A method and system for rapid analysis and prediction of battery failure and short circuits

Abstract

A method for quickly analyzing and predicting battery failure and short circuit, mainly using a battery state sensing unit to continuously obtain a state signal value of a battery cell, presenting the state signal value with time and state signal value as a time domain result, converting the time domain result into a frequency domain result, and judging that the battery cell has a micro short circuit and issuing a warning when the intensity value in the frequency domain result exceeds a preset threshold value when the battery cell is in a normal operating state; the present application accurately analyzes battery data through mathematical analysis method, effectively distinguishes all stages of the battery, accurately knows when early micro short circuit occurs, helps to predict battery failure and short circuit, and effectively reduces disasters.

Description

Technical Field

[0001] This invention relates to a method for predicting battery failure, specifically a method for accurately predicting the possibility of battery failure while the battery is still in normal operation. Background Technology

[0002] With technological advancements, electric vehicles are likely to gradually replace gasoline-powered vehicles as the new mode of transportation. Battery development has become a crucial technology for the electric vehicle industry. Improving and enhancing the current issues of short driving range, short cycle life, and safety in electric vehicle batteries is a key trend in the industry's technological development.

[0003] Electric vehicles are generally composed of multiple battery cells connected in series. Currently, most systems used to monitor batteries employ Battery Management System (BMS), which is a system that estimates the battery's condition by monitoring abnormal changes in parameters such as temperature, voltage, and current through sensors.

[0004] A battery failure begins with an extremely small micro-short circuit that occurs during normal operation. Early micro-short circuits cannot be detected and measured accurately by the BMS. The BMS will only be notified and issue a short circuit warning when the changes in values ​​that can be recognized by the sensors (such as the polarization stage). However, by this time, the battery may already be in a state of imminent short circuit. If the user cannot perform battery repair or replacement in time, the rapid and complete failure of the battery may cause the battery-powered device to stop or shut down, or there is a risk of battery explosion. Summary of the Invention

[0005] To address the problem that existing BMS systems cannot effectively detect battery short circuits in advance, and can only measure them after a micro-short circuit has already occurred, this invention provides a method for rapidly analyzing and predicting battery failure and short circuits, the steps of which include:

[0006] This invention uses mathematical analysis methods to accurately analyze battery data, effectively distinguish all battery life stages, accurately determine when early micro-short circuits occur, help predict battery failure and short circuits, and effectively reduce the occurrence of disasters.

[0007] Firstly, the first inventive concept of this invention provides a method for rapidly analyzing and predicting battery failure and short circuits, the steps of which include:

[0008] A battery status sensing unit is used to continuously acquire a status signal value of a battery cell;

[0009] The state signal value obtained from the battery state sensing unit is first determined to be of the type of state signal value, and a time domain result is presented in terms of time and state signal value to determine whether the state signal value is higher than a preset first time domain threshold.

[0010] The time-domain result that is not higher than the first time-domain threshold is converted from the time domain to the frequency domain to obtain a frequency-domain result; and

[0011] When the value of the frequency domain result exceeds a second frequency domain threshold, the battery cell is assessed to have a micro short circuit and the battery cell issues a warning.

[0012] The time-domain result is converted to the frequency-domain result by performing the following formula (1);

[0013] in:

[0014] N is the number of samples; n is the current sample; k is the current frequency, and k∈[0,N-1]; x(n) is the sine value of n; X(n) is the frequency domain result of the frequency domain relationship between the fast Fourier transform and the intensity.

[0015] The status signal value includes the voltage, current, impedance, or temperature of the battery cell.

[0016] The battery cell includes a normal operating state, a polarized state, and an internal short-circuit state.

[0017] The micro-short circuit occurred during the normal operation of the battery cell.

[0018] The frequency intensity of this frequency domain result gradually shifts from low frequency to high frequency as the battery cell transitions from its normal operating state to its polarized state and then to its internal short-circuit state.

[0019] The frequency domain result is filtered using a filter.

[0020] The frequency domain results were further verified using the Welch method.

[0021] Furthermore, the present invention provides a system for rapidly analyzing and predicting battery failure and short circuits, comprising: a battery terminal, a cloud terminal, and a receiving terminal that are interconnected by signals, wherein:

[0022] The battery terminal includes a battery cell, which is connected to a battery status sensing unit and continuously senses the status signal value of the battery cell during charge and discharge cycles. The status signal value is then transmitted outward through a transmission unit also located in the battery terminal.

[0023] The cloud includes a storage unit, a computing unit, and a database. The storage unit receives and stores the status signal values ​​transmitted through the transmission unit and then transmits them to the computing unit for calculation using the aforementioned method of rapid analysis and prediction of battery failure and short circuit. The calculation results are compared with the standard values ​​stored in the database to obtain the analysis and prediction results. The receiving terminal is any electronic device capable of receiving electrical signals.

[0024] As can be seen from the above description, this invention uses mathematical analysis methods to accurately analyze battery data, effectively distinguish all battery life stages, accurately determine when early micro-short circuits occur, help predict battery failure and short circuits, and effectively reduce the occurrence of disasters. Attached Figure Description

[0025] The present invention will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, the same reference numerals denote the same structures, wherein:

[0026] Figure 1 This is a schematic diagram of a first preferred embodiment of a system for rapidly analyzing and predicting battery failure and short circuits according to the present invention.

[0027] Figure 2 This is a flowchart illustrating the system and method steps for rapidly analyzing and predicting battery failures and short circuits according to the present invention.

[0028] Figure 3 This is a time-domain diagram showing the time-voltage relationship of the battery cell in normal operation, polarization, and internal short-circuit states according to the first preferred embodiment of the present invention.

[0029] Figure 4A , 4B This is a frequency domain diagram showing the relationship between the frequency and intensity of the battery cell in normal operation and in a micro-short circuit state, according to the first preferred embodiment of the present invention.

[0030] Figure 5 This is a frequency domain diagram showing the relationship between the frequency and intensity of an internal short circuit in the battery cell according to the first preferred embodiment of the present invention.

[0031] Figure 6 In response to the aforementioned Figure 4B Validation data plots from spectral analysis using the Welch method.

[0032] Figure 7 This is a schematic diagram of a second preferred embodiment of the system for rapidly analyzing and predicting battery failure and short circuits according to the present invention.

[0033] Symbol explanation:

[0034] 10 Battery end

[0035] 11 Battery cells

[0036] 111 Battery Status Sensing Unit

[0037] 12 Transmission Units

[0038] 20 Cloud

[0039] 21 storage units

[0040] 22 arithmetic units

[0041] 23 Databases

[0042] 30 Receiving Telecommunication Terminal

[0043] Zone 1

[0044] Zone 2

[0045] Zone 3

[0046] Steps S1-S6 Detailed Implementation

[0047] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of the present invention. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0048] It should be understood that the terms “system,” “apparatus,” “unit,” and / or “module” used herein are methods of distinguishing different components, parts, components, sections, or assemblies at different levels. However, if other words can achieve the same purpose, they may be replaced by other expressions. As indicated in the invention and claims, unless the context clearly indicates otherwise, words such as “a,” “an,” “an,” and / or “the” do not specifically refer to the singular and may also include the plural. Generally speaking, the terms “comprising” and “including” only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0049] This invention uses flowcharts to illustrate the operations performed by the system according to embodiments of the invention. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0050] This invention provides a system and method for rapidly analyzing and predicting battery failure and short circuits. Please refer to [link / reference]. Figure 1 The present invention first provides a preferred embodiment of a battery system comprising a battery terminal 10.

[0051] The battery terminal 10 includes a battery cell 11. A battery status sensing unit 111 is connected to the battery cell 11 and continuously senses its status signal value during charge-discharge cycles. This status signal value is then transmitted externally through a transmission unit 12 also located in the battery terminal 10, for example, via Bluetooth or wireless signal transmission. In the first preferred embodiment of the present invention, the battery cell 11 is a lithium-ion battery, and a preferred embodiment of the lithium-ion battery uses an LPSC solid electrolyte.

[0052] The status signal value in this invention includes, but is not limited to, electrical-related signal data of the battery cell 11, such as voltage, current, and impedance, or it may also be physiological data of the battery cell 11, such as temperature.

[0053] Next, please refer to the following: Figure 2 The present invention provides a method for rapidly analyzing and predicting battery failure and short circuits using the aforementioned battery system as an example. The steps include:

[0054] Step S1) The battery status sensing unit 111 continuously acquires the status signal value of the battery cell 11;

[0055] Step S2) Determine the signal type of the status signal value and present a time-domain result with time and status signal value. At the same time, determine whether the status signal value is higher than a preset first time-domain threshold. If it is not higher than the first time-domain threshold, proceed to the next step; if it is higher, stop.

[0056] In the aforementioned first time domain threshold, the so-called time domain refers to the change data of the sensed state signal value over time (or time domain). This step presets the first time domain threshold to determine whether the state signal value is higher than the first time domain threshold.

[0057] Step S3) The state signal value that is not higher than the first time domain threshold is converted from the time domain to the frequency domain to obtain a frequency domain result. The signal data conversion performed in this invention mainly uses Fourier Transform, or preferably Fast Fourier Transform (FFT), to convert the change data of the sensed state signal value over time into frequency data (or frequency domain) through specific mathematical operations. However, Fourier Transform or Fast Fourier Transform is a specific embodiment of this invention, and other possible calculation methods for converting the time domain to the frequency domain should also be covered within the scope claimed by this invention.

[0058] Step S4) (optionally), if the converted frequency domain signal contains too much noise, it may be filtered by a filter, such as an infinite impulse response (IIR) or finite impulse response (FIR) filter.

[0059] Step S5) When the converted frequency domain value exceeds a preset second frequency domain threshold, the battery cell 11 is evaluated to have a micro short circuit and the battery cell 11 issues an alarm.

[0060] Step S6) (Optionally), the determination of whether the frequency domain value obtained in step 5 of the present invention actually exceeds the domain value can be further verified by Welch method.

[0061] Specifically, step S3 mentioned above refers to the relationship between the time and state signal values ​​continuously measured during the charge-discharge cycle of the battery cell 11, as shown in the graph. Figure 3 This illustration shows how the voltage of the lithium battery changes over time in this embodiment. It can be basically divided into three regions: the normal working zone (Zone 1), the polarization zone (Zone 2), and the internal short-circuit zone (Zone 3). Figure 3 The embodiment shown uses a current density of 0.5 mA / cm². 2 The test was conducted with a cycle time of 5 hours. Preferably, the first time-domain threshold in step 2 of the present invention refers to the voltage value when the lithium battery voltage is in the normal operating zone of Zone 1, for example... Figure 3As shown in region 1, the first time-domain threshold in this embodiment can be set to whether the measured lithium battery voltage is higher than 0.014 volts (V). If it is not higher than this first time-domain threshold, it indicates that the lithium battery is in normal operating condition, and the present invention will perform frequency domain conversion on the state signal value in this region. However, this first time-domain threshold may be adjusted depending on the type of battery being monitored or the user's needs.

[0062] The present invention utilizes the signal taken by the battery cell 11 in the above system during the normal operation state of region 1, for example... Figure 3 The voltage generated at the location marked in box 1 within Zone 1, and its time domain variation with time, is converted to the frequency domain using the following Fast Fourier Transform formula (1). The time when a micro short-circuit occurs in the normal operating state of Zone 1 is found, thereby predicting the possibility of subsequent internal short circuits or even short circuits.

[0063]

[0064] The meanings of each symbol in formula (1) are shown in Table 1 below.

[0065] Table 1

[0066]

[0067]

[0068] Please refer to the corresponding information. Figures 4A-4B The result of converting the time domain to the frequency domain using the above formula is as follows: Figure 4A The middle is the corresponding Figure 3 The state of Zone 1 during the 9th charge-discharge cycle under normal operating conditions. Figure 4B This corresponds to the time-frequency domain state during the 10th charge-discharge cycle and the occurrence of a micro-short circuit. From Figure 4A During the 9th charge-discharge cycle under normal operating conditions, depending on the different types of battery cells 11 being tested, this invention will first set the second frequency domain threshold as the system judgment standard, such as... Figure 4A The preset intensity of 20 dB in this embodiment may be adjusted depending on the type of battery being monitored or the user's needs.

[0069] With continuous voltage monitoring and formula conversion to such Figure 4BThe time-domain to frequency-domain result obtained during the 10th charge-discharge cycle indicates that the intensity of this 10th charge-discharge cycle exceeds the threshold of 20 dB. This is the moment when the monitored battery cell 11 experiences a micro-short circuit in the normal operating state of Zone 1. Since the occurrence of a micro-short circuit in the normal operating state of the battery cell 11 indicates that an internal short circuit will inevitably occur subsequently, this invention can issue a warning notification when a micro-short circuit occurs in the normal operating state of the battery cell 11, thereby ensuring the safety of the user when using the battery.

[0070] Next, to confirm that the lithium battery did indeed subsequently experience an internal short circuit, this embodiment continuously monitored the voltage, such as... Figure 3 The battery cell 11 shown does indeed exhibit a polarization state in Zone 2 that exceeds the first time-domain threshold and an internal short-circuit state in Zone 3 during the 54th charge-discharge cycle.

[0071] Further, please refer to Figure 5 This is the time-domain to frequency-domain result of the internal short-circuit state corresponding to the 54th charge-discharge cycle (Zone 3) in the final region. As time progresses and the time-domain to frequency-domain conversion is performed, the internal short circuit, compared to the normal operating state, shows that the intensity peaks are oriented towards or concentrated at higher frequencies. Figure 5 It can be seen that there are two distinct high peaks at 33Hz and 37Hz, compared to... Figure 4B The micro-short circuit exhibits a distribution of high-frequency peaks at low frequencies, while the internal short circuit tends to be distributed in the high-frequency region, displaying high peaks. Test results show that the frequency intensity of the frequency domain result of this invention gradually shifts from low frequency to high frequency from the normal operating state of the battery cell to the polarized state, and finally to the internal short circuit state.

[0072] Further, in step S6 above, the converted frequency domain value (X(n)) is further verified by applying the following Welch method formulas (2), (3), and (4), and the results are as follows. Figure 6 It is the corresponding Figure 4B Comparison of transformed data using Fourier formula (1), such as... Figure 6 According to the spectral purification analysis performed by Welch's formula (2), the corresponding or very similar frequency peak phenomenon was indeed obtained. Therefore, the effectiveness of the Fourier transform used in step S3 of the present invention can be determined.

[0073]

[0074]

[0075]

[0076] The meanings of the symbols in the aforementioned formulas (2) to (4) are shown in Table 2.

[0077] Table 2

[0078]

[0079] Please refer to Figure 7 The system and method provided above in this invention can be further integrated into a cloud or online monitoring and management system, which may include the battery terminal 10, a cloud terminal 20, and a receiving terminal 30 that are interconnected by signals, wherein:

[0080] The battery terminal 10, as described above, includes the battery unit 11, the battery status sensing unit 111, and the transmission unit 12. The transmission unit 12 continuously transmits the status signal values ​​of the battery unit 11 obtained by the battery status sensing unit 111, which may be transmitted in a wired or wireless manner.

[0081] The cloud 20 includes a storage unit 21, a computing unit 22, and a database 23. The storage unit 21 receives and stores the status signal value transmitted through the transmission unit 12, and then transmits it to the computing unit 22 for processing. The result of the processing is compared with the standard value stored in the database 23 to obtain the analysis and prediction result.

[0082] The receiving terminal 30 can be any electronic device capable of receiving electrical signals, including mobile phones, computers, or vehicle computers, to receive the analysis and prediction results obtained by the cloud 20 and to remind the user of the possible short circuit of the battery.

[0083] Furthermore, the above describes the key method of predicting battery short circuits by converting micro-short circuit signals. In actual application, it is possible that a system for quickly analyzing and predicting battery failure and short circuits will be used to sense and predict the electrical system under test. This invention can also be integrated into existing battery management systems (BMS) to obtain the timing of micro-short circuits and predict and analyze the possibility of internal short circuits or even short circuits in the battery in advance.

[0084] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant figures and employ a general method of preserving decimal places. Although the numerical ranges and parameters used to confirm their breadth of scope in some embodiments of the invention are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0085] Finally, it should be understood that the embodiments described in this invention are merely illustrative of the principles of the invention. Other modifications may also fall within the scope of this invention. Therefore, alternative configurations of the embodiments of this invention are considered as examples and not limitations, and are regarded as consistent with the teachings of this invention. Accordingly, the embodiments of this invention are not limited to those explicitly described and illustrated herein.

Claims

1. A method for rapidly analyzing and predicting battery failure and short circuits, characterized in that, The steps include: A battery status sensing unit is used to continuously acquire a status signal value of a battery cell; The state signal value obtained from the battery state sensing unit is first determined to be of the type of state signal value, and a time domain result is presented in terms of time and state signal value to determine whether the state signal value is higher than a preset first time domain threshold. The time-domain result that is not higher than the first time-domain threshold is converted from the time domain to the frequency domain to obtain a frequency domain result; as well as When the value of the frequency domain result exceeds a second frequency domain threshold, the battery cell is assessed to have a micro short circuit and the battery cell issues a warning.

2. The method for rapid analysis and prediction of battery failure and short circuit as described in claim 1, characterized in that, The time-domain result is converted to the frequency-domain result by performing the following formula (1); in: N is the number of samples; n represents the current sample; k is the current frequency, and k∈[0,N-1]; x(n) is the sine value of n; and X(n) is the frequency domain result of the frequency domain relationship between the frequency and intensity of the Fast Fourier Transform.

3. The method for rapid analysis and prediction of battery failure and short circuit as described in claim 1, characterized in that: The status signal value includes the voltage, current, impedance, or temperature of the battery cell.

4. The method for rapid analysis and prediction of battery failure and short circuit as described in claim 1, 2, or 3, characterized in that: The battery cell includes a normal operating state, a polarized state, and an internal short-circuit state.

5. The method for rapid analysis and prediction of battery failure and short circuit as described in claim 4, characterized in that: The micro-short circuit occurred during the normal operating state of the battery cell.

6. The method for rapid analysis and prediction of battery failure and short circuit as described in claim 1, 2, or 3, characterized in that: The frequency intensity of the frequency domain result gradually changes from low frequency to high frequency from the normal operating state of the battery cell to the polarized state and then to the internal short circuit state.

7. The method for rapid analysis and prediction of battery failure and short circuit as described in claim 1 or 2, characterized in that: The frequency domain results are filtered using a filter.

8. The method for rapid analysis and prediction of battery failure and short circuit as described in claim 1 or 2, characterized in that: The frequency domain results were further verified using the Welch method.

9. A system for rapidly analyzing and predicting battery failure and short circuits, characterized in that, It includes: a battery terminal, a cloud terminal, and a receiving telecommunications terminal that are interconnected by signals, wherein: The battery terminal includes a battery cell, which is connected to a battery status sensing unit and continuously senses the status signal value of the battery cell during charge and discharge cycles. The status signal value is then transmitted outward through a transmission unit also located in the battery terminal. The cloud platform includes a storage unit, a computing unit, and a database. The storage unit receives and stores the status signal values ​​transmitted via the transmission unit, then transmits them to the computing unit for computation using the rapid analysis and prediction method for battery failure and short circuits as described in any one of claims 1 to 8. The computational result is compared with the standard values ​​stored in the database to obtain the analysis and prediction result. The receiving end is any electronic device capable of receiving telecommunication signals.

Images