A Model-based online current optimisation of sensorless control of synchronous reluctance machine using Adaptive Full Order Observer (AFO)

This paper proposes an online maximum torque per ampere (MTPA)-based current control and a modified speed estimation algorithm using a full-order speed observer for field-oriented control (FOC) of a synchronous reluctance motor (SynRM) traction drive for EVs. Unlike conventional MTPA methods based on offline look-up tables, the proposed approach computes the d-axis current reference online using a current-optimizing factor. The key concept is that the current-optimizing factor adapts automatically with operating conditions to keep the excitation level optimal: when load torque increases, the flux-producing component is increased to support torque production; however, during transient events, the current-optimizing factor decreases automatically, which limits the rise in flux and current and prevents over-excitation. At low speed or light load, the current-optimizing factor maintains an optimal stator current, reducing losses and improving overall efficiency. Quantitatively, although the conventional method also maintains the operating point, the proposed optimization reduces the flux from about 1.00 pu to about 0.85 pu at nearly nominal load (0.9 pu), while improving the power factor from about 0.45 to 0.65 at low load (0.2 pu) and from about 0.75 to 0.87 at high load (0.9 pu) in both motoring and regenerative modes. Additionally, to improve the robustness of speed estimation, the full-order observer is augmented with an explicit stabilization function. The stabilization function is obtained from the dot product of stator current and flux and is used to minimize oscillations and instability during low-speed motoring and regenerative modes, including under parameter variations and transients. The proposed speed estimator is evaluated by comparing the estimated speed with the motor speed across several EV driving profiles, including motoring, constant-speed, low- and zero-speed, and regenerative modes. The results show stable operation under load–torque disturbances and accurate speed tracking across the tested profiles, demonstrating that the proposed online current-optimizing MTPA strategy and stabilization-function-enhanced full-order observer are effective for sensorless SynRM traction control.