Enhanced state of charge estimation for Li-ion batteries through adaptive maximum correntropy Kalman filter with open circuit voltage correction

Digital twin with augmented state extended Kalman filters for forecasting electric power consumption of industrial production systems

“…This algorithm and its numerous variants, such as the Extended Kalman Filter (EKF) and the Unscented Kalman Filter, are widely applied in navigation, guidance and robotics technologies (position estimation, trajectory tracking and object detection), and are also suitable for solving problems in many other fields, such as econometrics and medicine [ 30 ]. In industrial electronics, the main implementations concern signal processing and instrumentation, electric motor sensorless control and health monitoring, and other control systems [ 31 ], as well as energy storage systems for charge state estimation [ [32] , [33] , [34] ]. The Augmented State Kalman Filter effectively deals with models containing parameters which deviate from nominal values due to unknown biases, by including the bias terms in the state vector [ 35 ].…”

Beyond conventional predictions: unfolding the ensemble Kalman filter's publications in renewable energy

“…The current transition towards renewable energy sources raises the role of advanced technical and methodological innovations in the energy industry with respect to solving the necessity of reducing dependence on fossil fuel and countering the consequences of climate change [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. Of these, the Ensemble Kalman Filter (EnKF) has become the central component in the accurate modelling, prediction, and optimal operation of renewable energy systems [17][18][19][20][21][22][23][24][25][26].…”