A battery life prediction method and system for fire protection products

Abstract

The present application discloses a battery life prediction method and system for fire protection products. The method includes obtaining the battery surface temperature, drawing a first working curve of the battery according to the battery surface temperature, the first working curve is used to reflect the battery charging performance under the influence of temperature; obtaining the battery environment humidity, drawing a second working curve of the battery according to the battery environment humidity, the second working curve is used to reflect the battery discharge performance under the influence of humidity; based on the first working curve and the second working curve, obtaining a third working curve of the battery, the third working curve is used to reflect the battery health status; judging the remaining life of the battery based on the slope change rate of each point on the third curve. The method and system disclosed in the present application can improve the accuracy of battery life prediction by coupling the four aspects of temperature, humidity, charging and discharging.

Description

Technical Field

[0001] The present invention generally relates to the field of battery health detection. More specifically, the present invention relates to a battery life prediction method applied to fire protection products and a battery life prediction method system applied to fire protection products. Background Art

[0002] Traditional fire-fighting lithium battery-powered equipment relies on the protection board of the secondary lithium battery for battery safety. There is no task protection action before thermal runaway occurs. When thermal runaway occurs and the battery's own protection fails, it cannot effectively prevent the thermal runaway process. With the increasing application of lithium batteries in fire-fighting products, the protection method relying on the battery itself can no longer meet the needs of industry technology development.

[0003] In the prior art, the battery's state of health (SOH) is obtained by analyzing the surface temperature of the battery during operation, thereby predicting the remaining life of the battery. However, the battery prediction in the prior art is only based on the impact of temperature on the battery, without considering that the humidity of the environment in which the battery is located will also affect the battery life. On the other hand, when predicting the battery SOH, only the parameters of battery charging or discharging are used, and the impact of charging and discharging is not considered in an integrated manner, resulting in low accuracy in battery life prediction.

[0004] In summary, how to accurately predict the battery life in the early stage of battery out of control has become an urgent problem that needs to be solved. Summary of the invention

[0005] In order to at least solve the technical problems described in the above background technology section, the present invention proposes a battery life prediction method and system for fire protection products. By using the solution of the present invention, the effects of temperature, humidity, charging and discharging on the battery can be effectively coupled, and the accuracy of battery life prediction can be improved. In view of this, the present invention provides solutions in the following aspects.

[0006] The first aspect of the present invention provides a battery life prediction method applied to fire protection products, comprising: obtaining the battery surface temperature, drawing a first working curve of the battery according to the battery surface temperature, the first working curve being used to reflect the battery charging performance under the influence of temperature; obtaining the battery environmental humidity, drawing a second working curve of the battery according to the battery environmental humidity, the second working curve being used to reflect the battery discharge performance under the influence of humidity; obtaining a third working curve of the battery based on the first working curve and the second working curve, the third working curve being used to reflect the battery health status; judging the remaining life of the battery based on the slope change rate of each point on the third curve.

[0007] In one embodiment, drawing a first working curve of a battery according to the battery surface temperature includes: obtaining a first initial battery health state coefficient, establishing a first theoretical battery health state curve according to the first initial battery health state coefficient, wherein the first theoretical battery health state curve is a 15-order function; obtaining test data of the battery at different temperatures to obtain a first battery health state correction coefficient; and establishing a first working curve of the battery according to the first initial battery health state coefficient, the first battery health state correction coefficient and the first theoretical battery health state curve.

[0008] In one embodiment, drawing a second working curve of the battery according to the battery environmental humidity includes: obtaining a second battery health status initial coefficient, establishing a second theoretical battery health status curve according to the second battery health status initial coefficient, wherein the second theoretical battery health status curve is a 6th-order function; obtaining test data of the battery under different humidity conditions to obtain a second battery health status correction coefficient; and establishing a second working curve of the battery according to the second battery health status initial coefficient, the second battery health status correction coefficient and the second theoretical battery health status curve.

[0009] In one embodiment, obtaining a third working curve of the battery based on the first working curve and the second working curve includes: obtaining a difference curve based on the difference between the first working curve and the second working curve; and smoothing the difference curve to obtain the third working curve.

[0010] In one embodiment, judging the remaining life of the battery based on the slope change rate of each point on the third curve includes: obtaining the slope change rate of each point on the third curve; and issuing a warning when the slope change rate exceeds a preset value.

[0011] The first aspect of the present invention provides a battery life prediction system applied to fire protection products, including: a temperature processing module, used to obtain the battery surface temperature, and draw a first working curve of the battery according to the battery surface temperature, the first working curve is used to reflect the battery charging performance under the influence of temperature; a humidity processing module, used to obtain the battery environmental humidity, and draw a second working curve of the battery according to the battery environmental humidity, the second working curve is used to reflect the battery discharge performance under the influence of humidity; a calculation module, used to obtain a third working curve of the battery based on the first working curve and the second working curve, the third working curve is used to reflect the battery health status; a judgment module, used to judge the remaining life of the battery based on the slope change rate of each point on the third curve.

[0012] In one embodiment, drawing a first working curve of a battery according to the battery surface temperature includes: obtaining a first initial battery health state coefficient, establishing a first theoretical battery health state curve according to the first initial battery health state coefficient, wherein the first theoretical battery health state curve is a 15-order function; obtaining test data of the battery at different temperatures to obtain a first battery health state correction coefficient; and establishing a first working curve of the battery according to the first initial battery health state coefficient, the first battery health state correction coefficient and the first theoretical battery health state curve.

[0013] In one embodiment, drawing a second working curve of the battery according to the battery environmental humidity includes: obtaining a second battery health status initial coefficient, establishing a second theoretical battery health status curve according to the second battery health status initial coefficient, wherein the second theoretical battery health status curve is a 6th-order function; obtaining test data of the battery under different humidity conditions to obtain a second battery health status correction coefficient; and establishing a second working curve of the battery according to the second battery health status initial coefficient, the second battery health status correction coefficient and the second theoretical battery health status curve.

[0014] In one embodiment, obtaining a third working curve of the battery based on the first working curve and the second working curve includes: obtaining a difference curve based on the difference between the first working curve and the second working curve; and smoothing the difference curve to obtain the third working curve.

[0015] In one embodiment, judging the remaining life of the battery based on the slope change rate of each point on the third curve includes: obtaining the slope change rate of each point on the third curve; and issuing a warning when the slope change rate exceeds a preset value.

[0016] By using the solution provided by the present invention, the third working curve is obtained by coupling the first working curve affected by temperature and the second working curve affected by humidity. The third working curve combines the effects of temperature, humidity, charging and discharging on battery life. Therefore, the battery life can be predicted more accurately, thereby improving the reliability in firefighting applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0018] Figure 1 is a schematic diagram showing a battery life prediction method according to an embodiment of the present invention;

[0019] Figure 2 is a schematic diagram showing a method for drawing a first working curve of a battery according to a battery surface temperature according to an embodiment of the present invention;

[0020] Figure 3 is a schematic diagram showing a method for drawing a second working curve of a battery according to the battery environment humidity according to an embodiment of the present invention;

[0021] Figure 4 is a schematic diagram showing a method for obtaining a third working curve of a battery according to an embodiment of the present invention;

[0022] Figure 5 FIG. 4 is a schematic diagram of a battery life prediction system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0024] It should be understood that the terms "first", "second", "third" and "fourth" etc. in the claims, specifications and drawings of the present invention are used to distinguish different objects rather than to describe a specific order. The terms "include" and "comprise" used in the specification and claims of the present invention indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their collections.

[0025] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the claims, the singular forms of "a", "an" and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in the specification of the present invention and the claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0026] As used in this specification and claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0027] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0028] A first aspect of the present invention provides a battery life prediction method for fire protection products. Figure 1 Schematic diagram of a battery life prediction method according to an embodiment of the present invention. A battery life prediction method according to the present invention can be implemented as steps S100-S400 described below:

[0029] Step S100, obtaining the battery surface temperature, and drawing a first battery working curve according to the battery surface temperature;

[0030] Step S200, obtaining the battery environment humidity, and drawing a second battery working curve according to the battery environment humidity;

[0031] Step S300, acquiring a third working curve of the battery based on the first working curve and the second working curve;

[0032] Step S400, judging the remaining life of the battery based on the slope change rate of each point on the third curve.

[0033] In an embodiment of the present invention, the first working curve is used to reflect the battery charging performance under the influence of temperature, the second working curve is used to reflect the battery discharging performance under the influence of humidity, and the third working curve is used to reflect the battery health status. In the present invention, on the one hand, by fitting the charging performance curve and the discharging performance curve of the battery, the actual working conditions of the battery can be more completely reflected. On the other hand, by fitting the effects of temperature and humidity on the battery, the effect of the external environment on the battery life can be more accurately reflected. The present invention can more accurately predict the health status of the battery through the integrated consideration of the above two aspects, thereby effectively accurately estimating the battery life in firefighting applications and improving the reliability of batteries for firefighting products.

[0034] In an embodiment of the present invention, the specific method for obtaining the first working curve of the battery, the second working curve of the battery, and the third working curve of the battery is described below. The above three working curves can all be curves of voltage changes over time. When external variables are excluded and constant current charging and discharging is used, the first working curve representing the charging performance of the battery can be a curve whose trend is roughly that of increasing voltage over time, and the second working curve representing the discharge performance of the battery can be a curve whose trend is roughly that of decreasing voltage over time. It should be noted here that the specific form or acquisition method of the working curve does not need to be limited in the present invention, as long as it can reflect the actual working state of the battery. Therefore, the above curves can also be curves of the relationship between capacity and potential.

[0035] It should be emphasized that in the actual application of batteries in fire protection products, temperature will have a greater impact on the charging performance of the battery, while humidity will affect the discharge performance of the battery. Therefore, when obtaining the above-mentioned first working curve, the present invention uses different temperatures and the same humidity to perform voltage-time tests, thereby fitting the first working curve; and when obtaining the second working curve, different humidity and the same temperature are used to perform voltage-time tests, thereby fitting the second working curve. In the present invention, by making different trade-offs for different influencing factors in charging and discharging, the obtained curve can better reflect the state of the battery in the actual application process, thereby improving the accuracy.

[0036] Considering that the battery life presents a "horsetail curve", that is, when the remaining battery life is long, the loss is slow, and when the remaining battery life is short, the loss is aggravated. Therefore, in order to be able to judge the remaining battery life in advance and leave sufficient margin for remedial operations such as battery replacement, in the present invention, when judging the remaining battery life, a technical means of judging the slope change rate of the third working curve is adopted. When the slope change rate exceeds a preset threshold, it indicates that a sudden change has occurred in the battery life. The battery life is judged by the above-mentioned sudden change, and an alarm is issued when necessary. In the present invention, the above-mentioned remaining life judgment means, on the one hand, has higher accuracy than the prior art directly judging according to the SOH curve, and on the other hand, the judgment threshold can be adjusted according to actual needs, thereby providing operational flexibility for the remaining life judgment.

[0037] In a preferred embodiment of the present invention, the specific steps of drawing the first working curve of the battery according to the battery surface temperature are shown in Figure 2 . Figure 2 The method of drawing a first working curve of a battery according to the surface temperature of the battery according to one embodiment of the present invention is shown in a schematic diagram, which can be implemented as steps S210-S230 described below:

[0038] Step S210, obtaining a first battery health state initial coefficient, and establishing a first theoretical battery health state curve according to the first battery health state initial coefficient;

[0039] Step S220, acquiring test data of the battery at different temperatures to obtain a first battery health status correction coefficient;

[0040] Step S230 , establishing a first battery operating curve according to the first battery health state initial coefficient, the first battery health state correction coefficient and the first theoretical battery health state curve.

[0041] In a preferred embodiment of the present invention, the first theoretical battery health status curve in step S210 is a 15th order function. For example, it can be the following formula:

[0042] V1(t1)=A1t1 15 +B1t1 14 +C1t1 10 +D1t1 6 +E1t1 2 +F1 (1)

[0043] In the above formula (1), V1 represents voltage, t1 represents time, A1 represents the 15th-order battery health state initial coefficient of the first theoretical battery health state curve, B1 represents the 14th-order battery health state initial coefficient of the first theoretical battery health state curve, C1 represents the 10th-order battery health state initial coefficient of the first theoretical battery health state curve, D1 represents the 6th-order battery health state initial coefficient of the first theoretical battery health state curve, E1 represents the 2nd-order battery health state initial coefficient represented by the first theoretical battery health state curve, and F1 represents the constant coefficient (also called the 0th-order coefficient) of the first theoretical battery health state curve. Generally speaking, the higher the order of curve fitting, the more accurate the result obtained. However, the present invention makes a reasonable balance between actual computing consumption and accuracy, and selects the first temperature-related working curve as a 15th-order function. On the one hand, it is considered that temperature has a greater actual impact on battery life. On the other hand, the optimal order selection is obtained through computer simulation, and the most accurate result can be obtained with the smallest possible computing consumption. It should be noted that the above formula is only a representative implementation method, and any battery working curve that can represent the battery temperature can be included in the protection scope of the present invention.

[0044] The above-mentioned initial coefficient of the battery health state can be a preset value pre-configured when the battery leaves the factory or an actual value generated after calibration according to the last production batch of the battery. Since neither the factory preset value nor the last batch value can accurately predict the actual working state of this batch of batteries, it is necessary to calibrate the initial coefficient of the battery health state of each order to obtain the actual working curve of the batch.

[0045] In step S220, sample batteries are taken from a batch of multiple batteries, and the number of sample batteries can be selected as one or more according to actual conditions. The sample batteries are placed in different temperature and humidity environments for multiple voltage-time relationship tests. The first battery health state correction coefficient can be obtained by comparing it with the first theoretical battery health state curve. At this time, the corrected coefficient is expressed by the following formula (2):

[0046]

[0047] In the above formula (2), A1' to F1' represent the corrected coefficients of each order, and ΔA1 to ΔF1 represent the health status correction coefficients of each order.

[0048] In the above step 220, multiple battery working curves are obtained at different temperatures. In step S230, the actual curve can be fitted by the least square method in the actual operation process to obtain the above first battery working curve. Therefore, according to formula (1) and formula (2), the corrected first battery working curve can be obtained, which can be expressed in the following form:

[0049] V1(t1)=(A1+ΔA1)t1 15 +(B1+ΔB1)t1 14 +(C1+ΔC1)t1 10 +(D1+ΔD1)t1 6 +(E1+ΔE1)t1 2 +(F1+ΔF1) (3)

[0050] In a preferred embodiment of the present invention, the specific steps of drawing the second working curve of the battery according to the battery environmental humidity are shown in FIG. Figure 3 . Figure 3 The method of drawing a second working curve of a battery according to the battery environment humidity according to one embodiment of the present invention is shown in a schematic diagram, which can be implemented as steps S310-S330 described below:

[0051] Step S310, obtaining a second battery health state initial coefficient, and establishing a second theoretical battery health state curve according to the second battery health state initial coefficient;

[0052] Step S320, acquiring test data of the battery at different humidity levels to obtain a second battery health status correction coefficient;

[0053] Step S330 , establishing a second battery operating curve according to the second battery health state initial coefficient, the second battery health state correction coefficient, and the second theoretical battery health state curve.

[0054] In a preferred embodiment of the present invention, the second theoretical battery health status curve in step S310 is a sixth-order function. For example, it can be the following formula (4):

[0055] V2(t2)=A2t2 6 +B2t2 5 +C2t2 2 +D2t2+E2 (4)

[0056] In the above formula (4), V2 represents voltage, t2 represents time, A2 represents the 6th-order battery health initial coefficient of the second theoretical battery health curve, B2 represents the 5th-order battery health initial coefficient of the second theoretical battery health curve, C2 represents the 2nd-order battery health initial coefficient of the second theoretical battery health curve, D2 represents the 1st-order battery health initial coefficient of the second theoretical battery health curve, and E2 represents the constant coefficient (also called the 0th-order coefficient) of the second theoretical battery health curve. In the present invention, unlike the 15th-order function selected for the temperature test curve, the battery life consumption in the fire protection product has little to do with humidity. On the other hand, in the actual production process, it is found that the overall function trend of the 6th-order function is the same as that of the 15th-order function, and there are fewer singular points in the curve, so the comprehensive performance is higher than that of the 1-10th-order function. Therefore, in the present invention, considering the computational complexity and prediction accuracy, the 6th-order function is selected to achieve the best configuration of computational performance and accuracy.

[0057] The specific method for obtaining the second working curve of the battery in the present invention is similar to the specific method for obtaining the first working curve of the battery, and will not be repeated here. It should be noted that the specific method for obtaining the second working curve of the battery is different from the specific method for obtaining the first working curve of the battery in that the second working curve is obtained under different humidity and the same temperature. Finally, the obtained second working curve of the battery can be expressed in the following form:

[0058] V2(t2)=(A2+ΔA2)t2 6 +(B2+ΔB2)t2 5 +(C2+ΔC2)t2 2 +(D2+ΔD2)t2+(E2+ΔE2) (5)

[0059] In the above formula (5), ΔA2 to ΔF2 represent health status correction coefficients of each order respectively.

[0060] In a preferred embodiment of the present invention, the specific steps of obtaining the third working curve of the battery based on the first working curve and the second working curve are shown in Figure 4 . Figure 4It is a schematic diagram showing a method for obtaining a third working curve of a battery according to an embodiment of the present invention, which can be implemented as steps S410-S420 described below:

[0061] Step S410, obtaining a difference curve based on the first working curve and the second working curve;

[0062] Step S420: Smoothing the difference curve to obtain the third working curve.

[0063] In the embodiment of the present invention, the first working curve is used to describe the charging process of the battery, and its curve change can be roughly described as the following rule: the initial charging voltage rises faster, then there is a relatively long platform, and the change is slow. Before the charging is close to the termination point, the voltage has a small jump, which is maintained for a certain time until the termination. The second working curve is used to describe the discharge process of the battery, and its curve change can be roughly described as the following rule: the voltage drops faster in the initial stage, becomes gentle in the middle stage, and the voltage drops faster when approaching the discharge termination point in the later stage, to the specified termination voltage value. In order to couple the effects of temperature, humidity, charging and discharging on the battery life in the present invention, the difference between the first working curve and the second working curve is taken to obtain a difference curve. After obtaining the difference curve, in order to eliminate the influence of undesirable jumps on the final judgment, the difference curve is smoothed. It can be understood that the method for smoothing the curve can use any existing method, such as median filtering, etc. The curve obtained after filtering is the third working curve, which combines the characteristics of temperature, humidity, charging and discharging to obtain a more accurate basis for judging the battery life, thereby improving the accuracy of the prediction.

[0064] based on Figure 1-Figure 4 The battery life prediction method for fire fighting products described above, the second aspect of the present invention also provides a battery life prediction system for fire fighting products; the battery life prediction system can be implemented Figure 1-Figure 4 A battery life prediction method for fire protection products is described, so as to achieve a more accurate prediction of the battery life of fire protection applications; Figure 5 As shown, a battery life prediction system 500 applied to fire protection products of the present invention includes:

[0065] A temperature processing module 510 is used to obtain a battery surface temperature and draw a first working curve of the battery according to the battery surface temperature, wherein the first working curve is used to reflect the battery charging performance under the influence of temperature;

[0066] A humidity processing module 520 is used to obtain the battery environment humidity and draw a second battery working curve according to the battery environment humidity, wherein the second working curve is used to reflect the battery discharge performance under the influence of humidity;

[0067] A calculation module 530, configured to obtain a third working curve of the battery based on the first working curve and the second working curve, wherein the third working curve is used to reflect the health status of the battery;

[0068] The judgment module 540 is used to judge the remaining life of the battery based on the slope change rate of each point on the third curve.

[0069] In a preferred embodiment of the present invention, the step of drawing a first working curve of the battery according to the surface temperature of the battery includes:

[0070] Acquire a first battery health state initial coefficient, and establish a first theoretical battery health state curve according to the first battery health state initial coefficient, wherein the first theoretical battery health state curve is a 15th order function;

[0071] Acquire test data of the battery at different temperatures to obtain a first battery health status correction coefficient;

[0072] A first battery operating curve is established according to the first battery health state initial coefficient, the first battery health state correction coefficient and the first theoretical battery health state curve.

[0073] In a preferred embodiment of the present invention, the step of drawing a second working curve of the battery according to the battery environment humidity includes:

[0074] Acquire a second battery health state initial coefficient, and establish a second theoretical battery health state curve according to the second battery health state initial coefficient, wherein the second theoretical battery health state curve is a sixth-order function;

[0075] Acquire test data of the battery under different humidity conditions to obtain a second battery health status correction coefficient;

[0076] A second battery operating curve is established according to the second battery health state initial coefficient, the second battery health state correction coefficient and the second theoretical battery health state curve.

[0077] In a preferred embodiment of the present invention, the step of acquiring a third working curve of the battery based on the first working curve and the second working curve includes:

[0078] Obtaining a difference curve based on the difference between the first working curve and the second working curve;

[0079] The difference curve is smoothed to obtain the third working curve.

[0080] In a preferred embodiment of the present invention, judging the remaining life of the battery based on the slope change rate of each point on the third curve includes:

[0081] Obtaining the slope change rate of each point on the third curve;

[0082] A warning is issued when the slope change rate exceeds a preset value.

[0083] Although this specification has shown and described a plurality of embodiments of the present invention, it is obvious to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will appreciate many changes, modifications and alternatives without departing from the thought and spirit of the present invention. It should be understood that in the process of practicing the present invention, various alternatives to the embodiments of the present invention described herein may be adopted. The attached claims are intended to define the scope of protection of the present invention, and therefore cover the modular compositions, equivalents or alternatives within the scope of these claims.

Claims

1. A battery life prediction method for fire protection products, characterized in that: include; Acquiring a battery surface temperature, and drawing a first working curve of the battery according to the battery surface temperature, wherein the first working curve is used to reflect the battery charging performance under the influence of temperature; Acquiring the battery environment humidity, and drawing a second working curve of the battery according to the battery environment humidity, wherein the second working curve is used to reflect the battery discharge performance under the influence of humidity; Based on the first working curve and the second working curve, obtaining a third working curve of the battery, wherein the third working curve is used to reflect the health status of the battery; Determining the remaining life of the battery based on the slope change rate of each point on the third working curve; The obtaining a third working curve of the battery based on the first working curve and the second working curve comprises: Obtaining a difference curve based on the difference between the first working curve and the second working curve; The difference curve is smoothed to obtain the third working curve.

2. The battery life prediction method according to claim 1, characterized in that: The step of drawing a first working curve of the battery according to the surface temperature of the battery comprises: Acquire a first battery health state initial coefficient, and establish a first theoretical battery health state curve according to the first battery health state initial coefficient, wherein the first theoretical battery health state curve is a 15th order function; Acquire test data of the battery at different temperatures to obtain a first battery health status correction coefficient; A first battery operating curve is established according to the first battery health state initial coefficient, the first battery health state correction coefficient and the first theoretical battery health state curve.

3. The battery life prediction method according to claim 1, characterized in that: The step of drawing a second working curve of the battery according to the battery environment humidity comprises: Acquire a second battery health state initial coefficient, and establish a second theoretical battery health state curve according to the second battery health state initial coefficient, wherein the second theoretical battery health state curve is a sixth-order function; Acquire test data of the battery under different humidity conditions to obtain a second battery health status correction coefficient; A second battery operating curve is established according to the second battery health state initial coefficient, the second battery health state correction coefficient and the second theoretical battery health state curve.

4. The battery life prediction method according to claim 3, characterized in that: Determining the remaining life of the battery based on the slope change rate of each point on the third working curve includes: Obtaining the slope change rate of each point on the third working curve; A warning is issued when the slope change rate exceeds a preset value.

5. A battery life prediction system for fire protection products, characterized in that: include; A temperature processing module, used for obtaining a battery surface temperature, and drawing a first working curve of the battery according to the battery surface temperature, wherein the first working curve is used for reflecting the battery charging performance under the influence of temperature; A humidity processing module, used for obtaining the battery environment humidity, and drawing a second working curve of the battery according to the battery environment humidity, wherein the second working curve is used for reflecting the battery discharge performance under the influence of humidity; a calculation module, configured to obtain a third working curve of the battery based on the first working curve and the second working curve, wherein the third working curve is used to reflect the health status of the battery; A judgment module, used for judging the remaining life of the battery based on the slope change rate of each point on the third working curve; The acquiring a third working curve of the battery based on the first working curve and the second working curve comprises: Obtaining a difference curve based on the difference between the first working curve and the second working curve; The difference curve is smoothed to obtain the third working curve.

6. The battery life prediction system according to claim 5, characterized in that: The step of drawing a first working curve of the battery according to the surface temperature of the battery comprises: Acquire a first battery health state initial coefficient, and establish a first theoretical battery health state curve according to the first battery health state initial coefficient, wherein the first theoretical battery health state curve is a 15th order function; Acquire test data of the battery at different temperatures to obtain a first battery health status correction coefficient; A first battery operating curve is established according to the first battery health state initial coefficient, the first battery health state correction coefficient and the first theoretical battery health state curve.

7. The battery life prediction system according to claim 5, characterized in that: The step of drawing a second working curve of the battery according to the battery environment humidity comprises: Acquire a second battery health state initial coefficient, and establish a second theoretical battery health state curve according to the second battery health state initial coefficient, wherein the second theoretical battery health state curve is a sixth-order function; Acquire test data of the battery under different humidity conditions to obtain a second battery health status correction coefficient; A second battery operating curve is established according to the second battery health state initial coefficient, the second battery health state correction coefficient and the second theoretical battery health state curve.

8. The battery life prediction system according to claim 7, characterized in that: Determining the remaining life of the battery based on the slope change rate of each point on the third working curve includes: Obtaining the slope change rate of each point on the third working curve; A warning is issued when the slope change rate exceeds a preset value.

Images