Thermal Stress Based Model Predictive Control of Electric Drives

The reliable operation of the power electronics system of an electric drive is a critical design target. Thermal cycling of the semiconductors in the power module is one of the main stressors. Active thermal control is a possibility to control the junction temperatures of power modules in order to reduce the thermal stress. In this paper, the finite control set model predictive control is designed for thermal stress based driving of electric drives converters. The optimal switching vector is selected using a multiparameter optimization that includes the current reference error, the additional thermal stress that a specific switching vector applies to each semiconductor, the temperature spread between semiconductors in the module, overall efficiency, and device constraints. This enables relieving the stress due to thermal cycles and reducing unsymmetrical fatigue of the modules chips while avoiding unnecessary losses. The approach is derived in theory and applied in simulation and experiment.


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