Variable Fractional-Order Equivalent Circuit Model for Lithium-Ion Battery via Chaotic Adaptive Fractional Particle Swarm Optimization Method
A variable fractional-order equivalent circuit model is proposed to accurately describe the dynamic characteristics of lithium-ion batteries (LIBs). Firstly, a fractional impedance model (FIM) is established, such that the fractional-order (FO) is a polynomial function of the LIB state of charge (&l...
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MDPI AG
2022-11-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/14/11/2407 |
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| author | Deshun Wang Haikun Wei Jinhua Xue Fubao Wu António M. Lopes |
| author_facet | Deshun Wang Haikun Wei Jinhua Xue Fubao Wu António M. Lopes |
| author_sort | Deshun Wang |
| collection | DOAJ |
| description | A variable fractional-order equivalent circuit model is proposed to accurately describe the dynamic characteristics of lithium-ion batteries (LIBs). Firstly, a fractional impedance model (FIM) is established, such that the fractional-order (FO) is a polynomial function of the LIB state of charge (<i>SOC</i>). Then, a chaotic adaptive fractional particle swarm optimization (CAFPSO) method is derived to identify the parameters of the FIM. Experiments reveal the reliability of the novel approach through the root-mean-squared error (RMSE) and the mean absolute error (MAE) of the LIB terminals voltage, yielding the values 8.99 mV and 4.56 mV, respectively. This translates into accuracy improvements of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>22.5</mn><mo>%</mo></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>34.4</mn><mo>%</mo></mrow></semantics></math></inline-formula> for the particle swarm optimization (PSO) algorithm and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>57.9</mn><mo>%</mo></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>72.8</mn><mo>%</mo></mrow></semantics></math></inline-formula> for the adaptive fractional particle swarm optimization (AFPSO) algorithm, respectively. |
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| language | English |
| last_indexed | 2024-03-09T17:57:27Z |
| publishDate | 2022-11-01 |
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| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-bb6853b0fdc44f54a6c2765be6d6ab982023-11-24T10:13:31ZengMDPI AGSymmetry2073-89942022-11-011411240710.3390/sym14112407Variable Fractional-Order Equivalent Circuit Model for Lithium-Ion Battery via Chaotic Adaptive Fractional Particle Swarm Optimization MethodDeshun Wang0Haikun Wei1Jinhua Xue2Fubao Wu3António M. Lopes4School of Automation, Southeast University, Nanjing 210096, ChinaSchool of Automation, Southeast University, Nanjing 210096, ChinaState Grid Shanghai Energy Interconnection Research Institute Co., Ltd., Shanghai 201203, ChinaJiangsu Engineering Technology Research Center for Energy Storage Conversion and Application, China Electric Power Research Institute, Nanjing 210003, ChinaLAETA/INEGI, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, PortugalA variable fractional-order equivalent circuit model is proposed to accurately describe the dynamic characteristics of lithium-ion batteries (LIBs). Firstly, a fractional impedance model (FIM) is established, such that the fractional-order (FO) is a polynomial function of the LIB state of charge (<i>SOC</i>). Then, a chaotic adaptive fractional particle swarm optimization (CAFPSO) method is derived to identify the parameters of the FIM. Experiments reveal the reliability of the novel approach through the root-mean-squared error (RMSE) and the mean absolute error (MAE) of the LIB terminals voltage, yielding the values 8.99 mV and 4.56 mV, respectively. This translates into accuracy improvements of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>22.5</mn><mo>%</mo></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>34.4</mn><mo>%</mo></mrow></semantics></math></inline-formula> for the particle swarm optimization (PSO) algorithm and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>57.9</mn><mo>%</mo></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>72.8</mn><mo>%</mo></mrow></semantics></math></inline-formula> for the adaptive fractional particle swarm optimization (AFPSO) algorithm, respectively.https://www.mdpi.com/2073-8994/14/11/2407FO equivalent circuitparameters’ identificationparticle swarm optimization |
| spellingShingle | Deshun Wang Haikun Wei Jinhua Xue Fubao Wu António M. Lopes Variable Fractional-Order Equivalent Circuit Model for Lithium-Ion Battery via Chaotic Adaptive Fractional Particle Swarm Optimization Method Symmetry FO equivalent circuit parameters’ identification particle swarm optimization |
| title | Variable Fractional-Order Equivalent Circuit Model for Lithium-Ion Battery via Chaotic Adaptive Fractional Particle Swarm Optimization Method |
| title_full | Variable Fractional-Order Equivalent Circuit Model for Lithium-Ion Battery via Chaotic Adaptive Fractional Particle Swarm Optimization Method |
| title_fullStr | Variable Fractional-Order Equivalent Circuit Model for Lithium-Ion Battery via Chaotic Adaptive Fractional Particle Swarm Optimization Method |
| title_full_unstemmed | Variable Fractional-Order Equivalent Circuit Model for Lithium-Ion Battery via Chaotic Adaptive Fractional Particle Swarm Optimization Method |
| title_short | Variable Fractional-Order Equivalent Circuit Model for Lithium-Ion Battery via Chaotic Adaptive Fractional Particle Swarm Optimization Method |
| title_sort | variable fractional order equivalent circuit model for lithium ion battery via chaotic adaptive fractional particle swarm optimization method |
| topic | FO equivalent circuit parameters’ identification particle swarm optimization |
| url | https://www.mdpi.com/2073-8994/14/11/2407 |
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