Remaining useful life prediction of lithium-ion batteries with adaptive unscented kalman filter and optimized support vector regression.
Zhiwei XueYong ZhangCheng ChengGuijun MaPublished in: Neurocomputing (2020)
Keyphrases
- support vector regression
- autoregressive conditional heteroscedasticity
- unscented kalman filter
- support vector
- regression model
- prediction accuracy
- hybrid model
- prediction model
- kernel function
- support vector classification
- support vector machine
- dynamic model
- electric vehicles
- support vector machine svm
- prediction error
- position and orientation
- state estimation
- constant velocity
- artificial neural networks
- extended kalman filter
- pattern recognition
- visual tracking
- machine learning