Estimation of Optimal Energy Consumption for Fuel Cell Vehicle Based on Macroscopic Traffic Dynamics

Zihong Yang; Xingyu Zhou; Chao Sun; Xiaodong Wei

doi:10.1109/VPPC53923.2021.9699251

Estimation of Optimal Energy Consumption for Fuel Cell Vehicle Based on Macroscopic Traffic Dynamics

Zihong Yang, Xingyu Zhou, Chao Sun, Xiaodong Wei

School of Mechanical Engineering

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

Abstract

This paper addresses the estimation problem of the minimum required energy of fuel cell vehicle (FCV) driving through a road link conditioned on the current and future traffic states. The challenge is to estimate driving profile of individual vehicles and obtain the corresponding optimal energy consumption of powertrain. Combining the powertrain model and macroscopic traffic dynamics, the FCV tank-to-traffic energy dissipation model is established. Based on the optimal energy consumption within each road segment solved by dynamic programming, the optimal demand power field is obtained. According to the estimated driving profile, optimal segmental energy consumption (OSEC) is calculated by interpolation of optimal demand power field, whose summation is utilized as the estimator for global optimal accumulative energy consumption (GOAEC). The validation result indicates that the highest Pearson correlation coefficient between the sequence of OSEC and GOAEC reaches 0.86, while in the case of the poorest estimation performance, the sequences share a similar shape. The effective estimator for GOAEC provides the quantified evidence supporting decisions on route planning and velocity planning.

Original language	English
Title of host publication	2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665405287
DOIs	https://doi.org/10.1109/VPPC53923.2021.9699251
Publication status	Published - 2021
Event	18th IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - Virtual, Gijon, Spain Duration: 25 Oct 2021 → 28 Oct 2021

Publication series

Name	2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS

Conference

Conference	18th IEEE Vehicle Power and Propulsion Conference, VPPC 2021
Country/Territory	Spain
City	Virtual, Gijon
Period	25/10/21 → 28/10/21

Keywords

Energy consumption
Fuel cell vehicle
Optimal control
Traffic dynamics

UN SDGs

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

Access to Document

10.1109/VPPC53923.2021.9699251

Cite this

Yang, Z., Zhou, X., Sun, C., & Wei, X. (2021). Estimation of Optimal Energy Consumption for Fuel Cell Vehicle Based on Macroscopic Traffic Dynamics. In 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS (2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VPPC53923.2021.9699251

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title = "Estimation of Optimal Energy Consumption for Fuel Cell Vehicle Based on Macroscopic Traffic Dynamics",

abstract = "This paper addresses the estimation problem of the minimum required energy of fuel cell vehicle (FCV) driving through a road link conditioned on the current and future traffic states. The challenge is to estimate driving profile of individual vehicles and obtain the corresponding optimal energy consumption of powertrain. Combining the powertrain model and macroscopic traffic dynamics, the FCV tank-to-traffic energy dissipation model is established. Based on the optimal energy consumption within each road segment solved by dynamic programming, the optimal demand power field is obtained. According to the estimated driving profile, optimal segmental energy consumption (OSEC) is calculated by interpolation of optimal demand power field, whose summation is utilized as the estimator for global optimal accumulative energy consumption (GOAEC). The validation result indicates that the highest Pearson correlation coefficient between the sequence of OSEC and GOAEC reaches 0.86, while in the case of the poorest estimation performance, the sequences share a similar shape. The effective estimator for GOAEC provides the quantified evidence supporting decisions on route planning and velocity planning.",

keywords = "Energy consumption, Fuel cell vehicle, Optimal control, Traffic dynamics",

author = "Zihong Yang and Xingyu Zhou and Chao Sun and Xiaodong Wei",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 18th IEEE Vehicle Power and Propulsion Conference, VPPC 2021 ; Conference date: 25-10-2021 Through 28-10-2021",

year = "2021",

doi = "10.1109/VPPC53923.2021.9699251",

language = "English",

series = "2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS",

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

booktitle = "2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS",

address = "United States",

}

Yang, Z, Zhou, X, Sun, C & Wei, X 2021, Estimation of Optimal Energy Consumption for Fuel Cell Vehicle Based on Macroscopic Traffic Dynamics. in 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS. 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS, Institute of Electrical and Electronics Engineers Inc., 18th IEEE Vehicle Power and Propulsion Conference, VPPC 2021, Virtual, Gijon, Spain, 25/10/21. https://doi.org/10.1109/VPPC53923.2021.9699251

Estimation of Optimal Energy Consumption for Fuel Cell Vehicle Based on Macroscopic Traffic Dynamics. / Yang, Zihong; Zhou, Xingyu; Sun, Chao et al.
2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS).

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

TY - GEN

T1 - Estimation of Optimal Energy Consumption for Fuel Cell Vehicle Based on Macroscopic Traffic Dynamics

AU - Yang, Zihong

AU - Zhou, Xingyu

AU - Sun, Chao

AU - Wei, Xiaodong

PY - 2021

Y1 - 2021

N2 - This paper addresses the estimation problem of the minimum required energy of fuel cell vehicle (FCV) driving through a road link conditioned on the current and future traffic states. The challenge is to estimate driving profile of individual vehicles and obtain the corresponding optimal energy consumption of powertrain. Combining the powertrain model and macroscopic traffic dynamics, the FCV tank-to-traffic energy dissipation model is established. Based on the optimal energy consumption within each road segment solved by dynamic programming, the optimal demand power field is obtained. According to the estimated driving profile, optimal segmental energy consumption (OSEC) is calculated by interpolation of optimal demand power field, whose summation is utilized as the estimator for global optimal accumulative energy consumption (GOAEC). The validation result indicates that the highest Pearson correlation coefficient between the sequence of OSEC and GOAEC reaches 0.86, while in the case of the poorest estimation performance, the sequences share a similar shape. The effective estimator for GOAEC provides the quantified evidence supporting decisions on route planning and velocity planning.

AB - This paper addresses the estimation problem of the minimum required energy of fuel cell vehicle (FCV) driving through a road link conditioned on the current and future traffic states. The challenge is to estimate driving profile of individual vehicles and obtain the corresponding optimal energy consumption of powertrain. Combining the powertrain model and macroscopic traffic dynamics, the FCV tank-to-traffic energy dissipation model is established. Based on the optimal energy consumption within each road segment solved by dynamic programming, the optimal demand power field is obtained. According to the estimated driving profile, optimal segmental energy consumption (OSEC) is calculated by interpolation of optimal demand power field, whose summation is utilized as the estimator for global optimal accumulative energy consumption (GOAEC). The validation result indicates that the highest Pearson correlation coefficient between the sequence of OSEC and GOAEC reaches 0.86, while in the case of the poorest estimation performance, the sequences share a similar shape. The effective estimator for GOAEC provides the quantified evidence supporting decisions on route planning and velocity planning.

KW - Energy consumption

KW - Fuel cell vehicle

KW - Optimal control

KW - Traffic dynamics

UR - http://www.scopus.com/inward/record.url?scp=85126200836&partnerID=8YFLogxK

U2 - 10.1109/VPPC53923.2021.9699251

DO - 10.1109/VPPC53923.2021.9699251

M3 - Conference contribution

AN - SCOPUS:85126200836

T3 - 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS

BT - 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 18th IEEE Vehicle Power and Propulsion Conference, VPPC 2021

Y2 - 25 October 2021 through 28 October 2021

ER -

Yang Z, Zhou X, Sun C, Wei X. Estimation of Optimal Energy Consumption for Fuel Cell Vehicle Based on Macroscopic Traffic Dynamics. In 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS. Institute of Electrical and Electronics Engineers Inc. 2021. (2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS). doi: 10.1109/VPPC53923.2021.9699251

Estimation of Optimal Energy Consumption for Fuel Cell Vehicle Based on Macroscopic Traffic Dynamics

Abstract

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Keywords

UN SDGs

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