Real-time estimation of battery state-of-charge with unscented Kalman filter and RTOS μCOS-II platform

2016 ◽  
Vol 162 ◽  
pp. 1410-1418 ◽  
Author(s):  
Hongwen He ◽  
Rui Xiong ◽  
Jiankun Peng
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Unscented Kalman Filter ◽  
Time Estimation ◽  
State Of Charge ◽  
Battery State Of Charge ◽  
Real Time Estimation

scholarly journals Real-Time Estimation of Battery State of Charge With Metabolic Grey Model and LabVIEW Platform

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 13170-13180 ◽  
Author(s):  
Dong Zheng ◽  
Huimin Wang ◽  
Jingjing An ◽  
Jing Chen ◽  
Haihong Pan ◽  
...  
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
State Of Charge ◽  
Grey Model ◽  
Battery State Of Charge ◽  
Real Time Estimation ◽  
Labview Platform

Real-Time Estimation of Lithium-Ion Concentration in Both Electrodes of a Lithium-Ion Battery Cell Utilizing Electrochemical–Thermal Coupling

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
Satadru Dey ◽  
Beshah Ayalew
Keyword(s):  
Real Time ◽  
Unscented Kalman Filter ◽  
Lithium Ion ◽  
Time Estimation ◽  
Li Ion Battery ◽  
Battery Cell ◽  
Thermal Dynamics ◽  
Estimation Scheme ◽  
Real Time Estimation ◽  
Li Ion

This paper proposes and demonstrates an estimation scheme for Li-ion concentrations in both electrodes of a Li-ion battery cell. The well-known observability deficiencies in the two-electrode electrochemical models of Li-ion battery cells are first overcome by extending them with a thermal evolution model. Essentially, coupling of electrochemical–thermal dynamics emerging from the fact that the lithium concentrations contribute to the entropic heat generation is utilized to overcome the observability issue. Then, an estimation scheme comprised of a cascade of a sliding-mode observer and an unscented Kalman filter (UKF) is constructed that exploits the resulting structure of the coupled model. The approach gives new real-time estimation capabilities for two often-sought pieces of information about a battery cell: (1) estimation of cell-capacity and (2) tracking the capacity loss due to degradation mechanisms such as lithium plating. These capabilities are possible since the two-electrode model needs not be reduced further to a single-electrode model by adding Li conservation assumptions, which do not hold with long-term operation. Simulation studies are included for the validation of the proposed scheme. Effect of measurement noise and parametric uncertainties is also included in the simulation results to evaluate the performance of the proposed scheme.

scholarly journals A Mobile Kalman-Filter Based Solution for the Real-Time Estimation of Spatio-Temporal_newline Gait Parameters

2016 ◽  
Vol 24 (7) ◽  
pp. 764-773 ◽  
Author(s):  
Alberto Ferrari ◽  
Pieter Ginis ◽  
Michael Hardegger ◽  
Filippo Casamassima ◽  
Laura Rocchi ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Time Estimation ◽  
The Real ◽  
Gait Parameters ◽  
Real Time Estimation

A Method for Real-Time Estimating Pose of Large Aircraft Component in Process of Pose Adjustment Based on the Unscented Kalman Filter

2012 ◽  
Vol 442 ◽  
pp. 251-255
Author(s):  
Zheng Ying
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Unscented Kalman Filter ◽  
Kinematic Model ◽  
Estimation Method ◽  
Time Estimation ◽  
Measuring Point ◽  
Aircraft Component ◽  
Forward Kinematic ◽  
Large Aircraft

To estimate the pose of large aircraft component in pose adjustment quickly and accurately, a real-time estimation method based on Unscented Kalman filter (UKF) is proposed. Firstly, in the process of the aircraft component adjustment, a rough value of aircraft component’s pose is acquired by using forward kinematic model and the displacement of positioners on real time. Then, position of a measuring point fixed on aircraft component is obtained by a laser tracker. At last, UKF is employed to integrate the previous rough value and the measuring point position for evaluating the accurate pose of aircraft component. Numerical simulation results show that the presented method is achieved easily, calculated fast and high accurate.

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