Scipediacontent: Scipediacontent moved page Draft Content 981428375 to Zhang Pang 2018a

2021-02-12T13:11:40Z

Scipediacontent moved page Draft Content 981428375 to Zhang Pang 2018a

Scipediacontent: Created page with " == Abstract == It is well known that accurate identification of the key state parameters and State of Charge (SOC) estimation method for a Li-ion battery cell is of great si..."

2021-02-12T13:11:37Z

Created page with " == Abstract == It is well known that accurate identification of the key state parameters and State of Charge (SOC) estimation method for a Li-ion battery cell is of great si..."

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== Abstract ==

It is well known that accurate identification of the key state parameters and State of Charge (SOC) estimation method for a Li-ion battery cell is of great significance for advanced battery management system (BMS) of electric vehicles (EVs), which further facilitates the commercialization of EVs. This study proposed a systematic experimental data-driven parameter identification scheme and an adaptive extended Kalman Filter (AEKF)-based SOC estimation algorithm for a Li-Ion battery equivalent circuit model in EV applications. The key state parameters of Li-ion battery cell were identified based on the second-order resistor capacitor (RC) equivalent circuit model and the experimental battery test data using genetic algorithm (GA). Meanwhile, the proposed parameter identification procedure was validated by carrying out a comparative study of the simulated and experimental output voltage under the same input current profile. Then, SOC estimation was performed based on the AEKF algorithm. Finally, the effectiveness and feasibility of the proposed SOC estimator was verified by loading different operating profiles.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_981428375-beopen290-9479-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.3390/en11051033 http://dx.doi.org/10.3390/en11051033] under the license https://creativecommons.org/licenses/by

* [https://www.mdpi.com/1996-1073/11/5/1033/pdf https://www.mdpi.com/1996-1073/11/5/1033/pdf] under the license https://creativecommons.org/licenses/by/4.0

* [http://www.mdpi.com/1996-1073/11/5/1033 http://www.mdpi.com/1996-1073/11/5/1033],
: [https://doaj.org/toc/1996-1073 https://doaj.org/toc/1996-1073] under the license cc-by

* [http://www.mdpi.com/1996-1073/11/5/1033/pdf http://www.mdpi.com/1996-1073/11/5/1033/pdf],
: [http://dx.doi.org/10.3390/en11051033 http://dx.doi.org/10.3390/en11051033]

* [https://ideas.repec.org/a/gam/jeners/v11y2018i5p1033-d142884.html https://ideas.repec.org/a/gam/jeners/v11y2018i5p1033-d142884.html],
: [https://doi.org/10.3390/en11051033 https://doi.org/10.3390/en11051033],
: [https://core.ac.uk/display/156976803 https://core.ac.uk/display/156976803],
: [https://academic.microsoft.com/#/detail/2802551211 https://academic.microsoft.com/#/detail/2802551211] under the license https://creativecommons.org/licenses/by/4.0/

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Zhang Pang 2018a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 981428375 to Zhang Pang 2018a

Scipediacontent: Created page with " == Abstract == It is well known that accurate identification of the key state parameters and State of Charge (SOC) estimation method for a Li-ion battery cell is of great si..."