Estimating the State of Charge of Lithium-Ion Batteries Based on the Transfer Function of the Voltage Response to the Current Pulse
There are several methods for estimating the <i>SoC</i> of lithium-ion batteries that use electrochemical battery models or artificial intelligence and intelligent algorithms. These methods have numerous advantages but are complex and computationally intensive. This paper presents a new...
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MDPI AG
2022-09-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/18/6495 |
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| author | Ivan Radaš Nicole Pilat Daren Gnjatović Viktor Šunde Željko Ban |
| author_facet | Ivan Radaš Nicole Pilat Daren Gnjatović Viktor Šunde Željko Ban |
| author_sort | Ivan Radaš |
| collection | DOAJ |
| description | There are several methods for estimating the <i>SoC</i> of lithium-ion batteries that use electrochemical battery models or artificial intelligence and intelligent algorithms. These methods have numerous advantages but are complex and computationally intensive. This paper presents a new method for estimating the <i>SoC</i> of lithium-ion batteries based on identifying the transfer function of the measured battery voltage response to the charging current pulse. It is assumed that the transfer function of the battery changes with the state of charge. In the learning phase, a reference table of known <i>SoC</i>s and associated transfer functions is created. The parameters of these transfer functions form the reference points in hyperspace. In the phase of determining the unknown <i>SoC</i> of the battery, the parameters of the measured transfer function form a point in hyperspace that is compared with the reference points of the transfer functions for known <i>SoC</i>s. The unknown <i>SoC</i> of the battery at the particular measurement time is obtained by finding the two reference points closest to the point of unknown <i>SoC</i> using the Euclidean distance and a linear interpolation based on this distance. The method is simple, computationally undemanding, insensitive to measurement noise, and has high accuracy in <i>SoC</i> estimation. |
| first_indexed | 2024-03-10T00:10:24Z |
| format | Article |
| id | doaj.art-b7292b5bd7804719a2ae680866e71cdb |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T00:10:24Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-b7292b5bd7804719a2ae680866e71cdb2023-11-23T16:00:41ZengMDPI AGEnergies1996-10732022-09-011518649510.3390/en15186495Estimating the State of Charge of Lithium-Ion Batteries Based on the Transfer Function of the Voltage Response to the Current PulseIvan Radaš0Nicole Pilat1Daren Gnjatović2Viktor Šunde3Željko Ban4Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, CroatiaFaculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, CroatiaFaculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, CroatiaFaculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, CroatiaFaculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, CroatiaThere are several methods for estimating the <i>SoC</i> of lithium-ion batteries that use electrochemical battery models or artificial intelligence and intelligent algorithms. These methods have numerous advantages but are complex and computationally intensive. This paper presents a new method for estimating the <i>SoC</i> of lithium-ion batteries based on identifying the transfer function of the measured battery voltage response to the charging current pulse. It is assumed that the transfer function of the battery changes with the state of charge. In the learning phase, a reference table of known <i>SoC</i>s and associated transfer functions is created. The parameters of these transfer functions form the reference points in hyperspace. In the phase of determining the unknown <i>SoC</i> of the battery, the parameters of the measured transfer function form a point in hyperspace that is compared with the reference points of the transfer functions for known <i>SoC</i>s. The unknown <i>SoC</i> of the battery at the particular measurement time is obtained by finding the two reference points closest to the point of unknown <i>SoC</i> using the Euclidean distance and a linear interpolation based on this distance. The method is simple, computationally undemanding, insensitive to measurement noise, and has high accuracy in <i>SoC</i> estimation.https://www.mdpi.com/1996-1073/15/18/6495lithium-ion batteriesestimating the <i>SoC</i> of batterybattery’s equivalent circuit modeltransfer function of batteryEuclidean hyperspace of transfer function parameters |
| spellingShingle | Ivan Radaš Nicole Pilat Daren Gnjatović Viktor Šunde Željko Ban Estimating the State of Charge of Lithium-Ion Batteries Based on the Transfer Function of the Voltage Response to the Current Pulse Energies lithium-ion batteries estimating the <i>SoC</i> of battery battery’s equivalent circuit model transfer function of battery Euclidean hyperspace of transfer function parameters |
| title | Estimating the State of Charge of Lithium-Ion Batteries Based on the Transfer Function of the Voltage Response to the Current Pulse |
| title_full | Estimating the State of Charge of Lithium-Ion Batteries Based on the Transfer Function of the Voltage Response to the Current Pulse |
| title_fullStr | Estimating the State of Charge of Lithium-Ion Batteries Based on the Transfer Function of the Voltage Response to the Current Pulse |
| title_full_unstemmed | Estimating the State of Charge of Lithium-Ion Batteries Based on the Transfer Function of the Voltage Response to the Current Pulse |
| title_short | Estimating the State of Charge of Lithium-Ion Batteries Based on the Transfer Function of the Voltage Response to the Current Pulse |
| title_sort | estimating the state of charge of lithium ion batteries based on the transfer function of the voltage response to the current pulse |
| topic | lithium-ion batteries estimating the <i>SoC</i> of battery battery’s equivalent circuit model transfer function of battery Euclidean hyperspace of transfer function parameters |
| url | https://www.mdpi.com/1996-1073/15/18/6495 |
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