-(7)Research on the Diagnosis Method of Micro Short Circuit in Lithium Iron Phosphate Battery Pack

(7)Research on the Diagnosis Method of Micro Short Circuit in Lithium Iron Phosphate Battery Pack
author:enerbyte source:本站 click200 Release date: 2023-10-18 08:54:21
abstract:
Analyzing the battery pack Δ At the same time as C, inspect the battery pack's various modules Δ U for analysis. Figure 5 shows the voltage curves of each module at the end of each charge in three battery pack tests, which can be calculated Δ U. Each module Δ The U-curve is shown in Fi...

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Analyzing the battery pack Δ At the same time as C, inspect the battery pack's various modules Δ U for analysis. Figure 5 shows the voltage curves of each module at the end of each charge in three battery pack tests, which can be calculated Δ U. Each module Δ The U-curve is shown in Figure 6. Most of the 13 modules in the battery pack have Δ U does not exceed ± 10mV, with -10mV ≤ Δ U ≤ 10mV is the charging data selection condition, and combined with Figure 5 and Figure 6, select the 6-9 charging data in Test 1, the 11-17 charging data in Test 2, and the 20-25 charging data in Test 3.

Considering the battery pack comprehensively Δ C and each module's Δ V. The specific charging data selected is shown in Table 1.

Table 1 Selected Charging Data Statistics

2.3 Analysis of micro short circuits in modules in battery packs

Select the module that first reaches the charging cutoff voltage, and use its voltage curve as the reference to calculate the relative charging time of each module during each charging Δ Tn, j. The voltage curve of the battery pack during a certain charge is shown in Figure 7. During the charging process, module 10 first reaches the charging cutoff voltage. Based on the charging voltage curve of module 10, the relative charging time of other modules is calculated Δ Tn, j, and Kn-n-1, j values, and analyze the consistency of Kn-n-1, j values through box plots.

The box diagram of Kn-n-1 and j values for each module is shown in Figure 8. Multiple abnormal values appear in the figure. According to the statistics of Kn-n-1, the module numbers with abnormal j values are shown in Table 2. The modules with abnormal Kn-n-1 and j values are Module 2 and Module 6. There are two reasons for the abnormal values of Kn-n-1 and j, namely micro short circuits and high internal resistance. Calculate the internal resistance of each module for further analysis.

Table 2Kn-n-1, Statistics of Module Numbers with Abnormal j Values

Calculate the DC internal resistance of each module based on the static voltage and charging voltage before each test [11]. The formula for calculating the DC internal resistance is

Among them, k is the number of tests; U1-k, j is the voltage of module j during k-th test quiescence; U2-k, j is the voltage of module j at 10 seconds after the start of the k-th test of charging; Ik is the charging current for k tests.

According to formula (4), calculate the DC internal resistance of each module in the three tests. The DC internal resistance curve of each module is shown in Figure 9. The maximum DC internal resistance value of module 6 in the figure proves that the reason for the abnormal Kn-n-1 and j of module 6 is the large DC internal resistance value. Analyze the consistency of DC internal resistance of modules in the battery pack using a box diagram, as shown in Figure 10. There are no modules with abnormal DC internal resistance in the battery pack. To eliminate the impact of DC internal resistance on diagnostic results, module data with DC internal resistance values not exceeding the median of 3/4, namely the data of modules 6, 7, and 10 with larger DC internal resistance values, are selected to ensure the accuracy of diagnostic results.

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