A new inductance estimator based on Lagrange Form polynomials for real-time switched reluctance machine control (Research, Society and Development, 2022)
This paper presents a new methodology for modeling the inductance curves of switched-reluctance machines using cubic splines based on Lagrange form polynomials. The proposed methodology allows for the estimation of the instantaneous inductance and derivative of the inductance in each phase of the machine. All steps of the proposed methodology are presented and discussed, detailing the information necessary for its use. The results of an experimental and computational simulation, both as a motor and a generator, are presented and discussed, and the estimated curves are compared with the design curves of each result. The inductance estimator was embedded in a low-cost DSP, and the machine was driven using an experimental bench. The experimental results are presented and compared with the simulation results, allowing for the evaluation of the accuracy level obtained by the proposed estimator. The estimator combines precision with low computational cost, which makes this method a strong candidate for systems that require estimation of machine parameters in real time, such as torque and flux, permitting the implementation of new control techniques.