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| Format: | Artículo científico |
| Sprache: | es |
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Universidad Distrital Francisco José de Caldas
2023
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| Online-Zugang: | https://www.redalyc.org/articulo.oa?id=498875016010 https://www.redalyc.org/journal/4988/498875016010/ https://www.redalyc.org/journal/4988/498875016010/html/ https://www.redalyc.org/journal/4988/498875016010/498875016010.epub https://www.redalyc.org/journal/4988/498875016010/movil |
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| _version_ | 1866817761337933824 |
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| author | Fabián Gutiérrez-Castillo |
| author_facet | Fabián Gutiérrez-Castillo |
| contents | Dual-Polarization Equivalent Circuit Model Parameterization of a Lithium-Ion Cell Using the Modified Particle Swarm Optimization Technique Fabián Gutiérrez-Castillo Kevin Smit Montes-Villa Juan Pablo Villegas-Ceballos Cristian Escudero-Quintero Ingeniería PSO dual polarization equivalent model parameterization Context: Battery modeling can be a complex activity if techniques based on chemical behavior are employed. To facilitate this, inverse modeling techniques have been used which are based on experimental curves and adjustments of circuit models. Different techniques are used for parameterization according to their complexity, accuracy, and convergence time. Method: This paper uses a particle swarm optimization algorithm to parameterize a dual-polarization model for a 18650-type lithium cell. The proposed methodology divides the problem into different optimization cases and proposes a localized search strategy based on the experience of the previous case. Results: The PSO algorithm allows adjusting the model parameters for each case analyzed. Dividing the problem by stages allows improving the global precision while reducing the convergence times of the algorithm. Based on the possible cases, it is possible to find the dynamics of each of the parameters as a function of the charge state. Conclusions: The proposed methodology allows reducing the parameterization times of the dual-polarization model. Due to the approximation generated by previous experiences, it is possible to reduce the swarm population and further decrease the convergence time of the process. Additionally, the methodology can be used with different optimization algorithms. 2023 artículo científico 0121-750X https://www.redalyc.org/articulo.oa?id=498875016010 https://www.redalyc.org/journal/4988/498875016010/ https://www.redalyc.org/journal/4988/498875016010/html/ https://www.redalyc.org/journal/4988/498875016010/498875016010.epub https://www.redalyc.org/journal/4988/498875016010/movil 10.14483/23448393.17304 es http://www.redalyc.org/revista.oa?id=4988 Ingeniería application/pdf Universidad Distrital Francisco José de Caldas Ingeniería (Colombia) Num.1 Vol.28 |
| format | Artículo científico |
| id | redalyc_498875016010 |
| language | es |
| publishDate | 2023 |
| publisher | Universidad Distrital Francisco José de Caldas |
| spellingShingle | Dual-Polarization Equivalent Circuit Model Parameterization of a Lithium-Ion Cell Using the Modified Particle Swarm Optimization Technique Fabián Gutiérrez-Castillo Ingeniería PSO dual polarization equivalent model parameterization Dual-Polarization Equivalent Circuit Model Parameterization of a Lithium-Ion Cell Using the Modified Particle Swarm Optimization Technique Fabián Gutiérrez-Castillo Kevin Smit Montes-Villa Juan Pablo Villegas-Ceballos Cristian Escudero-Quintero Ingeniería PSO dual polarization equivalent model parameterization Context: Battery modeling can be a complex activity if techniques based on chemical behavior are employed. To facilitate this, inverse modeling techniques have been used which are based on experimental curves and adjustments of circuit models. Different techniques are used for parameterization according to their complexity, accuracy, and convergence time. Method: This paper uses a particle swarm optimization algorithm to parameterize a dual-polarization model for a 18650-type lithium cell. The proposed methodology divides the problem into different optimization cases and proposes a localized search strategy based on the experience of the previous case. Results: The PSO algorithm allows adjusting the model parameters for each case analyzed. Dividing the problem by stages allows improving the global precision while reducing the convergence times of the algorithm. Based on the possible cases, it is possible to find the dynamics of each of the parameters as a function of the charge state. Conclusions: The proposed methodology allows reducing the parameterization times of the dual-polarization model. Due to the approximation generated by previous experiences, it is possible to reduce the swarm population and further decrease the convergence time of the process. Additionally, the methodology can be used with different optimization algorithms. 2023 artículo científico 0121-750X https://www.redalyc.org/articulo.oa?id=498875016010 https://www.redalyc.org/journal/4988/498875016010/ https://www.redalyc.org/journal/4988/498875016010/html/ https://www.redalyc.org/journal/4988/498875016010/498875016010.epub https://www.redalyc.org/journal/4988/498875016010/movil 10.14483/23448393.17304 es http://www.redalyc.org/revista.oa?id=4988 Ingeniería application/pdf Universidad Distrital Francisco José de Caldas Ingeniería (Colombia) Num.1 Vol.28 |
| title | Dual-Polarization Equivalent Circuit Model Parameterization of a Lithium-Ion Cell Using the Modified Particle Swarm Optimization Technique |
| topic | Ingeniería PSO dual polarization equivalent model parameterization |
| url | https://www.redalyc.org/articulo.oa?id=498875016010 https://www.redalyc.org/journal/4988/498875016010/ https://www.redalyc.org/journal/4988/498875016010/html/ https://www.redalyc.org/journal/4988/498875016010/498875016010.epub https://www.redalyc.org/journal/4988/498875016010/movil |