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Développement d'une méthodologie d'analyse comparative de performances basée sur les données pour un grand nombre de conditionneurs d'air d'autobus.

Development of data-driven performance benchmarking methodology for a large number of bus air conditioners.

Auteurs : CHEN Z., GUO F., XIAO F., JIN X., SHI J., HE W.

Type d'article : Article de la RIF

Résumé

Bus air conditioners (ACs) are responsible for providing a comfortable cabin environment for passengers. Identifying the bus ACs with degraded performance from a large number of city buses is a critical and challenging task in the development of smart cities. This study developed a data-driven benchmarking methodology to detect anomalous operations with degraded energy performance from a large number of bus ACs. For each target AC to be benchmarked, its similar operation data in other ACs, termed comparable peer samples, are first identified by a Long-Short-Term-Memory (LSTM) autoencoder-based similarity measurement method. The comparable peer samples are then used to develop a LSTM network-based reference model for predicting the power consumption of the target AC. A key energy performance indicator termed power consumption ratio (PCR) is defined for the target AC as the ratio of its measured power to the predicted power. Statistical analysis-based trend and change detection algorithms are designed to identify a trend or change of PCR over a few days for anomalous detection. To validate the benchmarking methodology, two fault experiments were conducted in field-operating bus ACs, and the results show encouraging potentials of the proposed methodology for health monitoring of a large number of ACs serving the city bus fleet.

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Format PDF

Pages : 105-118

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Détails

  • Titre original : Development of data-driven performance benchmarking methodology for a large number of bus air conditioners.
  • Identifiant de la fiche : 30031537
  • Langues : Anglais
  • Sujet : Technologie
  • Source : International Journal of Refrigeration - Revue Internationale du Froid - vol. 149
  • Date d'édition : 05/2023
  • DOI : http://dx.doi.org/10.1016/j.ijrefrig.2022.12.027

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