Li-ion battery aging test & data analytics
With the rising popularity of Li-ion batteries, the ability to attain accurate estimation of the battery core and surface temperature is of crucial importance to ensure the operational performance, safety, and reliability usage of Li-ion batteries. Impedance-based and data-driven based temperat...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/157723 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | With the rising popularity of Li-ion batteries, the ability to attain accurate estimation of the battery
core and surface temperature is of crucial importance to ensure the operational
performance, safety, and reliability usage of Li-ion batteries.
Impedance-based and data-driven based temperature estimation gaining
substantial popularity in recent years because of their sensorless estimation
characteristic and lower modeling complexity, this study proposes to study a hybrid
model of impedance-based temperature estimation method with Stochastic
Configuration Network (SCN) approach. To further explore on the accuracy
performance of SCN, the model will be compared against Artificial Neural Network
(ANN) and Support Vector Regression (SVR). The performance of the models will then be assessed
in terms of root mean square error (RMSE) and mean absolute error (MAE). |
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