State of Health estimation of battery systems
(2023)Department of Automatic Control
- Abstract
- This study focuses on estimating the state of health (SoH) of a lithium iron phosphate (LFP) battery system, which is crucial for assessing the value and lifespan of new or used batteries in energy storage, grid support, and electric vehicle applications. A proposed method for determining SoH based on comparing useful and nominal useful capacities in Ah and Wh, as well as total and nominal capacity, has been presented. To validate the method, 200 charging and discharging cycles over five months were performed. Three models were developed to track battery behavior and one model to simulate degradation. An extended Kalman filter has been used in the model to estimate the battery’s non-linear parameters and filter the noisy measurements. The... (More)
- This study focuses on estimating the state of health (SoH) of a lithium iron phosphate (LFP) battery system, which is crucial for assessing the value and lifespan of new or used batteries in energy storage, grid support, and electric vehicle applications. A proposed method for determining SoH based on comparing useful and nominal useful capacities in Ah and Wh, as well as total and nominal capacity, has been presented. To validate the method, 200 charging and discharging cycles over five months were performed. Three models were developed to track battery behavior and one model to simulate degradation. An extended Kalman filter has been used in the model to estimate the battery’s non-linear parameters and filter the noisy measurements. The models revealed that while estimating capacity using Coulomb and Watt counting proved difficult for the battery system that has been used, weighted least squares and recursive weighted least squares methods showed promise for determining current capacity. Furthermore, an attempt to estimate the battery’s equivalent series resistance was performed, but no conclusion could be drawn due to limited knowledge of battery parameters. The findings highlight the challenges of modeling and estimating the SoH of used batteries and suggest the need for more targeted experimentation to improve battery modeling and estimation accuracy. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9136987
- author
- Spångberg, Carl
- supervisor
- organization
- year
- 2023
- type
- H3 - Professional qualifications (4 Years - )
- subject
- report number
- TFRT-6214
- other publication id
- 0280-5316
- language
- English
- id
- 9136987
- date added to LUP
- 2023-09-12 14:07:10
- date last changed
- 2023-09-12 14:07:10
@misc{9136987,
abstract = {{This study focuses on estimating the state of health (SoH) of a lithium iron phosphate (LFP) battery system, which is crucial for assessing the value and lifespan of new or used batteries in energy storage, grid support, and electric vehicle applications. A proposed method for determining SoH based on comparing useful and nominal useful capacities in Ah and Wh, as well as total and nominal capacity, has been presented. To validate the method, 200 charging and discharging cycles over five months were performed. Three models were developed to track battery behavior and one model to simulate degradation. An extended Kalman filter has been used in the model to estimate the battery’s non-linear parameters and filter the noisy measurements. The models revealed that while estimating capacity using Coulomb and Watt counting proved difficult for the battery system that has been used, weighted least squares and recursive weighted least squares methods showed promise for determining current capacity. Furthermore, an attempt to estimate the battery’s equivalent series resistance was performed, but no conclusion could be drawn due to limited knowledge of battery parameters. The findings highlight the challenges of modeling and estimating the SoH of used batteries and suggest the need for more targeted experimentation to improve battery modeling and estimation accuracy.}},
author = {{Spångberg, Carl}},
language = {{eng}},
note = {{Student Paper}},
title = {{State of Health estimation of battery systems}},
year = {{2023}},
}