesize the output waveform by injecting or absorbing reactive power and enable the real power flow required by the load. The system reduces the burden on the conventional source and utilizes μWEGS and battery storage power under critical load constraints. The system provides rapid response to support the critical loads. The scheme can also be operated as a stand-alone system in case of grid failure like a uninterrupted power supply. The system is simulated in MATLAB/SIMULINK and results are presented.

KEYWORDS:

  1. Battery energy storage
  2. Micro-wind energy generating system
  3. Power quality

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig. 1. Scheme of micro-wind generator with battery storage for critical load application.

EXPECTED SIMULATION RESULTS:

 Fig. 2. (a) Source current. (b) Inverter injected current. (c) Load current.

 Fig. 3. (a) Source current. (b) Load current. (c) Inverter-injected current.

Fig. 4. (a) DC link voltage. (b) Rectified current of wind generator.

(c) Current supplied by battery. (d) Charging-discharging of dc link capacitor.

Fig. 5. Source current and source voltage at PCC.

Fig. 6. (a) Source current. (b) FFT of source current.

Fig. 7. (a) Source current. (b) FFT of source current.

Fig. 8. Active and reactive power (a) at source, (b) load, and (c) inverter.

CONCLUSION:

In this project, modeling of bi-directional DC-DC converter is developed for wind energy generation and simulated in MATLAB/SIMULINK. The performance of the bi-directional converter using triangle PWM technique has been analyzed from the prospective of input/output characteristics and harmonic content of output voltage and current. The multi-stage current charging method is used to charge the batteries. At various wind speeds, the system can use the battery for energy storage to keep the load voltage and load current stable. Control strategy and system design can be easily implemented and able to improve the efficiency of wind turbine systems.

 REFERENCES:

[1] Kusiak, A., Zhang, Z. and Li, M.Y. (2010) Optimization of Wind Turbine Performance with Data-Driven Models. IEEE Transactions on Sustainable Energy, 1, 66-76. http://dx.doi.org/10.1109/TSTE.2010.2046919

[2] Tita, I. and Calarasu, D. (2009) Wind Power Systems with Hydrostatic Transmission for

Clean Energy. Environmental Engineering and Management Journal , 8, 327-334.

[3] Quaschning, V. (2005) Understanding Renewable Energy Systems. Earthscan, London.

[4] Kazimierczuk, M.K. and Czarkowski, D. (1993) Application of the Principle of Energy Conservation to Modeling the PWM Converters. Second IEEE Conference on Control Applications , 13-16 September 1993, 291-296. http://dx.doi.org/10.1109/cca.1993.348274

[5] Miao, Z. and Fan, L. (2012) Modeling and Small Signal Analysis of a PMSG Based Wind Generator with Sensor Less Maximum Power Extraction. 2012 IEEE Power and Energy Society General Meeting , 22-26 July 2012, 1-8.

 

Speed Control of BLDC Motor Using Fuzzy Logic Controller Based on Sensorless Technique

ABSTRACT

Brushless dc (BLDC) motors are very popular and are replacing brush motors in numerous applications due to its superior electrical and mechanical characteristics owing to its trouble free construction. This paper presents the BLDC motor sensorless speed control system with fuzzy logic implementation. The sensorless techniques based on the back EMF sensing and the rotor position detection with a high starting torque is suggested. The rotor position is aligned at standstill for without an additional sensor. Also, the stator current can be easily adjusted by modulating the pulse width of the switching devices during alignment which will be helpful to reduce cost and complexity of the drive system without compromising the performance. The design analysis and simulation of the proposed system is done using MATLAB version 2010a and the simulation results of sensored drive using PI controller and sensorless drive using proposed methods are analyzed.

KEYWORDS:

  1. Brushless dc motor
  2. Hall sensored drive
  3. PI controller
  4. Back EMF sensorless drive
  5. Fuzzy controller

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1.Proposed block diagram of sensorless speed control of BLDC motor.

EXPECTED SIMULATION RESULTS:

Fig. 2(a) Variation of Back EMF signal with reference set at 1400 rpm

Fig. 2(b) Variation of stator current with reference set at 1400 rpm.

Fig. 3.Generated pulse from fuzzy logic controller.

Fig. 4(a) Speed response of sensored drive technique using PI controller.

Fig. 4(b) Speed response of sensorless drive technique using PI controller.

Fig. 4(c) Speed response of sensorless drive technique using fuzzy logic controller.

Fig. 5(a) Variation of Electromagnetic torque with reference set at 1400 rpm under sensorless drive using PI controller.

Fig. 5(b) Variation of Electromagnetic torque with reference set at 1400rpm under sensorless drive using fuzzy logic controller.

CONCLUSION

Sensorless speed control of BLDC motor drive with fuzzy logic implementation based on comparator with zero crossing detection have been experimented using MATLAB and evaluation of results are observed. The simulation results have shown that speed response of the BLDC motor can be controlled without sensors and also reduces the torque ripple. The results obtained from sensorless speed control of BLDC motor demonstrates that the system is less cost compared to sensored control and also good dynamic performance is obtained. This makes the motor suitable in application such as fuel pump, robotics and industrial automation. The proposed speed control scheme is robust, efficient and easy to implement in place of sensored applications.

REFERENCES

  • Nobuyuki Matsui, “Sensorless PM Brushless DC Motor Drives”, IEEE Trans. on Industrial Electronics, Vol.43, No.2,pp.300-308, April 1996.
  • P, Somasiri.P, Wipauramonton.P and Nakmahachalasint.P, “Initial Rotor Position Estimation for Sensorless Brushless DC Drives”, IEEE Trans. on Ind. Applications, Vol.45,No.4, pp.1318-1324,July 2009.
  • R, Prasad.P.V.N, Rajkumar.A.D, “Modelling and Simulation of Sensorless Control of PMBLDC Motor Using Zero-Crossing Back EMF Detection” IEEE SPEEDAM 2006 International Symposium on Power Electronics, Drives, Automotive and Motion.
  • Bimal K Bose, “Modern Power Electronics and AC Drives”, Pearson Education Asia
  • T.J.E., “Brushless permanent magnet and reluctance motor drives “, Clarendon Press, Oxford, 1989.

 

FLC-Based DTC Scheme to Improve the Dynamic Performance of an IM Drive

 

ABSTRACT:

This paper presents a fuzzy logic hysteresis comparator-based direct torque control (DTC) scheme of an induction motor (IM) under varying dynamic conditions. The fuzzy logic controller (FLC) is used to adjust the bandwidth of the torque hysteresis controller in order to reduce the torque and flux ripples and, hence, to improve motor dynamic response. The effects of torque hysteresis bandwidth on the amplitude of torque ripples of an IM are also discussed in this paper. Based on the slopes of motor-estimated torque and stator current, an FLC is designed to select the optimum bandwidth of the torque hysteresis controller. This paper also proposes a simpler algorithm than the conventional trigonometric function-based algorithm to evaluate the sector number (required for DTC scheme) of the stator flux-linkage space vector. The proposed algorithm reduces the computational burden on the microprocessor. In order to test the performance of the proposed FLC-based DTC scheme for IM drive, a complete simulation model is developed using MATLAB/ Simulink. The proposed FLC-based DTC scheme is also implemented in real time using DSP board DS1104 for a prototype 1/3 hp motor. The performance of the proposed drive is tested in both simulation and experiment.

KEYWORDS:

1          Direct torque control (DTC)

2          Field-oriented control(FOC)

3          Fuzzy logic controller (FLC)

4          Induction motor (IM)

5          Torque and flux hysteresis controllers

6          Torque ripples

SOFTWARE: MATLAB/SIMULINK

CONVENTIONAL BLOCK DIAGRAM:

 Fig. 1. Conventional DTC scheme for IM drive.

SIMULATION RESULTS:

Fig. 2. Steady-state speed responses of the IM drive for a step change in load from 0.3 to 0.8 N · m at 120 rad/s. (a) Conventional DTC. (b) FLC-based DTC.

Fig. 3. Developed torque responses of the IM drive for a step change in load from 0.3 to 0.8 N · m at speed of 120 rad/s. (a) Conventional DTC. (b) FLC-based DTC scheme.

Fig. 4. Developed torque of the IM drive at 40% of rated load. The step change in speed from 100 to 150 rad/s is applied at 0.15 s. (a) Conventional DTC. (b) FLC-based DTC scheme.

Fig. 5. Steady-state stator flux-linkage responses of the IM drive, at 40% rated load and speed of 120 rad/s. (a) Conventional DTC. (b) Proposed FLCbased DTC scheme.

Fig. 6. Steady-state stator current response of the IM drive at 40% rated load and speed of 120 rad/s. (a) Conventional DTC. (b) FLC-based DTC scheme.

CONCLUSION:

A novel FLC-based DTC scheme for IM drive has been presented in this paper. The proposed FLC-based IM drive has been successfully implemented in real time using DSP board DS1104 for a laboratory 1/3 hp IM. The FLC is used to adapt the bandwidth of the torque hysteresis controller in order to reduce the torque ripple of the motor. A performance comparison of the proposed FLC-based DTC scheme with a conventional DTC scheme has also been provided both in simulation and experiment. Comparative results show that the torque ripple of the proposed drive has considerably been reduced. The dynamic speed response of the proposed FLC-based DTC scheme has also been found better as compared to the conventional DTC scheme.

REFERENCES:

[1] I. Takahashi and T. Nouguchi, “A new quick response and high efficiency control strategy for an induction motor,” IEEE Trans. Ind. Appl., vol. IA- 22, no. 5, pp. 820–827, Sep. 1986.

[2] L. Tang, L. Zhong, M. F. Rahman, and Y. Hu, “A novel direct torque control for interior permanent-magnet synchronous machine drive with low ripple in torque and flux-a speed-sensorless approach,” IEEE Trans. Ind. Appl., vol. 39, no. 6, pp. 1748–1756, Sep./Oct. 2003.

[3] S. Kouro, R. Bernal, H. Miranda, C. A. Silva, and J. Rodriguez, “Highperformance torque and flux control for multilevel inverter fed induction motors,” IEEE Trans. Power Electron., vol. 22, no. 6, pp. 2116–2123, Nov. 2007.

[4] D. Casadei and T. Angelo, “Implementation of a direct torque control algorithm for induction motors based on discrete space vector modulation,” IEEE Trans. Power Electron., vol. 15, no. 4, pp. 769–777, July 2000.

[5] C.-T. Lin and C. S. G. Lee, Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to Intelligent Systems. Upper Saddle River, NJ: Prentice-Hall, 1996.

Adaptive fuzzy controller based MPPT for photovoltaic systems

 

ABSTRACT:

This paper presents an intelligent approach to optimize the performances of photovoltaic systems. The system consists of a PV panel, a DC–DC boost converter, a maximum power point tracker controller and a resistive load. The key idea of the proposed approach is the use of a fuzzy controller with an adaptive gain as a maximum power point tracker. The proposed controller integrates two different rule bases. The first is used to adjust the duty cycle of the boost converter as in the case of a conventional fuzzy controller while the second rule base is designed for an online adjusting of the controller’s gain. The performances of the adaptive fuzzy controller are compared with those obtained using a conventional fuzzy controllers with different gains and in each case, the proposed controller outperforms its conventional counterpart.

KEYWORDS:

  1. PV panel
  2. Adaptive fuzzy controller
  3. Output scaling factor
  4. Fuzzy rules

 SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig.1.Block diagram of the adaptive fuzzy controller.

EXPECTED SIMULATION RESULTS:

Fig. 2.Comparative study under changing atmospheric conditions.

 CONCLUSION:

In this work, an adaptive fuzzy controller is used to track the maximum power point in photovoltaic systems. The gain of the controller is adjusted online by fuzzy rules defined on error and change of error. Simulation results show that the proposed controller can track the maximum power point with better performances when compared to its conventional counterpart. Thus the introducing of an adaptive gain in the structure of conventional fuzzy controllers is well justified.

REFERENCES:

[1] Xiao W, Dunford WG. A modified adaptive hill climbing MPPT method for photovoltaic power systems. In: 35th Annual IEEE Power Electronics, Specialists Conference, Aachen, Germany; 2004. p. 1957–63.

[2] Femia N, Petrone G, Spagnuolo G, Vitelli M. Optimization of perturb and observe maximum power point tracking method. IEEE Trans Power Electron 2004;20(4):16–9.

[3] Kuo YC, Liang TJ, Chen JF. Novel maximum power point tracking controller for photovoltaic energy conversion system. IEEE Trans Ind Electron 2001;48(3):594–601.

[4] Liao CC. Genetic k-means algorithm based RBF network for photovoltaic MPP prediction. Energy 2010;35:529–36.

[5] Hadji S, Krimand F, Gaubert JP. Development of an algorithm of maximum power point tracking for photovoltaic systems using genetic algorithms. In: 7th International Workshop on Systems, Signal Processing and their Applications (WOSSPA); 2011. p. 43–6.

Novel Back EMF Zero Difference Point Detection Based Sensorless Technique for BLDC Motor

ABSTRACT

In this paper a novel position sensorless scheme named Back EMF Zero Difference Point (ZDP) detection has been proposed for six-switch VSI converter fed permanent magnet BLDC motor. This technique is based on the comparison of back EMFs and detection of the points in the back EMF waveforms where they cross each other or in other words they are equal. Commutation point is achieved exactly at the same instant when the difference of back EMFs of any two phases becomes zero. The simulation study has been carried out for the proposed sensorless scheme. The proposed sensorless scheme has the excellent performance from zero to the extra high speed. The method needs no additional delay circuit as used for calculation of commutation point from back EMF ZCP and involves less calculation burden. The method is fault tolerant and accurate even in the case of noise in measurement (or estimation) of phase back EMFs. A nonzero threshold value proportional to input voltage (or reference speed) is used for overcoming the problem due to quantization and sampling for digital implementation. This method proves to be excellent substitute of hall sensing scheme as it also senses at zero speed.

 KEYWORDS:

  1. BLDC motor
  2. Back EMF ZDP
  3. Commutation
  4. Sensorless control
  5. Zero difference point.

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

Fig.1 VSI fed BLDC motor with indirect Back EMF detection scheme

EXPECTED SIMULATION RESULTS:

Fig.2. Phase Back EMF ZDPs, switching signals, counter output and triggering sequence signals.

Fig.3. Steady state operation at the low speed of 600 rpm.

Fig.4. performance of proposed sensorless scheme at 17000 rpm

Fig.5. Noise immune performance during steady state operation for reference speed of 17000 rpm.

Fig.6. sensing fault occurs at 0.5 second in the measurement of phase-B back EMF.

Fig.7. speed increases when sensing fault occurs (here phase-B sensing fault

 

CONCLUSION

In the proposed Back EMF Zero Difference Point (ZDP) detection method, the very first commutation signal is achieved at starting itself i.e. one step before the ZCP method, which proves the superiority of the method. The back EMF for the proposed scheme can be applied to various existing back EMF detection or estimation techniques. This technique is insensitive to the inherent noise in measurement (or estimation) of back EMF. This method does not need extra Circuitry as needed for delay after ZCP for getting commutation point, thereby less computational complexity is involved. The speed (or input voltage) proportional threshold used for avoiding uncertainty in the zero difference of back EMF, sets its scope of wide usability in precise operation from zero to extra high speed. Operation at initial zero back EMF is the main strength of this method and it doesn’t necessitate separate starting techniques. Speed response at transient period is 0.15 ms faster than previous methods for identical motor parameters.

REFERENCES

  • V.Kesava Rao, Department of Electrical technology, IISc Bangalore, ‘‘Brush Contact Drops in DC machines’’, Accepted 25-6-1934, Bangalore Press.
  • S. Jeon, H.S. Mok, G.H. Choe, D.K. Kim, J.S. Ryu, “A New Simulation Model of BLDC Motor with Real Back EMF waveform”, 7 th workshop on Computers in power Electronics , 2000 (COMPEL 2000), page 217- 220.
  • Padmaja yedmale, “Brushless DC (BLDC) Motor Fundamentals”, AN885, 2003 Microchip Technology.
  • Tara , Syfullah Khan Md “Simulation of sensorless operation of BLDC motor based on the zero cross detection from the line voltage” International Journal of Advanced Research in Electrical Electronics and Instrumentation Engineering, vol 2, issue 12 , December 2013, ISSN 2320-3765.
  • R. Frus and B. C. Kuo, “Closed-loop control of step motors using waveform detection,” in Proc. Int. Conf. Stepping Motors and Systems, Leeds, U.K., 1976, pp. 77–84.