
Predictive torque control of electric vehicle
Author(s) -
Mohammed El Amin Abdelkoui,
Abdeldjebar Hazzab
Publication year - 2019
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v9i5.pp3522-3530
Subject(s) - control theory (sociology) , torque , stator , electric vehicle , direct torque control , induction motor , robustness (evolution) , transient (computer programming) , inverter , vector control , computer science , model predictive control , traction (geology) , automotive engineering , engineering , voltage , control (management) , physics , electrical engineering , mechanical engineering , power (physics) , biochemistry , chemistry , quantum mechanics , artificial intelligence , gene , thermodynamics , operating system
The following article represents the development of a traction system of an electrical vehicle (EV) that consist of two Three-phase squirel-cage induction motors (IM) that permit the drive of the two front driving wheels. The two motors are controlled using the Predictive Torque Control (PTC) method; A technique based on the next step prediction and evaluation of the electromagnetic torque and stator flux In a cost function in order to determinate the inverter switching vector that minimize the error between references and predicted values. PTC is what we tried to underline in this paper, so we explain below the principle of the method; and the system mathematical description is provided. An electronic differential is applied on the system to control independently the speed of the two wheels at different operating conditions in order to characterize the driving wheel system behavior, the robustness in steady state and in transient state.