Single Stage Solar PV Fed Brushless DC Motor Driven Water Pump

ABSTRACT:

In order to optimize the solar photovoltaic (PV) generated power using a maximum power point tracking (MPPT) technique, a DC-DC conversion stage is usually required in solar PV fed water pumping which is driven by a brushless DC (BLDC) motor. This power conversion stage leads to an increased cost, size, complexity and reduced efficiency. As a unique solution, this work addresses a single stage solar PV energy conversion system feeding a BLDC motor-pump, which eliminates the DC-DC conversion stage. A simple control technique capable of operating the solar PV array at its peak power using a common voltage source inverter (VSI), is proposed for BLDC motor control. The proposed control eliminates the BLDC motor phase current sensors. No supplementary control is associated for the speed control of motor-pump and its soft start. The speed is controlled through the optimum power of solar PV array. The suitability of proposed system is manifested through its performance evaluation using MATLAB/Simulink based simulated results and experimental validation on a developed prototype, under the practical operating conditions.

KEYWORDS:

1.      MPPT

2.       Solar PV array

3.      BLDC motor

4.       Water pump

5.      VSI

6.      Soft starting

7.      Speed control

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1 Proposed water pumping based on a single stage solar PV energy conversion system.

 EXPECTED SIMULATION RESULTS:

 Fig.2 Steady state and starting performance of (a) PV array and (b) motor pump, of proposed system at 1 kW/m².

Fig.3 Steady state and starting response of (a) PV array and (b) motor-pump, of proposed system at 200 W/m².

Fig.4 Dynamic performance of (a) PV array and (b) BLDC motor Pump ,of Proposed  water pumping system.

Fig. 5 Responses of (a) PV array and (b) BLDC motor, under partial shading

CONCLUSION:

The proposed BLDC motor driven water pumping based on a single stage solar PV generation has been validated through a demonstration of its various steady state, starting and dynamic performances. The system has been simulated using the MATLAB toolboxes, and implemented on an experimental prototype. The topology of the proposed system has provided a DC-DC converter-less solution for PV fed brushless DC motor driven water pumping. Moreover, the motor phase current sensing elements have been eliminated, resulting in a simple and cost-effective drive. The other desired functions are the speed control without any additional circuit and a soft start of the motor-pump. A detailed comparative analysis of the proposed and the existing topologies has ultimately manifested the superiority of the proposed work.

REFERENCES:

[1] C. Jain and B. Singh, “An Adjustable DC Link Voltage Based Control of Multifunctional Grid Interfaced Solar PV System,” IEEE J. Emerg. Sel. Topics Power Electron., Early Access.

[2] A. A. A. Radwan and Y. A. R. I. Mohamed, “Power Synchronization Control for Grid-Connected Current-Source Inverter-Based Photovoltaic Systems,” IEEE Trans. Energy Convers., vol. 31, no. 3, pp. 1023-1036, Sept. 2016.

[3] P. Vithayasrichareon, G. Mills and I. F. MacGill, “Impact of Electric Vehicles and Solar PV on Future Generation Portfolio Investment,” IEEE Trans. Sustain. Energy, vol. 6, no. 3, pp. 899-908, July 2015.

[4] A. K. Mishra and B. Singh, “A single stage solar PV array based water pumping system using SRM drive,” IEEE Ind. Appl. Soc. Annu. Meeting, Portland, OR, 2016, pp. 1-8.

[5] S. Jain, A.K. Thopukara, R. Karampuri and V.T. Somasekhar, “A Single-Stage Photovoltaic System for a Dual-Inverter-Fed Open-End Winding Induction Motor Drive for Pumping Applications,” IEEE Trans. Power Electron., vol. 30, no. 9, pp. 4809 - 4818, Sept. 2015.

BLDC Motor Driven Solar PV Array Fed Water Pumping System Employing Zeta Converter

ABSTRACT:

This paper proposes a simple, cost effective and efficient brushless DC (BLDC) motor drive for solar photovoltaic (SPV) array fed water pumping system. A zeta converter is utilized in order to extract the maximum available power from the SPV array. The proposed control algorithm eliminates phase current sensors and adapts a fundamental frequency switching of the voltage source inverter (VSI), thus avoiding the power losses due to high frequency switching. No additional control or circuitry is used for speed control of the BLDC motor. The speed is controlled through a variable DC link voltage of VSI. An appropriate control of zeta converter through the incremental conductance maximum power point tracking (INC-MPPT) algorithm offers soft starting of the BLDC motor. The proposed water pumping system is designed and modeled such that the performance is not affected under dynamic conditions. The suitability of proposed system at practical operating conditions is demonstrated through simulation results using MATLAB/ Simulink followed by an experimental validation.

KEYWORDS:

1.      BLDC motor

2.      SPV array

3.      Water pump

4.      Zeta converter

5.      VSI

6.      INC-MPPT

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1 Configuration of proposed SPV array-Zeta converter fed BLDC motor drive for water pumping system.

 EXPECTED SIMULATION RESULTS:

Fig.2 Performances of the proposed SPV array based Zeta converter fed BLDC motor drive for water pumping system (a) SPV array variables, (b) Zeta converter variables, and (c) BLDC motor-pump variables.

CONCLUSION:

The SPV array-zeta converter fed VSI-BLDC motor-pump for water pumping has been proposed and its suitability has been demonstrated by simulated results using MATLAB/Simulink and its sim-power-system toolbox. First, the proposed system has been designed logically to fulfil the various desired objectives and then modelled and simulated to examine the various performances under starting, dynamic and steady state conditions. The performance evaluation has justified the combination of zeta converter and BLDC motor drive for SPV array based water pumping. The system under study availed the various desired functions such as MPP extraction of the SPV array, soft starting of the BLDC motor, fundamental frequency switching of the VSI resulting in a reduced switching losses, reduced stress on IGBT switch and the components of zeta converter by operating it in continuous conduction mode and stable operation. Moreover, the proposed system has operated successfully even under the minimum solar irradiance.

REFERENCES:

[1] M. Uno and A. Kukita, “Single-Switch Voltage Equalizer Using Multi- Stacked Buck-Boost Converters for Partially-Shaded Photovoltaic Modules,” IEEE Transactions on Power Electronics, no. 99, 2014.

[2] R. Arulmurugan and N. Suthanthiravanitha, “Model and Design of A Fuzzy-Based Hopfield NN Tracking Controller for Standalone PV Applications,” Electr. Power Syst. Res. (2014). Available: http://dx.doi.org/10.1016/j.epsr.2014.05.007

[3] S. Satapathy, K.M. Dash and B.C. Babu, “Variable Step Size MPPT Algorithm for Photo Voltaic Array Using Zeta Converter – A Comparative Analysis,” Students Conference on Engineering and Systems (SCES), pp.1-6, 12-14 April 2013.

[4] A. Trejos, C.A. Ramos-Paja and S. Serna, “Compensation of DC-Link Voltage Oscillations in Grid-Connected PV Systems Based on High Order DC/DC Converters,” IEEE International Symposium on Alternative Energies and Energy Quality (SIFAE), pp.1-6, 25-26 Oct. 2012.

[5] G. K. Dubey, Fundamentals of Electrical Drives, 2nd ed. New Delhi, India: Narosa Publishing House Pvt. Ltd., 2009.

A Comparative Study on the Speed Response of BLDC Motor Using Conventional PI Controller, Anti-windup PI Controller and Fuzzy Controller

ABSTRACT: 

 Brushless dc motors (BLDC) are widely used for various applications because of high torque, high speed and smaller size. This type of motors are non linear in nature and are affected highly by the non-linearities like load disturbance. Speed control of this motor is traditionally handled by conventional PI and PID controllers. This paper presents the speed control of BLDC motor using anti wind up PI controller. Problems like rollover can arise in conventional PI controller due to saturation effect. In order to avoid such problems anti wind up schemes are introduced. As the fuzzy controller has the ability to control and as it is simple to calculate, a fuzzy controller is also designed for speed control of BLDC motor. The control and simulation of BLDC motor have been done using software MATLAB/SIMULINK. The simulation results using anti wind up PI controller and fuzzy controller are compared with PI controller.

KEYWORDS: 
1. BLDC
2. Speed response
3. PI controller
4. Fuzzy
5. Anti windup

SOFTWARE: MATLAB/SIMULINK


BLOCK DIAGRAM:

Fig.1. Simulation block diagram

EXPECTED SIMULATION RESULTS: 

Fig.2. Speed response under no load

Fig.3. Speed response for step increase in speed

Fig.4. Speed response for step increase in speed

Fig.5. Speed response under loaded condition

Fig.6.Speed response under load condition

CONCLUSION:

This paper presents the speed control of BLDC motor using anti wind up PI controller and fuzzy controller for three phase BLDC motor. The simulation results are compared with PI controller results. The conventional PI controller results are slower compared to fuzzy and anti wind up controllers. From the simulation results, it is clear that for the load variation anti wind up PI controller gave better response than conventional PI and fuzzy controller. Hence anti wind up PI controller is found to be more suitable for BLDC motor drive during load variation. It can also be observed from the simulation results that performance of fuzzy controller is better during the case of speed variation.

REFERENCES:

[1] R. Arulmozhiyal, R. Kandibanv, “Design of Fuzzy PID Controller for Brushless DC Motor”, in Proc. IEEE International Conference on Computer Communication and Informatics, Coimbatore, 2012. 

[2] Anirban Ghoshal and Vinod John, “Anti-windup Schemes for Proportional Integral and Proportional Resonant Controller”, in Proc. National Power electronic conference, Roorkee, 2010. 

[3] M. F. Z. Abidin, D. Ishak and A. Hasni Abu Hassan, “A Comparative Study of PI, Fuzzy and Hybrid PI Fuzzy Controller for Speed Control of Brushless DC Motor Drive”, in Proc. IEEE International conference on Computer applications and and Industrial electronics, Malysia, 2011. 

[4] J. Choi, C. W Park, S. Rhyu and H. Sung, “Development and Control of BLDC Motor using Fuzzy Models”,in Proc. IEEE international Conference on Robotics, Automation and Mechatronics, Chengdu, 2004. 

[5] C. Bohn and D.P. Atherton, “An analysis package comparing PID anti-windup strategies,” IEEE Trans. controls system, Vol.15, No. 2, pp.34-40, 1995.

A Comparative Study of Speed Control of D.C. Brushless Motor Using PI and Fuzzy Controller

ABSTRACT: 

This paper presents an intelligent control architecture for a sensor based brushless DC motor. A BLDC motor is superior to a brushed DC motor, as it replaces the mechanical commutation unit with an electronic one; hence improving the dynamic characteristics, efficiency and reducing the noise level marginally. Conventionally a PI-controller is used for speed control purpose in many industrial BLDC motor drives. But the accuracy level obtained by the PI-controlled drive is insufficient for advanced sophisticated applications. So as a better choice, a fuzzy logic control technique is applied to this motor to achieve a greater accuracy in controlling the speed.

KEYWORDS: 
1. Intelligent control
2. BLDC motor
3. Dynamic characteristics
4. Accuracy
5. Fuzzy logic

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAMS:

Fig. 1. Block diagram for speed control of BLDCM using PI controller.

Fig. 2. Block diagram of a fuzzy logic controlled BLDC motor drive.

EXPECTED SIMULATION RESULTS: 

                 

Fig. 3. Speed response of PI controlled BLDC motor drive(Nref=1500 r.p.m)

Fig. 4. Speed response of fuzzy logic controlled BLDC motor drive (Nref=1500 r.p.m)

Fig. 5. Speed response of PI controlled BLDC motor drive(transition from 1500 r.p.m to 1400 r.p.m)

Fig. 6. Speed response of fuzzy logic controlled BLDC motor drive (transition from 1500 r.p.m to 1400 r.p.m)

                                                                                                                                                                     CONCLUSION:

In this paper we discussed the BLDC motor speed control using a fuzzy logic controller. A detailed analysis was done on fuzzification, fuzzy rules and defuzzification methods and lookup table was obtained by using fuzzy algorithm. The PI control scheme and fuzzy based PI scheme were simulated using MATLAB and compared. The dynamic response of speed in using FLC was better than only PI scheme. These results show that a PI based FLC technique is a better choice for BLDC motor drive and favors to widen its area of application in near future.

REFERENCES:

[1] Paul C. Krause, "Analysis of electric machinary", McGraw-Hill, 1984.

[2] P.S. Bimbhra, “ Generalized Theory of Electrical Machines”, Khanna Publishers.

[3] P. Yedamale, Brushless DC (BLDC) Motor Fundamentals. Application Note 885, Microchip Technology Inc., Chandler, AZ,2003.

[4] Dutta, P.; Mahato, S.N., "Design of mathematical model and performance analysis of BLBLDC motor," Control, Instrumentation, Energy and Communication (CIEC), 2014 International Conference on , vol., no., pp.457,461, Jan. 31 2014-Feb. 2 2014

[5] Ko, J.S.; Jae Gyu Hwang; Myung-Joong Youn, "Robust position control of BLDD motors using integral-proportional plus fuzzy logic controller," Industrial Electronics, Control, and Instrumentation, 1993. Proceedings of the IECON '93., International Conference on , vol., no., pp.213,218 vol.1, 15-19 Nov 1993

A Comparative Study of PI, Fuzzy and Hybrid PI Fuzzy Controller for Speed Control of Brushless DC Motor Drive

ABSTRACT: 

This paper presents the comparative study between PI, fuzzy and hybrid PI-Fuzzy controller for speed control of brushless dc (BLDC) motor. The control structure of the proposed drive system is described. The simulation results of the drive system for different operation modes are evaluated and compared. A fuzzy controller offers better speed response for start-up while PI controller has good compliance over variation of load torque but has slow settling response. Hybrid controller has an advantage of integrating a superiority of these two controllers for better control performances. Matlab/Simulink is used to carry out the simulation.

KEYWORDS: 
1. PI
2. Fuzzy
3. Hybrid Controller
4. BLDC Motor
5. Speed Control

SOFTWARE: MATLAB/SIMULINK

SIMULINK DIAGRAM:

Figure 1: Simulation model BLDC motor drive

EXPECTED SIMULATION RESULTS: 

Figure 2: PI controller

Figure 3: Fuzzy controller

Figure 4: Hybrid controller

Figure 5: Comparison of speed response

Figure 6: PI controller

Figure 7: Fuzzy controller

Figure 8: Hybrid controller

Figure 9: Comparison of speed response

CONCLUSION:

From simulation results, it was shown that PI controller maintained the steady state accuracy while the fuzzy controller performed well in the case of sufficiently large reference input changes with shorter settling time. The hybrid controller has integrated both fuzzy controller and PI controller. During the large speed error, the fuzzy controller will be selected by switch. When the speed error is less than 0.28 rpm, the PI controller will be selected to maintain the high steady-state accuracy. The simulation results showed that the hybrid controller has incorporated advantage of both fuzzy and PI controller. As a conclusion, the hybrid controller has improved the dynamic performance of BLDC motor.

REFERENCES:

[1] F. Farkas, A. Zakharov and S.Z. Varga, “Speed and position controller for dc drives using fuzzy logic”, Studies in Applied Electromagnetics and Mechanics (Vol. 16): Applied Electromagnetics and Computational Technology II, Amsterdam: IOS Press, 2000.

[2] Zulkifilie Ibrahim and Emil Levi, "A comparative analysis of fuzzy logic and pi speed control in high-performance ac drives using experimental approach", IEEE Trans. on Industry Applications 38(5): pg 1210-1218, 2002.

[3] L.S. Xuefang, F. Morel, A.M. Llor, B. Allard, J.-M. Retif, "Implementation of hybrid control for motor drives", IEEE Trans. Industrial Electronics, vol.38, No. 5, pp. 1210-1218, Sep. 2002.

[4] Krishnan R, Permanent magnet synchronous and brushless DC motor drives, Boca Raton: CRC Press, 2010

[5] Lini Mathew and Vivek Kumar Pandey, “Design and deelopment of fuzzy logic controller to control the speed of permanent magnet synchronous motor”, JEEER, vol. 3(3), pp. 52-61, March 2011.

Control of BLDC Motor Based on Adaptive Fuzzy Logic PID Controller

ABSTRACT: 

This paper presents an Adaptive fuzzy logic PID controller for speed control of Brushless Direct current Motor drives which is widely used in various industrial systems, such as servo motor drives, medical, automobile and aerospace industry. BLDC motors were electronically commutated motor offer many advantages over Brushed DC Motor which includes increased efficiency, longer life, low volume and high torque. This paper presents an overview of performance of fuzzy PID controller and Adaptive fuzzy PID controller using Simulink model. Tuning Parameters and computing using Normal PID controller is difficult and also it does not give satisfied control characteristics when compare to Adaptive Fuzzy PID controller. From the Simulation results we verify that Adaptive Fuzzy PID controller give better control performance when compared to fuzzy PID controller. The software Package SIMULINK was used in control and Modelling of BLDC Motor.

KEYWORDS: 

1. Brushless DC motors (BLDCM)
2. Fuzzy PID controller
3. Adaptive Fuzzy PID controller

SOFTWARE: MATLAB/SIMULINK


BLOCK DIAGRAM:

 Fig.1. Speed control of BLDC motor

EXPECTED SIMULATION RESULTS: 

Fig.2. Speed characteristics with no load speed of 3000 rpm

Fig.3. Torque characteristics with no load speed of 3000 rpm

Fig. 4. Speed characteristics with no load step down speed of 3000- 2500 rpm

Fig.5. Torque characteristics with no load step down speed of 3000-2500 rpm

Fig.6. Speed characteristics with load speed of 3000 rpm

Fig.7. Torque characteristics with load speed of 3000 rpm

                                                                                                                                                                     CONCLUSION:

This paper presents the performance of fuzzy PID controller and Adaptive Fuzzy PID controller of BLDC motor for speed control using Simulink model. Combination of fuzzy control and conventional PID controller establishes an intelligent control, which regulates the control parameters depending upon the error. Two inputs and three outputs were used in this fuzzy adaptive PID controller. From the Simulation, BLDC motor speed control of Adaptive fuzzy PID controller had better performance than fuzzy PID controller for the same operation condition, mainly when BLDC motor operates in different speed and also BLDC motor speed to be constant when the load varies. Simulation results were also shows that fuzzy logic adaptive PID controller had lesser overshoot, faster response and better stability.

REFERENCES:

[1] Anjali.A.R “Control Of Three Phase BLDC Motor Using Fuzzy Logic Controller” International Journal of Engineering Research & Technology (IJERT), Vol. 2, Issue 7, July 2013.

[2] R. Kandiban, R. Arulmozhiyal “Design of Adaptive Fuzzy PID Controller for Speed control of BLDC Motor” International Journal of Soft Computing and Engineering ,Volume-2, Issue-1, March 2012.

[3] Uzair Ansari, Saqib Alam, Syed Minhaj un Nabi Jafri, “Modelling and Control of Three Phase BLDC Motor using PID with Genetic Algorithm”, UK Sim 13th International Conference on Modelling and Simulation,pp.189-194,2011

[4] R.Arulmozhiyal and K.Baskaran, “Implementation of Fuzzy PI Controller for Speed Control of Induction Motor Using FPGA”, Journal of Power Electronics, Vol.10, No.1, pp.65-71, Jan 2010.

[5] Vinod Kr Singh Patel, A.K.Pandey, “Modelling and Simulation of Brushless DC Motor Using PWM Control Technique”, International Journal of Engineering Research and Applications, Vol. 3, Issue 3, May-Jun 2013, pp.612-620.

Design and Implementation of a Novel Multilevel DC–AC Inverter

 ABSTRACT:

 In this paper, a novel multilevel dc–ac inverter is proposed. The proposed multilevel inverter generates seven-level ac output voltage with the appropriate gate signals’ design. Also, the low-pass filter is used to reduce the total harmonic distortion of the sinusoidal output voltage. The switching losses and the voltage stress of power devices can be reduced in the proposed multilevel inverter. The operating principles of the proposed inverter and the voltage balancing method of input capacitors are discussed. Finally, a laboratory prototype multilevel inverter with 400-V input voltage and output 220 Vrms/2 kW is implemented. The multilevel inverter is controlled with sinusoidal pulse-width modulation (SPWM) by TMS320LF2407 digital signal processor (DSP). Experimental results show that the maximum efficiency is 96.9% and the full load efficiency is 94.6%.

KEYWORDS:

1.      DC–AC inverter

2.      Digital signal processor (DSP)

3.      Maximum power point tracking (MPPT)

4.      Multilevel

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. Block diagram of renewable system.

EXPECTED SIMULATION RESULTS:

Fig. 2. Waveforms of v_gs1, v_ab, v_o, and i_o at 500 W.

Fig. 3. Output voltage harmonic spectrum of v_ab calculated by FFT.

Fig. 4. Output voltage harmonic spectrum of v_o calculated by FFT

Fig. 5. Waveforms of vC2, v_o, and i_o at 1000 W.

Fig. 6. Waveforms of vC2, v_o, and i_o at 2000 W.

Fig. 7. Waveforms of v_o and i_o at 400 VA.

CONCLUSION:

A novel seven-level inverter was designed and implemented with DSP in this paper. The main idea of the proposed configuration is to reduce the number of power device. The reduction of power device is proved by comparing with traditional structures. Finally, a laboratory prototype of seven-level inverter with 400-V input voltage and output 220 Vrms/2kW is implemented. Experimental results show that the maximum efficiency is 96.9% and the full load efficiency is 94.6%.

REFERENCES:

[1] R. Gonzalez, E. Gubia, J. Lopez, and L. Marroyo, “Transformerless single-phase multilevel-based photovoltaic inverter,” IEEE Trans. Ind. Electron., vol. 55, no. 7, pp. 2694–2702, Jul. 2008.

[2] S. Daher, J. Schmid, and F. L.M. Antunes, “Multilevel inverter topologies for stand-alone PV systems,” IEEE Trans. Ind. Electron., vol. 55, no. 7, pp. 2703–2712, Jul. 2008.

[3] W. Yu, J. S. Lai, H. Qian, and C. Hutchens, “High-efficiency MOSFET inverter with H6-type configuration for photovoltaic nonisolated, acmodule applications,” IEEE Trans. Power Electron., vol. 26, no. 4, pp. 1253–1260, Apr. 2011.

[4] R. A. Ahmed, S. Mekhilef, and W. P. Hew, “New multilevel inverter topology with minimum number of switches,” in Proc. IEEE Region 10 Conf. (TENCON), 2010, pp. 1862–1867.

[5] M. R. Banaei and E. Salary, “New multilevel inverter with reduction of switches and gate driver,” in Proc. IEEE 18th Iran. Conf. Elect. Eng. (IECC), 2010, pp. 784–789.