Efficient transient correlation of thermal lumped network models to reference data

Abstract

In this paper, an efficient algorithm for correlating the transient behaviour of thermal lumped models to reference data is reported. The algorithm is based on an iterative non-linear least-squares minimization process that allows for fast convergence. The correlation process requires the calculation of the so-called Moore–Penrose pseudoinverse of the Jacobian matrix. However, obtaining the transient Jacobian matrix can be computationally expensive for large models. A new method for calculating the transient Jacobian matrix of lumped thermal models, called Jacobian Propagation, is also presented. For large models, the Jacobian Propagation method, when combined with an implicit solver, has a negligible computational cost compared to the solving process. The correlation algorithm and the Jacobian Propagation method have been successfully tested with two thermal models, obtaining better performance than previous approaches.