Asosiy kontentga oʻtish
Maqola

Energy-Optimal and Thermally Robust Predictive Flux Control of Industrial Induction Motor Drives

Oybek IshnazarovLaboratory of Electrical Power Systems and Complexes, Institute of Energy Problems, Academy of Sciences of the Republic of Uzbekistan, Tashkent 100125, UzbekistanUral Kh. KhoshimovLaboratory of Electrical Power Systems and Complexes, Institute of Energy Problems, Academy of Sciences of the Republic of Uzbekistan, Tashkent 100125, UzbekistanMuslimbek B. NabiyevLaboratory of Electrical Power Systems and Complexes, Institute of Energy Problems, Academy of Sciences of the Republic of Uzbekistan, Tashkent 100125, UzbekistanBotirjon I. KurvonboevDepartment of Power Engineering, Faculty of Energy, Namangan State Technical University, Namangan 160107, UzbekistanJamoldin N. AbdullayevDepartment of Engineering of Electric Machines and Drives, Faculty of Energy Engineering, Tashkent State Technical University, Tashkent 100095, Uzbekistan
2026en
Ochiq kirishOltin

Litsenziya: cc-by

ABI

Annotatsiya

Variable-speed induction motor drives spend most of their service life at partial load, where rated-flux field-oriented control (FOC) is inefficient and where loss-minimizing control (LMC) recovers a large part of the loss. LMC, however, is brittle in two ways that matter in industry: it is tuned isothermally, so as the windings heat, the rotor-resistance drift detunes the field orientation and corrupts torque; and it treats the loss-optimal flux as a quasi-static set-point, so an abrupt load rise from a light-load, low-flux condition forces a slow flux rebuild that throttles torque. This paper proposes a thermally adaptive economic model predictive controller (TA-EMPC) that retains the energy optimum of LMC while removing both weaknesses. A temperature-coupled total-loss model (machine copper and core loss plus inverter conduction and switching loss) is minimized over a finite horizon subject to a torque-delivery constraint; a reduced-order two-node thermal observer updates the loss-defining resistances online without a temperature sensor; and a load-demand-aware flux-reservation term pre-magnetizes the machine ahead of anticipated torque rises. In simulations on a representative 7.5 kW drive, TA-EMPC matched the energy of static LMC to within 0.3% across pump, conveyor, and fast-cycling duty profiles—both saving 1.4–2.3% of cycle energy relative to rated-flux FOC, and up to about 14.7 efficiency points at very light load—while, unlike LMC, holding the steady torque error below 0.5% when the winding temperature rose by about 95 °C, to a hot steady state near 115 °C (a stator-resistance increase of roughly 37%) (against an 8% error for the non-adaptive scheme) and reducing the torque undershoot during a light-to-heavy load step from about 23% to near zero. All quantitative results reported in this work are obtained entirely in simulation. A per-step operation-count analysis—not an on-target timing measurement—indicates that the condensed quadratic-program formulation with move blocking is executable within the 100 µs sampling interval on a production digital signal controller for the chosen control horizon; experimental validation on a loaded dynamometer bench, together with on-target timing measurement, is identified as future work. The contribution is thus energy-efficient operation delivered with the torque robustness that loss minimization alone does not provide.

Hali tarjima qilinmagan

Identifikatorlar

Iqtiboslar va manbalar