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Ageing of refrigerated transport vehicles: development of a numerical predictive model.

Vieillissement des véhicules de transport frigorifique : développement d'un modèle prédictif numérique.

Résumé

Ageing is a common problem for refrigerated vehicles. It involves both physio-chemical and mechanical factors. This phenomenon is quantified by the comparison of the 𝐾 value of the in-service vehicles at twelve years of use with the 𝐾 value of their prototypes. The Datafrig® database, managed by Cemafroid, records more than 350 000 vehicles having almost one hundred features, including 𝐾 coefficient values. This amount of data opens up the opportunity to predict the ageing by building a numerical model, using supervised machine learning techniques. This paper presents the development of a model using a random forest algorithm. Results based on a first dataset, composed of 1158 vehicles extracted from the Datafrig® database, agree with the knowledge of the experts from field experience as well as with previous studies based on statistical analysis. After a careful feature selection, the mean percentage error reached by the model for this first dataset is estimated at 6%.

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Détails

  • Titre original : Ageing of refrigerated transport vehicles: development of a numerical predictive model.
  • Identifiant de la fiche : 30027606
  • Langues : Anglais
  • Sujet : Technologie
  • Source : 6th IIR International Conference on Sustainability and the Cold Chain. Proceedings: Nantes, France, August 26-28 2020
  • Date d'édition : 26/08/2020
  • DOI : http://dx.doi.org/10.18462/iir.iccc.2020.294815
  • Disponible à la bibliothèque de l'IIF

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