Research On Lithiumion Battery Detection And Diagnosis And Energy Management Strategy

With the development of new energy vehicles,the second use of power lithium batteries in the field of energy storage has received widespread attention.The safety and reliability of power lithium batteries are the key technology and technical difficulties.The power lithium battery has the following challenges in safety and reliability of energy storage:1)The difference of cells affects the remaining life of battery packs,and poor cells are prone to safety risks.Battery internal resistance is one of the key parameters to characterize the health status of lithium batteries,but it is difficult to measure.2)In engineering battery systems,there are usually a large number of cells and a large amount of cell information.In the application process,how to quickly and accurately obtain valid information to identify the progressive failure signal.3)Lithium batteries have battery aging,and self-discharge.So for energy storage power supply systems,how to effectively ensure that the energy of the energy storage unit that has been used as backup power for a long time can meet the requirements of backup power.About the above problems,the specific research content is as follows:1)this article first analyzed the charging voltage curve and IC curve of the lithiumion cell cycled 400 times,and proposed a characteristic parameter that characterizes the difference between the monomers:the capacity increase internal resistance difference?35?R_IC.The cubic spline interpolation method was used to obtain the peak d Q/d V of the battery pack cell charge,extracted the parameters that characterize the consistency of the cells,and used the box plot to detect and diagnose abnormal cells.Compared with the normal HPPC pulsed DC internal resistance test results,the comparison error is 2.5%.2)combined with the voltage model,the charging and discharging behavior of the battery pack's individual voltage extremes was analyzed,and the characteristics of the voltage extreme number distribution characteristics were studied.The discharge voltage extreme difference?V was proposed as a detection parameter.The detection and diagnosis technology:the decay path k of the discharge voltage extreme difference?V with the number of cycles to identify the progressive failure signal of the battery pack,and its technology considered non-property failure.It has been tested and applied in laboratory data and engineering application data.As a result,the battery pack's gradual failure signal can be identified in advance before the battery fails.3)proposed the"N+2"backup strategy for the lithium battery in the energy storage DC system,and carried out an orderly exchange of the identity of the energy storage unit,so as to realize the detection of the entire system while it is running.The inflection point of the curve was obtained by processing the V-Q curve using Python.The energy in the inflection point range was compared with the energy in 20%?80%SOC interval.The pre-backup power was subjected to a check discharge based on the accident load curve in the two interval.The result showed inflection interval can maximize the use of energy,and reduce the impact of the SOC error.On the whole,this paper studied the safety and reliability of lithium battery second energy storage applications.At some point in the time axis,the battery pack internal resistance consistency test is performed using charging data,and in the time axis dimension,the discharge voltage extreme value within a period identified a gradual failure signal.The"N+2"backup principle and a check-discharge strategy for the inflection interval of the backup unit are proposed.The research content provides a certain reference value for the application of lithium battery energy storage technology.The method of running and detecting improved the data utilization rate,reduced the operation and maintenance cost of energy storage batteries,and promoted the detection of lithium batteries to energy-saving,fast,efficient,and high-performance directions.