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author:

Lin, Xinyou (Lin, Xinyou.) [1] (Scholars:林歆悠) | Zhang, Guangji (Zhang, Guangji.) [2] | Wei, Shenshen (Wei, Shenshen.) [3] | Yin, Yanli (Yin, Yanli.) [4]

Indexed by:

EI Scopus SCIE

Abstract:

The drive range of electric vehicle (EV) is one of the major limitations that impedes its universalism. A great deal of research has been devoted to drive range improvement of EV, an accurate and efficiency energy consumption estimation plays a crucial role in these researches. However, the majority of EV's energy consumption estimation models are based on single motor EV, these models are not suitable for dual-motor EVs, which are composed of more complex transmission mechanisms and multiple operating modes. Thus, an energy consumption estimation model for dual-motor EV is proposed to estimate battery power. This article focuses on studying the operating modes and system efficiency in each operating mode. The limitation of working area of each mode ensures the vehicle dynamic performance, then PSO algorithm is adopted to optimize the torque (speed) distribution between two motors to improve the system efficiency in the coupled driving mode. Finally, the energy consumption estimation model is established by multiple linear regression (MLR). The result shows that the proposed model has a high precision in energy consumption estimation of dual-motor EV.

Keyword:

dual-motor electric vehicles efficiency optimization Energy consumption MLR PSO algorithm

Community:

  • [ 1 ] [Lin, Xinyou]Fuzhou Univ, Coll Mech Engn & Automat, Fuzhou, Peoples R China
  • [ 2 ] [Zhang, Guangji]Fuzhou Univ, Coll Mech Engn & Automat, Fuzhou, Peoples R China
  • [ 3 ] [Wei, Shenshen]Fuzhou Univ, Coll Mech Engn & Automat, Fuzhou, Peoples R China
  • [ 4 ] [Lin, Xinyou]Chongqing Univ Technol, Key Lab Adv Manufacture Technol Automobile Parts, Minist Educ, Chongqing, Peoples R China
  • [ 5 ] [Yin, Yanli]Chongqing Jiaotong Univ, Sch Mechatron & Vehicle Engn, Chongqing, Peoples R China

Reprint 's Address:

  • 林歆悠

    [Lin, Xinyou]Fuzhou Univ, Coll Mech Engn & Automat, Fuzhou, Peoples R China

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Source :

INTERNATIONAL JOURNAL OF GREEN ENERGY

ISSN: 1543-5075

Year: 2020

Issue: 8

Volume: 17

Page: 488-500

2 . 4 5 9

JCR@2020

3 . 1 0 0

JCR@2023

ESI Discipline: ENGINEERING;

ESI HC Threshold:132

JCR Journal Grade:2

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count: 9

SCOPUS Cited Count: 11

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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