Sensorless Direct Torque Control of Induction Motor using fuzzy logic controller applied to electric vehicle

Abstract

This paper treats a speed-sensorless drive of a three phase Induction Motor (squirrel-cage). The purpose is to implement an electric traction system, based on the use of 1M controlled by power electronic converter. This system allows the speed control of the vehicle, forward, backward and regenerative braking. The four quadrants operation is required. The developed control strategy is based on classical Direct Torque and Flux Control (DTC). Both rotor speed controller and rotor speed estimator are based on fuzzy logic controller (FLC). The obtained control performances are shown by simulation using MA TLAB and its toolbox SIMULINK.

Power optimisation scheme of induction motor using FLC for electric vehicle

“…The IM is more common to use for the traction drive and is the best candidate for EVs because of its strength, lower cost and low maintenance need [13][14][15][16], but its' losses are significantly higher in the EV application [17,18] and this leads to a drop in the machine efficiency. The most restrictive barriers to accepting such vehicles in the transport system are low energy density, heavier weight, longer charging times and longer battery life [19].…”

“…The synchronous motors and induction motors (IMs) are the main types of machines that can be utilised in EVs [9]. The EV‐drive motor should feature the following propulsion [7, 10–12]: (i) high torque density to give enough driving force during startup, climbing and acceleration; (ii) high efficiency to increase driving distance; (iii) good flow regulating ability to extend the static power speed range. The IM is more common to use for the traction drive and is the best candidate for EVs because of its strength, lower cost and low maintenance need [13–16], but its’ losses are significantly higher in the EV application [17, 18] and this leads to a drop in the machine efficiency. The most restrictive barriers to accepting such vehicles in the transport system are low energy density, heavier weight, longer charging times and longer battery life [19].…”

Direct Torque Control Induction Motor Drive for Speed Estimation Using Modified Particle Swarm Optimization Algorithm

“…This sensor, however, reduces the system reliability, increasing the cost of the drive, and is unsuitable for hostile environments. A number of speed estimation approaches for DTC IM drives have been developed, including from a stator flux estimator or observer, (3)(4)(5)(6)(7) by the application of adaptive control theory, (8)(9)(10)(11) from fuzzy logic control or a neural network, (12)(13)(14)(15) and using an extended Kalman filter. (16)(17)(18)(19) In this system, the Lyapunov stability theory was used to design a stator flux observer, and the rotor speed of the speed estimation DTC IM drive was estimated from this observer.…”

“…(12), if G and Q are selected to guarantee that the inequality in Eq. (13) is valid, then the time derivative of the defined Lyapunov function is a negative definite function.…”