LAPSE:2023.22403
Published Article

LAPSE:2023.22403
Li-Ion Battery Performance Degradation Modeling for the Optimal Design and Energy Management of Electrified Propulsion Systems
March 24, 2023
Abstract
Heavy-duty hybrid electric vehicles and marine vessels need a sizeable electric energy storage system (ESS). The size and energy management strategy (EMS) of the ESS affects the system performance, cost, emissions, and safety. Traditional power-demand-based and fuel-economy-driven ESS sizing and energy management has often led to shortened battery cycle life and higher replacement costs. To consider minimizing the total lifecycle cost (LCC) of hybrid electric propulsion systems, the battery performance degradation and the life prediction model is a critical element in the optimal design process. In this work, a new Li-ion battery (LIB) performance degradation model is introduced based on a large set of cycling experiment data on LiFePO4 (LFP) batteries to predict their capacity decay, resistance increase and the remaining cycle life under various use patterns. Critical parameters of the semi-empirical, amended equivalent circuit model were identified using least-square fitting. The model is used to calculate the investment, operation, replacement and recycling costs of the battery ESS over its lifetime. Validation of the model is made using battery cycling experimental data. The new LFP battery performance degradation model is used in optimizing the sizes of the key hybrid electric powertrain component of an electrified ferry ship with the minimum overall LCC. The optimization result presents a 12 percent improvement over the traditional power demand-driven hybrid powertrain design method. The research supports optimal sizing and EMS development of hybrid electric vehicles and vessels to achieve minimum lifecycle costs.
Heavy-duty hybrid electric vehicles and marine vessels need a sizeable electric energy storage system (ESS). The size and energy management strategy (EMS) of the ESS affects the system performance, cost, emissions, and safety. Traditional power-demand-based and fuel-economy-driven ESS sizing and energy management has often led to shortened battery cycle life and higher replacement costs. To consider minimizing the total lifecycle cost (LCC) of hybrid electric propulsion systems, the battery performance degradation and the life prediction model is a critical element in the optimal design process. In this work, a new Li-ion battery (LIB) performance degradation model is introduced based on a large set of cycling experiment data on LiFePO4 (LFP) batteries to predict their capacity decay, resistance increase and the remaining cycle life under various use patterns. Critical parameters of the semi-empirical, amended equivalent circuit model were identified using least-square fitting. The model is used to calculate the investment, operation, replacement and recycling costs of the battery ESS over its lifetime. Validation of the model is made using battery cycling experimental data. The new LFP battery performance degradation model is used in optimizing the sizes of the key hybrid electric powertrain component of an electrified ferry ship with the minimum overall LCC. The optimization result presents a 12 percent improvement over the traditional power demand-driven hybrid powertrain design method. The research supports optimal sizing and EMS development of hybrid electric vehicles and vessels to achieve minimum lifecycle costs.
Record ID
Keywords
battery sizing, electrified propulsion, li-ion battery, optimal energy management, performance degradation modelling, powertrain optimization
Subject
Suggested Citation
Chen L, Tong Y, Dong Z. Li-Ion Battery Performance Degradation Modeling for the Optimal Design and Energy Management of Electrified Propulsion Systems. (2023). LAPSE:2023.22403
Author Affiliations
Chen L: Department of Mechanical Engineering, Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada
Tong Y: Department of Mechanical Engineering, Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada; State-assigned Electric Vehicle Power Battery Center, Beijing 100072, China
Dong Z: Department of Mechanical Engineering, Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada [ORCID]
Tong Y: Department of Mechanical Engineering, Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada; State-assigned Electric Vehicle Power Battery Center, Beijing 100072, China
Dong Z: Department of Mechanical Engineering, Institute for Integrated Energy Systems, University of Victoria, Victoria, BC V8W 2Y2, Canada [ORCID]
Journal Name
Energies
Volume
13
Issue
7
Article Number
E1629
Year
2020
Publication Date
2020-04-02
ISSN
1996-1073
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Original Submission
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PII: en13071629, Publication Type: Journal Article
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LAPSE:2023.22403
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https://doi.org/10.3390/en13071629
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Mar 24, 2023
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