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Integrated velocity prediction method and application in vehicle-environment cooperative control based on Internet of Vehicles

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posted on 2023-02-14, 10:11 authored by Yuanjian ZhangYuanjian Zhang, Zheng Chen, Guang Li, Yonggang Liu, Yanjun Huang, Geoff Cunningham, Juliana Early
Rapid progress has been gained in the field of advanced communication technologies, which also promote parallel developments in the Internet of Vehicles (IoVs). In this context, vehicle-environment cooperative control can be integrated into next-generation vehicles to further improve the vehicle's performance, in particular energy efficiency. Accurate prediction of future velocity profiles on basis of IoVs can be a critical breakthrough, which can contribute much to vehicle operation efficiency promotion. In this paper, an integrated velocity prediction (IVP) method fully taking advantage of IoVs is proposed and demonstrated through a case study. In the IVP method, both the macroscopically and microscopically predicted velocity profiles are considered. The macroscopic velocity profiles are predicted via traffic flow analysis (TFA) in multi-access edge computing units (MECUs) which are situated alongside the route. Microscopic velocity profiles are forecasted through Mondrian forest (MF) algorithm in the on-board vehicle control unit (VCU). Final velocity prediction is generated through combination of the macroscopic and microscopic profiles in frequency domain in on-board VCU through fast Fourier transform (FFT) and inverse FFT. A case study validates the distinguished performance of IVP method and demonstrates its significant contribution to vehicle performance improvement.

Funding

Research on Stratified Optimization Energy Management Strategy of Plug-in Hybrid Electric Vehicle Considering Traffic Information

National Natural Science Foundation of China

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Research on Predictive Energy Management Strategy of Intelligent Plug-in Hybrid Electric Vehicle Based on Multi-source Information Fusion

National Natural Science Foundation of China

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National Key R&D Program of China (No. 2018YFB0104000)

Hierarchical Optimal Energy Management of Electric Vehicles

European Commission

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History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

IEEE Transactions on Vehicular Technology

Volume

71

Issue

3

Pages

2639 - 2654

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Acceptance date

2021-12-26

Publication date

2021-12-31

Copyright date

2021

ISSN

0018-9545

eISSN

1939-9359

Language

  • en

Depositor

Dr Yuanjian Zhang. Deposit date: 13 February 2023