Efficiency Optimization of Induction Motor Drive at Steady-State Condition

 

ABSTRACT:

Induction motors are workhorse of industries due to its power/mass relation, efficiency, low cost and nearly maintenance free operation in its life cycle. However motors with low efficiency waste a lot of energy that will increase its operational cost. As a result of high energy consumption and the huge number of operating units, even a small increase in efficiency improvement has significant effect on the entire energy consumptions and operational cost. This paper uses key features of loss model control (LMC) and search control (SC) together for estimation and reproduction of optimal flux component of current (Ids), for optimal efficiency operation of induction motor. At first, a d-q loss model of induction motor is used to derive a loss-minimization expression considering core saturation. The loss expression is used to derive optimal Ids expression and then Ids is estimated for various load profiles and finally tabulated. Based on those tabulated values, a look-up table in MATLAB is designed, and thus optimal Ids* value can be reproduced, depending upon run-time load profile, in feed-forward manner, and thus eliminates run-time loss model complex computation. Efficiency is compared for conventional vector control (constant Ids) and proposed optimal control (optimal Ids) operations. Superior efficiency performance (1-18%) is observed in optimal flux operation at steady-state, for load torque above 60% in simulation, for wide range of speed. The proposed hybrid concept is easy to implement, run-time computation free operation, ripple free operation, and offers higher power saving ratio with respect to useful output power.

KEYWORDS:

  1. Induction motor drive
  2. Efficiency optimization
  3. Vector control
  4. Optimal control
  5. Look-up table

 SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig. 1(a). MATLAB model for efficiency validation

EXPECTED SIMULATION RESULTS:

Fig. 2. Speed, Torque and Efficiency perfonnance at (a) at rated load torque (200N-m) at 120 radis speed, 12% efficiency rise, (b) at 3/4th rated load torque (150Nm) at 120 radis speed, 5% efficiency rise

Fig.3 Ids* values at different speeds

Fig. 4(a) Efliciency- vs- Load-Torque at 120 radis, (b) Efliciency- vs- Speed

Fig. 5(a) Input Power- vs- Speed, (b) %age power saving- vs- speed

CONCLUSION:

In this work, it is verified that the optimal flux operation is superior to that of vector control method under steady – state condition, in terms of efficiency enhancement and hence energy-saving. In general I – 18% improvement is observed on 50 HP, 60 Hz motor, at different load-torques (above 60%) and speeds, in simulink environment. Efficiency improvement margin is seen degraded below 60% of rated load, and conventional vector control performs better. This can be seen as shortcoming of proposed method. The dynamic performance is seen satisfactory (similar to vector control), but speed and torque tracking accuracy is degraded a bit, but still the proposed approach is extremely suitable for such an application where maintaining speed and torque very precisely is not a critical issue, such as an induction motor drive used in an industrial HV AC applications. A lot of electricity can be saved with this minute compromise in speed and torque, since it offers higher amount of energy savings as compared to existing methods, hence a great contribution towards social and environmental aspects. The proposed method can be easily implemented on other induction motor drive systems also, for which the steady-state speed-vs.-torque load characteristics are already known or can be predicted. Also, the proposed hybrid approach eliminates the need of runtime computation complexity in traditional loss model controller (LMC), so less hardware installations required in implementation, hence cost-effective. Also, since no runtime perturbations happening as it usually happen in conventional search control (SC), so no torque ripples, hence less wear and tear of induction motor drive.

REFERENCES:

[1] A. H. M. Yatim and W. M. Utomo, “To develop an efficient variable speed compressor motor system,” universiti teknologi Malaysia (UTM), Skudai, Malasia, 2007.

[2] R. Hanitsch, “Energy efficienct electric motors,” university of technology berlin, germany, 2000.

[3] Y. Yakhelet: “Energy efficiency optimization of induction motors,” Boumerdes University, Boumerdes, Algeria, 2007.

[4] M. W. Turner, V. E. McCormick and 1. G. Cleland, Efficiency optimization control of AC induction motors: Initial laboratory results, United States Environmental Protection Agency, Research and Development, National Risk Management Research Laboratory, 1996.

[5] T. Fletier, W. Eichhammer and 1. Schleich, “Energy efficiency in electric motor systems: Technical potentials and policy approacehs fir developing countries,” United Nations Industrila Development, Vienna,2011.

 

Fuzzy Efficiency Enhancement of Induction Motor Drive

 

ABSTRACT:

Efficiency improvement of motor drives is important not only from the viewpoints of energy loss and hence cost saving, but also from the perspective of environmental pollution. Several efficiency optimization methods for induction motor (IM) drives have been introduced nowadays by researchers. Distinctively, artificial intelligence (AI)-based techniques, in particular Fuzzy Logic (FL) one, have been emerged as a powerful complement to conventional methods. Design objectives that are mathematically hard to express can be incorporated into a Fuzzy Logic Controller (FLC) using simple linguistic terms. The merit of FLC relies on its ability to express the amount of ambiguity in human reasoning. When the mathematical model of a process does not exist or exists with uncertainties, FLC has proven to be one of the best alternatives to move with unknown process. Even when the process model is well-known, there may still be parameter variation issues and power electronic systems, which are known to be often approximately defined.

The purpose of this paper is to demonstrate that a great efficiency improvement of motor drive can be achieved and hence a significant amount of energy can be saved by adjusting the flux level according to the applied load of an induction motor by using an on-line fuzzy logic optimization controller based on a vector control scheme. An extensive simulation results highlight and confirm the efficiency improvement with the proposed algorithm.

KEYWORDS:

  1. Induction Motor Drive
  2. Indirect Field Oriented Control (IFOC)
  3. Efficiency Enhancement
  4. Losses Minimization
  5. Optimization
  6. Fuzzy Logic

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 

Fig.1, Block diagram of the optimization system

EXPECTED SIMULATION RESULTS:

 

 Fig.2, Motor Performances Comparison

Fig.3, Motor efficiency evolution with motor load

CONCLUSION:

This paper aims to improve the induction motor drive efficiency that leads to a significant amount of energy saving. This efficiency enhancement is carried out by adjusting the flux level depending on the applied load of an induction motor by using an on-line fuzzy logic optimization controller based on a vector control scheme. A series of the induction motor drive performances are obtained with a variable load under this proposed algorithm. The application of the proposed algorithm yields to a series of simulation performances of the induction motor drive with a variable load. They present the IM drive efficiency evolution with a certain load profile with the suggested losses minimization strategy based on fuzzy control and the conventional field oriented control. The comparison between these two control schemes reveals that the achieved results are of a great interest. Indeed, the fuzzy control contributes with a great deal to the efficiency improvement for all operating speeds particularly in light load region. This contribution conducts to a paramount energy saving and hence to environment protection.

REFERENCES:

[1] I. Boldea, A. Nasser, The Induction Machine Design Handbook, CRC Press Inc; 2nd Revised Edition, 2009.

[2] Jinchuan. Li and all, “A new Optimization Method on Vector Control of Induction Motors”, Electric Machines and Drives, 2005 IEEE International Conference, 15-18 May 2005, pp.1995-2001.

[3] H. Sepahv and, Sh. Ferhangi, “Enhancing Performance of a Fuzzy Efficiency Optimizer for Induction Motor Drives”, Power Electronics Specialists Conference, 2006. PESC ’06. 37th IEEE, 18-22 June.2006, pp.1-5.

[4] Branko Blanusa and all, “An Improved Search Based Algorithm for Efficiency Optimization in the Induction Motor Drives”, XLII Konferencija- za ETRAN, Hercy-Novi, 2003.

[5] D. S. Kirischen, D. W. Novoty and T. A. Lipo, “Optimal Efficiency Control of an Induction Motor Drive”, IEEE Transaction on Energy Conversion, Vol. EC-2, N° 1, March 1987, pp.70-76.

Efficiency Optimization of Induction Motor Drive in Steady- State using Artificial Neural Network

 

ABSTRACT:

Induction motors have good efficiency at rated conditions, but at partial loads if operated with rated flux, they show poor efficiency, Motors in such conditions waste a lot of electricity, results in increased operational cost, hence significant loss of revenue, if run for long duration, Because of robustness, good power/mass relation, low cost and easy maintenance throughout its life cycle, induction motors, particularly squirrelcage induction motors are vastly used in industries. Because of the huge number of operational units worldwide, they consume a considerable amount of electrical energy, so even a minute efficiency improvement may lead to significant contributions in global electricity consumption, revenue saving and other environmental aspects. This paper uses key concepts of loss model control (LMC) and search control (SC) together for efficient operation of induction motors used in various industrial applications, where aforesaid load conditions may occur for prolonged durations. Based on the induction motor loss model in d-q frame, and using classical optimization techniques, done earlier, an optimal Ids expression in terms of machine parameters and load parameters is used to estimate optimal Ids values for various load conditions, offline, and finally tabulated. Based on which, an artificial neural network (ANN) controller is designed, taking torque and speed as input and Ids as output. The ANN controller reproduces the optimal Ids * value, as per load conditions, in feed-forward manner, and thus eliminates run-time computations and perturbations for optimal flux. The ANN training is performed in MA TLAB and the results have shown the superb accuracy of the model. Dynamic and steady-state performances are compared for conventional vector control (constant Ids) and proposed optimal control (optimal Ids) operations. Excellent dynamic as well as superior efficiency performance (1-18%) at steady- state, is observed in optimal flux operation, for load torque above 60% of rated, in simulation, for a wide range of speed, by the proposed method. Also, the method is easy to implement for real – time industrial facilities, fast response, ripple free operations, and offers higher energy savings ratio as compared to useful output power, in comparison with similar works done earlier.

KEYWORDS

  1. Energy-efficiency
  2. Induction motor drive
  3. Vector control
  4. Optimal control
  5. Efficiency optimization
  6. ANN

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

Fig. 1(a). MATLAB model for efficiency validation, (b) Id,* values at different speeds

EXPECTED SIMULATION RESULTS:

 

 

Fig. 2(a) Efficiency- vs- Load-Torque at 120 rad/s, (b) %age Power saving – vs- Speed

Fig. 3. Speed, Torque, Input power and Efficiency performance at for a load cycle of (150 N -m, 120 radls) for 4 sec, (200 N -m, 150 rad/s) for 3 sec, and (150 Nm, 90 rad/s) for 3 sec.

Fig. 4. Switching state performances at sample 120 rad/sec speed at a load cycle of 16 seconds.

CONCLUSION:

In this work, it is verified that the optimal flux operation is superior to that of vector control method under steady – state condition, in terms of efficiency enhancement and hence energy-saving. In general 1 – 18% efficiency improvement is observed on 50 HP, 60 Hz motor, at different load-torques (above 60%) and speeds, in Simulink environment. Efficiency improvement margin is seen degraded below 60% of rated load, and conventional vector control performs better. This can be seen as shortcoming of proposed method. The dynamic performance is seen satisfactory, similar to vector control or even better, in terms of overshoot, undershoot and settling time, speed and torque tracking accuracy is little bit deviated, but still the proposed approach is extremely suitable for such an application where maintaining speed and torque very precisely is not a critical issue, such as an induction motor drive used in an industrial HV AC applications [7, Bose 2004]. A lot of electricity can be saved with this minute compromise in speed and torque accuracy, since it offers higher amount of energy savings as compared to existing methods, hence a great contribution towards social and environmental aspects. The proposed method can be easily implemented on other induction motor drive systems also, for which the steady-state speed-vs.torque load characteristics are already known or can be predicted. The offline optimization as done here, is a limitation, as the optimal flux trajectories are only valid for one specific application, can also be considered as drawback. But, the proposed hybrid approach eliminates the need of run-time computation complexity in traditional loss model controller (LMC), so less hardware installations required in implementation, hence cost-effective. Also, since no run-time perturbations happening as it usually happen in conventional search control (SC), so no torque ripples, hence less wear and tear of induction motor drive.

REFERENCES:

[1] A. H. M. Yatim and W. M. Utomo, “To develop an efficient variable speed compressor motor system,” Universiti Teknologi Malaysia (UTM), Skudai, Malaysia, 2007.

[2] R. Hanitsch, “Energy efficient electric motors,” University of Technology, Berlin, Germany, 2000.

[3] Y. Yakhelef, “Energy efficiency optimization of induction motors,” Boumerdes University, Boumerdes, Algeria, 2007.

[4] M. W. Turner, V. E. McCormick and J. G. Cleland, Efficiency optimization control of AC induction motors: Initial laboratory results, United States Environmental Protection Agency, Research and Development, National Risk Management Research Laboratory, 1996.

[5] T. Fletier, W. Eichhammer and 1. Schleich, “Energy efficiency in electric motor systems: Technical potentials and policy approaches for developing countries,” United Nations Industrial Development, Vienna, 2011.

Efficiency Optimization of Induction Motor Drive at Steady-State Condition

ABSTRACT:

Induction motors are workhorse of industries due to its power/mass relation, efficiency, low cost and nearly maintenance free operation in its life cycle. However motors with low efficiency waste a lot of energy that will increase its operational cost. As a result of high energy consumption and the huge number of operating units, even a small increase in efficiency improvement has significant effect on the entire energy consumptions and operational cost. This paper uses key features ofloss model control (LMC) and search control (SC) together for estimation and reproduction of optimal flux component of current (Ids), for optimal efficiency operation of induction motor. At first, a d-q loss model of induction motor is used to derive a loss-minimization expression considering core saturation. The loss expression is used to derive optimalIds expression and then Ids is estimated for various load profiles and finally tabulated. Based on those tabulated values, a look-up table in MATLAB is designed, and thus optimal Ids* value can be reproduced, depending upon run-time load profile, in feed-forward manner, and thus eliminates run-time loss model complex computation. Efficiency is compared for conventional vector control (constant Ids) and proposed optimal control (optimal Ids) operations. Superior efficiency performance (1-18%) is observed in optimal flux operation at steady-state, for load torque above 60% in simulation, for wide range of speed. The proposed hybrid concept is easy to implement, run-time computation free operation, ripple free operation, and offers higher power saving ratio with respect to useful output power.
KEYWORDS:
1. Induction motor drive
2. Efficiency optimization
3. Vector control
4. Optimal control
5. Look-up table

SOFTWARE: MATLAB/SIMULINK
BLOCK DIAGRAM:

Fig.1. MATLAB model for efficiency validation

EXPECTED SIMULATION RESULTS:


Fig. 2. Speed, Torque and Efficiency perfonnance at (a) at rated load torque (200N-m) at 120 radis speed, 12% efficiency rise, (b) at 3/4th rated load torque (150Nm) at 120 radis speed, 5% efficiency rise

Fig 3. Ids* values at different speeds

Fig. 4 Efficiency- vs- Load-Torque at 120 radis, (b) Efliciency- vs- Speed

Fig. 5 Input Power- vs- Speed, (b) %age power saving- vs- speed

CONCLUSION:
In this work, it is verified that the optimal flux operation is superior to that of vector control method under steady – state condition, in terms of efficiency enhancement and hence energy-saving. In general I – 18% improvement is observed on 50 HP, 60 Hz motor, at different load-torques (above 60%) and speeds, in simulink environment. Efficiency improvement margin is seen degraded below 60% of rated load, and conventional vector control performs better. This can be seen as shortcoming of proposed method. The dynamic performance is seen satisfactory (similar to vector control), but speed and torque tracking accuracy is degraded a bit, but still the proposed approach is extremely suitable for such an application where maintaining speed and torque very precisely is not a critical issue, such as an induction motor drive used in an industrial HV AC applications. A lot of electricity can be saved with this minute compromise in speed and torque, since it offers higher amount of energy savings as compared to existing methods, hence a great contribution towards social and environmental aspects. The proposed method can be easily implemented on other induction motor drive systems also, for which the steady-state speed-vs.-torque load characteristics are already known or can be predicted. Also, the proposed hybrid approach eliminates the need of runtime computation complexity in traditional loss model controller (LMC), so less hardware installations required in implementation, hence cost-effective. Also, since no runtime perturbations happening as it usually happen in conventional search control (SC), so no torque ripples, hence less wear and tear of induction motor drive.

REFERENCES:

[I] A. H. M. Yatim and W. M. Utomo, “To develop an efficient variable speed compressor motor system,” universiti teknologi Malaysia (UTM), Skudai, Malasia, 2007.
[2] R. Hanitsch, “Energy efficienct electric motors,” university of technology berlin, germany, 2000.
[3] Y. Yakhelet: “Energy efficiency optimization of induction motors,” Boumerdes University, Boumerdes, Algeria, 2007.
[4] M. W. Turner, V. E. McCormick and 1. G. Cleland, Efficiency optimization control of AC induction motors: Initial laboratory results, United States Environmental Protection Agency, Research and Development, National Risk Management Research Laboratory, 1996.
[5] T. Fletier, W. Eichhammer and 1. Schleich, “Energy efficiency in electric motor systems: Technical potentials and policy approacehs fir developing countries,” United Nations Industrila Development, Vienna,2011.

Performance Investigation of Space Vector Pulse Width Modulated Inverter fed Induction Motor Drive

ABSTRACT

This paper introduces Space Vector Pulse Width Modulation (SVPWM) Technique in detail and its implementation in MATLAB. Performance investigation of Sinusoidal Pulse Width Modulated and Space Vector Modulated Voltage Source Inverter (VSI) fed Induction Motor (1M) drive has done and their simulation results are compared with each other. Also FFT analysis for Sinusoidal Pulse Width Modulated and Space Vector Pulse Width Modulated VSl fed 1M drive is done and compared with each other. 20 HP 1M is used. The study confirms that 1M gives improved performance when it is fed from Space Vector Pulse Width Modulated VS1.

 

KEYWORDS

  1. Space Vector Pulse Width Modulation (SVPWM)
  2. Sinusoidal Pulse Width Modulation (SPWM)
  3. Two Level Voltage Source Inverter (VSI)
  4. Total Harmonic Distortion (THD)
  5. Three Phase Induction Motor (1M).

 

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

image001

Figure 1. Block diagram of SVPWM

EXPECTED SIMULATION RESULTS

image002

Figure 2. (a) Line to Line Voltage (Vab) of Space Vector Modulated VSI (b) Stator current (i,..) of IM (c) Electromagnetic Torque (Te) of IM (d) Rotor Speed (Nm) of 1M.

image003

Figure 3 (a) Line to Line Voltage (Vab) of Sinusoidal Pulse Width Modulated VSI (b) Stator current (i,a) of IM ( c) Electromagnetic Torque (Te) of IM (d) Rotor Speed (Nm) of IM

image004

Figure 4. FFT Analysis of Line to Line Voltage (Vab) of (a) Sinusoidal Pulse Width Modulated VSL (b) Space Vector Modulated VSL

CONCLUSION

The simulation study of SVPWM technique was presented and compared with SPWM technique. It was found that by using SVPWM technique, THD content present in inverter output voltage is less as compared with SPWM technique. Table III shows that the utilization of DC bus is l3.55% more for SVPWM compared TO SPWM technique. i. e. SVPWM technique achieved a better utilization of DC bus as compared with SPWM technique. The performance investigation of SPWM inverter and SVPWM inverter fed 1M drive was done. Table IV shows, in case of SVPWM increased rotor speed with reduced error band achieved as compared with SPWM. Also settling time is less for SVPWM as compared with SPWM. It was conclude that results for SVPWM technique are more convenient than SPWM technique.

 

REFERENCES

  1. W. Van der Broeck, H. C. Skudelny and G. V. Stanke, “Analysis and realization of a pulsewidth modulator based on voltage space vectors,” IEEE Trans. Ind. Applicat., vol. 24,no. I, pp. 142-150, Jan.lFeb. 1988.
  2. Fukuda, Y. Iwaji, and H. Hasegawa, “PWM technique for inverter with sinusoidal output current,” IEEE Trans. Power Electron., vol. 5, no. I, pp. 54-61, Jan. 1990.
  3. Kolar, H. Ertl, and F. C. Zach, “Inf1uence of the modulation method on the conduction and switching losses of a PWM converter system,” IEEE Trans. Ind. Application., vol. 27, no. 6, pp. 1063-1075, Nov.lDec. 1991.
  4. Joachim Holtz,. “Pulsewidth modulation – A survey,” IEEE Trans. on Ind. Electron, vol. 1, pp. 11-18, Dec. 1992.
  5. H. Kwon and B. D. Min, “A fully software-controlled PWM rectifier with current link,” IEEE Trans. Ind. Electron., vol. 40, no. 3, pp. 355-363, June 1993.

Fuzzy Controller for Three Phases Induction Motor Drives

ABSTRACT:

Because of the low maintenance and robustness induction motors have many applications in the industries. Most of these applications need fast and smart speed control system. This paper introduces a smart speed control system for induction motor using fuzzy logic controller. Induction motor is modeled in synchronous reference frame in terms of dq form. The speed control of induction motor is the main issue achieves maximum torque and efficiency. Two speed control techniques, Scalar Control and Indirect Field Oriented Control are used to compare the performance of the control system with fuzzy logic controller. Indirect field oriented control technique with fuzzy logic controller provides better speed control of induction motor especially with high dynamic disturbances. The model is carried out using Matlab/Simulink computer package. The simulation results show the superiority of the fuzzy logic controller in controlling three-phase induction motor with indirect field oriented control technique.

 KEYWORDS:

  1. Vector control
  2. Fuzzy logic
  3. Induction motor drive

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

image001

Fig. 1. Block diagram of scalar controller for IM.

image002

Fig. 2. Indirect Field Oriented Control of IM.

 EXPECTED SIMULATION RESULTS:

 image003

Fig. 3. Speed response of scalar and vector control

image004

Fig 4. Torque response of scalar and vector control.

image005

Fig. 5. Flux response of scalar control.

image006

Fig. 6. Flux response of vector control.

CONCLUSION:

Fuzzy logic controller shows fast control response with three-phase induction motor. Two different control techniques are used with Fuzzy logic controllers which are scalar and field oriented control techniques. Fuzzy logic controller system shows better response with these two techniques. Meanwhile, the scalar controller has a sluggish response than FOC because of the inherent coupling effect in field and torque components. However, the developed fuzzy logic control with FOC shows fast response, smooth performance, and high dynamic response with speed changing and transient conditions.

 REFERENCES:

 [1] A. Mechernene, M. Zerikat and M. Hachblef, “Fuzzy speed regulation for induction motor associated with field-oriented control”, IJ-STA, volume 2, pp. 804-817, 2008.

[2] Leonhard, W.,” Controlled AC drives, a successful transfer from ideas to industrial practice”, CETTI, pp: 1-12, 1995.

[3] M. Tacao, “Commandes numérique de machines asynchrones par lagique floue”, thése de PHD, Université de Lava- faculté des science et de génie Québec, 1997.

[4] Fitzgerald, A.E. et al., Electric Machinery, 5th Edn, McGraw-Hill, 1990.

[5] Marino, R., S. Peresada and P. Valigi, “Adaptive input-output linearizing control of induction motors”, IEEE Trans. Autom. Cont., 1993.