Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles

444 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries (2019, background): “The initial SOC [176], battery charge/discharge current [60] and battery capacity [177] are required for the calculation of the predicted SOC.”
A Study on the Open Circuit Voltage and State of Charge Characterization of High Capacity Lithium-Ion Battery Under Different Temperature (2018, methodology): “Besides, open circuit voltage is used to correct the estimated SOC, the OCV-SOC modeling is very important not only in OCV-based estimation but also in model-based estimation [29].”
State-of-Health Estimation Based on Differential Temperature for Lithium Ion Batteries (2020, methodology): “However, the ICA theory was developed based on OCV data which are usually obtained through 1/25 C charging/discharging [15].”
Online State-of-Health Estimation for Li-Ion Battery Using Partial Charging Segment Based on Support Vector Machine (2019, background): “And the co-estimation is essential to guarantee the stable operation of a BMS [24], [25].”