Multi-objective optimal energy management strategy and economic analysis for an range-extended electric bus

Jun Qiu Li; Xin Jin; Rui Xiong

doi:10.1016/j.egypro.2016.06.133

Multi-objective optimal energy management strategy and economic analysis for an range-extended electric bus

Jun Qiu Li^*, Xin Jin, Rui Xiong

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

Research output: Contribution to journal › Conference article › peer-review

8 Citations (Scopus)

Abstract

An optimal energy management strategy is proposed to match engine fuel consumption and battery SOH of REEB. Models of APU fuel consumption and battery SOH loss are established and multi-objective performance function is provided. DP algorithm is adopted to solve the optimization problem. Under the conditions of different drive cycles, different SOH penalty coefficients are analyzed to reveal its effects. Considering the total life-cycle costs, simulations prove that when battery is not to be replaced, and the capacity configuration and SOH penalty coefficient of battery are both taken the minimum, the best economical results can be achieved.

Original language	English
Pages (from-to)	814-820
Number of pages	7
Journal	Energy Procedia
Volume	88
DOIs	https://doi.org/10.1016/j.egypro.2016.06.133
Publication status	Published - 1 Jun 2016
Event	Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems, CUE 2015 - Fuzhou, China Duration: 15 Nov 2015 → 17 Nov 2015

Keywords

Dynamic programming
Energy management
Multi-objective optimization
Range-extended electric vehicle

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10.1016/j.egypro.2016.06.133

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@article{ea00abce613d47c7b4b4d246391a2848,

title = "Multi-objective optimal energy management strategy and economic analysis for an range-extended electric bus",

abstract = "An optimal energy management strategy is proposed to match engine fuel consumption and battery SOH of REEB. Models of APU fuel consumption and battery SOH loss are established and multi-objective performance function is provided. DP algorithm is adopted to solve the optimization problem. Under the conditions of different drive cycles, different SOH penalty coefficients are analyzed to reveal its effects. Considering the total life-cycle costs, simulations prove that when battery is not to be replaced, and the capacity configuration and SOH penalty coefficient of battery are both taken the minimum, the best economical results can be achieved.",

keywords = "Dynamic programming, Energy management, Multi-objective optimization, Range-extended electric vehicle",

author = "Li, {Jun Qiu} and Xin Jin and Rui Xiong",

note = "Publisher Copyright: {\textcopyright} 2016 Published by Elsevier Ltd.; Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems, CUE 2015 ; Conference date: 15-11-2015 Through 17-11-2015",

year = "2016",

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day = "1",

doi = "10.1016/j.egypro.2016.06.133",

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journal = "Energy Procedia",

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TY - JOUR

T1 - Multi-objective optimal energy management strategy and economic analysis for an range-extended electric bus

AU - Li, Jun Qiu

AU - Jin, Xin

AU - Xiong, Rui

PY - 2016/6/1

Y1 - 2016/6/1

N2 - An optimal energy management strategy is proposed to match engine fuel consumption and battery SOH of REEB. Models of APU fuel consumption and battery SOH loss are established and multi-objective performance function is provided. DP algorithm is adopted to solve the optimization problem. Under the conditions of different drive cycles, different SOH penalty coefficients are analyzed to reveal its effects. Considering the total life-cycle costs, simulations prove that when battery is not to be replaced, and the capacity configuration and SOH penalty coefficient of battery are both taken the minimum, the best economical results can be achieved.

AB - An optimal energy management strategy is proposed to match engine fuel consumption and battery SOH of REEB. Models of APU fuel consumption and battery SOH loss are established and multi-objective performance function is provided. DP algorithm is adopted to solve the optimization problem. Under the conditions of different drive cycles, different SOH penalty coefficients are analyzed to reveal its effects. Considering the total life-cycle costs, simulations prove that when battery is not to be replaced, and the capacity configuration and SOH penalty coefficient of battery are both taken the minimum, the best economical results can be achieved.

KW - Dynamic programming

KW - Energy management

KW - Multi-objective optimization

KW - Range-extended electric vehicle

UR - http://www.scopus.com/inward/record.url?scp=85007530469&partnerID=8YFLogxK

U2 - 10.1016/j.egypro.2016.06.133

DO - 10.1016/j.egypro.2016.06.133

M3 - Conference article

AN - SCOPUS:85007530469

SN - 1876-6102

VL - 88

SP - 814

EP - 820

JO - Energy Procedia

JF - Energy Procedia

T2 - Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems, CUE 2015

Y2 - 15 November 2015 through 17 November 2015

ER -

Multi-objective optimal energy management strategy and economic analysis for an range-extended electric bus

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Keywords

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