期刊
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
卷 58, 期 1, 页码 742-752出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIA.2021.3131973
关键词
Torque; Predictive models; Induction motors; Stators; Inductance; Adaptation models; Voltage control; Adaptive full order observer (AFO); bidirectional dc-dc converter; electric vehicle (EV); predictive torque control (PTC); torque ripple
资金
- Department of Science and Technology [RP03195, RP03128]
This article presents a sliding model-based predictive torque control (S-PTC) method for an induction motor in electric vehicle applications. The control algorithm is verified experimentally to demonstrate its effectiveness and robustness.
This article presents a sliding model-based predictive torque control (S-PTC) of an induction motor for the electric vehicle application. In this work, a battery-operated bidirectional converter fed induction machine-driven power train system is considered. In the conventional predictive torque control (C-PTC), only the machine model is used for the prediction of stator flux, current, and electromagnetic torque. Unlike the C-PTC, the presented control scheme offers a nonlinear switching feedback term in the prediction equation to overcome the model uncertainties, disturbances, and variation in motor parameters. The gains of the feedback terms are selected based on the Lyapunov stability criterion. Adaptive full order observer is used for the estimation of speed and rotor flux. This method is implemented and the speed response and torque ripple of the motor are analyzed for various operating modes of the vehicle. The robustness of the control is verified for variation in motor parameters and a comparison is shown to justify the achievement of objectives through S-PTC than with C-PTC. The control algorithm for the developed system is verified experimentally through the laboratory prototype.
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