New energy vehicle energy balance control method and system based on intelligent internet of things

A technology for new energy vehicles and smart objects, applied in electric vehicles, charge balance circuits, battery/fuel cell control devices, etc., can solve problems such as the great influence of battery health status, and achieve the effect of improving accuracy and estimation accuracy

Active Publication Date: 2021-09-07
HUANGHUAI UNIV
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Problems solved by technology

There are few researches on the existing methods of active equalization of parallel battery packs. The main method is to equalize the terminal voltages of parallel battery packs through discharge and other measures. Since the number of charge and discharge times has a great impact on the health status of the battery, it is difficult for the existing technology to efficiently use parallel battery packs. Improve the overall service life of the battery pack at the same time

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  • New energy vehicle energy balance control method and system based on intelligent internet of things

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Embodiment 1

[0043] An energy balance control method for new energy vehicles based on the intelligent Internet of Things, comprising:

[0044] Step 1. Based on the charging curves of each battery pack of the new energy vehicle, use the first SOH estimation network to perform SOH estimation on each battery pack respectively to obtain the first SOH estimation sequence.

[0045] In the field of battery balancing, there have been many achievements on the power balance in the case of series power supply units, but there are few studies on the power balance between parallel power supply units. Existing power balancing is mainly realized through passive balancing or active balancing. Passive equalization, although it can achieve power balance, wastes part of the electric energy, which is not conducive to energy saving; active equalization achieves power balance by charging low-battery or low-voltage power supply units, and its disadvantage is that although power balance is achieved, it increases ...

Embodiment 2

[0074] This implementation presents an energy balance control method for new energy vehicles based on the intelligent Internet of Things. In order to improve the accuracy of the power estimation neural network, the power estimation neural network also includes a fourth network branch, which is used to analyze the power supply and obtain the fourth Eigenvectors; electricity forecasting network, used to analyze the eigenvectors after the fusion of the first, second, third, and fourth eigenvectors to obtain an estimated electricity sequence.

Embodiment 3

[0076] This embodiment provides an energy balance control method for new energy vehicles based on the intelligent Internet of Things, which is improved based on Embodiment 1. The second SOH estimation network also includes a charging frequency analysis network branch, which is used to analyze the charging frequency sequence , to get the charging times analysis vector. The charging times of each battery pack is the charging times of each battery pack receiving the BMS power balance module in the access mode corresponding to the second access time matrix, obtained through monitoring, and the charging times of each battery constitute a charging times sequence [B 1 ,B 2 ,...,B K ]. The SOH estimation network branch in the second SOH estimation network is used to analyze the eigenvectors after fusion of the initial SOH analysis vector, power change analysis vector, access time analysis vector, and charging times analysis vector to obtain the second SOH estimation sequence.

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Abstract

The invention discloses a new energy vehicle energy balance control method and system based on the intelligent internet of things. The method includes: using the first SOH estimation network to perform SOH estimation on each battery pack of the new energy vehicle to obtain a first SOH estimation sequence; generating a first access time matrix according to the first SOH estimation sequence and the starting power of the vehicle; generating a first access time matrix according to the access time The window size and battery pack access constraints are used to expand and correct the first access time matrix to obtain the second access time tensor; according to the first SOH estimation sequence and the second access time tensor, use the second SOH to estimate the network pair Each battery pack performs SOH estimation to obtain the second SOH estimation sequence; according to the second SOH estimation sequence of each battery pack, the energy balance degree of the new energy vehicle is calculated, and according to the second access time tensor channel matrix corresponding to the highest energy balance degree, The equilibrium control strategy of the new energy vehicle battery pack is obtained. The invention realizes the health state balance of the energy source of the automobile battery pack.

Description

technical field [0001] The invention relates to the field of new energy technology, in particular to an energy balance control method and system for new energy vehicles based on the intelligent internet of things. Background technique [0002] Active balancing is the mainstream direction of energy balancing for new energy batteries. Active balancing methods in the existing technology include temperature balancing, charging and discharging balancing, changing loads to increase uninterrupted output energy, etc. There are few researches on the existing methods of active equalization of parallel battery packs, and the main method is to equalize the terminal voltages of parallel battery packs through discharge and other measures. Since the number of charge and discharge times has a great impact on the health status of the battery, it is difficult for the existing technology to efficiently use parallel battery packs. At the same time as the battery pack, the overall service life o...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B60L58/22B60L58/16H02J7/00
CPCB60L58/16B60L58/22H02J7/0014Y02T10/70
Inventor 高海宁于磊张志勇沈红丹王银玲杨勇刘文富徐静贾锦婷杨一帆李锦杰
Owner HUANGHUAI UNIV
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