Transfer between multiple working conditions: A new TCCHC-based exponential semi-deterministic extended Kalman filter for bearing remaining useful life prediction

Measurement ◽  
2019 ◽  
Vol 142 ◽  
pp. 148-162 ◽  
Author(s):  
Fei Shen ◽  
Jiawen Xu ◽  
Chuang Sun ◽  
Xuefeng Chen ◽  
Ruqiang Yan
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Working Conditions ◽  
Life Prediction ◽  
Remaining Useful Life ◽  
Useful Life

scholarly journals Remaining Useful Life Prediction of Li-Po Batteries in UAVs Using Extended Kalman Filter

2015 ◽  
Vol 5 (12) ◽  
Author(s):  
Darielson A. Souza ◽  
João L. O. Torres ◽  
João Paulo P. Gomes ◽  
Leonardo R. Rodrigues ◽  
Rômulo N. de C. Almeida ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Life Prediction ◽  
Remaining Useful Life ◽  
Li Po ◽  
Useful Life

Automotive Battery Prognostics Using Dual Extended Kalman Filter

2009 ◽  
Author(s):  
Matteo Rubagotti ◽  
Simona Onori ◽  
Giorgio Rizzoni
Keyword(s):  
Experimental Data ◽  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Remaining Useful Life ◽  
State Of Charge ◽  
Future Evolution ◽  
On Line ◽  
Automotive Batteries ◽  
Useful Life ◽  
Simulation Results

This paper proposes a strategy for estimating the remaining useful life of automotive batteries based on dual Extended Kalman Filter. A nonlinear model of the battery is exploited for the on-line estimation of the State of Charge, and this information is used to evaluate the actual capacity and predict its future evolution, from which an estimate of the remaining useful life is obtained with suitable margins of uncertainty. Simulation results using experimental data from lead-acid batteries show the effectiveness of the approach.

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