Post-processing-based Flux-weakening Control of Variable Flux Reluctance Machines

This paper proposes a novel post-processing-based control strategy for the flux-weakening operation of variable flux reluctance machines. The proposed method achieves a high-efficiency operation at elevated speeds by determining the optimal values for both d- and q-axis currents together with the dc-field current. A 5 kW variable flux reluctance machine, which develops a continuous maximum torque of 16 Nm at a base speed of 3000 rpm, is modeled using a nonlinear magnetodynamic finite element method model. The nonlinear magnetic characteristics of the laminated rotor and stator steels are simulated in transient to calculate the torque production, back-EMF voltage, and efficiency in relation to the excitation parameters. The proposed control algorithm applies the scattered data interpolation in the post-process to obtain possible combinations of the excitation currents for a specific torque reference. An efficiency map for the analyzed variable flux reluctance machine has been generated at a rotor speed of 5000 rpm, taking both copper and iron losses into account. The findings demonstrate that the proposed control strategy ensures an efficiency exceeding 85% during the flux-weakening operation by manipulating the controllable dc-field current, thereby enabling high-efficiency performance beyond the base speed.