A GA-based adaptive mechanism for sensorless vector control of induction motor drives for urban electric vehicles

Abstract

Induction motors are more attractive to car manufacturers because they are more robust and more costeffective to maintain in comparison with other types of electric machines. The evolution of their control makes themmore efficient and less expensive. However, a new control technique known as sensorless control is being used to simplifythe implementation of electric machines in electric vehicles. This technique involves replacing the flux and speed sensorswith an observer. The estimation of these elements is based on the measurement of currents and voltages. The mainpurpose of the present study is to design a novel robust structure of the sensorless vector control for an urban electricvehicle. The proposed structure aims to improve the accuracy of dynamics at low speeds, eliminate sensitivity to themachine’s parameters, and maintain the stability of the system even if the variation reaches high values. The speedestimation is ensured by an enhanced PI adaptation mechanism based on the full order Luenberger observer. The proofof this stability is based on the Lyapunov theorem. Moreover, a GA-based adaptive control is used for self-tuning of thestator resistance. By combining these techniques, we can enhance the efficiency and stability of the whole system.