Adaptive Microfluidic Modeling of a Membraneless Micro Redox Flow Battery Using Extended Kalman Filter
Membraneless micro redox flow batteries are a promising technology that can improve traditional redox flow batteries performance. However, a precise modeling and control of the microfluidic dynamics is a complex task for which only open loop control strategies can be found in the literature. In this...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10244190/ |
| _version_ | 1827813762920349696 |
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| author | Alberto Bernaldo De Quiros Alberto E. Quintero Airan Frances Javier Uceda |
| author_facet | Alberto Bernaldo De Quiros Alberto E. Quintero Airan Frances Javier Uceda |
| author_sort | Alberto Bernaldo De Quiros |
| collection | DOAJ |
| description | Membraneless micro redox flow batteries are a promising technology that can improve traditional redox flow batteries performance. However, a precise modeling and control of the microfluidic dynamics is a complex task for which only open loop control strategies can be found in the literature. In this work, a strategy for the adaptive modeling of the microfluidic dynamics of a membraneless micro redox flow battery is presented. The model is based on proposed equations whose constant parameters are identified using grey-box modeling techniques. Intrinsic limitations of applying these equations to the real system (stochasticity of the microfluidic system, non-considered variables, non-linearities) are overcome by adapting the model through the addition of correction factors calculated in real time. In the proposed use case, an extended Kalman filter is used to estimate the factors. Also, the model with real-time adaption is proven to be suitable for control design using a model-based control technique such as incremental state optimal control. The modeling and the controller adequacy are validated in simulation and real experiments. Model adequacy to real system is demonstrated through fitness measurements of the deviation from it, which show prominent values under various conditions. It also allows a model-based control design that improves microfluidic response, with zero steady state error and fast and non-overshooting action, which is expected to result in higher battery efficiency and reactant conversion ratio. |
| first_indexed | 2024-03-11T23:36:40Z |
| format | Article |
| id | doaj.art-2235963df698470da414fa8ae55569cd |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T23:36:40Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2235963df698470da414fa8ae55569cd2023-09-19T23:01:02ZengIEEEIEEE Access2169-35362023-01-011110020710021710.1109/ACCESS.2023.331341610244190Adaptive Microfluidic Modeling of a Membraneless Micro Redox Flow Battery Using Extended Kalman FilterAlberto Bernaldo De Quiros0https://orcid.org/0000-0003-1486-6422Alberto E. Quintero1https://orcid.org/0000-0002-3316-8219Airan Frances2https://orcid.org/0000-0003-3389-0815Javier Uceda3https://orcid.org/0000-0001-9534-5914Centro de Electrónica Industrial, Universidad Politécnica de Madrid, Madrid, SpainResearch and Development Department, Micro Electrochemical Technologies S.L., Leganés, SpainCentro de Electrónica Industrial, Universidad Politécnica de Madrid, Madrid, SpainCentro de Electrónica Industrial, Universidad Politécnica de Madrid, Madrid, SpainMembraneless micro redox flow batteries are a promising technology that can improve traditional redox flow batteries performance. However, a precise modeling and control of the microfluidic dynamics is a complex task for which only open loop control strategies can be found in the literature. In this work, a strategy for the adaptive modeling of the microfluidic dynamics of a membraneless micro redox flow battery is presented. The model is based on proposed equations whose constant parameters are identified using grey-box modeling techniques. Intrinsic limitations of applying these equations to the real system (stochasticity of the microfluidic system, non-considered variables, non-linearities) are overcome by adapting the model through the addition of correction factors calculated in real time. In the proposed use case, an extended Kalman filter is used to estimate the factors. Also, the model with real-time adaption is proven to be suitable for control design using a model-based control technique such as incremental state optimal control. The modeling and the controller adequacy are validated in simulation and real experiments. Model adequacy to real system is demonstrated through fitness measurements of the deviation from it, which show prominent values under various conditions. It also allows a model-based control design that improves microfluidic response, with zero steady state error and fast and non-overshooting action, which is expected to result in higher battery efficiency and reactant conversion ratio.https://ieeexplore.ieee.org/document/10244190/Adaptive modelextended Kalman filtergrey box model identificationincremental state modelmicrofluidicsredox flow battery |
| spellingShingle | Alberto Bernaldo De Quiros Alberto E. Quintero Airan Frances Javier Uceda Adaptive Microfluidic Modeling of a Membraneless Micro Redox Flow Battery Using Extended Kalman Filter IEEE Access Adaptive model extended Kalman filter grey box model identification incremental state model microfluidics redox flow battery |
| title | Adaptive Microfluidic Modeling of a Membraneless Micro Redox Flow Battery Using Extended Kalman Filter |
| title_full | Adaptive Microfluidic Modeling of a Membraneless Micro Redox Flow Battery Using Extended Kalman Filter |
| title_fullStr | Adaptive Microfluidic Modeling of a Membraneless Micro Redox Flow Battery Using Extended Kalman Filter |
| title_full_unstemmed | Adaptive Microfluidic Modeling of a Membraneless Micro Redox Flow Battery Using Extended Kalman Filter |
| title_short | Adaptive Microfluidic Modeling of a Membraneless Micro Redox Flow Battery Using Extended Kalman Filter |
| title_sort | adaptive microfluidic modeling of a membraneless micro redox flow battery using extended kalman filter |
| topic | Adaptive model extended Kalman filter grey box model identification incremental state model microfluidics redox flow battery |
| url | https://ieeexplore.ieee.org/document/10244190/ |
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