An accurate and economical approach for induction motor field efficiency estimation using bacterial foraging algorithm

Abstract As the demand of electrical energy increases, it is vital to replace inefficient motors with new energy efficient ones. The first step towards achieving this goal is to estimate the existing motors efficiencies accurately to determine how much energy saving will be achieved by using energy efficient motors. This paper proposes an economical and accurate approach for motor field efficiency estimation using bacterial foraging algorithm. The approach relies on the measurement of the stator current, stator voltage, input power, stator resistance and rotor speed of the motor without conducting no-load and locked-rotor tests. The BF algorithm is used to determine the equivalent circuit parameters of the motor. The efficiency is then estimated using these parameters. The advantages of the proposed method over the existing methods are simple procedure, efficiency can be estimated accurately without conducting any invasive tests and inexpensive. The approach has been tested on a 5 HP motor and the results are compared with particle swarm optimization method, immune algorithm method, torque gauge method, equivalent circuit method, slip method, current method and segregated loss method. The results demonstrate that the proposed approach can accurately estimate the field efficiency of motor. Accordingly, it is suitable for conducting energy audits and management of the motor.

[1]  David B. Fogel,et al.  Evolutionary Computation: Towards a New Philosophy of Machine Intelligence , 1995 .

[2]  Teresa Orlowska-Kowalska,et al.  Identification of the induction motor parameters at standstill using soft computing methods , 2006 .

[3]  Kevin M. Passino,et al.  Biomimicry of bacterial foraging for distributed optimization and control , 2002 .

[4]  S. Mishra Bacteria foraging based solution to optimize both real power loss and voltage stability limit , 2007, 2007 IEEE Power Engineering Society General Meeting.

[5]  Sukumar Mishra,et al.  A hybrid least square-fuzzy bacterial foraging strategy for harmonic estimation , 2005, IEEE Transactions on Evolutionary Computation.

[6]  T.G. Habetler,et al.  A survey of efficiency-estimation methods for in-service induction motors , 2006, IEEE Transactions on Industry Applications.

[7]  Vahid Rashtchi,et al.  Parameter identification of deep-bar induction motors using genetic algorithm , 2007 .

[8]  R. R. Bishop,et al.  Identifying induction machine parameters using a genetic optimization algorithm , 1990, IEEE Proceedings on Southeastcon.

[9]  Srikrishna Subramanian,et al.  Evolutionary Programming Based Determination of Induction Motor Efficiency , 2006 .

[10]  Francesco Alonge,et al.  Parameter identification of induction motor model using genetic algorithms , 1998 .

[11]  Pragasen Pillay,et al.  Application of genetic algorithms to motor parameter determination , 1994, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting.

[12]  Weisi Lin,et al.  Hammerstein model identification based on bacterial foraging , 2006 .

[13]  B. ABDELHADI,et al.  Identification of Induction Machine Parameters Using a New Adaptive Genetic Algorithm , 2004 .

[14]  Ieee Standards Board IEEE standard test procedure for polyphase induction motors and generators , 1992 .

[15]  P. Vadstrup,et al.  Parameter identification of induction motors using differential evolution , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[16]  Pragasen Pillay,et al.  Application of genetic algorithms to motor parameter determination for transient torque calculations , 1997 .

[17]  C. N. Bhende,et al.  Bacterial Foraging Technique-Based Optimized Active Power Filter for Load Compensation , 2007, IEEE Transactions on Power Delivery.

[18]  K. S. Huang,et al.  Parameter Identification for FOC Induction Motors Using Genetic Algorithms with Improved Mathematical Model , 2001 .

[19]  Y. El-Ibiary An accurate low cost method for determining electric motors' efficiency for the purpose of plant energy management , 2002, Record of Conference Papers. Industry Applications Society. Forty-Ninth Annual Conference. 2002 Petroleum and Chemical Industry Technical Conference.