System and Component Level Risk Assessment for SiC MOSFET Based Inverter for Traction Application at High Coolant Temperatures and Off-Road Mission Profile

Abstract

Monitoring and predicting temperatures at critical locations of a power electronic system is important for safety, reliability, and efficiency. As the market share of vehicles with electric powertrains continues to increase, there is also an important economic cost of failing electronic components. For inverters present in such a drive system, exceeding the temperature limit for certain critical components, such as DC-link capacitors and Silicon carbide MOSFETs, can lead to failure of the system. In such an application, extracting the temperatures using sensors from locations such as dies and capacitors require expensive modifications and poses technical challenges. It is therefore necessary to create a thermal model for the inverter system to estimate the temperature at various components in order to ensure operation within temperature limits. The model approach is also suitable for predicting the effect on the component temperature and reliability of boundary conditions such as coolant, ambient temperature, and mission profile. This study assesses the reliability of a 250 kW liquid cooled inverter system designed for traction application. The critical failure areas are the DC-link capacitors, and the SiC MOSFET dies, which are rated at 175 °C. The system is modeled as a compact system by reasonably considering each component as a lumped capacitance and estimating the thermal resistance using physical dimensions. Results from the model are then compared against experimental data from constant power testing, and good agreement is observed for the cold plate and gate driver temperatures. With the model fidelity established, the model is then used to implement drive cycles from the Environmental Protection Agency for nonroad applications. The resulting temperature profile for each component is a series of temperature peaks and troughs that contribute to damage and failure. Rainflow counting algorithm is then used to quantify the damage per mini-cycles and used to estimate the predicted life for each component based on their manufacturer provided reliability qualification, and the mission profile is executed on the test bench for validation. The results are then used to generate a system risk matrix that relates the failure risk associated with a certain mission profile and the cooling scheme. It therefore demonstrates that an automotive inverter with SiC switching devices can be credibly assessed for failure risk using a compact model that is independent of boundary conditions, in combination with established reliability correlations and techniques.