Identification of parameters for equivalent circuit model of Li-ion battery cell with population based optimization algorithms

As EVs are sold to worldwide area with different latitudes, it also implies that lithium-ion batteries need to be safely operated in different climatic environments. To ensure the robustness and safeness of EVs, the characteristics of lithium-ion batteries must be taken into considerations. To compr...

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Main Author: Yu-Shan Cheng
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Ain Shams Engineering Journal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2090447923003702
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author Yu-Shan Cheng
author_facet Yu-Shan Cheng
author_sort Yu-Shan Cheng
collection DOAJ
description As EVs are sold to worldwide area with different latitudes, it also implies that lithium-ion batteries need to be safely operated in different climatic environments. To ensure the robustness and safeness of EVs, the characteristics of lithium-ion batteries must be taken into considerations. To comprehensively grasp the key information of battery cell in an efficient way, building a battery model is one of the most effective ways. Based on the model, one can get rid of time-consuming experiments. Moreover, the model enables to simulate and observe battery behaviors under extreme test condition safely. In this paper, an equivalent electric circuit (EEC) of a Li-ion battery cell is investigated. Based on 2nd order RC circuit, an Extended Hybrid Pulse Power Characterization (EHPPC) is designed and carried out to observe the dynamic response of battery cell in time domain. Once substantial measurement results are obtained, the parameterization turns out to be an important issue. This paper investigates the most appropriate metaheuristic based method to rapidly and systematically identify the EEC parameters. Totally four different methods, namely Particle Swarm Optimization, Grey Wolf Optimizer, Harmony Search, and Golden Eagle Optimization, are realized and equally compared by 100 implementations. Eventually, a mission profile of driving pattern, Dynamic Stress Testing (DST), is used to validate the proposed EEC model. The 2RC EEC model is able to simulate battery voltage response with root-mean-squared error as low as 0.0045.
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spelling doaj.art-43d28ce2e85e480097335406f03d63932024-03-21T05:36:22ZengElsevierAin Shams Engineering Journal2090-44792024-03-01153102481Identification of parameters for equivalent circuit model of Li-ion battery cell with population based optimization algorithmsYu-Shan Cheng0Department of Electrical Engineering, National Taiwan Ocean University, 2, Beining Rd, Zhongzheng District, Keelung City 202, TaiwanAs EVs are sold to worldwide area with different latitudes, it also implies that lithium-ion batteries need to be safely operated in different climatic environments. To ensure the robustness and safeness of EVs, the characteristics of lithium-ion batteries must be taken into considerations. To comprehensively grasp the key information of battery cell in an efficient way, building a battery model is one of the most effective ways. Based on the model, one can get rid of time-consuming experiments. Moreover, the model enables to simulate and observe battery behaviors under extreme test condition safely. In this paper, an equivalent electric circuit (EEC) of a Li-ion battery cell is investigated. Based on 2nd order RC circuit, an Extended Hybrid Pulse Power Characterization (EHPPC) is designed and carried out to observe the dynamic response of battery cell in time domain. Once substantial measurement results are obtained, the parameterization turns out to be an important issue. This paper investigates the most appropriate metaheuristic based method to rapidly and systematically identify the EEC parameters. Totally four different methods, namely Particle Swarm Optimization, Grey Wolf Optimizer, Harmony Search, and Golden Eagle Optimization, are realized and equally compared by 100 implementations. Eventually, a mission profile of driving pattern, Dynamic Stress Testing (DST), is used to validate the proposed EEC model. The 2RC EEC model is able to simulate battery voltage response with root-mean-squared error as low as 0.0045.http://www.sciencedirect.com/science/article/pii/S2090447923003702Lithium-ion batteryEquivalent electric circuit modelMetaheuristicExtended hybrid pulse power characterization
spellingShingle Yu-Shan Cheng
Identification of parameters for equivalent circuit model of Li-ion battery cell with population based optimization algorithms
Ain Shams Engineering Journal
Lithium-ion battery
Equivalent electric circuit model
Metaheuristic
Extended hybrid pulse power characterization
title Identification of parameters for equivalent circuit model of Li-ion battery cell with population based optimization algorithms
title_full Identification of parameters for equivalent circuit model of Li-ion battery cell with population based optimization algorithms
title_fullStr Identification of parameters for equivalent circuit model of Li-ion battery cell with population based optimization algorithms
title_full_unstemmed Identification of parameters for equivalent circuit model of Li-ion battery cell with population based optimization algorithms
title_short Identification of parameters for equivalent circuit model of Li-ion battery cell with population based optimization algorithms
title_sort identification of parameters for equivalent circuit model of li ion battery cell with population based optimization algorithms
topic Lithium-ion battery
Equivalent electric circuit model
Metaheuristic
Extended hybrid pulse power characterization
url http://www.sciencedirect.com/science/article/pii/S2090447923003702
work_keys_str_mv AT yushancheng identificationofparametersforequivalentcircuitmodelofliionbatterycellwithpopulationbasedoptimizationalgorithms