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SOC estimation optimization method for power battery under simulated vehicle working conditions

A power battery and state of charge technology, which is applied in the field of SOC estimation and optimization of the power battery state of charge under simulated vehicle working conditions, can solve the problems of unfixed sampling time interval and discrete collection time, and achieve the effect of improving the stability of estimation

Active Publication Date: 2020-07-17
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

This method provides a method for calculating the state of charge of lithium-ion batteries in electric vehicles, which can predict the SOC of single batteries through training data sets. The collection time is discrete and the sampling time interval is not fixed, and the training data used in the battery SOC prediction is the state of charge after the battery capacity is converted, but the battery capacity is quite different under different operating temperatures

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  • SOC estimation optimization method for power battery under simulated vehicle working conditions
  • SOC estimation optimization method for power battery under simulated vehicle working conditions
  • SOC estimation optimization method for power battery under simulated vehicle working conditions

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Embodiment Construction

[0021] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the embodiments and accompanying drawings.

[0022] Such as figure 1 As shown, the SOC estimation method and evaluation workflow of the power battery state of charge under simulated vehicle dynamic conditions include: controlling the power battery to perform constant power and variable power mode charge and discharge simulations under different initial working conditions and ambient temperatures, using interpolation to adjust sampling Data, grouping the data set, training the training set, optimizing the network structure through the test set to improve accuracy and stability; specifically include the following steps:

[0023] Step 10 Control the operating temperature of the power battery module in the temperature control box, so that the battery module operates under constant power charging ...

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Abstract

The invention discloses an SOC estimation optimization method for a power battery under simulated vehicle working conditions. The method comprises the following steps of controlling a power battery toperform constant-power and variable-power mode charging and discharging simulation at different initial working condition environment temperatures, adjusting sampling data by utilizing interpolation,grouping a data set, training a training set, and optimizing a network structure through a test set to improve the precision and the stability. The estimation stability for different temperature environments and charging and discharging switching working conditions is improved.

Description

technical field [0001] The invention relates to the technical field of battery management systems, in particular to a method for estimating and optimizing the SOC of a power battery under simulated vehicle operating conditions. Background technique [0002] The state of charge (SOC) of the power battery is an important parameter for evaluating the operating state of the battery in the battery management system. The SOC of the battery state of charge represents the remaining power of the battery and has reference value for the cruising range of the vehicle. Moreover, the battery state of charge SOC is an important basis for predicting other battery parameters such as battery state of health (SOH), battery state of energy (SOE), and battery state of power (SOP). [0003] At present, the SOC prediction methods of domestic power batteries are mainly divided into ampere-hour integral method, open circuit voltage method, and model-based method. Among them, the model-based method ...

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Application Information

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IPC IPC(8): G01R31/367G06N3/08
CPCG06N3/084G01R31/367
Inventor 刘桂雄李泓沛李远茂
Owner SOUTH CHINA UNIV OF TECH
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