Thermal-based finite control set model predictive control for IGBT power electronic converters

Abstract

Abstract-Thermal cycling is one of the main sources of aging and failure in power electronics. A possibility to reduce the thermal stress of semiconductors is to control the losses occurring in the semiconductor devices with the target to reduce the thermal cycles. This approach is known as active thermal control. The hardest limit of the existing active thermal control approaches is that they do not offer a general framework where the optimal switching sequence is selected in order to fulfill the applications demand and reduce the thermal stress in specific semiconductors. The goal is to achieve the minimum thermal stress for the best possible overall performance. For this purpose finite control-set model predictive control (FCS-MPC) seems the optimal approach because it allows including of non-linear thermal and lifetime related models into the control law. A precise control of the thermal stress in the semiconductors can be achieved as the optimal switching vector is directly applied to the physical system. This allows to avoid overrating of the used module or to increase its lifetime. In the paper the approach is proven using simulation and experimental results.

Junction Temperature Control for More Reliable Power Electronics

“…The limit of modulator based active thermal control structures is that they cannot reduce the thermal stress in a specific semiconductor, as the conductivity and switching of the semiconductors in the converter is selected by the modulator. In [42] a thermal controller is presented, that applies a Finite Control-Set Model Predictive Control (FCS-MPC) in order to achieve a more precise junction temperature control. The predictive control selects the optimal switching vector, that fulfills the applications demand and reduces the thermal stress.…”

Active and Reactive Power Control based on an Inner Predictive Voltage Control Loop for AC generation systems with Direct Matrix Converter

“…The control objectives in the MPC are represented by a cost function, which evaluates the errors between the references and the actual values of the variables of interest. In addition, it is possible to add some additional control objectives such as temperature control and minimisation of commutation and conduction losses [19], common mode voltages reduction [20], among others. Also, non-linear operations, such as restrictions and limitations can be easily added, greatly increasing the flexibility and richness of the control strategy.…”

Predictive Voltage Control of the Direct Matrix Converter applied to Grid Current Injection

“…Los objetivos de control en el MPC son representados mediante una función de costo, la cual evalúa los errores entre las referencias y los valores reales de las variables de interés. Además, es posible agregar algunos objetivos de control adicionales como control de temperatura y minimización de las pérdidas por conmutación y conducción [16], tensiones de modo común [17], entre otros. Así también, operaciones no lineales, como restricciones y limitaciones pueden ser fácilmente agregadas, aumentando en gran medida la flexibilidad y riqueza de la estrategia de control.…”