Battery health-life prediction method based on piezoelectric ultrasonic sensor's ultrasonic frequency response calculation varying with soc

Abstract

The application discloses a battery health life prediction method based on an ultrasonic frequency response calculation of a piezoelectric ultrasonic sensor, and the method is used for predicting the health life of a battery by converting the signal of the swelling and deformation of a battery cell in the SOC change process into an ultrasonic frequency signal through piezoelectric induction of the piezoelectric ultrasonic sensor, establishing the correlation between the ultrasonic frequency signal and the charging and discharging cycle process of the battery cell, and predicting the health life of the battery. The physical state variable is converted into the ultrasonic frequency signal variable, so that the health state of the battery cell is predicted, the non-internal contact type life health prediction is realized, and a powerful method is provided for predicting the health attenuation state of the battery cell in the whole life cycle.

Description

Technical Field

[0001] This invention relates to the field of control algorithm technology for new energy battery management. Specifically, it is a method for predicting the healthy lifespan of a battery as its state of charge (SOC) changes, based on the ultrasonic frequency response calculation using a piezoelectric ultrasonic sensor. Background Technology

[0002] Current cell lifespan prediction based on SOC cycles is inaccurate and not real-time, representing a blind spot in measuring the entire lifespan of cells. Because a cell is a complete electrochemical variable, its complex and variable internal kinetic equations make it impossible to accurately predict its true lifespan during dynamic changes throughout its entire lifespan, thus affecting the full-cycle health management of cells.

[0003] Current methods for predicting battery cell lifespan are limited and cannot accurately analyze test data throughout the entire process. They also cannot accurately reflect the uncertainties brought about by the cell expansion pressure constraint mechanism. Summary of the Invention

[0004] Therefore, the technical problem to be solved by the present invention is to provide a method for predicting the healthy lifespan of a battery as its state of charge (SOC) changes by calculating the ultrasonic frequency response based on a piezoelectric ultrasonic sensor.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: A method for predicting the healthy lifespan of a battery as its state of charge (SOC) changes is based on ultrasonic frequency response calculation using a piezoelectric ultrasonic sensor. The signal of the cell's expansion and deformation during SOC changes is converted into an ultrasonic frequency signal through piezoelectric induction by the piezoelectric ultrasonic sensor. The correlation between the ultrasonic frequency signal and the charge-discharge cycle process of the battery cell is established, thereby predicting the battery's healthy lifespan.

[0006] The above-mentioned method for predicting the healthy lifespan of a battery as a function of SOC based on the ultrasonic frequency response calculation using a piezoelectric ultrasonic sensor specifically includes the following steps: (1) Constructing an experimental testing model; (2) Connect the experimental testing system; (3) Conduct experimental tests; (4) Find the correlation between ultrasonic frequency signal and SOC change to predict battery life.

[0007] In the above-mentioned method for predicting the healthy lifespan of a battery based on the ultrasonic frequency response calculation of a piezoelectric ultrasonic sensor, in step (1), a clamp is used to fix the ultrasonic transmitter and receiver of the piezoelectric ultrasonic sensor to both ends of the battery cell.

[0008] The above-mentioned method for predicting the healthy lifespan of a battery based on the ultrasonic frequency response calculation of a piezoelectric ultrasonic sensor and the change of SOC includes, in step (2), an experimental testing system comprising an ultrasonic display system, an NI data acquisition card, a power amplifier, and a battery charging and discharging system. The signal input / output terminals of the ultrasonic display system are connected to the signal input / output terminals of the NI data acquisition card. The signal output terminal of the NI data acquisition card is connected to the signal input terminal of the power amplifier. The output terminal of the power amplifier is connected to the ultrasonic transmitter of the piezoelectric ultrasonic sensor. The ultrasonic receiver of the piezoelectric ultrasonic sensor is connected to the signal receiver of the NI data acquisition card. At the same time, the battery charging and discharging system is electrically connected to the battery cell to manage and control the charging and discharging of the battery cell.

[0009] The above-mentioned method for predicting the healthy lifespan of a battery based on the ultrasonic frequency response calculation using a piezoelectric ultrasonic sensor, in step (3), The battery charging and discharging system controls the battery cells to perform cyclic charging and discharging; simultaneously, ultrasonic parameters are set in the ultrasonic display system, and then the signal is transmitted to the NI data acquisition card. The NI data acquisition card transmits the ultrasonic frequency signal through a power amplifier to the ultrasonic transmitter of the piezoelectric ultrasonic sensor. The ultrasonic receiver of the piezoelectric ultrasonic sensor transmits the received ultrasonic frequency signal to the NI data acquisition card, and the NI data acquisition card displays the obtained ultrasonic frequency signal data in the ultrasonic display system.

[0010] The above-mentioned method for predicting the healthy lifespan of a battery based on the ultrasonic frequency response calculation of a piezoelectric ultrasonic sensor, in step (4), finds the correlation between the ultrasonic frequency signal representing the change in cell expansion force obtained by the NI data acquisition card and the cycle period of the cell in the charge-discharge cycle obtained by the battery charging and discharging system, thereby predicting the battery lifespan degradation characteristics.

[0011] The above-mentioned method for predicting the healthy life of a battery based on the ultrasonic frequency response calculation of a piezoelectric ultrasonic sensor and the change of SOC is shown in Method 1: The ultrasonic display system obtains the ultrasonic frequency response signal of the battery in different charge-discharge cycles and obtains the modal component diagram of different battery charge-discharge cycles; then, the flight time variation diagram is obtained by using the flight time as the vertical axis and the battery charge-discharge cycle as the vertical axis. In the flight time variation graph, the flight time increases significantly with the increase of battery charge and discharge cycles, indicating battery aging and degradation; the cell life degradation can be obtained by the flight time variation.

[0012] The above-mentioned method for predicting the healthy lifespan of a battery based on the ultrasonic frequency response calculation using a piezoelectric ultrasonic sensor, along with method two, involves: An ultrasonic display system obtains the ultrasonic frequency response signal of the battery in different charge-discharge cycles, thus generating an ultrasonic frequency signal amplitude map of the cell in different charge-discharge cycles; subsequently, peak value maps of the ultrasonic frequency signal amplitude are obtained for SOC=0% and SOC=100% respectively. The peak value maps of the ultrasonic frequency signal amplitude are then normalized to obtain a normalized difference map of the ultrasonic frequency signal amplitude; simultaneously, the average ultrasonic frequency signal amplitude of SOC is calculated using the peak values ​​of the ultrasonic frequency signal amplitude at SOC=0% and SOC=100%. A mean SOC graph is plotted with the average ultrasonic frequency signal amplitude of SOC as the ordinate and the charge-discharge cycle period as the abscissa. The slope of the mean SOC graph is obtained by comparing the past maximum value with the current value. A change slope curve is then added to the mean SOC graph, with the slope as the ordinate and the charge-discharge cycle period as the abscissa, resulting in a mean SOC-change slope curve. In the normalized graph of ultrasonic signal amplitude difference, an increase in the normalization rate indicates battery aging and degradation; that is, the cell life degradation can be obtained through the normalization rate of ultrasonic signal amplitude difference. In the SOC mean-change slope curve, a significant increase in slope indicates battery aging and degradation. In other words, the cell life degradation can be determined by the slope of the change in ultrasonic signal amplitude.

[0013] The above-mentioned method for predicting the healthy lifespan of a battery based on the ultrasonic frequency response calculation using a piezoelectric ultrasonic sensor and the change in SOC is shown in Method 3: Obtain the center frequency, center frequency amplitude, and total signal energy from the ultrasonic frequency response signal of the battery in different charge-discharge cycles from the ultrasonic display system; plot the center frequency characteristic map, center frequency amplitude characteristic map, and total signal energy characteristic map with the center frequency, the logarithm of the center frequency amplitude, and the total energy as the ordinate and the charge-discharge cycle as the ordinate, respectively. In the center frequency characteristic graph, a decrease in center frequency indicates battery aging and degradation. In the center frequency amplitude characteristic graph, a continuous and rapid decrease in the center frequency amplitude indicates battery aging and degradation. In the total signal energy characteristic diagram, the total signal energy gradually decreases and the surface cell ages and decays. The cell lifespan degradation is determined by analyzing the center frequency characteristic map, center frequency amplitude characteristic map, and total signal energy characteristic map.

[0014] The technical solution of the present invention achieves the following beneficial technical effects: 1. This application can effectively measure non-internal contact life health prediction, providing a powerful method for predicting the health degradation safety status of battery cells throughout their entire life cycle.

[0015] 2. Accurately predict the health status of battery cells by converting physical state variables into ultrasonic frequency signal variables.

[0016] 3. This application obtains the law of ultrasonic frequency signal and battery cell attenuation change through ultrasonic frequency signal analysis, thereby predicting battery life. Attached Figure Description

[0017] Figure 1 A schematic diagram showing the fixed positions of the ultrasonic transmitter and receiver of the piezoelectric ultrasonic sensor of the present invention. Figure 2 Schematic diagram of a piezoelectric ultrasonic sensor fixed with a clamp; Figure 3 Schematic diagram of the experimental test model; Figure 4a The modal component diagram of cell No. 1 at a cycle period of 40 cycles; Figure 4b The modal component diagram of cell No. 1 at a cycle period of 200 cycles; Figure 5a The modal component diagram of cell No. 2 at a cycle period of 40 cycles; Figure 5b The modal component diagram of cell No. 2 at a cycle period of 200 cycles; Figure 6 The graph shows the flight time variation of battery cells No. 1 and No. 2. Figure 7a The modal component diagram of cell No. 3 at a cycle period of 160 cycles; Figure 7b The flight time variation graphs for cells No. 3 and No. 4; Figure 8a The modal component diagrams for cell No. 6 are shown for cycle periods of 40, 80, and 160 cycles, respectively. Figure 8b The flight time variation graphs for cells 5 and 6 are shown. Figure 9 This is a schematic diagram illustrating the process of obtaining the peak amplitude diagram of the ultrasonic frequency signal at SOC=0% from the ultrasonic frequency signal amplitude diagrams of cell No. 1 at different charge and discharge cycles. Figure 10 This is a schematic diagram illustrating the process of obtaining the peak amplitude diagram of the ultrasonic frequency signal at SOC=0% from the ultrasonic frequency signal amplitude diagrams of cell No. 2 at different charge and discharge cycles. Figure 11 The ultrasonic frequency signal amplitude diagrams for cells 1 and 2 under different charge-discharge cycles are shown. Figure 12a The peak amplitude diagram of ultrasonic frequency signal for cells 1 and 2 under different charge and discharge cycles at SOC=0% is shown. Figure 12bNormalized graph of the difference in ultrasonic frequency signal amplitude between cell 1 and cell 2; Figure 13a This is a schematic diagram showing the process of cell No. 1 from the peak amplitude graph of the ultrasonic frequency signal to the mean SOC-slope curve. Figure 13b This is a schematic diagram showing the process of cell No. 2 from the peak amplitude graph of the ultrasonic frequency signal to the mean SOC-slope curve. Figure 14 This is a schematic diagram illustrating the process of obtaining the peak amplitude diagram of the ultrasonic frequency signal at SOC=0% from the ultrasonic frequency signal amplitude diagrams of cell No. 3 at different charge and discharge cycles. Figure 15 This is a schematic diagram illustrating the process of obtaining the peak amplitude diagram of the ultrasonic frequency signal at SOC=0% from the ultrasonic frequency signal amplitude diagrams of cell No. 4 at different charge and discharge cycles. Figure 16 The ultrasonic frequency signal amplitude diagrams for cells No. 3 and No. 4 under different charge and discharge cycles; Figure 17a The peak amplitude diagram of ultrasonic frequency signal for cells 3 and 4 under different charge and discharge cycles at SOC=0% is shown. Figure 17b Normalized graph of the difference in ultrasonic frequency signal amplitude between cells 3 and 4; Figure 18a This is a schematic diagram showing the process of cell No. 3 from the peak amplitude graph of the ultrasonic frequency signal to the mean SOC-slope curve. Figure 18b This is a schematic diagram showing the process of cell No. 4 from the peak amplitude graph of the ultrasonic frequency signal to the mean SOC-slope curve. Figure 19 This is a schematic diagram illustrating the process of obtaining the peak amplitude diagram of the ultrasonic frequency signal at SOC=0% from the ultrasonic frequency signal amplitude diagrams of cell No. 5 at different charge and discharge cycles. Figure 20 This is a schematic diagram illustrating the process of obtaining the peak amplitude of the ultrasonic frequency signal at SOC=0% from the ultrasonic frequency signal amplitude diagrams of cell No. 6 at different charge and discharge cycles. Figure 21 The ultrasonic frequency signal amplitude diagrams for cells No. 5 and No. 6 under different charge and discharge cycles; Figure 22a The peak amplitude diagram of ultrasonic frequency signal for cells 5 and 6 under different charge-discharge cycles at SOC=0% is shown. Figure 22b Normalized graph of the difference in ultrasonic frequency signal amplitude between cells 5 and 6; Figure 23a This is a schematic diagram showing the process of cell No. 5 changing from the peak amplitude graph of the ultrasonic frequency signal to the mean SOC and the slope of the change. Figure 23bThis is a schematic diagram showing the process of cell No. 6 from the peak amplitude graph of the ultrasonic frequency signal to the mean SOC-slope curve. Figure 24a The center frequency characteristic diagrams for cells 1 and 2 are shown. Figure 24b The center frequency characteristic diagrams for cells No. 3 and No. 4; Figure 24c The center frequency characteristic diagrams for cells No. 5 and No. 6; Figure 25a The center frequency amplitude characteristic diagrams for cells 1 and 2 are shown. Figure 25b The center frequency amplitude characteristic diagrams for cells No. 3 and No. 4; Figure 25c The center frequency amplitude characteristic diagrams for cells No. 5 and No. 6; Figure 26a The signal total energy characteristic diagrams for cells 1 and 2 are shown. Figure 26b The signal total energy characteristic diagrams for cells No. 3 and No. 4 are shown. Figure 26c The signal total energy characteristic diagrams for cells 5 and 6 are shown.

[0018] The reference numerals in the figure are: 1-ultrasonic transmitter; 2-ultrasonic receiver; 3-ultrasonic display system; 4-NI data acquisition card; 5-power amplifier; 6-battery charging and discharging system. Detailed Implementation

[0019] I. Principles of this application The signal of cell expansion and deformation during SOC charging and discharging is converted into an ultrasonic frequency signal by piezoelectric induction by piezoelectric ultrasonic sensors placed at both ends of the cell. The correlation between the ultrasonic frequency signal and the battery cell charging and discharging cycle process is established, thereby predicting the battery's healthy lifespan.

[0020] In this embodiment, taking six square-shell battery cells as an example, the predictive response process of the battery cells is reflected by building an experimental test bench.

[0021] II. Building an Experimental Testing Model like Figure 1 and Figure 2 As shown, a clamp is used to fix the ultrasonic transmitter 1 and ultrasonic receiver 2 of the piezoelectric ultrasonic sensor to both ends of the battery cell.

[0022] III. Connection Experiment Test Model The experimental testing equipment includes: an ultrasonic display system 3, an NI data acquisition card 4, a power amplifier 5, and a battery charging and discharging system 6.

[0023] Specific connection methods are as follows: Figure 3As shown: the signal input / output terminals of the ultrasonic display system 3 are connected to the signal input / output terminals of the NI data acquisition card 4; the signal output terminal of the NI data acquisition card 4 is connected to the signal input terminal of the power amplifier 5; the output terminal of the power amplifier 5 is connected to the ultrasonic transmitter 1 of the piezoelectric ultrasonic sensor; and the ultrasonic receiver 2 of the piezoelectric ultrasonic sensor is connected to the signal receiver 4 of the NI data acquisition card 4. At the same time, the battery charging / discharging system 6 is electrically connected to the battery cell to manage and control the charging and discharging of the battery cell.

[0024] IV. Conduct experimental tests The test signal was obtained using the following method: The battery charging and discharging system 6 controls the battery cells to perform cyclic charging and discharging; at the same time, the ultrasonic parameters are set in the ultrasonic display system 3, and then the signal is transmitted to the NI data acquisition card 4. The NI data acquisition card 4 transmits the ultrasonic frequency signal to the ultrasonic transmitter 1 of the piezoelectric ultrasonic sensor through the power amplifier 5. The ultrasonic receiver 2 of the piezoelectric ultrasonic sensor transmits the received ultrasonic frequency signal to the NI data acquisition card 4. The NI data acquisition card 4 displays the obtained ultrasonic frequency signal data in the ultrasonic display system 3.

[0025] Simultaneously, tests were conducted to obtain ultrasonic frequency signals and corresponding flight times under different charge-discharge cycles.

[0026] V. Establishing an analysis of the correlation between ultrasonic frequency signals and SOC changes 5.1. Determining cell lifespan degradation through changes in flight time. The No. 1 and No. 2 cells were compared together, the No. 3 and No. 4 cells were compared together, and the No. 5 and No. 6 cells were compared together.

[0027] The ultrasonic display system 3 obtains the ultrasonic frequency response signals of the battery in different charge-discharge cycles, and obtains the modal component diagrams of different battery charge-discharge cycles; such as Figure 4a and Figure 4b Modal component diagrams of cell No. 1 at 40 and 200 charge / discharge cycles respectively; as shown. Figure 5a and Figure 5b Modal component diagrams of cell No. 2 at charge / discharge cycles of 40 and 200 cycles respectively.

[0028] like Figure 6 By plotting flight time on the ordinate and battery charge / discharge cycle on the ordinate, a flight time variation graph is obtained. Figure 6 Compare cell No. 1 and cell No. 2 using the same coordinate system.

[0029] Depend on Figure 4a and Figure 4bIt can be seen that the modal components of cell No. 1 are basically the same under both low-cycle and high-cycle conditions; while from Figure 5a and Figure 5b The data shows that cell #2 exhibits a superposition of multiple modes during high-cycle operation. From... Figure 6 It can be seen that as the number of cycles increases, the flight time of cell 1 remains basically the same, while the flight time of cell 2 starts to increase from 60 cycles, indicating battery degradation. Cell 2 ages faster than cell 1.

[0030] Therefore, the cell lifespan degradation can be determined by the change in flight time.

[0031] Comparative analysis of battery cells No. 3 and No. 4: Figure 7a During high-cycle (160 cycles) charge / discharge, the second wave packet of the No. 3 cell significantly increased, exceeding the first main wave packet; while... Figure 7b In the flight time variation graph, the flight time of cell 4 is basically stable, while the flight time of cell 3 increases at 120 cycles. The aging rate of cell 3 is greater than that of cell 4.

[0032] Comparative analysis of No. 5 and No. 6 battery cells: Figure 8a The image shows the modal component diagrams of cell No. 6 at different cycle periods. With increasing cycle periods, multiple modes superimpose at high cycles (160 cycles), and the second wave packet exceeds the first main wave packet during high-cycle charging and discharging. Figure 8b The flight time variation graphs for cells 5 and 6 show that the flight time of cell 5 remains relatively stable with increasing cycle number, while the flight time of cell 6 increases significantly at higher cycle times. Cell 6 ages faster than cell 5.

[0033] Summary: 1) The modal component changes of cells 1, 3, 4 and 5 are stable; cells 2 and 6 exhibit multimodal component superposition at high cycles; and cells 3 and 6 show a second wave packet larger than the main wave packet at high cycles.

[0034] 2) The cell life decay is obtained by converting the modal components into flight time variations.

[0035] 5.2 Cell life degradation determined by the peak value of the main wave packet of the ultrasonic frequency The ultrasonic display system 3 acquires the ultrasonic frequency response signals of the battery during different charge-discharge cycles, thereby obtaining ultrasonic frequency signal amplitude maps of the battery during different charge-discharge cycles. Furthermore, it obtains peak amplitude maps of the ultrasonic frequency signals at SOC=0% and SOC=100%, respectively, and performs difference normalization processing on the peak amplitude maps to obtain ultrasonic frequency signal amplitude difference normalized maps. Simultaneously, it calculates the average ultrasonic frequency signal amplitude of SOC using the peak amplitudes at SOC=0% and SOC=100%, and plots the SOC mean value with the average ultrasonic frequency signal amplitude of SOC as the ordinate and the charge-discharge cycle as the abscissa. It also obtains the slope by comparing the past maximum value with the current value on the SOC mean value curve, and adds a slope change curve to the SOC mean value curve with the slope as the ordinate and the charge-discharge cycle as the abscissa, thus obtaining the SOC mean value-slope change curve. like Figure 9 and Figure 10 The ultrasonic frequency signal amplitude diagrams for cells 1 and 2 at different charge and discharge cycles are used to obtain the peak amplitude diagram of the ultrasonic frequency signal at SOC=0%.

[0036] Figure 11 The image shows the amplitude of the ultrasonic frequency signal for cells 1 and 2 under different charge / discharge cycles at SOC=0%.

[0037] Figure 12a The peak amplitude graphs of ultrasonic frequency signals for cells 1 and 2 at SOC=0% under different charge-discharge cycles are shown. Then, difference normalization (i.e., the difference between the highest and lowest peak values ​​of the ultrasonic frequency signal amplitude) is performed to obtain... Figure 12b Normalized graph of the amplitude difference of ultrasonic frequency signals.

[0038] Figure 13a The image above and Figure 13b The above figures show the peak amplitude of the ultrasonic frequency signal at SOC=0% and the peak amplitude of the ultrasonic frequency signal at SOC=100% for cells 1 and 2, respectively. Figure 13a The image below and Figure 13b The blue curve in the figure below represents the average ultrasonic frequency signal of the SOC versus the number of cycles. Figure 13a The image below and Figure 13b The red curve in the image below represents the slope curve. This slope is calculated by comparing the current value with the historical maximum value obtained from the SOC mean curve, as shown in the following formula: exist Figure 13a The image below and Figure 13b The following figure shows the SOC mean-change slope curve.

[0039] from Figure 12bIt can be seen that the normalization rate of the difference in cell 1 is still in the narrowing range, while the normalization rate of the difference in cell 2 is the first to show a rebound range. Figure 12b (the area circled in black), and Figure 11 The peak battery performance continues to decrease.

[0040] from Figure 13a The image below and Figure 13b As shown in the figure below, the peak values ​​of cells 1 and 2 gradually decrease and the slope increases after entering high-cycle testing. However, the peak value of cell 2 decreases faster and the slope changes more significantly. With both short-cycle and long-cycle testing, the slope of cell 2 changes more dramatically, resulting in a significantly greater lifespan degradation than cell 1.

[0041] All of the above indicate that the aging rate of cell #2 is greater than that of cell #1.

[0042] The analysis methods for cells No. 3 and No. 4, as well as cells No. 5 and No. 6, are the same as those for cells No. 1 and No. 2.

[0043] Cells 3 and 4: See Figure 14-Figure 1 8; From Figure 14 It can be seen that cell No. 3 exhibits a distinct second wave of signal, with mode superposition and dispersion phenomena; from Figure 15 It can be seen that cell No. 4 exhibits a distinct second wave of packets, but the two modes are clearly separated.

[0044] from Figure 16 It can be seen that the peak value of cell No. 3 continues to decline, from Figure 17b The difference normalization rate first showed a rebound range, while the difference normalization rate of cell 4 continued to narrow, and cell 3 accelerated aging after 150 cycles. The aging rate of cell 3 was greater than that of cell 4. Therefore... Figure 18a and Figure 18b As shown in the figure below, the peak value of cell 3 drops rapidly while the slope increases significantly, while the changes in peak value and slope of cell 4 are not as large as those of cell 3.

[0045] With both short-cycle and long-cycle testing, the slope of cell No. 3 changed significantly (under long-cycle cycles), and its lifespan degradation was significantly greater than that of cell No. 4.

[0046] Battery cells #5 and #6: See Figures 19-23b .from Figure 19 It can be seen that cell No. 5 has modal components, exhibiting slight modal superposition and dispersion; from Figure 20 It can be seen that cell No. 6 exhibits obvious mode superposition, with the second wave being prominent and gradually becoming the main component at higher cycles.

[0047] from Figure 21It can be seen that the peak values ​​of both No. 5 and No. 6 cells show a simultaneous decreasing trend. Figure 22b The normalization rate of the differential value in the No. 5 battery cell continued to decrease, while the No. 6 battery cell showed multiple rebound intervals, indicating that the aging rate of the No. 6 battery cell was greater than that of the No. 5 battery cell.

[0048] thereby Figure 23a and Figure 23b As shown in the figure below, cell No. 6 has a larger slope change, while cell No. 5 has a more stable slope change.

[0049] With both short-cycle and long-cycle testing, the slope of cell #6 changed significantly (under long-cycle cycles), and its lifespan degradation was significantly greater than that of cell #5.

[0050] Analysis of the data from the above six cells shows that the lifespan degradation of different cells can be determined by the slope of the amplitude change from SOC=0% to SOC=100% at the ultrasonic frequency.

[0051] 5.3. By analyzing the center frequency amplitude, center frequency characteristics, and total signal energy in the ultrasonic frequency, the overall cell lifespan is determined and the cell lifespan degradation is predicted.

[0052] The ultrasonic frequency response signal of the battery in different charge and discharge cycles is obtained from the ultrasonic display system (3) to obtain the center frequency, center frequency amplitude and total signal energy; the center frequency characteristic map, center frequency amplitude characteristic map and total signal energy characteristic map are respectively made with the center frequency, the logarithm of the center frequency amplitude and the total energy as the vertical axis and the charge and discharge cycle as the vertical axis.

[0053] exist Figures 24a-24c middle: Figure 24a The center frequency of the No. 2 battery cell shows a trend of decreasing gradually. Figure 24b and Figure 24c In the middle, the center frequency of cells No. 3 and No. 6 decreased significantly.

[0054] exist Figures 25a-25c middle: Figure 25b and Figure 25c The center frequency amplitude of cells No. 3 and No. 6 in the battery pack continued to decline rapidly.

[0055] exist Figures 26a-26c middle: Figure 26b and Figure 26c The signal energy of cells 3 and 6 decreases progressively, and the signal energy of cell 5 is also relatively low.

[0056] The lifespan of cells #2, #3, and #6 has significantly decreased.

[0057] Based on the content of 5.1, 5.2 and 5.3, the ultrasonic frequency signal obtained by the piezoelectric ultrasonic sensor can predict the life decay characteristics of different cells during the charge and discharge cycle. Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of the claims of this patent application.

Claims

1. A method for predicting the healthy lifespan of a battery as a function of state of charge (SOC) based on ultrasonic frequency response calculation using a piezoelectric ultrasonic sensor, characterized in that... The signal of the cell expanding and deforming during the SOC change process is converted into an ultrasonic frequency signal through the piezoelectric induction of the piezoelectric ultrasonic sensor. The correlation between the ultrasonic frequency signal and the charge and discharge cycle process of the battery cell is established, thereby predicting the battery's healthy lifespan.

2. The method for predicting the healthy lifespan of a battery based on the ultrasonic frequency response calculation using a piezoelectric ultrasonic sensor according to claim 1, characterized in that, Specifically, the steps include the following: (1) Establish experimental testing models; (2) Connect the experimental testing system; (3) Conduct experimental tests; (4) Find the correlation between ultrasonic frequency signal and SOC change to predict battery life.

3. The method for predicting the healthy lifespan of a battery as a function of SOC by calculating the ultrasonic frequency response based on a piezoelectric ultrasonic sensor according to claim 1, characterized in that, In step (1), a clamp is used to fix the ultrasonic transmitter (1) and ultrasonic receiver (2) of the piezoelectric ultrasonic sensor to both ends of the battery cell.

4. The method for predicting the healthy lifespan of a battery based on the ultrasonic frequency response calculation using a piezoelectric ultrasonic sensor according to claim 1, characterized in that, In step (2), the experimental testing system includes an ultrasonic display system (3), an NI data acquisition card (4), a power amplifier (5), and a battery charging and discharging system (6); The signal input / output terminals of the ultrasonic display system (3) are connected to the signal input / output terminals of the NI data acquisition card (4). The signal output terminal of the NI data acquisition card (4) is connected to the signal input terminal of the power amplifier (5). The output terminal of the power amplifier (5) is connected to the ultrasonic transmitter (1) of the piezoelectric ultrasonic sensor. The ultrasonic receiver (2) of the piezoelectric ultrasonic sensor is connected to the signal receiver of the NI data acquisition card (4). At the same time, the battery charging and discharging system (6) is electrically connected to the battery cell to manage and control the charging and discharging of the battery cell.

5. The method for predicting the healthy lifespan of a battery as a function of SOC by calculating the ultrasonic frequency response based on a piezoelectric ultrasonic sensor according to claim 1, characterized in that, In step (3), The battery charging and discharging system (6) controls the battery cells to perform cyclic charging and discharging; at the same time, the ultrasonic parameters are set in the ultrasonic display system (3), and then the signal is transmitted to the NI data acquisition card (4). The NI data acquisition card (4) transmits the ultrasonic frequency signal to the ultrasonic transmitter (1) of the piezoelectric ultrasonic sensor through the power amplifier (5). The ultrasonic receiver (2) of the piezoelectric ultrasonic sensor transmits the received ultrasonic frequency signal to the NI data acquisition card (4). The NI data acquisition card (4) displays the obtained ultrasonic frequency signal data in the ultrasonic display system (3).

6. The method for predicting the healthy lifespan of a battery as a function of SOC by calculating the ultrasonic frequency response based on a piezoelectric ultrasonic sensor according to claim 1, characterized in that, In step (4), the correlation between the ultrasonic frequency signal representing the change of cell expansion force obtained by the NI data acquisition card (4) and the cycle period of the cell in the charge and discharge cycle obtained by the battery charging and discharging system (6) is found, thereby predicting the battery life decay characteristics.

7. The method for predicting the healthy lifespan of a battery as a function of SOC by calculating the ultrasonic frequency response based on a piezoelectric ultrasonic sensor according to claim 6, characterized in that, Prediction Method 1: The ultrasonic display system (3) obtains the ultrasonic frequency response signal of the battery in different charge and discharge cycles, and obtains the modal component diagram of different battery charge and discharge cycles; then, with the flight time as the vertical axis and the battery charge and discharge cycle as the vertical axis, it transforms to obtain the flight time variation diagram; In the flight time variation graph, the flight time increases significantly with the increase of battery charge and discharge cycles, indicating battery aging and degradation; the cell life degradation can be obtained by the flight time variation.

8. The method for predicting the healthy lifespan of a battery as a function of SOC by calculating the ultrasonic frequency response based on a piezoelectric ultrasonic sensor according to claim 6, characterized in that, Prediction Method 2: Ultrasonic display system (3) obtains the ultrasonic frequency response signal of the battery in different charge and discharge cycles, thereby obtaining the ultrasonic frequency signal amplitude map of the cell in different charge and discharge cycles; then obtains the peak value map of the ultrasonic frequency signal amplitude under the conditions of SOC=0% and SOC=100%, respectively, performs difference normalization processing on the peak value map of the ultrasonic frequency signal amplitude, and obtains the ultrasonic frequency signal amplitude difference normalization map; at the same time, it also calculates the average value of the ultrasonic frequency signal of SOC by the peak value of the ultrasonic frequency signal amplitude of SOC=0% and the peak value of the ultrasonic frequency signal amplitude of SOC=100%, and makes the SOC average value map with the average value of the ultrasonic frequency signal of SOC as the vertical axis and the charge and discharge cycle as the horizontal axis, and obtains the slope by comparing the past maximum value with the current value with the SOC average value curve, and adds the change slope curve obtained by the slope as the vertical axis and the curve charge and discharge cycle as the horizontal axis to the SOC average value map, thereby obtaining the SOC average value-change slope curve map; In the normalized graph of ultrasonic signal amplitude difference, an increase in the normalization rate indicates battery aging and degradation; that is, the cell life degradation can be obtained through the normalization rate of ultrasonic signal amplitude difference. In the SOC mean-change slope curve, a significant increase in slope indicates battery aging and degradation. In other words, the cell life degradation can be determined by the slope of the change in ultrasonic signal amplitude.

9. The method for predicting the healthy lifespan of a battery as a function of SOC by calculating the ultrasonic frequency response based on a piezoelectric ultrasonic sensor according to claim 6, characterized in that, Method 3: Obtain the center frequency, center frequency amplitude and total signal energy from the ultrasonic frequency response signal of the battery in different charge and discharge cycles from the ultrasonic display system (3); with the center frequency, the logarithm of the center frequency amplitude and the total energy as the vertical axis and the charge and discharge cycle as the vertical axis, respectively make the center frequency feature map, the center frequency amplitude feature map and the total signal energy feature map; In the center frequency characteristic graph, a decrease in center frequency indicates battery aging and degradation. In the center frequency amplitude characteristic graph, a continuous and rapid decrease in the center frequency amplitude indicates battery aging and degradation. In the total signal energy characteristic diagram, the total signal energy gradually decreases and the surface cell ages and decays. The cell lifespan degradation is determined by analyzing the center frequency characteristic map, center frequency amplitude characteristic map, and total signal energy characteristic map.

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