Hindawi Publishing Corporation Advances in Power Electronics Volume 2013, Article ID 371842, 8 pages http://dx.doi.org/10.1155/2013/371842 Research Article Simple Hybrid Model for Efficiency Optimization of Induction Motor Drives with Its Experimental Validation Branko Blanuša 1 and Bojan Knezevic 2 1 Faculty of Electrical Engineering, University of Banja Luka, Patre 5, 78000 Banja Luka, Bosnia and Herzegovina 2 Faculty of Mechanical Engineering, University of Banja Luka, Bulevar Stepe Stepanovica 75, 78000 Banja Luka, Bosnia and Herzegovina Correspondence should be addressed to Branko Blanuˇ sa; bbranko@etfl.net Received 28 December 2012; Revised 14 February 2013; Accepted 14 February 2013 Academic Editor: Jose Pomilio Copyright © 2013 B. Blanuˇ sa and B. Knezevic. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. New hybrid model for efciency optimization of induction motor drives (IMD) is presented in this paper. It combines two strategies for efciency optimization: loss model control and search control. Search control technique is used in a steady state of drive and loss model during transient processes. As a result, power and energy losses are reduced, especially when load torque is signifcant less related to its rated value. Also, this hybrid method gives fast convergence to operating point of minimal power losses and shows negligible sensitivity to motor parameter changes regarding other published optimization strategies. Tis model is implemented in vector control induction motor drive. Simulations and experimental tests are performed. Results are presented in this paper. 1. Introduction Induction motor is a widely used electrical motor and a great energy consumer. Te vast majority of induction motor drives are used for heating, ventilation, and air condition- ing (HVAC). Tese applications require only low dynamic performance, and in most cases only voltage source inverter is inserted between grid and induction motor as cheapest solution. Te classical way to control these drives is constant V/f ratio, and simple methods for efciency optimization can be applied [1]. From the other side there are many applications where, like electrical vehicles, electric energy has to be consumed in the best possible way and use of induction motors. Tese applications require an energy optimized control strategy [2]. One interesting algorithm which can be applied in a drive controller is algorithm for efciency optimization. In a conventional setting, the feld excitation is kept constant at rated value throughout its entire load range. If machine is underloaded, this would result in overexcitation and unnecessary copper losses. Tus in cases where a motor drive has to operate in wider load range, the minimization of losses has great signifcance. It is known that efciency improvement of IMD can be implemented via motor fux level and this method has been proven to be particularly efective at light loads and in a steady state of drive. Also fux reduction at light loads gives less acoustic noise derived from both converter and machine. From the other side low fux makes motor more sensitive to load disturbances and degrades dynamic performances [3]. Drive loss model is used for optimal drive control in loss model control (LMC) [3–7]. Tese algorithms are fast because the optimal control is calculated directly from the loss model. But power loss modeling and calculation of the optimal control can be very complex. Ofen the loss model is not accurate enough. Search strategy methods have an important advantage compared to other strategies [8–11]. It is completely insen- sitive to parameter changes, while efects of the parameter variations caused by temperature and saturation are very expressed in two other strategies. Te online efciency optimization control on the basis of search, where the fux is decremented in steps until the measured input power settles down to the lowest value, is very attractive. Algorithm is applicable universally to any motor. Besides all good charac- teristics of search strategy methods, there is an outstanding