A lithium battery state-of-charge estimation method considering sensor and model errors

A technology of model error and state of charge, applied in the field of state of charge estimation of lithium batteries, can solve problems such as large SOC errors, and achieve the effects of improving accuracy and robustness, accurate and stable SOC estimation results, and simple and easy algorithms

Active Publication Date: 2019-12-06
UNIV OF SHANGHAI FOR SCI & TECH
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Problems solved by technology

Therefore, the traditional Ah integration method or EKF method will have a large SOC error

Method used

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  • A lithium battery state-of-charge estimation method considering sensor and model errors
  • A lithium battery state-of-charge estimation method considering sensor and model errors
  • A lithium battery state-of-charge estimation method considering sensor and model errors

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Embodiment

[0031] like figure 1 As shown, the present invention designs a SOC estimation fusion algorithm by combining the advantages of the Ah integral method and the EKF method. The specific implementation process is as follows:

[0032] The SOC value was estimated by Ah integral method and EKF method respectively.

[0033] (1) The formula for calculating SOC by Ah integral method is as follows:

[0034]

[0035] In the formula, SOC AH (t) is the SOC value obtained by Ah integration method at time t, SOC(t 0 ) is the initial time t 0 SOC value, C N is the capacity of the battery, i(τ) is the current at time τ, η c is Coulombic efficiency.

[0036] (2) The process of estimating SOC by EKF method is as follows:

[0037] Suppose the state vector to be estimated at time k is x k , the system output is y k , the system input is u k , the state equation can be expressed as:

[0038] x k+1 =f(x k ,u k )+w k

[0039] the y k =g(x k ,u k )+v k

[0040] In the formula, w...

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Abstract

The invention relates to a lithium battery state of charge (SOC) estimation method in consideration of sensor and model errors. The lithium battery SOC is estimated through integrating an Ah integralmethod and an EKF method. The method comprises the following steps: 1) the Ah integral method and the EKF method are adopted to acquire the SOC values and the SOC increments of the lithium battery atthe current moment; 2) according to the SOC increments acquired in the two methods, an SOC increment with higher credibility is judged; and 3) according to the SOC increment with higher credibility, the SOC value of the lithium battery at the current moment is calculated through a fusion algorithm. Compared with the prior art, the lithium battery state of charge (SOC) estimation method in consideration of sensor and model errors has the advantages that the precision is high; the robustness is good; the method is simple; the method is applicable to an electric vehicle; and the like.

Description

technical field [0001] The invention relates to the field of state of charge estimation of lithium batteries, in particular to a method for estimating state of charge of lithium batteries considering errors of sensors and models. Background technique [0002] Accurate estimation of battery status can improve battery performance and extend battery life, and is one of the key technologies in battery management systems for electric vehicles. However, SOC cannot be measured directly, but can only be estimated from other measurables (such as current, voltage, temperature, etc.). At present, the common SOC estimation methods include Ah integral method, open circuit voltage method, neural network method, support vector machine method, EKF method, etc. Judging from the literature at home and abroad, the Ah integration method and the EKF method are widely used SOC estimation methods. These two methods have their own advantages and disadvantages: the calculation process of the Ah int...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/382G01R31/378
CPCG01R31/367
Inventor 来鑫郑岳久周龙秦超金昌勇
Owner UNIV OF SHANGHAI FOR SCI & TECH
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