Design and analysis of the speed and torque control of IM with DTC based in predictive control and load angle control for electric vehicle applications

Predictive control is a sophisticated kind of automation control. The primary aim is to regulate intricate industrial systems. The essence of this method is in utilising a dynamic model of the process within the controller in real-time to predict the future behaviour of the process. This command is suitable for managing intricate systems with several inputs and outputs, where the basic PID controller is inadequate. This method is especially intriguing when the systems experience substantial time lags, opposite reactions, and multiple interferences. This article introduces a novel approach to Direct Torque Control (DTC) for an induction motor used in electric vehicles or hybrids. The method involves controlling the load angle and utilizes straightforward equations to derive the control algorithm, making it easily comprehensible and implementable. Space vector modulation is utilized to provide a consistent switching frequency and minimize torque fluctuations. In the regulation of the velocity that propels the electric vehicle, we employ predictive control. The inputs to this system include the desired speed set by the driver through the vehicle's pedal, the measured speed obtained from the vehicle's wheel, and the opposing torque to forecast the future behaviour of the speed. This control approach specifically targets the main drawbacks of standard Direct Torque Control (DTC), such as restrictions in static and dynamic performance, complexity in structure and implementation, lack of decoupling, and issues with torque and current ripple.