Model-Based Active Thermal Management for Neutral-Point Clamped Power Converter with Adaptive Weight

Permanent Magnet Synchronous Machines (PMSM) are commonly used for Electric Vehicles (EV) to benefit from their higher torque and efficiency, better performance, and heat dissipation capability than an asynchronous machine. The reliability of the power converters of PMSM drives is crucial for EV operation and is mainly related to the junction temperature of semiconductor devices. During operation, semiconductors experience periodic heating and cooling processes, which causes thermal stress. This stress causes failures of the devices and increases maintenance costs. This paper uses the Finite Control Set Model Predictive Control (FCS-MPC) approach to provide active thermal management (ATM) for a motor drive system. Active thermal management is a method to reduce the thermal cycling of the semiconductor device in order to improve the reliability of the motor drive system. The proposed method uses the FCS-MPC method to predict the three-level Neutral-Point Clamped (3L-NPC) converter’s electro-thermal characteristic to find its optimum state. The speed reference is converted to the reference current via Field-Oriented Control (FOC), and a Cauer-thermal network is used to predict the junction temperature of the semiconductors. The mission objectives vary during the EV operation; thus, adaptive weighting is applied to the objective function to control thermal cycling effectively. The preliminary results of the proposed method show that thermal cycling can be managed to improve reliability, and FCS-MPC is a powerful tool to provide multi-objective control for EV powertrains.