Thermal Parameter and State Estimation for Digital Twins of E-Powertrain Components

Abstract

The performance of powertrain components in electric vehicles is tightly intertwined with their thermal behavior. In practical applications, their temperature must be monitored and kept below certain thresholds to avoid performance drops and failure. Sensors, however, cannot always be placed at critical locations. Instead, it is possible to use numerical models to estimate relevant magnitudes during system operation. Thermal effects in electric and electronic components can be represented in a compact way using lumped-parameter equivalent circuits. These can be combined with sensor readings from the device under study to develop digital twins and use them to monitor temperatures during test and operation. In this paper, we put forward a method to generate thermal digital twins of e-powertrain elements such as power inverters. The thermal equivalent circuit equations are obtained from a general-purpose simulation software tool and optimized to enable real-time execution. Kalman filters are then used to fuse the simulation results from this model and sensor measurements of component temperatures. The proposed method provides a way to estimate the inputs and parameters of the thermal circuit and can be used to avoid the drift of the simulation away from actual component behavior. The performance of this approach is demonstrated with a simple benchmark example and the thermal equivalent circuit of a three-phase inverter.

Keywords

• Digital twin
• e-powertrain components
• Kalman filter
• lumped-parameter thermal network
• model-based monitoring
• thermal equivalent circuit