Neural Networks - A Way to Increase the Fuel Efficiency of Vehicles

Q3 Engineering
T. Milesich, J. Danko, J. Bucha
{"title":"Neural Networks - A Way to Increase the Fuel Efficiency of Vehicles","authors":"T. Milesich, J. Danko, J. Bucha","doi":"10.2478/scjme-2018-0008","DOIUrl":null,"url":null,"abstract":"Abstract This paper deals with the possibility of creating a vehicle model using a hierarchy of neural networks. Based on this model, it is possible to build an optimization cycle that looks for parameters which are influencing the driving of vehicles along given path. The given path must include a driving through the town, out of town and along the highway section, so the test track contains the greatest number of driving modes. Data for neural network are obtained from the CAN bus and the GPS sensor. Based on the built model and given route it is looking for such route drive, where it eventually came that the development of fuel consumption is lower than in unoptimized drive.","PeriodicalId":35968,"journal":{"name":"Strojnicky Casopis","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Strojnicky Casopis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/scjme-2018-0008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 3

Abstract

Abstract This paper deals with the possibility of creating a vehicle model using a hierarchy of neural networks. Based on this model, it is possible to build an optimization cycle that looks for parameters which are influencing the driving of vehicles along given path. The given path must include a driving through the town, out of town and along the highway section, so the test track contains the greatest number of driving modes. Data for neural network are obtained from the CAN bus and the GPS sensor. Based on the built model and given route it is looking for such route drive, where it eventually came that the development of fuel consumption is lower than in unoptimized drive.
神经网络——一种提高车辆燃油效率的方法
摘要本文讨论了使用层次神经网络创建车辆模型的可能性。基于该模型,可以建立一个优化循环,寻找影响车辆沿给定路径行驶的参数。给定的路径必须包括穿过城镇、出城和沿着高速公路路段行驶,因此测试车道包含最多的驾驶模式。神经网络的数据是从CAN总线和GPS传感器获得的。根据建立的模型和给定的路线,它正在寻找这样的路线行驶,最终发现油耗的发展低于未优化的行驶。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Strojnicky Casopis
Strojnicky Casopis Engineering-Mechanical Engineering
CiteScore
2.00
自引率
0.00%
发文量
33
审稿时长
14 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信