Degradation Abatement in Hybrid Electric Vehicles using Data-Driven Technique

Laxman Timilsina; Phuong H. Hoang; Ali Arsalan; Bill R. Badr; Gokhan Ozkan; Behnaz Papari; Christopher S. Edrington

doi:10.1016/j.trpro.2023.11.001

Degradation Abatement in Hybrid Electric Vehicles using Data-Driven Technique

Laxman Timilsina
, Phuong H. Hoang
, Ali Arsalan
, Bill R. Badr
, Gokhan Ozkan
, Behnaz Papari
, Christopher S. Edrington

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

13 Scopus citations

Abstract

Electrified transportation is considered one of the most feasible technological solutions to address the growing climate change challenges in the electric transportation sector. However, the batteries used in electric vehicles (EVs) and hybrid electric vehicles (HEVs) have limited life. The degradation of the battery is accelerated by the operating conditions of the vehicle, which further reduces its life and increases the reliability and economic concerns for the vehicle's operation. This paper provides a technique to minimize the degradation of the battery used in HEVs called a prognostic-based control framework. A data-driven method is used to predict the degradation path of the battery. Depending on the degradation, the control strategy of the system is reconfigured to reduce the degradation and increase the battery's operating life.

Original language	English
Pages (from-to)	52-60
Number of pages	9
Journal	Transportation Research Procedia
Volume	70
DOIs	https://doi.org/10.1016/j.trpro.2023.11.001
State	Published - 2023
Externally published	Yes
Event	8th International Electric Vehicle Conference, EVC 2023 - Edinburgh, United Kingdom Duration: Jun 21 2023 → Jun 23 2023

Funding

This work was supported by the Virtual Prototyping of Autonomy Enabled Ground Systems (VIPR-GS), a US Army Center of Excellence for modeling and simulation of ground vehicles, under Cooperative Agreement W56HZV-21-2-0001 with the US Army DEVCOM Ground Vehicle Systems Center (GVSC). Distribution A. Approved for public release: distribution unlimited. (OPSEC #7399)

Keywords

Battery Degradation
Degradation Abatement
Degradation Prediction
Hybrid Electric Vehicles
Lithium-ion Battery

Access to Document

10.1016/j.trpro.2023.11.001

Cite this

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title = "Degradation Abatement in Hybrid Electric Vehicles using Data-Driven Technique",

abstract = "Electrified transportation is considered one of the most feasible technological solutions to address the growing climate change challenges in the electric transportation sector. However, the batteries used in electric vehicles (EVs) and hybrid electric vehicles (HEVs) have limited life. The degradation of the battery is accelerated by the operating conditions of the vehicle, which further reduces its life and increases the reliability and economic concerns for the vehicle's operation. This paper provides a technique to minimize the degradation of the battery used in HEVs called a prognostic-based control framework. A data-driven method is used to predict the degradation path of the battery. Depending on the degradation, the control strategy of the system is reconfigured to reduce the degradation and increase the battery's operating life.",

keywords = "Battery Degradation, Degradation Abatement, Degradation Prediction, Hybrid Electric Vehicles, Lithium-ion Battery",

author = "Laxman Timilsina and Hoang, \{Phuong H.\} and Ali Arsalan and Badr, \{Bill R.\} and Gokhan Ozkan and Behnaz Papari and Edrington, \{Christopher S.\}",

year = "2023",

doi = "10.1016/j.trpro.2023.11.001",

language = "English",

volume = "70",

pages = "52--60",

journal = "Transportation Research Procedia",

issn = "2352-1457",

publisher = "Elsevier",

}

TY - JOUR

T1 - Degradation Abatement in Hybrid Electric Vehicles using Data-Driven Technique

AU - Timilsina, Laxman

AU - Hoang, Phuong H.

AU - Arsalan, Ali

AU - Badr, Bill R.

AU - Ozkan, Gokhan

AU - Papari, Behnaz

AU - Edrington, Christopher S.

PY - 2023

Y1 - 2023

N2 - Electrified transportation is considered one of the most feasible technological solutions to address the growing climate change challenges in the electric transportation sector. However, the batteries used in electric vehicles (EVs) and hybrid electric vehicles (HEVs) have limited life. The degradation of the battery is accelerated by the operating conditions of the vehicle, which further reduces its life and increases the reliability and economic concerns for the vehicle's operation. This paper provides a technique to minimize the degradation of the battery used in HEVs called a prognostic-based control framework. A data-driven method is used to predict the degradation path of the battery. Depending on the degradation, the control strategy of the system is reconfigured to reduce the degradation and increase the battery's operating life.

AB - Electrified transportation is considered one of the most feasible technological solutions to address the growing climate change challenges in the electric transportation sector. However, the batteries used in electric vehicles (EVs) and hybrid electric vehicles (HEVs) have limited life. The degradation of the battery is accelerated by the operating conditions of the vehicle, which further reduces its life and increases the reliability and economic concerns for the vehicle's operation. This paper provides a technique to minimize the degradation of the battery used in HEVs called a prognostic-based control framework. A data-driven method is used to predict the degradation path of the battery. Depending on the degradation, the control strategy of the system is reconfigured to reduce the degradation and increase the battery's operating life.

KW - Battery Degradation

KW - Degradation Abatement

KW - Degradation Prediction

KW - Hybrid Electric Vehicles

KW - Lithium-ion Battery

UR - https://www.scopus.com/pages/publications/85178062839

U2 - 10.1016/j.trpro.2023.11.001

DO - 10.1016/j.trpro.2023.11.001

M3 - Conference article

AN - SCOPUS:85178062839

SN - 2352-1457

VL - 70

SP - 52

EP - 60

JO - Transportation Research Procedia

JF - Transportation Research Procedia

T2 - 8th International Electric Vehicle Conference, EVC 2023

Y2 - 21 June 2023 through 23 June 2023

ER -

Degradation Abatement in Hybrid Electric Vehicles using Data-Driven Technique

Abstract

Funding

Keywords

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