TY - JOUR
T1 - A Novel Multiple Correction Approach for Fast Open Circuit Voltage Prediction of Lithium-ion Battery
AU - Jinhao, Meng
AU - Stroe, Daniel-Ioan
AU - Ricco, Mattia
AU - Guangzhao, Luo
AU - Maciej, Swierczynski
AU - Teodorescu, Remus
PY - 2019/6
Y1 - 2019/6
N2 - This paper proposes a novel fast open circuit voltage prediction approach for Lithium-ion battery, which is potential to facilitate a convenient battery modeling and states estimation in the energy storage system. Open circuit voltage measurement suffers from a long relaxation time (several hours, even days) to reach the thermodynamic equilibrium of the battery. On the basis of the feedback control theory, the proposed multiple correction approach utilizes the constrained nonlinear optimization of the power function in each curve fitting step. The voltage measurement in a short period is divided into several segments to correct the voltage prediction multiple times with the feedback errors after each curve fitting. The similarity between the shape of the power function and the variation of the terminal voltage during the relaxation time is utilized. The proposed method can speed up the time-consuming open circuit voltage measurement and predict the open circuit voltage with high accuracy. Experimental tests on a LiFePO4 battery prove the validation and effectiveness of the proposed method in accurately predicting the open circuit voltage within a very short relaxation time (less than 15 min).
AB - This paper proposes a novel fast open circuit voltage prediction approach for Lithium-ion battery, which is potential to facilitate a convenient battery modeling and states estimation in the energy storage system. Open circuit voltage measurement suffers from a long relaxation time (several hours, even days) to reach the thermodynamic equilibrium of the battery. On the basis of the feedback control theory, the proposed multiple correction approach utilizes the constrained nonlinear optimization of the power function in each curve fitting step. The voltage measurement in a short period is divided into several segments to correct the voltage prediction multiple times with the feedback errors after each curve fitting. The similarity between the shape of the power function and the variation of the terminal voltage during the relaxation time is utilized. The proposed method can speed up the time-consuming open circuit voltage measurement and predict the open circuit voltage with high accuracy. Experimental tests on a LiFePO4 battery prove the validation and effectiveness of the proposed method in accurately predicting the open circuit voltage within a very short relaxation time (less than 15 min).
KW - Open Circuit Voltage
KW - Multiple Correction Approach
KW - Fast Prediction
KW - Lithium-Ion Battery
UR - http://www.scopus.com/inward/record.url?scp=85056334758&partnerID=8YFLogxK
U2 - 10.1109/TEC.2018.2880561
DO - 10.1109/TEC.2018.2880561
M3 - Journal article
SN - 0885-8969
VL - 34
SP - 1115
EP - 1123
JO - I E E E Transactions on Energy Conversion
JF - I E E E Transactions on Energy Conversion
IS - 2
M1 - 8528545
ER -