Using an Extreme Learning Machine and an Extended Kalman Filter, State of Charge Estimation for Lithium-Ion Batteries
Author:
Affiliation:
1. K.S Rangasamy College of Technology (Autonomous),Department of Mechatronics Engineering,Tiruchengode,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10548017/10548035/10549247.pdf?arnumber=10549247
Reference15 articles.
1. State of charge estimation of Lithium-ion batteries based on the probabilistic fusion of two kinds of cubature Kalman filters
2. A comparative study of the influence of different open circuit voltage tests on model‐based state of charge estimation for lithium‐ion batteries
3. Research on Co-Estimation Algorithm of SOC and SOH for Lithium-Ion Batteries in Electric Vehicles
4. Online Estimations of Li-Ion Battery SOC and SOH Applicable to Partial Charge/Discharge
5. Novel method for modelling and adaptive estimation for SOC and SOH of lithium-ion batteries
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