Evaluation method for system on chip (SOC) of charging station battery

A charging station and battery technology, which is applied in computing, electrical digital data processing, special data processing applications, etc. Repair, improve computing efficiency, solve the effect of identity problems

Inactive Publication Date: 2012-03-21
XIANGTAN UNIV
View PDF0 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The internal resistance method is based on the relationship between the internal resistance of the battery and the SOC to predict the SOC, but the internal resistance of the battery is affected by many factors, the measurement results are easily disturbed, and the reliability is not high; Complicated and computationally intensive, so it is more difficult in practical applications

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Evaluation method for system on chip (SOC) of charging station battery
  • Evaluation method for system on chip (SOC) of charging station battery
  • Evaluation method for system on chip (SOC) of charging station battery

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0018] Embodiment 1, by figure 1 It can be seen that when the battery is charging, the acquisition module 5 collects external characteristic data such as voltage, current, and temperature from the battery pack, and passes the data to the neural network module 6 as input after processing through A / D conversion; There is inherent information of the battery, such as battery type and nominal capacity C, its data is read out through the read-write module and used as the input of the neural network module 6; at the same time, the obtained power Q and cycle times L are obtained through the network communication of the charging station As the input of the life factor prediction module 7, the curve f(x) is fitted to the power value of the fully charged battery when the number of cycles is used and its corresponding number of times, and then the differential operation is obtained to obtain the life factor K r =f'(x), the life factor is also used as the input of the neural network module...

Embodiment 2

[0021] Embodiment 2, by figure 1 , figure 2 It can be seen that when the battery is charged at the charging station, the data read-write module 8 sends a radio frequency signal of a specific frequency through the transmitting antenna 13, and the information chip 9 can generate an induced current, thereby obtaining energy and being activated, so that the information chip 9 transmits its own encoded information through The built-in radio frequency antenna sends out; the receiving antenna 13 of the data reading and writing module 8 receives the transmitted modulated signal, transmits it to the logic control unit 11 through the radio frequency interface module 12, and then sends the valid information to the background host system for related processing; the host system Identify the identity of the chip according to the logical operation, make corresponding processing and control, and finally issue an instruction signal to control the data reading and writing module 8 to complete ...

Embodiment 3

[0022] Embodiment 3, by figure 2 , image 3 It can be seen that the data detection and analysis module 14 detects a series of data such as the nominal capacity of the battery read in the data reading and writing module 8, the number of times of cycle use, the number of times of predicted use, and the charge and discharge records, analyzes the data, and transmits the preprocessed data blocks To the processing module 15, the life factor processing module 15 fits the curve to the data and processes the data according to a predetermined differential processing algorithm to obtain the life factor Kr of the battery, and outputs Kr to the neural network module 6 to realize accurate estimation of the SOC value; And the predicted life factor is stored in the information chip through the data reading and writing module. When the battery is working, it is used as a parameter for the battery management system of the electric vehicle to estimate the SOC, so as to improve the calculation e...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

An evaluation method for a system on a chip (SOC) of a charging station battery mainly solves the technical problem of charging station battery identity authentication and management and SOC evaluation algorithm of a charging station battery. The technical scheme is that: providing a charging station battery SOC nerve network evaluation method on the basis of standard model analysis of a charging station battery management scheme and a SOC evaluation method of a nerve network under the environment of an intelligent power grid based on type and life factor. A reading-writing module in a management system is used for reading inherent output information including a sole battery information identify (ID) number, a battery type, rated capacity and the like stored in an information chip of an ordinary battery, and rapid battery authentication under an united authentication system can be achieved. The charging station battery management system can use historic charging data of a battery from a network server through communication of a process layer network and a between station network of the charging battery so as to fit a curve of circulation time and electricity amount value, work out the life factor and judge the life state of the battery. On the basis that voltage, current and temperature serve as an input in the standard model of the nerve network, the battery type and life factor are added as input so as to achieve accurate evaluation of the charge state of the charging station battery.

Description

technical field [0001] The invention relates to a method for estimating the SOC of a rechargeable battery in a charging station, in particular to a battery type, and a method for accurately estimating the battery SOC by obtaining input data of a neural network part through a network communication method of the charging station. Background technique [0002] Most of the existing charging station planning electric vehicle charging schemes use electric vehicle on-site charging, and the management of the battery during charging is also carried out through the vehicle-mounted battery management system and the charging management system of the charging station. This charging method takes a long time to charge, and it is difficult to control the overcharge or undercharge of the battery. Fast charging with a large current will cause great damage to the battery and seriously affect the battery life. Yang Qing, deputy general manager of the State Grid Corporation, also said at the Chi...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00G06N3/02
Inventor 段斌邓清勇谭云强王林
Owner XIANGTAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap