This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Coast Down Curve Computational Modeling and Its Influence on Urban and Highway Autonomy Results
ISSN: 0148-7191, e-ISSN: 2688-3627
Published November 07, 2017 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Currently, fuels development is strongly dependent on experiments. New engines and vehicles simulation methodologies contribute to speed up R & D projects deadlines, as well as reducing costs. This paper presents a modeling methodology for a vehicle deceleration load curve (coast down) prediction and simulations of coast down variations impact on urban and highway autonomies. Two coast down curve mathematical models were successfully developed and validated. The first one, based on vehicles technical specifications and empirical equations, resulted in percent differences up to 9% compared to the experimental results. This is lower than the variation established on coast down standard, which is 15%. The second, generated by regression analysis between other vehicles characteristics versus experimental results of F0 and F2 (coast down curve parameters), resulted in percent differences up to 15%, for six of the eight vehicles. A simulator of urban and highway autonomies as coast down load functions was successfully implemented. Their results presented differences of up to 1% compared to the experiments. The models and simulations presented in this paper show potential to decrease coast down and autonomies experimental tests, which require considerable human and material resources. In addition, coast down models may compensate the low coast down tracks tests availability. Their results could be used when it is not possible perform track tests.
|Journal Article||Verification of ABS Models Applied in Programs for Road Accident Simulation|
|Technical Paper||High-Frequency Terrain Content and Surface Interactions for Off-Road Simulations|
CitationVillela, A. and de Carvalho, R., "Coast Down Curve Computational Modeling and Its Influence on Urban and Highway Autonomy Results," SAE Technical Paper 2017-36-0319, 2017, https://doi.org/10.4271/2017-36-0319.
Data Sets - Support Documents
|Unnamed Dataset 1|
|Unnamed Dataset 2|
|Unnamed Dataset 3|
|Unnamed Dataset 4|
- EPE - Empresa de Pesquisa Energética Demanda de Energia 2050 2014
- ABNT - Associação Brasileira de Normas Técnicas NBR 6601: Veículos rodoviários automotores leves - Determinação de hidrocarbonetos, monóxido de carbono, óxidos de nitrogênio, dióxido de carbono e material particulado no gás de escapamento Rio de Janeiro 2012
- ABNT - Associação Brasileira de Normas Técnicas NBR 7024: Veículos rodoviários automotores leves - Medição do consumo de combustível - Método de ensaio Rio de Janeiro 2010
- ABNT - Associação Brasileira de Normas Técnicas NBR 10312: Veículos rodoviários automotores leves -Determinação da resistência ao deslocamento por desaceleração livre em pista de rolamento e simulação em dinamômetro Rio de Janeiro 2014
- PBEV - Programa Brasileiro de Etiquetagem Veicular http://www.conpet.gov.br/portal/conpet/pt_br/conteudo-gerais/etiquetagem-veicular.shtml
- Fox , R. W. , Mcdonald , A. T. , Pritchard , P. J. Introdução À Mecânica Dos Fluidos. Ltc 2014