parameter identification

The progressive digitalization is providing more and more measurement data from building operation, in particular from heating, cooling and ventilation (HVAC) systems. This work investigates the potential use of data-driven models to simulate indoor environmental conditions, i.e. temperature and CO2 concentration, for fault detection applications.

Parameter identification techniques are a powerful tool for the determination of thermophysical properties of building components. However, their correct application often demands a certain degree of experience.Especially in short or/and heavily disturbed data sets a formal use of a parameter identification software can lead to completely wrong results.This paper illustrates these problems by means of some simulation calculations and encourages to a discussion about possible solutions.

The PASLINK test facilities and analysis procedures aim to obtain the thermal and solar characteristics of building components under real dynamic outdoor conditions. Both the analysis and the test methodology have evolved since the start of the PASSYS Project in 1985. A programme of upgrading the original PASSYS test cells has improved measurement accuracy. The emphasis has moved from steady state to dynamic methods with shorter test durations yielding improved information and more accurate results.