Distributed Drive Electric Vehicle State Estimation based on Extended Kalman Filter

Xue Xue; Wang Zhenpo

doi:10.1016/j.egypro.2016.12.091

Distributed Drive Electric Vehicle State Estimation based on Extended Kalman Filter

Xue Xue^*, Wang Zhenpo

^*此作品的通讯作者

机械与车辆学院

Beijing Institute of Technology

科研成果: 期刊稿件 › 会议文章 › 同行评审

1 引用（Scopus）

摘要

This paper researched an estimation method based on Extended Kalman Filter (EKF) for distributed drive electric vehicle states. A 7 DOF closed-loop vehicle simulation platform including driver model of preview follower method and 'Magic formula' tire model was established. A general 2-input-1-output and 3 states estimation system was established, considering the white Gauss measurement noise. The estimation algorithm was applied to a four-motor-driven vehicle during a double-lane-change process. The results showed that EKF estimator could effectively estimate the states of distributed drive electric vehicle with varying speed under simulative experimental condition.

源语言	英语
页（从-至）	538-543
页数	6
期刊	Energy Procedia
卷	104
DOI	https://doi.org/10.1016/j.egypro.2016.12.091
出版状态	已出版 - 2016
活动	Applied Energy Symposium and Forum: Low - Carbon Cities and Urban Energy Systems, CUE 2016 - Jinan, 中国期限: 13 6月 2016 → 15 6月 2016

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@article{44d1d482078244d3af8718ee6db0f4a3,

title = "Distributed Drive Electric Vehicle State Estimation based on Extended Kalman Filter",

abstract = "This paper researched an estimation method based on Extended Kalman Filter (EKF) for distributed drive electric vehicle states. A 7 DOF closed-loop vehicle simulation platform including driver model of preview follower method and 'Magic formula' tire model was established. A general 2-input-1-output and 3 states estimation system was established, considering the white Gauss measurement noise. The estimation algorithm was applied to a four-motor-driven vehicle during a double-lane-change process. The results showed that EKF estimator could effectively estimate the states of distributed drive electric vehicle with varying speed under simulative experimental condition.",

keywords = "Extended Kalman Filter, distributed drive electric vehicle, state estimation",

author = "Xue Xue and Wang Zhenpo",

note = "Publisher Copyright: {\textcopyright} 2016 The Authors. Published by Elsevier Ltd.; Applied Energy Symposium and Forum: Low - Carbon Cities and Urban Energy Systems, CUE 2016 ; Conference date: 13-06-2016 Through 15-06-2016",

year = "2016",

doi = "10.1016/j.egypro.2016.12.091",

language = "English",

volume = "104",

pages = "538--543",

journal = "Energy Procedia",

issn = "1876-6102",

publisher = "Elsevier B.V.",

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TY - JOUR

T1 - Distributed Drive Electric Vehicle State Estimation based on Extended Kalman Filter

AU - Xue, Xue

AU - Zhenpo, Wang

PY - 2016

Y1 - 2016

N2 - This paper researched an estimation method based on Extended Kalman Filter (EKF) for distributed drive electric vehicle states. A 7 DOF closed-loop vehicle simulation platform including driver model of preview follower method and 'Magic formula' tire model was established. A general 2-input-1-output and 3 states estimation system was established, considering the white Gauss measurement noise. The estimation algorithm was applied to a four-motor-driven vehicle during a double-lane-change process. The results showed that EKF estimator could effectively estimate the states of distributed drive electric vehicle with varying speed under simulative experimental condition.

AB - This paper researched an estimation method based on Extended Kalman Filter (EKF) for distributed drive electric vehicle states. A 7 DOF closed-loop vehicle simulation platform including driver model of preview follower method and 'Magic formula' tire model was established. A general 2-input-1-output and 3 states estimation system was established, considering the white Gauss measurement noise. The estimation algorithm was applied to a four-motor-driven vehicle during a double-lane-change process. The results showed that EKF estimator could effectively estimate the states of distributed drive electric vehicle with varying speed under simulative experimental condition.

KW - Extended Kalman Filter

KW - distributed drive electric vehicle

KW - state estimation

UR - http://www.scopus.com/inward/record.url?scp=85013072481&partnerID=8YFLogxK

U2 - 10.1016/j.egypro.2016.12.091

DO - 10.1016/j.egypro.2016.12.091

M3 - Conference article

AN - SCOPUS:85013072481

SN - 1876-6102

VL - 104

SP - 538

EP - 543

JO - Energy Procedia

JF - Energy Procedia

T2 - Applied Energy Symposium and Forum: Low - Carbon Cities and Urban Energy Systems, CUE 2016

Y2 - 13 June 2016 through 15 June 2016

ER -

Distributed Drive Electric Vehicle State Estimation based on Extended Kalman Filter

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