AUTOMATIC CONTROL SYSTEM OF INDUCTION MOTOR DRIVE WITH IMPROVED ENERGY CHARACTERISTICS
DOI:
https://doi.org/10.35546/kntu2078-4481.2025.3.1.26Keywords:
electric drive, induction motor, vector control, power losses, extremum, optimization, energy consumptionAbstract
In this paper, the problem of improving the energy efficiency of induction motor drives, which play a leading role in industry and are characterized by significant total energy consumption, is considered. Modern approaches to drive optimization are analyzed, including search-based extremum control systems and analytical loss minimization systems. The former are distinguished by low parametric sensitivity but demonstrate low response speed, which limits their application in mechanisms with frequently recurring dynamic modes. The latter provide high speed and stability but require sufficiently accurate parameters of the power loss model. The paper proposes an automatic control system of an induction motor drive with analytical loss optimization, which accounts for copper losses in the stator and rotor as well as iron losses in the stator core. Vector control with coordinate orientation by the rotor flux linkage, which is widely used in industrial applications, is applied. Based on mathematical analysis of the loss model, an optimization algorithm is derived that operates using rotor speed signals and the q-component of the stator current vector. This algorithm is simple enough for implementation on modern microcontrollers in real time. The control system was simulated using a 0.75 kW general-purpose induction motor. Its static and dynamic characteristics were investigated under varying load and motor speed. The obtained results show that the proposed optimization ensures a significant reduction of losses in different operating modes. The transient processes of loss minimization last 0.1–0.2 s, which is significantly shorter compared to the extremum search time in search-based systems. Thus, the developed system ensures energy-efficient operation of the induction motor drive not only under long-term steady-state conditions but also in technological processes with short intervals of static state, where the application of search-based methods becomes impractical.
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