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Lithium ion battery SOC estimation algorithm based on FFRLS and EKF

A lithium-ion battery, SOC-OCV technology, applied in the field of lithium-ion battery SOC estimation algorithms, can solve the problems of large error, low SOC estimation accuracy, inability to realize online real-time estimation of model parameters, etc., to prevent data saturation and reduce Effect of SOC estimation error

Pending Publication Date: 2021-03-02
NANJING UNIV OF SCI & TECH
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Problems solved by technology

[0004] The purpose of the present invention is to provide a lithium-ion battery SOC estimation algorithm based on FFRLS and EKF, to solve the problem that the traditional lithium-ion battery SOC estimation algorithm cannot realize online real-time estimation of model parameters, and the SOC estimation accuracy is low and the error is large.

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  • Lithium ion battery SOC estimation algorithm based on FFRLS and EKF
  • Lithium ion battery SOC estimation algorithm based on FFRLS and EKF
  • Lithium ion battery SOC estimation algorithm based on FFRLS and EKF

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Embodiment

[0053] combine figure 2 , to establish a second-order Thevenin lithium-ion battery model, use the open circuit voltage E(t) to represent the voltage source, R to represent the ohmic resistance of the battery, and use a second-order resistance-capacitance loop to simulate the polarization process of the battery.

[0054] combine image 3 and Figure 4 , the abscissa is time, image 3 The ordinate is the discharge current, Figure 4 The ordinate of is the open circuit voltage. The intermittent discharge static method is used to determine the relationship between SOC-OCV. First, the battery is fully charged to 100% SOC, and secondly, a negative pulse is used for every 10% SOC. The current discharges the battery, and then stands still for 1h to eliminate the polarization reaction, and finally calculates the average value during standing to obtain the SOC-OCV curve. The pulse discharge current is set as C / 2, and its discharge time width corresponds to a certain amount of charg...

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Abstract

The invention discloses a lithium ion battery SOC estimation algorithm based on FFRLS and EKF, and the algorithm comprises the steps: building a lithium ion battery model, determining the relation ofSOC-OCV through employing a discharge standing method, estimating the initial parameters of a battery model in an offline state, and carrying out the parameter recognition of the battery model throughemploying a least square method FFRLS algorithm with a forgetting factor in an online state; and estimating the SOC by using an extended Kalman filter algorithm EKF. The algorithm is simple in algorithm implementation and high in practicability, the problem of large estimation error caused by the fact that a traditional Kalman filter cannot achieve parameter online estimation is solved through FFRLS and EKF, and the accuracy of the lithium ion battery estimation algorithm is guaranteed.

Description

technical field [0001] The invention relates to the field of battery charge state estimation, in particular to a lithium-ion battery SOC estimation algorithm based on FFRLS and EKF. Background technique [0002] Power battery is the main energy source of electric vehicles, and its SOC is one of the most important and basic parameters in the energy management system; only accurate SOC value estimation can make reasonable energy allocation, so as to use limited energy more effectively; Predict the remaining driving range of the vehicle. The definition of SOC (State of Charge) is the state of charge of the battery, which is used to indicate the remaining power of the battery. The battery is a complex nonlinear system. When used in electric vehicles, it is difficult to obtain accurate noise statistics due to the large number of electronic devices and complex noise interference. In addition, the randomness of changes in external and internal environmental parameters makes the ma...

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Application Information

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IPC IPC(8): G01R31/367G01R31/388
CPCG01R31/367G01R31/388
Inventor 李庆超彭富明
Owner NANJING UNIV OF SCI & TECH
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