Optimal Sensor Placement for Thermal Virtual Sensing in electronic systems using Augmented Kalman Filtering

The estimation of thermal parameters varying during the lifecycle of Electronic Components and Systems (ECS) is enabled by Digital Twins (DTs). The estimation performance depends on the number and utility of the chosen sensing locations. Moreover, large thermal gradients in ECS may cause misleading measurements resulting in wrong estimates. The presented Optimal Sensor Placement (OSP) algorithm considers parameter uncertainties thanks to the utilized DT framework composed of an Augmented Kalman Filter employing a parameter dependent thermal Reduced Order Model. Robustness in the sensor selection process is enforced by providing the OSP algorithm with the thermal gradients in the candidate sensing locations. A simulation study highlights the validity of the proposed methodology and opens to experimental validation.