Salp swarm algorithm based optimal speed control for electric vehicles

Abstract

The paper is all about the implementation of a novel bio-inspired metaheuristic
salp swarm algorithm (SSA) for speed control of brushless DC
(BLDC) motor drive that is run in sensorless control mode. The angular
speed of the motor is evaluated using an extended kalman filter, in which the
dynamics of the motor are nonlinear. The error in speeds between actual and
estimated is fed to the PID controller. To achieve the good transient
operation of the motor drive, the parameters of the PID are tuned with the
SSA. The optimum PID gains are determined by the minimization of integral
square error and then final optimum gains are validated on the laboratory
testbed. The proposed method is also tested in various cases to check the
performance of the drive. The experiments are also performed at low speeds
to know the superiority of the proposed method.