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Implementation of a semi-empirical, electrochemistry-based Li-ion battery model for discharge characterization: Master of Science Thesis in Energy Systems
Mälardalen University, School of Business, Society and Engineering.
2021 (English)Independent thesis Basic level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Lithium-ion batteries are a rapidly growing power source for mobile applications such as electric vehicles. A battery model algorithm that estimates and predicts important battery parameters like terminal voltage and state-of-charge is necessary to maintain safe operation during discharge. Hence, a semi-empirical electrochemical-based model was proposed and implemented in MATLAB for discharge simulation and parameter estimation. This thesis also investigated several essential factors like internal resistance and operational temperature, which impact a battery cell during discharge. 

The proposed model was a modification of Shepherd’s model that included both kinetic and diffusive components representing the total battery overpotential and a temperature- dependent coefficient. These were used for the determination of the battery’s internal resistance and the temperature effect. The model accounts for all dynamic characteristics of a Li-ion battery, including non-linear open-circuit voltage, internal resistance, discharge current, and capacity. 

Model validation was performed using test profiles, including data provided by the battery manufacturer and experimental data for a test profile provided by Saab Dynamics. The simulated profiles were found to match the measured profiles. Although, some deviations occurred, especially during rapid changes in C-rates. The proposed model in this work shows that the simulation results compared to the experimental data had deviations within ~2% for the constant current discharge test, and the dynamic model managed to cover the experimental discharge voltage during different temperatures with good consistency and minor errors. Therefore, the proposed model can compete with other battery modeling methods. 

Place, publisher, year, edition, pages
2021. , p. 89
Keywords [en]
Battery Modeling, Li-ion Battery
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-55022OAI: oai:DiVA.org:mdh-55022DiVA, id: diva2:1570465
External cooperation
Saab Dynamics
Subject / course
Energy Engineering
Available from: 2021-06-22 Created: 2021-06-21 Last updated: 2021-06-22Bibliographically approved

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CiteExportLink to record
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