Lead-acid power battery system fault diagnosis method

A power battery and system failure technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of insufficient intelligence, low judgment and recognition rate, etc.

Inactive Publication Date: 2014-09-03
CHONGQING UNIV OF POSTS & TELECOMM
View PDF3 Cites 34 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the defects of low judgment recognition rate and insufficient intelligenc...

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
  • Lead-acid power battery system fault diagnosis method
  • Lead-acid power battery system fault diagnosis method
  • Lead-acid power battery system fault diagnosis method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0034] The invention relates to a fault diagnosis method for a lead-acid power battery system, which includes two parts: an off-line training and identification process and an online diagnosis and identification by adding a genetic algorithm to optimize parameter support vector machines. The steps taken are as follows figure 1 shown. The specific operation includes the following steps:

[0035] 1: Offline operation

[0036] (1) By adjusting different parameters in the virtual simulation model of the whole vehicle, the data collected by the battery system under standard working conditions, abnormal working conditions and extreme working conditions form a fault detection sample classification training set. The battery system selected in this project Fault samples are divided into no fault samples, abnormal battery total voltage samples, abnorma...

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

The invention provides a lead-acid power battery system fault diagnosis method. The method involves an off-line part and an on-line part. The method includes the specific steps that in the off-line state, data are collected through a simulation model, the data are preprocessed by using a normalization method, a data classification training set and a testing set of a power battery system of a support vector machine are obtained, parameter adaptive optimization is conducted through a GA algorithm, a one-to-one method is used for training to obtain a diagnostic model of the support vector machine, and SVM decision classification is conducted; in the on-line state, a fault generating device is used for simulating fault signals, the signals are collected through a collection module, the data are preprocessed by using the normalization method, the data are further input into an SVM module in off-line training, and fault online classification based on an SVM algorithm is conducted. According to the lead-acid power battery system fault diagnosis method, intelligent off-line and on-line diagnosis of faults of the battery system can be achieved, and meanwhile the fault diagnosis recognition rate is increased.

Description

technical field [0001] This patent belongs to the field of fault diagnosis of new energy vehicle systems, and in particular relates to a lead-acid power battery system fault diagnosis method based on GA optimal parameter support vector machine (SVM: Support Vector Machine). Background technique [0002] Electric vehicles are an important development direction of the future automobile industry. The power battery system is an important part of electric vehicles, and its safety and reliability are directly related to the safe driving of people and vehicles. However, at this stage, the failure of the power battery system cannot be diagnosed quickly, accurately, and intelligently, which will affect the normal driving of the vehicle, and even cause some safety hazards, which pose a great threat to the driver's safety. [0003] Too many parameters in the battery system bring great difficulties to the development of the fault diagnosis function. How to judge its fault quickly, accu...

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
IPC IPC(8): G06F17/50G06N3/12
Inventor 禄盛张骞陈平张艳
Owner CHONGQING UNIV OF POSTS & TELECOMM
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