Model Predictive Torque Control-Based Induction Motor Drive with Remote Control and Monitoring Interface for Electric Vehicles

While the increased use of internal combustion engine vehicles raises carbon emissions, electric vehicles (EVs) are becoming more important for reducing air pollution. EV production costs are decreasing as technology advances since they are typically powered by alternating current induction machines (ACIM). In EV configurations that are propelled with ACIM, an inverter is required to obtain appropriate voltage levels to drive the IM. Multilevel inverters are widely preferred in the industry for DC-AC voltage conversion due to their high-power quality. In this study, the ACIM is supplied with the appropriate voltage using an active neutral point clamped (ANPC) inverter. The ANPC inverter acting as ACIM driver is controlled with model predictive torque control. The simulation of the proposed ACIM drive has been performed with torque and speed control features to determine the operational features of the experimental test bench. Furthermore, the designed ACIM drive includes remote control and monitoring functions via an Internet of Things-based module. This allows for instant monitoring of the input, output, and current values of the ANPC inverter. The graphical monitoring function is used to track the speed and torque values of ACIM while the speed can be changed remotely via the web interface.

Automated summary

While internal combustion engine vehicles increase carbon emissions, electric vehicles (EVs) are becoming more important in reducing air pollution. EV production costs are decreasing due to advancements in technology, particularly in the use of alternating current induction machines (ACIM). This study explores the use of an active neutral point clamped (ANPC) inverter to provide the appropriate voltage for the ACIM in EV configurations. The ANPC inverter is controlled using model predictive torque control and includes remote control and monitoring functions via an Internet of Things-based module.