Title :
Induction machine DTC optimization using artificial intelligence for EV´s applications
Author :
Hachicha, M.R. ; Ghariani, M. ; Neji, R.
Author_Institution :
Lab. of Electron. & Inf. Technol. (LETI), Nat. Sch. of Eng. of Sfax, Sfax, Tunisia
Abstract :
A three-phase squirrel-cage induction motor is used as a propulsion system of an electric vehicle (EV). The motor is controlled at different operating conditions using a direct torque control (DTC) technique known to have simple control structure with comparable performance. Whereas in a conventional DTC drive, the weakest points is the optimal voltage space vector choice. In this paper Artificial Intelligence is used to achieve an optimal selection of voltage space vectors. The European drive cycle ECE-15 is used for validation. The simulation results show that the proposed DTC optimization using artificial intelligence scheme for induction motors is a good candidate for EVs propulsion.
Keywords :
artificial intelligence; control engineering computing; electric propulsion; electric vehicles; machine control; optimisation; power engineering computing; squirrel cage motors; torque control; EV applications; European drive cycle ECE-15; artificial intelligence scheme; direct torque control technique; electric vehicle; induction machine DTC optimization; propulsion system; three-phase squirrel-cage induction motor; voltage space vectors; Induction motors; Propulsion; Stators; Torque; Torque control; Vehicles; Artificial Intelligence; EVs propulsion; Electric vehicle; Induction motor; Road vehicle electric propulsion; direct torque control (DTC); voltage space vectors;
Conference_Titel :
Systems, Signals and Devices (SSD), 2011 8th International Multi-Conference on
Conference_Location :
Sousse
Print_ISBN :
978-1-4577-0413-0
DOI :
10.1109/SSD.2011.5767397
