Selection of relevant features to detect and diagnose single and multiple simultaneous soft faults in air-source heat pumps

Abstract

Soft faults in air-source heat pump systems can cause various issues, such as decreased performance, increased energy consumption, and long-term damage. This paper presents a comprehensive modeling approach of air-source heat pumps that considers individual and simultaneous soft faults validated against empirical experiments from the literature, a perspective limited in previous research. The methodology is based on the simulation of fault-free and faulty system performance utilizing heat pump modeling software. The results are a selection of variables and their trends to select the appropriate features to detect and diagnose single and double soft faults. The model also computes the impacts of these combined faults on COP, revealing significant reductions. Specifically, combinations of overcharge with condenser fouling and undercharge with compressor valve leakages induce COP reductions ranging from 17% to 38%, depending on operating conditions. The model can be used to develop faulty heat pump data, which can be adapted to other system typologies and conditions and used as input for data-driven Fault Detection and Diagnosis (FDD) methodologies.