Font Size: a A A

Research On Defect Detection Method Of Lithium Iron Phosphate Power Battery Based On Tomographic Image

Posted on:2017-05-28Degree:MasterType:Thesis
Country:ChinaCandidate:Y Q XuFull Text:PDF
GTID:2272330503468737Subject:Vehicle Engineering
Abstract/Summary:PDF Full Text Request
The defect detection of the power battery is one of the most important technology to improve the manufacturing of battery and the control strategy of electric vehicle. Aiming at the problem of long time and destructive to find out the structure form change of self-discharge and capacity loss in the power battery, the defect detection method of lithium iron phosphate power battery based on tomographic images was studied with the battery from production and process.Firstly, the defects of the battery from production and process were introduced, and the expression forms of the defects were discussed on the two aspects of cell electrochemical properties and the structure form. Then, the effects of the lithium iron phosphate power battery production process, working environment and the control strategy of electric vehicle battery on the lithium iron phosphate power battery defects were studied.Then, in allusion to the shortage of the current battery defect detection methods, the defect detection method of lithium iron phosphate power battery based on tomographic image was researched. This method include the method of electrochemical performance parameters and the X-ray tomography technique based on material attenuation theory. On this basis, the principle of the method and the electrochemical properties and the characteristics of the tomographic image analysis method were discussedIn the end,the experimental platform were designed, the defect detection experiment was carried out on the lithium iron phosphate power battery, to verify the effectiveness of the proposed lithium iron phosphate power battery defect detection method was feasible.
Keywords/Search Tags:lithium iron phosphate power battery, defect detection, tomographic image, capacity loss, self-discharge
PDF Full Text Request
Related items