State-of-the-Art Methodologies for Self-Fault Detection, Diagnosis and Evaluation (FDDE) in Residential Heat Pumps

Francesco Pelella, Adelso Flaviano Passarelli, Belén Llopis-Mengual, Luca Viscito, Emilio Navarro-Peris and Alfonso William Mauro ()
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Francesco Pelella: Department of Industrial Engineering, Università degli Studi di Napoli–Federico II, P.le Tecchio 80, 80125 Naples, Italy
Adelso Flaviano Passarelli: Department of Industrial Engineering, Università degli Studi di Napoli–Federico II, P.le Tecchio 80, 80125 Naples, Italy
Belén Llopis-Mengual: Instituto Universitario de Investigación de Ingeniería Energética (IUIIE), Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain
Luca Viscito: Department of Industrial Engineering, Università degli Studi di Napoli–Federico II, P.le Tecchio 80, 80125 Naples, Italy
Emilio Navarro-Peris: Instituto Universitario de Investigación de Ingeniería Energética (IUIIE), Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain
Alfonso William Mauro: Department of Industrial Engineering, Università degli Studi di Napoli–Federico II, P.le Tecchio 80, 80125 Naples, Italy

Energies, 2025, vol. 18, issue 13, 1-21

Abstract: The European Union’s 2050 targets for decarbonization and electrification are promoting the widespread integration of heat pumps for space heating, cooling, and domestic hot water in buildings. However, their energy and environmental performance can be significantly compromised by soft faults, such as refrigerant leakage or heat exchanger fouling, which may reduce system efficiency by up to 25%, even with maintenance intervals every two years. As a result, the implementation of self-fault detection, diagnosis, and evaluation (FDDE) tools based on operational data has become increasingly important. The complexity and added value of these tools grow as they progress from simple fault detection to quantitative fault evaluation, enabling more accurate and timely maintenance strategies. Direct fault measurements are often unfeasible due to spatial, economic, or intrusiveness constraints, thus requiring indirect methods based on low-cost and accessible measurements. In such cases, overlapping fault symptoms may create diagnostic ambiguities. Moreover, the accuracy of FDDE approaches depends on the type and number of sensors deployed, which must be balanced against cost considerations. This paper provides a comprehensive review of current FDDE methodologies for heat pumps, drawing insights from the academic literature, patent databases, and commercial products. Finally, the role of artificial intelligence in enhancing fault evaluation capabilities is discussed, along with emerging challenges and future research directions.

Keywords: heat pumps; fault detection and diagnosis; fault evaluation; state-of-the-art review; patents (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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