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akaturk Academic measurement

Article detail · 2024

Evaluating weather impact on vehicles: a systematic review of perceived precipitation dynamics and testing methodologies

Journal

Engineering Research Express

ISSN 2631-8695

YÖKSİS OpenAlex Open access · hybrid SJR Q2 JCR Q2 Citations 14 Top 10% Percentile 92.5% FWCI 4.47
Year
2024
Type
review

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue Engineering Research Express
  • Catalog match (ISSN) Engineering Research Express
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

Abstract The performance of road vehicles degrades when driving in adverse weather conditions. Weather testing for vehicles is important to understand the impacts of precipitation on vehicle performance, such as driver visibility, autonomous sensor signal, tire traction, and structural integrity due to corrosion, to ensure safety. This tutorial summarizes the essential elements for performing realistic testing by applying physical and meteorological rationale to vehicle applications. Three major topics are identified as crucial steps for precise quantitative studies, including understanding the natural precipitation characteristics, estimating the perceived precipitation experienced by a moving vehicle, and selecting data collection strategies. The methods used in current practices to investigate the effects of rain and snow on road vehicles at common facilities of outdoor test tracks, drive-through weather chambers, and climatic wind tunnels are summarized. The testing techniques and relevant instrumentations are also discussed, with considerations of factors that influence the measured data, such as particle size distribution, precipitation intensity, wind-induced droplet dynamic events, accumulation behaviour, etc. The goals of this paper are to provide a tutorial with guidelines on designing weather testing experiments for road vehicles and to promote the idea of establishing standardized methodologies for realistic vehicle testing that facilitates accurate prediction of vehicle performance in adverse weather conditions.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

14 citations

OpenAlex cited_by_count (cache / database)

Authors

  1. W.Y. PAO
  2. MATEUS CARVOLHO
  3. LONG Lİ
  4. Clement Rouaix
  5. Martin Agelin-Chaab
  6. Horia Hangan
  7. İSMAİL GÜLTEPE TÜRK HAVA KURUMU ÜNİVERSİTESİ
  8. John Komar