Abstract
To get computationally efficient algorithm which can diagnose the cell degradation by estimating the cell resistance in a battery management system (BMS), the ordinary least squares estimator (LMS filter) is employed to identify the parameter in the simple resistance model in the form of a first-order polynomial. As a result, the determined parameter estimate, the slope in the model, can be adapted to changes in the battery resistance. The devised algorithm is validated by using the cells with different state-of-health. These cells are aged at the elevated temperature over 24 weeks and tested at every four weeks to monitor changes in the cell resistance. Consequently, the devised algorithm can distinguish between the cell resistances which increase by 2 to 4% at every month.
| Original language | English |
|---|---|
| Pages (from-to) | 1195-1201 |
| Number of pages | 7 |
| Journal | Journal of Electrical Engineering and Technology |
| Volume | 11 |
| Issue number | 5 |
| DOIs | |
| State | Published - Sep 2016 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Battery management systems
- Degradation
- Internal resistance
- Least squares estimator
- Lithium-ion batteries
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