Lithium ion battery state-of-charge estimation method

Abstract

The invention relates to a lithium ion battery state-of-charge estimation method, belongs to the field of battery charge testing and provides a lithium ion battery SOC estimation method based on a fractional order Kalman filtering method. The lithium ion battery state-of-charge estimation method comprises the specific steps of establishing a fractional order state space model of a lithium ion battery, obtaining a relation curve of open-circuit voltage and a charge state through fitting and using the fractional order Kalman filtering method to estimate the SOC of the lithium ion battery. The lithium ion battery state-of-charge estimation method simulates complicated electric chemical reaction inside the battery well, improves the modeling accuracy of the lithium ion battery and further improves the estimation accuracy of the SOC of the lithium ion battery.

Description

technical field [0001] The invention belongs to the field of testing battery state of charge. Background technique [0002] The battery state of charge (State of Charge, SOC) is used to represent the remaining capacity of the battery, which can only be estimated indirectly by measuring the external characteristic parameters (such as voltage, current, and temperature) of the battery pack. During the use of lithium-ion power batteries for electric vehicles, the internal electrochemical reactions are complex, and its dynamic system is highly nonlinear, which makes it very difficult to accurately estimate the state of charge (SOC) of the battery. [0003] Scholars at home and abroad have done a lot of research on battery state of charge (SOC) estimation algorithms. At present, the commonly used model-based estimation algorithms include state observer method, Kalman filter method, extended Kalman filter method, etc., but the above methods only It can express the integer-order fu...

AI Technical Summary

Problems solved by technology

During the use of lithium-ion power batteries for electric vehicles, the internal electrochemical reactions are complex, and its dynamic system is highly nonlinear, which makes it very difficult to accurately estimate the state of charge (SOC) of the battery.

[0003] Scholars at home and abroad have done a lot of research on battery state of charge (SOC) estimation algorithms. At present, the commonly used model-based estimation algorithms include state observer method, Kalman filter method, extended Kalman filter method, etc., but the above methods only It can express the integer-order functional relationship between the battery current and the terminal voltage, but cannot express the fractional-order functional relationship embodied in the complex electrochemical reactions inside the battery

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