Hybrid electric vehicle power battery initial electric quantity algorithm

A technology of hybrid electric vehicles and initial power, applied in the field of power calculation, can solve problems such as the inapplicability of the open circuit voltage method, the accumulation of errors in the current integration method, and the calculation complexity of the Kalman filter, so as to improve the estimation accuracy and strong versatility , Adaptable effect

Pending Publication Date: 2019-08-30
HANTENG AUTOMOBILE CO LTD
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Problems solved by technology

Due to the highly nonlinear characteristics of the battery, the traditional SOC evaluation method cannot effectively reflect the accuracy of the evaluation. For example, the current integration method has error accumulation, and the open circuit voltage method is not suitable for frequent fluctuations in the pulsating current process; fuzzy control relies on Engineering experience, neural network depends on the selection of samples, Kalman filter depends on accurate calculation complexity, impedance spectroscopy method needs to construct additional functions and increases computer complexity; linear model method is only suitable for low current conditions

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  • Hybrid electric vehicle power battery initial electric quantity algorithm
  • Hybrid electric vehicle power battery initial electric quantity algorithm
  • Hybrid electric vehicle power battery initial electric quantity algorithm

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Embodiment 1

[0045] A hybrid electric vehicle power battery initial power algorithm, specifically comprising the following steps:

[0046] S1. ANFIS construction: Assuming that the fuzzy neural network has two input variables x and y, and one output variable z, according to the first-order T-S fuzzy model, the calculation formula is as follows:

[0047] Equation 1: For x∈A 1 , y∈B 1 ,but:

[0048] f 1 =p 1 x+q 1 y+r 1 ;

[0049] Equation 2: For x∈A 2 , y∈B 2 ,but:

[0050] f 2 =p 2 x+q 2 y+r 2 ;

[0051] S2,A 1 and B 1is the input variable fuzzy set, the node activation function of this layer represents the membership function of the fuzzy variable, and the output represents the fuzzy result, that is, the degree of membership. Among them, the node transfer function can be expressed as:

[0052] o 1，i =f x，i (X), i=1, 2

[0053] o 1，j =f y(j-2) (y),j=3,4

[0054] The Gaussian function is usually used as the activation function;

[0055] S3, multiplied by fuzzy to get...

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Abstract

The invention discloses a hybrid electric vehicle power battery initial electric quantity algorithm, comprising: ANFIS construction, ANFIS network structure determination, selection of a Gaussian membership function as an input and output membership function, division of an input variable space, and calculation of battery initial electric quantity Q1 by using a BP neural network and an ANFIS model. According to the scheme, the algorithm can monitor the electric quantity of the power battery in real time. The service life of the power battery is prevented from being influenced by overcharging or overdischarging of the power battery. Through analyzing the charging and discharging process of the battery is analyzed, key parameters of SOC is determined, the test model is corrected on the MatLab platform. Comparison by experimental simulation shows that ANFIS has good adaptive ability and generalization ability. The initial electric quantity estimation error of the battery is reduced to belower than 3%. The method can be used for an intelligent monitoring system of the hybrid electric vehicle, a temperature compensation coefficient is added, the temperature influence is corrected through the temperature compensation coefficient, and the estimation precision can be better improved.

Description

technical field [0001] The invention relates to the technical field of power calculation, in particular to an initial power calculation of a power battery of a hybrid electric vehicle. Background technique [0002] The battery management system is a power battery control system used in hybrid electric vehicles or pure electric vehicles, which controls the parameters and performance of all aspects of the power battery according to the needs of the vehicle. The battery management system is the bridge between the battery and the user. The main control object is the secondary battery. Its ultimate goal is to improve the efficiency of the battery, prevent the battery from overcharging and discharging, and protect the power battery as much as possible. Maximize performance. [0003] As the remaining power, SOC represents the percentage of remaining capacity in the initial capacity, ranging from 0% to 100%. Traditional SOC evaluation methods mainly include current integration meth...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06F17/15G06N3/04G01R31/367G01R31/387
CPCG06F17/15G01R31/387G01R31/367G06F2119/08G06F30/20G06N3/043
Inventor 段永生张佳谋常康伟
Owner HANTENG AUTOMOBILE CO LTD
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