The Multi-objective Optimization of Cost, Energy Consumption and Battery Degradation for Fuel Cell-Battery Hybrid Electric Vehicle

Jiageng Ruan; Bin Zhang; Bendong Liu; Shuo Wang

doi:10.1109/CPEEE51686.2021.9383396

The Multi-objective Optimization of Cost, Energy Consumption and Battery Degradation for Fuel Cell-Battery Hybrid Electric Vehicle

Jiageng Ruan
, Bin Zhang
, Bendong Liu
, Shuo Wang^*

^*Corresponding author for this work

School of Mechanical Engineering

Beijing University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

18 Citations (Scopus)

Abstract

As one of the promising solutions to air pollution and energy crisis caused by the transportation sector, fuel cell hybrid electric vehicles (FC HEVs) attract great attention around the world. Given the under power of the fuel cell to meet the requirements of daily driving, a power supplement system, generally battery, is essential to make up a multi-power hybrid powertrain. In this paper, the power matching strategies are optimized, considering the system cost, energy efficiency, and battery degradation, by particle swarm optimization (PSO) algorithm. Based on the change of the degree of hybridization (DOH), two hybrid systems are proposed, and the corresponding optimal hybridization degrees of the hybrid powertrain are found under four groups of weighting factors. Based on multi-objective optimization, the optimal degrees powertrain hybridization of the hybrid are proposed to extend battery life, improve energy consumption, and reduce powertrain cost according to individual requirements.

Original language	English
Title of host publication	2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	50-55
Number of pages	6
ISBN (Electronic)	9781728177175
DOIs	https://doi.org/10.1109/CPEEE51686.2021.9383396
Publication status	Published - 26 Feb 2021
Event	11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021 - Virtual, Shiga, Japan Duration: 26 Feb 2021 → 28 Feb 2021

Publication series

Name	2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021

Conference

Conference	11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021
Country/Territory	Japan
City	Virtual, Shiga
Period	26/02/21 → 28/02/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Battery
electric vehicle
fuel cell
optimization
particle swarm optimization

Access to Document

10.1109/CPEEE51686.2021.9383396

Cite this

Ruan, J., Zhang, B., Liu, B., & Wang, S. (2021). The Multi-objective Optimization of Cost, Energy Consumption and Battery Degradation for Fuel Cell-Battery Hybrid Electric Vehicle. In 2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021 (pp. 50-55). Article 9383396 (2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CPEEE51686.2021.9383396

Ruan, Jiageng ; Zhang, Bin ; Liu, Bendong et al. / The Multi-objective Optimization of Cost, Energy Consumption and Battery Degradation for Fuel Cell-Battery Hybrid Electric Vehicle. 2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 50-55 (2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021).

@inproceedings{4620f61fe42f4ac6acc4906887f9c597,

title = "The Multi-objective Optimization of Cost, Energy Consumption and Battery Degradation for Fuel Cell-Battery Hybrid Electric Vehicle",

abstract = "As one of the promising solutions to air pollution and energy crisis caused by the transportation sector, fuel cell hybrid electric vehicles (FC HEVs) attract great attention around the world. Given the under power of the fuel cell to meet the requirements of daily driving, a power supplement system, generally battery, is essential to make up a multi-power hybrid powertrain. In this paper, the power matching strategies are optimized, considering the system cost, energy efficiency, and battery degradation, by particle swarm optimization (PSO) algorithm. Based on the change of the degree of hybridization (DOH), two hybrid systems are proposed, and the corresponding optimal hybridization degrees of the hybrid powertrain are found under four groups of weighting factors. Based on multi-objective optimization, the optimal degrees powertrain hybridization of the hybrid are proposed to extend battery life, improve energy consumption, and reduce powertrain cost according to individual requirements.",

keywords = "Battery, electric vehicle, fuel cell, optimization, particle swarm optimization",

author = "Jiageng Ruan and Bin Zhang and Bendong Liu and Shuo Wang",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021 ; Conference date: 26-02-2021 Through 28-02-2021",

year = "2021",

month = feb,

day = "26",

doi = "10.1109/CPEEE51686.2021.9383396",

language = "English",

series = "2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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address = "United States",

}

Ruan, J, Zhang, B, Liu, B & Wang, S 2021, The Multi-objective Optimization of Cost, Energy Consumption and Battery Degradation for Fuel Cell-Battery Hybrid Electric Vehicle. in 2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021., 9383396, 2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021, Institute of Electrical and Electronics Engineers Inc., pp. 50-55, 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021, Virtual, Shiga, Japan, 26/02/21. https://doi.org/10.1109/CPEEE51686.2021.9383396

The Multi-objective Optimization of Cost, Energy Consumption and Battery Degradation for Fuel Cell-Battery Hybrid Electric Vehicle. / Ruan, Jiageng; Zhang, Bin; Liu, Bendong et al.
2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 50-55 9383396 (2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - The Multi-objective Optimization of Cost, Energy Consumption and Battery Degradation for Fuel Cell-Battery Hybrid Electric Vehicle

AU - Ruan, Jiageng

AU - Zhang, Bin

AU - Liu, Bendong

AU - Wang, Shuo

PY - 2021/2/26

Y1 - 2021/2/26

N2 - As one of the promising solutions to air pollution and energy crisis caused by the transportation sector, fuel cell hybrid electric vehicles (FC HEVs) attract great attention around the world. Given the under power of the fuel cell to meet the requirements of daily driving, a power supplement system, generally battery, is essential to make up a multi-power hybrid powertrain. In this paper, the power matching strategies are optimized, considering the system cost, energy efficiency, and battery degradation, by particle swarm optimization (PSO) algorithm. Based on the change of the degree of hybridization (DOH), two hybrid systems are proposed, and the corresponding optimal hybridization degrees of the hybrid powertrain are found under four groups of weighting factors. Based on multi-objective optimization, the optimal degrees powertrain hybridization of the hybrid are proposed to extend battery life, improve energy consumption, and reduce powertrain cost according to individual requirements.

AB - As one of the promising solutions to air pollution and energy crisis caused by the transportation sector, fuel cell hybrid electric vehicles (FC HEVs) attract great attention around the world. Given the under power of the fuel cell to meet the requirements of daily driving, a power supplement system, generally battery, is essential to make up a multi-power hybrid powertrain. In this paper, the power matching strategies are optimized, considering the system cost, energy efficiency, and battery degradation, by particle swarm optimization (PSO) algorithm. Based on the change of the degree of hybridization (DOH), two hybrid systems are proposed, and the corresponding optimal hybridization degrees of the hybrid powertrain are found under four groups of weighting factors. Based on multi-objective optimization, the optimal degrees powertrain hybridization of the hybrid are proposed to extend battery life, improve energy consumption, and reduce powertrain cost according to individual requirements.

KW - Battery

KW - electric vehicle

KW - fuel cell

KW - optimization

KW - particle swarm optimization

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U2 - 10.1109/CPEEE51686.2021.9383396

DO - 10.1109/CPEEE51686.2021.9383396

M3 - Conference contribution

AN - SCOPUS:85103981398

T3 - 2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021

SP - 50

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BT - 2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021

Y2 - 26 February 2021 through 28 February 2021

ER -

Ruan J, Zhang B, Liu B, Wang S. The Multi-objective Optimization of Cost, Energy Consumption and Battery Degradation for Fuel Cell-Battery Hybrid Electric Vehicle. In 2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 50-55. 9383396. (2021 11th International Conference on Power, Energy and Electrical Engineering, CPEEE 2021). doi: 10.1109/CPEEE51686.2021.9383396

The Multi-objective Optimization of Cost, Energy Consumption and Battery Degradation for Fuel Cell-Battery Hybrid Electric Vehicle

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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