An Intelligent System-on-a-Chip for a Real-Time Assessment of Fuel Consumption to Promote Eco-Driving

被引:10
|
作者
Mata-Carballeira, Oscar [1 ]
Diaz-Rodriguez, Mikel [1 ]
del Campo, Ines [1 ]
Martinez, Victoria [1 ]
机构
[1] Univ Basque Country UPV EHU, Fac Sci & Technol, Dept Elect & Elect, Leioa 48940, Spain
来源
APPLIED SCIENCES-BASEL | 2020年 / 10卷 / 18期
关键词
advanced driving assistance systems (ADAS); ADAS on-board vehicles; fuel consumption; eco-driving; driving style; machine learning (ML); unsupervised clustering; self-organizing map (SOM); field-programmable gate array (FPGA); programmable system-on-a-chip (PSoC); NEURAL-NETWORK; AIR-POLLUTION; BEHAVIOR; FOOTPRINT; EMISSIONS; FEEDBACK; CITIES; DRIVER; CARBON;
D O I
10.3390/app10186549
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Pollution that originates from automobiles is a concern in the current world, not only because of global warming, but also due to the harmful effects on people's health and lives. Despite regulations on exhaust gas emissions being applied, minimizing unsuitable driving habits that cause elevated fuel consumption and emissions would achieve further reductions. For that reason, this work proposes a self-organized map (SOM)-based intelligent system in order to provide drivers with eco-driving-intended driving style (DS) recommendations. The development of the DS advisor uses driving data from the Uyanik instrumented car. The system classifies drivers regarding the underlying causes of non-optimal DSs from the eco-driving viewpoint. When compared with other solutions, the main advantage of this approach is the personalization of the recommendations that are provided to motorists, comprising the handling of the pedals and the gearbox, with potential improvements in both fuel consumption and emissions ranging from the 9.5% to the 31.5%, or even higher for drivers that are strongly engaged with the system. It was successfully implemented using a field-programmable gate array (FPGA) device of the Xilinx ZynQ programmable system-on-a-chip (PSoC) family. This SOM-based system allows for real-time implementation, state-of-the-art timing performances, and low power consumption, which are suitable for developing advanced driving assistance systems (ADASs).
引用
收藏
页数:33
相关论文
共 50 条
  • [1] Eco-driving using real-time optimization
    Kamal, M. A. S.
    Kawabe, T.
    2015 EUROPEAN CONTROL CONFERENCE (ECC), 2015, : 111 - 116
  • [2] Real-time eco-driving for connected electric vehicles
    Ngo, Caroline
    Solano-Araque, Edwin
    Aguado-Rojas, Missie
    Sciarretta, Antonio
    Chen, Bicheng
    El Baghdadi, Mohamed
    IFAC PAPERSONLINE, 2021, 54 (10): : 126 - 131
  • [3] Neurocomputing for minimizing energy consumption of real-time operating system in the system-on-a-chip
    Guo, Bing
    Wang, Dianhui
    Shen, Yan
    Li, Zhishu
    NEURAL INFORMATION PROCESSING, PT 3, PROCEEDINGS, 2006, 4234 : 1189 - 1198
  • [4] Real-time Driving Mode Advice for Eco-driving using MPC
    Chen, Yutao
    Lazar, Mircea
    IFAC PAPERSONLINE, 2020, 53 (02): : 13830 - 13835
  • [5] Real-Time Feedback Impacts on Eco-Driving Behavior and Influential Variables in Fuel Consumption in a Lisbon Urban Bus Operator
    Rolim, Catarina
    Baptista, Patricia
    Duarte, Goncalo
    Farias, Tiago
    Pereira, Joao
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2017, 18 (11) : 3061 - 3071
  • [6] A Real-time Eco-Driving Strategy for Automated Electric Vehicles
    Leon Ojeda, Luis
    Han, Jihun
    Sciarretta, Antonio
    De Nunzio, Giovanni
    Thibault, Laurent
    2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2017,
  • [7] Real-Time Implementation Comparison of Urban Eco-Driving Controls
    Rabinowitz, Aaron I.
    Ang, Chon Chia
    Mahmoud, Yara Hazem
    Araghi, Farhang Motallebi
    Meyer, Richard T.
    Kolmanovsky, Ilya
    Asher, Zachary D.
    Bradley, Thomas H.
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2024, 32 (01) : 143 - 157
  • [8] Advanced Real time IoT Eco-Driving Assistant System
    Jouini, Anis
    Cherif, Adnane
    Hasnaoui, Salem
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2022, 22 (04): : 237 - 244
  • [9] Uncertainties in Eco-Driving Instructions and Perceptions about Fuel Consumption Reduction Applying Eco-Driving Techniques
    Kreicbergs, J.
    Gailis, M.
    TRANSPORT MEANS 2015, PTS I AND II, 2015, : 119 - 122
  • [10] Development of a System to Promote Eco-Driving and Safe-Driving
    Ando, Ryosuke
    Nishihori, Yasuhide
    Ochi, Daisuke
    SMART SPACES AND NEXT GENERATION WIRED/WIRELESS NETWORKING, 2010, 6294 : 207 - +