Grey prediction models for the standard limit of vehicle noise

With an increasing number of vehicles and increasing environmental protection requirements, countries have accelerated the rate of revision of automobile noise standards and legislation. Scientific prediction of the limiting values in future noise standards is helpful to promote the development of automobile noise reduction technology and measurement analysis technology. The development of noise standard limits has its own objective laws and is restricted to the current and future developments in automotive technology. The amplitude of noise will be reduced increasingly less in the future. Grey prediction theory can explore the variation rules by processing a few effective data. In this paper, grey theory is used to deal with the limited original data in the vehicle noise standard. Non-equal-interval quadratic fitting of the grey Verhulst direct model to predict the future noise standard limits is selected on the basis of calculation and comparison of different models. The Verhulst model is employed to describe the system development by using the characteristics of saturation. By means of quadratic fitting, the accuracy of the Verhulst model can be further improved. The simulation results show the validity and the accuracy of the model. The prediction result is useful for standards and regulations makers and for car manufacturers.

• Record URL:
  • https://doi.org/10.1177/0954407017701774
• Record URL:
  • http://journals.sagepub.com/doi/abs/10.1177/0954407017701774
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09544070
• Supplemental Notes:
  • Reprinted by permission of Sage Publications, Ltd.
• Authors:
  • Zhao, Zhendong
  • Hu, Changzheng
• Publication Date: 2018-6

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 973-979
• Serial:
  • Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
  • Volume: 232
  • Issue Number: 7
  • Publisher: Sage Publications Limited
  • ISSN: 0954-4070
  • EISSN: 2041-2991
  • Serial URL: http://pid.sagepub.com/content/current

Subject/Index Terms

• TRT Terms: Automobiles; Mathematical prediction; Noise; Standards
• Uncontrolled Terms: Grey models
• Subject Areas: Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01673907
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 27 2018 4:54PM