[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.1145/3548608.3559173acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiccirConference Proceedingsconference-collections
research-article

Estimation of centroid sideslip angle and roll angle of multi-axle special vehicle based on neural network

Published: 14 October 2022 Publication History

Abstract

Aiming at the problems of high test cost, nonlinear dynamics and uncertainty in the direct measurement of the side-slip angle and roll angle of the center of mass by the on-board sensors of multi-axis heavy-duty special vehicles, in order to realize the observation of steering instability under high maneuvering conditions, Neural Network (NN) is used to estimate the side-slip angle and roll angle of the vehicle center of mass., and use the Trucksim model verified by real vehicle experiments to obtain the data set required by the neural network. The neural network estimates the sideslip angle and roll angle through easily measurable variables. Finally, the effectiveness and reliability of the algorithm are further verified by simulation experiments.

References

[1]
JIN X, YIN G, CHEN N. Advanced Estimation Techniques for Vehicle System Dynamic State: A Survey[J]. Sensors, 2019, 19(19):4289.
[2]
CHINDAMO D, LENZO B, GADOLA M. On the Vehicle Sideslip Angle Estimation: A Literature Review of Methods, Models, and Innovations[J]. Applied Sciences, 2018, 8:355.
[3]
SELMANAJ D, CORNO M, PANZANI G, Robust Vehicle Sideslip Estimation Based on Kinematic Considerations[J]. IFAC-PapersOnLine, 2017, 50:14855-14860.
[4]
MOHAMED O, STEPHANT J, MEIZEL D. Simultaneous observation of the wheels’ torques and the vehicle dynamic state[J]. Vehicle System Dynamics, 2013, 51.
[5]
CHEN L, BIAN M, LUO Y, Tire–road friction coefficient estimation based on the resonance frequency of in-wheel motor drive system[J]. Vehicle System Dynamics, 2015.
[6]
LIAN Y F, ZHAO Y, HU L L, Cornering stiffness and sideslip angle estimation based on simplified lateral dynamic models for four-in-wheel-motor-driven electric vehicles with lateral tire force information[J]. International Journal of Automotive Technology, 2015, 16.
[7]
TIAN Y T, ZHANG Y, WANG X Y, Estimation of side-slip angle of electric vehicle based on square root unscented Kalman filter algorithm [J]. Journal of Jilin University: Engineering(Engineering and Technology Edition), 2018, 48(3):8.
[8]
CHEROUAT H, BRACI M, DIOP S. Vehicle velocity, side slip angles and yaw rate estimation[M]. 2005:349-354.
[9]
DING N, CHEN W, ZHANG Y, An extended Luenberger observer for estimation of vehicle sideslip angle and road friction[J]. International Journal of Vehicle Design, 2014, 66:385.
[10]
ZHANG H, ZHANG G, WANG J. Sideslip Angle Estimation of An Electric Ground Vehicle via Finite-frequency H∞ Approach[J]. IEEE Transactions on Transportation Electrification, 2015, 2:1-1.
[11]
CHEN T, CHEN L, XU X, Robust sideslip angle observer with regional stability constraint for an uncertain singular intelligent vehicle system[J]. IET Control Theory & Applications, 2018, 12.
[12]
CHEN Y, JI Y, GUO K. A reduced-order nonlinear sliding mode observer for vehicle slip angle and tyre forces[J]. Vehicle System Dynamics, 2014, 52.
[13]
ZHAO J, ZHANG J, ZHU B. Coordinative traction control of vehicles based on identification of the tyre-road friction coefficient[J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2015, 230.
[14]
NAM K, OH S, FUJIMOTO H, Estimation of Sideslip and Roll Angles of Electric Vehicles Using Lateral Tire Force Sensors Through RLS and Kalman Filter Approaches[J]. Industrial Electronics, IEEE Transactions on, 2013, 60:988-1000.
[15]
LIN F, WANG S B, ZHAO Y Q, Road Friction Coefficient Estimation Based on Improved Keras Model [J]. Chinese Journal of Mechanical Engineering, 2021.
[16]
ZHANG J, WANG F, WANG K, Data-Driven Intelligent Transportation Systems: A Survey[J]. IEEE Transactions on Intelligent Transportation Systems, 2011, 12(4):1624-1639.
[17]
WEI Y, ZHANG X, SHI Y, A review of data-driven approaches for prediction and classification of building energy consumption[J]. Renewable and Sustainable Energy Reviews, 2017, 82.
[18]
SASAKI H, NISHIMAKI T. A SideSlip Angle Estimation Using Neural Network for a Wheeled Vehicle[J], 2000.
  1. Estimation of centroid sideslip angle and roll angle of multi-axle special vehicle based on neural network

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICCIR '22: Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics
    June 2022
    905 pages
    ISBN:9781450397179
    DOI:10.1145/3548608
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 14 October 2022

    Permissions

    Request permissions for this article.

    Check for updates

    Qualifiers

    • Research-article
    • Research
    • Refereed limited

    Conference

    ICCIR 2022

    Acceptance Rates

    Overall Acceptance Rate 131 of 239 submissions, 55%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 36
      Total Downloads
    • Downloads (Last 12 months)17
    • Downloads (Last 6 weeks)5
    Reflects downloads up to 28 Jan 2025

    Other Metrics

    Citations

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    HTML Format

    View this article in HTML Format.

    HTML Format

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media