Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer
In order to safely and efficiently use the power as well as to extend the lifetime of the traction battery pack, accurate estimation of State of Charge (SoC) is very important and necessary. This paper presents an adaptive observer-based technique for estimating SoC of a lithium-ion battery pack use...
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Online Access: | http://www.mdpi.com/1996-1073/3/9/1586/ |
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doaj-7a33c14882cb4e1288ff5ebaaebbce5f2020-11-24T23:36:21ZengMDPI AGEnergies1996-10732010-09-01391586160310.3390/en3091586Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger ObserverYuan ZouFengchun SunXiaosong HuIn order to safely and efficiently use the power as well as to extend the lifetime of the traction battery pack, accurate estimation of State of Charge (SoC) is very important and necessary. This paper presents an adaptive observer-based technique for estimating SoC of a lithium-ion battery pack used in an electric vehicle (EV). The RC equivalent circuit model in ADVISOR is applied to simulate the lithium-ion battery pack. The parameters of the battery model as a function of SoC, are identified and optimized using the numerically nonlinear least squares algorithm, based on an experimental data set. By means of the optimized model, an adaptive Luenberger observer is built to estimate online the SoC of the lithium-ion battery pack. The observer gain is adaptively adjusted using a stochastic gradient approach so as to reduce the error between the estimated battery output voltage and the filtered battery terminal voltage measurement. Validation results show that the proposed technique can accurately estimate SoC of the lithium-ion battery pack without a heavy computational load. http://www.mdpi.com/1996-1073/3/9/1586/State of Chargelithium-ion batteryelectric vehicleadaptive observer |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yuan Zou Fengchun Sun Xiaosong Hu |
spellingShingle |
Yuan Zou Fengchun Sun Xiaosong Hu Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer Energies State of Charge lithium-ion battery electric vehicle adaptive observer |
author_facet |
Yuan Zou Fengchun Sun Xiaosong Hu |
author_sort |
Yuan Zou |
title |
Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer |
title_short |
Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer |
title_full |
Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer |
title_fullStr |
Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer |
title_full_unstemmed |
Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer |
title_sort |
estimation of state of charge of a lithium-ion battery pack for electric vehicles using an adaptive luenberger observer |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2010-09-01 |
description |
In order to safely and efficiently use the power as well as to extend the lifetime of the traction battery pack, accurate estimation of State of Charge (SoC) is very important and necessary. This paper presents an adaptive observer-based technique for estimating SoC of a lithium-ion battery pack used in an electric vehicle (EV). The RC equivalent circuit model in ADVISOR is applied to simulate the lithium-ion battery pack. The parameters of the battery model as a function of SoC, are identified and optimized using the numerically nonlinear least squares algorithm, based on an experimental data set. By means of the optimized model, an adaptive Luenberger observer is built to estimate online the SoC of the lithium-ion battery pack. The observer gain is adaptively adjusted using a stochastic gradient approach so as to reduce the error between the estimated battery output voltage and the filtered battery terminal voltage measurement. Validation results show that the proposed technique can accurately estimate SoC of the lithium-ion battery pack without a heavy computational load. |
topic |
State of Charge lithium-ion battery electric vehicle adaptive observer |
url |
http://www.mdpi.com/1996-1073/3/9/1586/ |
work_keys_str_mv |
AT yuanzou estimationofstateofchargeofalithiumionbatterypackforelectricvehiclesusinganadaptiveluenbergerobserver AT fengchunsun estimationofstateofchargeofalithiumionbatterypackforelectricvehiclesusinganadaptiveluenbergerobserver AT xiaosonghu estimationofstateofchargeofalithiumionbatterypackforelectricvehiclesusinganadaptiveluenbergerobserver |
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