Abstract
A fuzzy model was established to estimate the state of charge (SOC) of a lithium-ion battery for electric vehicles. The robust Gustafson-Kessel (GK) clustering algorithm based on clustering validity indices was applied to identify the structure and antecedent parameters of the model. The least squares algorithm was utilized to determine the consequent parameters. Validation results show that this model can provide accurate SOC estimation for the lithium-ion battery and satisfy the requirement for practical electric vehicle applications. Copyright.
| Original language | English |
|---|---|
| Pages (from-to) | 416-421 |
| Number of pages | 6 |
| Journal | Journal of Beijing Institute of Technology (English Edition) |
| Volume | 19 |
| Issue number | 4 |
| Publication status | Published - Dec 2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Electric vehicle
- Fuzzy identification
- Gustafson-Kessel (GK) clustering
- Lithium-ion battery
- State of charge (SOC)
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