On Using Quasi-Newton Algorithms of the Broyden Class for Model-to-Test Correlation

ABSTRACT: The correlation of a model with test results is a common task in engineering. Often genetic algorithms or adaptive particle swarm algorithms are used for this task. In this paper another approach is presented using two quasi-Newton algorithms of the class defined by Broyden. A study was conducted with thermal models showing the performance of this approach. Comparing the results to other studies reveals that the approach reduces the number of iterations by several orders of magnitude; typical calculation times for model correlation times are reduced from the order of weeks and months to the order of hours and days.