A new control technique for improving dynamic performance of mono inverter dual parallel induction motors in railway traction systems

This paper presents the use of particle swarm optimization (PSO) technique in order to find the best values of reference q axis currents, flux levels and slip frequency applied for adaptively control of mono inverter dual parallel (MIDP) induction motor drive systems. In most railway traction system applications, light railway vehicle bogie is actuated by two identical induction motors driven by a single inverter. Control of such a system is a hard task because two parallel connected induction motors may not be operated under exactly the same operating conditions at any time due to the slip-slide phenomenon. In order to satisfy good dynamic performance, the field oriented control method tailored with PSO based new method is used. The proposed control technique is based on the strategy that flux level in a motor can be optimized to operate at maximum efficiency for a given load torque and rotor speed. Moreover, a comparative study among master/slave, mean average, and new proposed PSO based control technique is presented and individual speed/torque performances are demonstrated under unbalanced motor loading conditions. The boundaries of PSO variables are limited with efficiency, magnetic saturation and inverter output voltage. This analysis is verified by simulations. Simulation results show that PSO is so efficient in order to find the optimum flux level. The new control technique is superior to the traditional ones in such a way that it has a faster torque response and reduced speed reference tracking error.