The benefits of utilizing Switched Reluctance Motor (SRM) drives in traction applications can be realized fully by improving the electromagnetic performance of the machine in the generating mode of operation. This is because the generating capability of an SRM drive could be utilized for regenerative braking and also for the machine to generate power for the vehicle while the engine is in operation. In this paper, a current profiling-based control strategy is proposed to reduce the torque ripple in an SRM drive in the generating mode. The reference current profile is determined using a multi-step computation method to minimize torque ripple and maximize the average torque. The reference current profile is derived based on the reference torque command by utilizing the torque–current–angle look up table. The flux linkage characteristics of the SRM are considered when deriving the phase reference current profile. Then, the performance of the proposed profiling method, analytical linear and cubic torque sharing functions (TSFs), and the average torque optimization scheme are compared using simulation results. Finally, an experimental correlation is performed to validate the efficacy of the proposed control scheme.

It is essential to experimentally evaluate a Switched Reluctance Motor’s (SRM) flux-linkage characteristics to verify that its magnetic behavior aligns with design targets. This paper presents the development of a novel, fully automated custom experimental test bed and a control model capable of characterizing the static self- and mutual flux linkages of a switched reluctance motor. The proposed setup is programmed with MATLAB/Simulink for automatic characterization across various rotor positions and excitation currents, which has not been previously addressed in the literature. The automated measurement algorithm is implemented and validated on a 70 kW, 18/12 propulsion SRM prototype. Flux-linkage data is obtained across a full 360° mechanical rotation, with self-flux linkages measured up to 210 A and mutual flux linkages up to 130 A. Experimental results indicate a maximum 6% deviation from the finite element analysis (FEA) results for mutual flux linkage and below 5% for self-flux linkage. The developed flux-linkage characterization approach demonstrates good accuracy and repeatability, enabling the construction of reliable flux–current–position datasets essential for SRM modeling and validation.