Battery use state prediction method and device, equipment and medium

Abstract

The invention relates to the technical field of battery management, and discloses a battery use state prediction method and device, equipment and a medium, and the method comprises the steps: obtaining an initial charging and discharging strategy and a battery use position set by a user; determining the temperature of each preset time period in a set period according to the battery use position; according to the initial charging and discharging strategy and the temperature of each preset time period, determining each use condition in a set period and the proportion of the use time of each use condition in the set period; and calculating the remaining service life according to each use condition in the set period, the proportion of the use time of each use condition in the set period and the actually measured or simulated service life of the battery under different pre-obtained use conditions. According to the method, the remaining service life of the battery under the initial charging and discharging strategy set by the user can be calculated, dynamic evaluation can be carried out according to the actual use condition of the battery, and the prediction result is more accurate.

Description

Technical Field

[0001] This invention relates to the field of battery management technology, and specifically to a method, apparatus, device, and medium for predicting battery usage status. Background Technology

[0002] During battery use, many factors can affect the lifespan of energy storage batteries, including usage rate, depth of discharge (DOD), time, and temperature.

[0003] Currently, existing solutions control the battery's depth of discharge based on the cumulative depth of discharge and the number of charge-discharge cycles, reducing deep discharge behavior during subsequent use and ensuring battery safety and charge-discharge cycle life. Alternatively, by analyzing peak and off-peak electricity prices, energy storage batteries are scheduled to be charged during off-peak hours and discharged during peak hours to avoid frequent charging and discharging and reduce operating costs. However, neither controlling the depth of discharge nor adjusting the battery's charge-discharge time can optimize battery usage in a single way; they cannot effectively predict the remaining battery life, and users cannot fully obtain information about the battery's condition. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and medium for predicting battery usage status, addressing the problem that existing methods cannot effectively predict the remaining lifespan of a battery.

[0005] In a first aspect, the present invention provides a method for predicting battery usage status, the method comprising: Obtain the user-defined initial charge / discharge strategy and battery usage location; The temperature for each preset time period within the set cycle is determined based on the battery's location. Based on the initial charging and discharging strategy and the temperature of each preset time period, determine the operating conditions within the set cycle and the proportion of the operating time of each operating condition to the set cycle. The remaining service life is calculated based on the various operating conditions within the set period, the proportion of the usage time of each operating condition to the set period, and the measured or simulated years of the battery under different operating conditions obtained in advance.

[0006] The battery usage status prediction method of the present invention comprehensively considers the user-set initial charge and discharge strategy and the temperature conditions corresponding to the battery usage location to determine the various usage conditions and the proportion of the usage time of each usage condition to the set period within a set period. Based on the determination of each usage condition and its proportion, combined with the measured or simulated years of the battery under different usage conditions obtained in advance, the remaining service life of the battery under the user-set initial charge and discharge strategy can be calculated. It can dynamically evaluate according to the actual usage of the battery. Compared with the traditional single-condition model prediction, the prediction results are more accurate and help users to reasonably arrange the battery usage and maintenance plan.

[0007] In one optional implementation, the formula for calculating the remaining service life is as follows:

[0008] In the formula, For the remaining service life, This represents the proportion of the usage time for the nth usage condition to the set cycle. This represents the measured or simulated lifespan of the battery under the nth operating condition.

[0009] This method uses a quantitative approach to weight and sum the proportion of each usage condition and the battery life under the corresponding condition, making the calculation of the remaining service life more intuitive and clear.

[0010] In one optional implementation, after determining the operating conditions and the proportion of the operating time of each operating condition to the set period within the set period based on the initial charge / discharge strategy and the temperature of each preset time period, the process includes: The remaining total discharge energy is calculated based on the various operating conditions within the set period, the proportion of the usage time of each operating condition to the set period, and the measured or simulated remaining discharge capacity of the battery under different operating conditions obtained in advance.

[0011] This method allows users to gain a more comprehensive understanding of the battery's usage status and make reasonable usage plans by predicting the total remaining discharge energy.

[0012] In one optional implementation, the formula for calculating the total remaining discharge energy is:

[0013] In the formula, This represents the total remaining discharge energy. This represents the proportion of the usage time for the nth usage condition to the set cycle. This represents the measured or simulated remaining discharge capacity of the battery under the nth operating condition.

[0014] This method calculates the total remaining discharge energy in a quantitative way, making the results more accurate and reliable.

[0015] In one alternative implementation, after calculating the remaining useful life, the process includes: After a set cycle, the current health status of the battery is calculated based on the remaining total discharge energy at the end of the previous set cycle. The remaining service life is calculated based on the user's re-entered charging and discharging strategy and the battery's current health status under different usage conditions. The optimal usage condition that maximizes the remaining service life is then obtained. Output the current optimal operating condition and its corresponding remaining service life.

[0016] This method calculates and outputs the current optimal operating conditions that maximize the remaining service life, providing users with clear usage suggestions. Users can adjust the battery charging and discharging strategy according to these suggestions to avoid premature battery degradation due to improper use and maximize battery life.

[0017] In one optional implementation, the current health status of the battery is calculated based on the remaining total discharge energy at the end of the previous set cycle, including: Divide the remaining total discharge energy at the end of the previous set cycle by the maximum total discharge energy of the battery to obtain the current health status of the battery.

[0018] This method can accurately determine the current health status based on the remaining total discharge energy, providing accurate data for a comprehensive assessment of battery usage.

[0019] In one alternative implementation, the initial charge / discharge strategy includes using rate, depth of discharge, and cell voltage differential.

[0020] This approach, by comprehensively considering the use of rate, depth of discharge, and cell voltage difference as charging and discharging strategies, can more comprehensively consider the battery's usage and improve the accuracy of prediction and adjustment.

[0021] In a second aspect, the present invention provides a battery usage status prediction device, comprising: The parameter acquisition module is used to acquire the user-defined initial charge / discharge strategy and battery usage location; The temperature determination module is used to determine the temperature of each preset time period within a set cycle based on the battery's usage location. The operating condition division module is used to determine the operating conditions and the proportion of the operating time of each operating condition to the set period based on the initial charging and discharging strategy and the temperature of each preset time period. The remaining service life calculation module is used to calculate the remaining service life based on the various operating conditions within the set period, the proportion of the usage time of each operating condition to the set period, and the measured or simulated service life of the battery under different operating conditions obtained in advance.

[0022] Thirdly, the present invention provides an electronic device, comprising: The memory and the processor are interconnected and communicate with each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the battery usage state prediction method of the first aspect or any corresponding embodiment described above.

[0023] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the battery usage state prediction method of the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0024] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 This is a flowchart illustrating a battery usage status prediction method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the interface for inputting the charging and discharging strategy according to an embodiment of the present invention; Figure 3 This is a flowchart illustrating another battery usage state prediction method according to an embodiment of the present invention; Figure 4 This is a structural block diagram of a battery usage status prediction device according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0028] Numerous factors influence the lifespan of energy storage batteries during use, including the usage rate, depth of discharge (DOD), time, and temperature. High temperatures and repeated deep discharges significantly increase the probability of lifespan degradation and battery swelling. Therefore, extending battery lifespan, improving battery efficiency, and ensuring battery safety remain pressing issues that require solutions.

[0029] The proposed solutions cannot effectively predict the remaining lifespan of the battery, users cannot fully obtain information about the battery status, and only consider a single factor affecting battery life, namely the depth of charge and discharge or the number of cycles, without comprehensively optimizing multiple key factors. Therefore, they are not effective in improving battery lifespan.

[0030] In view of this, embodiments of the present invention provide a battery usage status prediction method, which can calculate the remaining service life of the battery under the initial charge and discharge strategy set by the user. It can dynamically evaluate the battery according to the actual usage situation. Compared with the traditional single-condition model prediction, the prediction results are more accurate, which helps users to reasonably arrange the battery usage and maintenance plan. Moreover, it can maximize the battery life by optimizing the battery usage conditions while ensuring that the user's normal usage needs are met.

[0031] The battery status prediction method of this invention can be executed by a terminal device or a server. Specifically, the terminal device can be a smartphone, tablet computer, laptop computer, PDA, or desktop computer, etc. The server can be a standalone physical server, a server cluster or distributed system, or a cloud server providing cloud services.

[0032] According to an embodiment of the present invention, a method for predicting battery usage status is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0033] This embodiment provides a battery usage status prediction method, which can be used in the aforementioned terminal devices, such as mobile phones and tablets. Figure 1 This is a flowchart of a battery usage state prediction method according to an embodiment of the present invention, such as... Figure 1As shown, the process includes the following steps: Step S101: Obtain the user-defined initial charge / discharge strategy and battery usage location.

[0034] Specifically, the initial charge / discharge strategy is set by the user at the beginning of each set cycle. The initial charge / discharge strategy can use one or more of the following: rate, depth of discharge, and cell voltage differential.

[0035] The ratio used is the ratio of the battery's charge / discharge rate to its rated capacity. Battery voltage difference refers to the voltage difference that occurs between individual cells in the battery pack during charging and discharging.

[0036] The depth of discharge is determined based on the user-defined state of charge (SOC) range. The depth of discharge is calculated by subtracting the lower limit of the SOC range from the upper limit of the SOC range. For example... Figure 2 As shown, the user inputs the state of charge interval information in the user interface of the terminal device, and the depth of discharge is calculated based on the state of charge interval.

[0037] In one embodiment, the initial charge / discharge strategy includes using rate, depth of discharge, and cell voltage difference. By comprehensively considering rate, depth of discharge, and cell voltage difference as the charge / discharge strategy, the battery usage can be considered more comprehensively, improving the accuracy of prediction and adjustment.

[0038] The battery usage location can be obtained through user input or by detecting the user's current location.

[0039] Step S102: Determine the temperature of each preset time period within the set cycle based on the battery usage location.

[0040] Specifically, the length of the set period can be set according to actual needs, such as a period of one month or one year. Correspondingly, each preset time period within a set period can be one day, one month, etc.

[0041] In one example, a set period is one year, and a preset time period is one month. Using hours or days as the time unit, the average temperature per hour or day is calculated to obtain the average temperature distribution for each month. Then, according to the specified temperature interval division points, all temperature information is divided to obtain the temperature for each preset time period within the set period, and the time corresponding to each defined temperature interval is obtained.

[0042] Step S103: Determine the operating conditions and the proportion of the operating time of each operating condition to the set period based on the initial charging and discharging strategy and the temperature of each preset time period.

[0043] Each temperature range and initial charge / discharge strategy are combined to form a usage condition. The proportion of each usage condition in the set cycle is obtained based on the ratio of the time of the corresponding temperature range in the previous year to the set cycle.

[0044] Step S104: Calculate the remaining service life based on the various operating conditions within the set period, the proportion of the usage time of each operating condition to the set period, and the measured or simulated years of the battery under different operating conditions obtained in advance.

[0045] The measured or simulated lifespan of the battery under different operating conditions is obtained by conducting actual measurements or simulations under various operating conditions. These different operating conditions include combinations of operating rate, depth of discharge, cell voltage difference, and temperature. One parameter is used as a variable, while the others are fixed. For example, the operating rate is selected as the variable. At the same temperature, depth of discharge, and cell voltage difference, at operating rates C1 and C2, actual measurements or simulations of battery usage are performed to obtain the battery's State of Health (SOH) degradation trend under the same temperature, depth of discharge, and cell voltage difference. For instance, based on measured data at temperature T1 / 90% depth of discharge / cell voltage difference of 150mV and operating rate C1, a degradation trend curve can be fitted. The remaining lifespan is obtained based on the time it takes for the battery's SOH to reach a set value. Similarly, the measured or simulated lifespan under different operating temperatures / depth of discharge / cell voltage difference / operating rates can be obtained. Furthermore, the battery's SOH after a set period can be obtained from the battery's SOH degradation trend curve.

[0046] Based on battery simulation models and measured data, such as measured data under C1 operating rate at temperature T1 / 90% DOD / 150mV, the predicted service life and total discharge energy under these conditions can be obtained. Similarly, the predicted service life and total discharge energy under different operating temperatures / depth of discharge / cell voltage difference / operating rate can be obtained.

[0047] In some embodiments, the formula for calculating the remaining useful life is as follows:

[0048] In the formula, For the remaining service life, This represents the proportion of the usage time for the nth usage condition to the set cycle. This represents the measured or simulated lifespan of the battery under the nth operating condition.

[0049] By using the above formula, the proportion of each operating condition and the battery life under the corresponding operating condition are weighted and summed, making the calculation result of the remaining service life more intuitive and clear.

[0050] The battery usage status prediction method of this invention comprehensively considers the user-set initial charge and discharge strategy and the temperature conditions corresponding to the battery usage location to determine the usage conditions and the proportion of usage time of each usage condition within the set period. Based on the determination of each usage condition and its proportion, combined with the measured or simulated years of the battery under different usage conditions obtained in advance, the remaining service life of the battery under the user-set initial charge and discharge strategy can be calculated. It can dynamically evaluate according to the actual usage of the battery. Compared with the traditional single-condition model prediction, the prediction results are more accurate and help users to reasonably arrange the battery usage and maintenance plan.

[0051] In one embodiment, after determining the usage conditions within a set period and the proportion of usage time of each usage condition to the set period based on the initial charge / discharge strategy and the temperature of each preset time period in step S103, the process includes: The remaining total discharge energy is calculated based on the various operating conditions within the set period, the proportion of the usage time of each operating condition to the set period, and the measured or simulated remaining discharge capacity of the battery under different operating conditions obtained in advance.

[0052] The measured or simulated remaining discharge capacity of a battery under different operating conditions is obtained by conducting actual measurements or simulations of the battery to obtain the decay trend curve of the remaining discharge capacity over time under the same temperature, depth of discharge, and cell voltage difference. For example, based on the measured data at temperature T1 / 90% depth of discharge / cell voltage difference of 150mV and usage rate C1, the decay trend curve of the remaining discharge capacity can be fitted, thus obtaining the remaining discharge capacity of the battery under various operating conditions after different times. The remaining service life can be obtained based on the time after the remaining discharge capacity reaches a set value. By analogy, the measured or simulated remaining discharge capacity under different operating temperatures / depth of discharge / cell voltage difference / usage rates can be obtained.

[0053] Furthermore, the formula for calculating the total remaining discharge energy is as follows:

[0054] In the formula, This represents the total remaining discharge energy. This represents the proportion of the usage time for the nth usage condition to the set cycle. This represents the measured or simulated remaining discharge capacity of the battery under the nth operating condition. Calculating the total remaining discharge energy using this formula makes the results more accurate and reliable.

[0055] By predicting the total remaining discharge energy, the above method allows users to gain a more comprehensive understanding of the battery's usage status and make reasonable usage plans.

[0056] In one embodiment, such as Figure 3As shown, after calculating the remaining service life in step S103, the process includes: Step S105: After a set cycle, the current state of health (SOH) of the battery is calculated based on the remaining total discharge energy at the end of the previous set cycle.

[0057] Battery health status is a measure of the battery's current performance compared to its performance at the time of manufacture, reflecting the degree of battery aging. For example, if a new battery has a rated capacity of 100Ah and its actual capacity drops to 80Ah after 3 years of use, its health status is 80%. After multiple charge-discharge cycles, the battery's health status will decline, and the degree of decline varies under different usage conditions. For example, under certain usage conditions, a single charge-discharge cycle may cause a 0.001% decrease in health status.

[0058] Specifically, the current health status of the battery is obtained by dividing the remaining total discharge energy at the end of the previous set cycle by the maximum total discharge energy of the battery.

[0059] Specifically, the maximum total discharge energy of a battery is the remaining total discharge energy of a new battery, which can be obtained from the battery's manufacturing information.

[0060] The remaining total discharge energy at the end of the previous set cycle is taken as the current remaining total discharge energy of the battery. Dividing this remaining total discharge energy by the battery's maximum total discharge energy yields the battery's current health status. The current health status of the battery can be 80%, 90%, etc., used to assess the battery's health level.

[0061] Step S106: Calculate the remaining service life based on the user's re-input charging / discharging strategy and the measured or simulated service life of the battery under different usage conditions in the current health state of the battery, and obtain the current optimal usage condition that maximizes the remaining service life.

[0062] For each set cycle, the user sets a charging and discharging strategy according to their needs, including the usage rate, maximum state of charge (SOC), and minimum SOC. The depth of discharge is then calculated based on the SOC and SOC. By obtaining the temperature at the user's location and combining it with the usage rate and depth of discharge, various operating conditions are determined.

[0063] The measured or simulated lifespan of a battery under different usage conditions is determined by using the current health state of the battery as the starting time for the measured or simulated lifespan, and then calculating the time from the starting time to when the battery becomes unusable.

[0064] The remaining service life calculated again is done in the same way as the remaining service life calculated in the previous set period. The difference is that the actual or simulated service life of the battery is different due to the different current health status of the battery and different usage conditions.

[0065] The current optimal operating condition is the one that maximizes the battery's lifespan, using the current battery health state as the starting point for actual testing or simulation. Since the degradation trend curves of the battery's health state under various operating conditions are pre-stored, the curve representing the longest time from the current battery health state to the point where the battery is no longer usable can be found. The operating condition corresponding to this degradation trend curve is then selected as the current optimal operating condition.

[0066] Step S107: Output the current optimal operating condition and its corresponding remaining service life.

[0067] Specifically, the user interface displays the current optimal operating conditions and their corresponding remaining service life, making it convenient for users to set optimal operating conditions and understand the current battery usage.

[0068] The above solution provides users with clear usage suggestions by calculating and outputting the current optimal usage conditions that maximize the remaining service life. Users can adjust the battery charging and discharging strategy according to these suggestions to avoid premature battery degradation due to improper use and maximize battery life.

[0069] This embodiment also provides a battery usage status prediction device, which is used to implement the above embodiments and preferred embodiments, and will not be repeated as already described. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0070] This embodiment provides a battery usage status prediction device, such as... Figure 4 As shown, it includes: The parameter acquisition module 401 is used to acquire the user-defined initial charge / discharge strategy and battery usage location; Temperature determination module 402 is used to determine the temperature of each preset time period within a set cycle based on the battery usage location. The working condition division module 403 is used to determine the various operating conditions within the set period and the proportion of the usage time of each operating condition to the set period based on the initial charging and discharging strategy and the temperature of each preset time period. The remaining service life calculation module 404 is used to calculate the remaining service life based on the various operating conditions within the set period, the proportion of the usage time of each operating condition to the set period, and the measured or simulated service life of the battery under different operating conditions obtained in advance.

[0071] In some optional implementations, the formula for calculating the remaining service life in the remaining service life calculation module 404 is as follows:

[0072] In the formula, For the remaining service life, This represents the proportion of the usage time for the nth usage condition to the set cycle. This represents the measured or simulated lifespan of the battery under the nth operating condition.

[0073] In some optional implementations, the battery usage status prediction device further includes: The remaining energy calculation module is used to calculate the total remaining discharge energy based on the various operating conditions within a set period, the proportion of the usage time of each operating condition to the set period, and the measured or simulated remaining discharge capacity of the battery under different operating conditions obtained in advance.

[0074] In some optional implementations, the formula for calculating the total remaining discharge energy in the remaining energy calculation module is as follows:

[0075] In the formula, This represents the total remaining discharge energy. This represents the proportion of the usage time for the nth usage condition to the set cycle. This represents the measured or simulated remaining discharge capacity of the battery under the nth operating condition.

[0076] In some optional implementations, the battery usage status prediction device further includes: The health status calculation module is used to calculate the current health status of the battery based on the remaining total discharge energy at the end of the previous set cycle after a set cycle has elapsed. The optimal operating condition acquisition module is used to calculate the remaining service life of the battery under different operating conditions based on the charging and discharging strategy input by the user and the battery's current health status, and to obtain the current optimal operating condition that maximizes the remaining service life. The operating condition and service life output module is used to output the current optimal operating condition and its corresponding remaining service life.

[0077] In some optional implementations, the health status calculation module is also used for: Divide the remaining total discharge energy at the end of the previous set cycle by the maximum total discharge energy of the battery to obtain the current health status of the battery.

[0078] In some alternative implementations, the initial charge / discharge strategy includes using rate, depth of discharge, and cell voltage differential.

[0079] The battery usage status prediction device provided in this embodiment of the invention can execute the battery usage status prediction method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the various modules and units described above are the same as in the corresponding embodiments described above, and will not be repeated here.

[0080] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0081] The following is a detailed reference. Figure 5 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from memory 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the electronic device. The processor 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0082] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0083] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a memory 508, or installed from a ROM 502. When the computer program is executed by the processor 501, it performs the functions defined in the battery usage state prediction method of the embodiments of the present invention.

[0084] Figure 5The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0085] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the battery usage state prediction method shown in the above embodiments is implemented.

[0086] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for predicting battery usage status, characterized in that, The method includes: Obtain the user-defined initial charge / discharge strategy and battery usage location; The temperature for each preset time period within the set cycle is determined based on the battery's location. Based on the initial charge / discharge strategy and the temperature of each preset time period, determine the operating conditions within the set cycle and the proportion of the operating time of each operating condition to the set cycle. The remaining service life is calculated based on the various operating conditions within the set period, the proportion of the usage time of each operating condition to the set period, and the measured or simulated years of the battery under different operating conditions obtained in advance.

2. The method according to claim 1, characterized in that, The formula for calculating the remaining useful life is as follows: In the formula, For the remaining service life, This represents the proportion of the usage time of the nth usage condition to the set cycle. This represents the measured or simulated lifespan of the battery under the nth operating condition.

3. The method according to claim 1, characterized in that, After determining the usage conditions within the set period and the proportion of the usage time of each usage condition to the set period based on the initial charge / discharge strategy and the temperature of each preset time period, the process includes: The remaining total discharge energy is calculated based on each operating condition within the set period, the proportion of the usage time of each operating condition to the set period, and the measured or simulated remaining discharge capacity of the battery under different operating conditions obtained in advance.

4. The method according to claim 3, characterized in that, The formula for calculating the total remaining discharge energy is: In the formula, This represents the total remaining discharge energy. This represents the proportion of the usage time of the nth usage condition to the set cycle. This represents the measured or simulated remaining discharge capacity of the battery under the nth operating condition.

5. The method according to claim 4, characterized in that, After calculating the remaining useful life, the following is included: After one set cycle, the current health status of the battery is calculated based on the remaining total discharge energy at the end of the previous set cycle. The remaining service life is calculated based on the user's re-entered charging and discharging strategy and the battery's current health status under different usage conditions. The optimal usage condition that maximizes the remaining service life is then obtained. Output the current optimal operating condition and its corresponding remaining service life.

6. The method according to claim 5, characterized in that, The current health status of the battery is calculated based on the total remaining discharge energy at the end of the previous set cycle, including: Divide the remaining total discharge energy at the end of the previous set cycle by the maximum total discharge energy of the battery to obtain the current health status of the battery.

7. The method according to claim 1, characterized in that, The initial charge / discharge strategy includes using the rate, depth of discharge, and cell voltage difference.

8. A battery usage status prediction device, characterized in that, The device includes: The parameter acquisition module is used to acquire the user-defined initial charge / discharge strategy and battery usage location; The temperature determination module is used to determine the temperature of each preset time period within a set cycle based on the battery's usage location. The operating condition division module is used to determine, based on the initial charge and discharge strategy and the temperature of each preset time period, each operating condition within the set period and the proportion of the operating time of each operating condition to the set period. The remaining service life calculation module is used to calculate the remaining service life based on the various operating conditions within the set period, the proportion of the usage time of each operating condition to the set period, and the measured or simulated service life of the battery under different operating conditions obtained in advance.

9. An electronic device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the battery usage state prediction method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the battery usage state prediction method according to any one of claims 1 to 7.

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