Method and system for predicting and early warning service life of vehicle storage battery

Abstract

The invention discloses a vehicle storage battery life prediction and early warning method and system. The method comprises the following steps: acquiring a first battery capacity value obtained based on an ampere-hour integral method; obtaining a second battery capacity value obtained by associating the battery internal resistance with the battery temperature; obtaining a third battery capacity value obtained by the associated battery voltage; respectively adjusting the first battery capacity value, the second battery capacity value and the third battery capacity value, and obtaining the current maximum available capacity of the battery according to the adjusted first battery capacity value, the adjusted second battery capacity value and the adjusted third battery capacity value; and carrying out battery life early warning according to the current maximum available capacity of the battery. Based on the above data processing flow, the method can dynamically adapt to the individual difference of the vehicle battery, fuses the multi-source data of the vehicle, and achieves the precise prediction of the service life of the battery.

Description

Technical Field

[0001] This invention relates to the fields of automotive electronics technology and predictive maintenance technology, and in particular to a method and system for predicting and warning the lifespan of vehicle batteries. Background Technology

[0002] Sudden battery failure is a major cause of vehicle starting failure, causing significant inconvenience and potential safety hazards to users. Current technologies for predicting the lifespan of automotive lead-acid batteries mainly fall into three categories: physical model-based methods, data-driven methods, and statistical methods. Each of these methods has significant limitations when applied individually.

[0003] Common solutions currently include: 1. Voltage Monitoring Method: This method monitors battery voltage via an OBD interface or simple sensors, triggering an alarm when the voltage falls below a threshold. This method suffers from significant lag, cannot predict gradual battery degradation, and is susceptible to temperature and transient load fluctuations, resulting in a high false alarm rate. Furthermore, it relies on a single monitoring parameter, failing to comprehensively reflect the battery's true condition under complex operating conditions.

[0004] 2. Isolated prediction models: Existing technologies mostly use a single prediction model, which makes it difficult to maintain prediction accuracy throughout the entire battery life cycle.

[0005] Because existing technologies mainly rely on single thresholds of temperature, voltage, and current to predict internal resistance and determine battery life, they fail to fully utilize multi-source vehicle data, resulting in low accuracy in determining battery failure. This fails to address the issue of users identifying risks in advance or misjudging and avoiding risks, thus ensuring that safety hazards still exist. Summary of the Invention

[0006] This invention provides a method and system for predicting and warning the lifespan of vehicle batteries, which can dynamically adapt to individual differences in vehicle batteries and integrate multi-source vehicle data to achieve accurate prediction of battery lifespan. Firstly, a method for predicting and warning the lifespan of a vehicle battery is provided, including: Obtain the first battery capacity value based on the ampere-hour integration method; The second battery capacity value is obtained by relating the battery internal resistance to the battery temperature. Obtain the third battery capacity value from the associated battery voltage; The first battery capacity value, the second battery capacity value, and the third battery capacity value are adjusted respectively, and the current maximum usable capacity of the battery is obtained based on the adjusted first battery capacity value, second battery capacity value, and third battery capacity value. Battery life warning is given based on the current maximum available capacity of the battery.

[0007] In some embodiments, the method for obtaining the first battery capacity value based on the ampere-hour integration method is shown in the following formula: ; In the formula, C ah t is the first battery capacity value; I(t) is the instantaneous current; SOC1 is the SOC value obtained by measuring the open-circuit voltage after the vehicle has been stationary for the first time; SOC2 is the SOC value obtained by measuring the open-circuit voltage after the vehicle has been stationary for the second time.

[0008] In some embodiments, the method for obtaining the second battery capacity value derived from the correlation between the battery internal resistance and battery temperature is shown in the following formula: ; In the formula, C r This is the second battery capacity value; C rated R0 is the battery's rated capacity; R0 is the battery's initial internal resistance; R is the battery's current internal resistance; k is the battery's empirical degradation coefficient; λ is the temperature influence coefficient; α and β are weighting coefficients; ΔT is the difference between the current ambient temperature and the standard temperature.

[0009] In some embodiments, the method for obtaining the third battery capacity value derived from the associated battery voltage is shown in the following formula: ; In the formula, C v This is the third battery capacity value; C rated γ is the rated capacity of the battery; γ is the curvature factor; V m V is the current terminal voltage of the battery. full This is the virtual full-charge voltage; V cutoff This is the operating condition cutoff voltage.

[0010] In some embodiments, adjusting the first battery capacity value, the second battery capacity value, and the third battery capacity value respectively includes: Obtain the battery capacity value corresponding to each day from the current time period to the previous n days, and calculate the average value of the first battery capacity value and all battery capacity values ​​to obtain the adjusted first battery capacity value. Obtain the battery capacity value corresponding to each day from the current time period to the previous n days, and calculate the average value of the second battery capacity value and all battery capacity values ​​to obtain the adjusted second battery capacity value. Obtain the battery capacity value corresponding to each day from the current time period to the previous n days, and calculate the average value of the third battery capacity value with all battery capacity values ​​to obtain the adjusted third battery capacity value.

[0011] In some embodiments, the method for obtaining the current maximum usable capacity of the battery based on the adjusted first battery capacity value, the second battery capacity value, and the third battery capacity value is shown in the following formula: ; In the formula, C current This represents the battery's current maximum usable capacity; w1, w2, and w3 are weighting coefficients. This is the adjusted first battery capacity value; This is the adjusted second battery capacity value; This is the adjusted third battery capacity value.

[0012] In some embodiments, the battery life warning based on the current maximum usable capacity of the battery includes: Calculate the current SOH value of the battery based on the current maximum usable capacity and the battery's rated capacity; When the current SOH value of the battery is detected to exceed the SOH threshold, an early warning is issued regarding the current battery life.

[0013] In some embodiments, after providing a battery life warning based on the current maximum available capacity of the battery, the process includes: Calculate the target SOH value of the battery for the future target period based on the current SOH value of the battery; When the target SOH value of the battery is detected to exceed the SOH threshold, an early warning is issued for the battery life in the future target period.

[0014] In some embodiments, the method for calculating the target SOH value of the battery for a future target period based on the current SOH value of the battery is shown in the following formula: ; In the formula, SOH future The target SOH value for the battery in the future target period; SOH now This represents the current SOH value of the battery; d SOH / d Cycle The SOH value corresponding to the average full-cycle decay value; d SOH / d Time ΔTime is the static sulfur decay rate; ΔTime is the difference between the current time and the future target time period; ΔCycle is the equivalent number of cycles for the future target time period.

[0015] Secondly, a vehicle battery life prediction and early warning system is provided, including: The first capacity calculation module is used to obtain the first battery capacity value based on the ampere-hour integration method. The second capacity calculation module is used to obtain the second battery capacity value obtained by relating the battery internal resistance and battery temperature. The third capacity calculation module is used to obtain the third battery capacity value obtained from the associated battery voltage. A battery capacity adjustment calculation module, communicatively connected to the first capacity calculation module, the second capacity calculation module, and the third capacity calculation module, is used to adjust the first battery capacity value, the second battery capacity value, and the third battery capacity value respectively, and to obtain the current maximum usable battery capacity based on the adjusted first battery capacity value, second battery capacity value, and third battery capacity value; and, The early warning module is communicatively connected to the battery capacity adjustment calculation module and is used to provide early warning of battery life based on the current maximum usable capacity of the battery.

[0016] Thirdly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the vehicle battery life prediction and early warning method as described above.

[0017] Fourthly, embodiments of the present invention provide an electronic device, including a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, wherein the processor executes the computer program to implement the vehicle battery life prediction and early warning method as described above.

[0018] Compared with the prior art, the advantages of the present invention are as follows: 1. This invention overcomes the limitations of single methods being susceptible to operating condition interference by integrating three independent dimensions of battery capacity characterization parameters: ampere-hour integration method, internal resistance-temperature correlation method, and voltage correlation method. The current maximum usable capacity of the battery obtained after adjustment and integration can more comprehensively characterize the actual health state of the battery, significantly improve the accuracy of capacity prediction, and provide a reliable basis for subsequent life assessment.

[0019] 2. This invention not only provides real-time early warning based on the current capacity, but also calculates the target SOH value for a future target period based on the current SOH value, and combines the SOH threshold to determine the future lifespan trend. This dual-layer early warning mechanism of current status monitoring + future trend prediction can identify potential accelerated aging risks of batteries in advance, avoiding vehicle breakdowns or safety accidents caused by a sudden drop in capacity. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a method for predicting and warning the lifespan of a vehicle battery according to the present invention. Figure 2 This is a schematic diagram of the structure of a vehicle battery life prediction and early warning system according to the present invention. Detailed Implementation

[0021] Referring now to specific embodiments of the invention, examples of which are illustrated in the accompanying drawings. Although the invention will be described in conjunction with specific embodiments, it will be understood that it is not intended to limit the invention to the described embodiments. Rather, it is intended to cover variations, modifications, and equivalents included within the spirit and scope of the invention as defined by the appended claims. It should be noted that the method steps described herein can be implemented by any functional block or functional arrangement, and any functional block or functional arrangement can be implemented as a physical entity or a logical entity, or a combination of both.

[0022] To enable those skilled in the art to better understand the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] Note: The examples described below are merely specific examples and are not intended to limit the embodiments of the present invention to the specific steps, values, conditions, data, order, etc. Those skilled in the art can utilize the concept of the present invention to construct more embodiments not mentioned herein by reading this specification.

[0024] Please see Figure 1 The present invention provides a method for predicting and warning the lifespan of a vehicle battery. The method includes: Step S100, the method for obtaining the first battery capacity value based on the ampere-hour integration method is shown in the following formula: ; In the formula, C ah t is the first battery capacity value; I(t) is the instantaneous current; SOC1 is the SOC value obtained by measuring the open-circuit voltage after the vehicle has been stationary for the first time; SOC2 is the SOC value obtained by measuring the open-circuit voltage after the vehicle has been stationary for the second time.

[0025] Specifically, let's assume that the integration starts from the last vehicle stationary calibration point. After the vehicle has been stationary for 4 hours, the open circuit voltage OCV (Open Circuit Voltage) is measured. Let OCV = 12.65V. From the table, SOC1 = 92%.

[0026] The cumulative discharge ampere-hours from the last time the vehicle was stationary until the current time are: ∫I(t) dt = 8.7 Ah.

[0027] At the current moment, after the vehicle has been stationary for 15 minutes, the OCV is measured to be 12.20V, and the SOC2 is found to be 63% according to the table. SOC, short for State of Charge, is the state of charge or remaining charge, representing the percentage of the battery's nominal capacity that is currently remaining.

[0028] Therefore, the first battery capacity value C is calculated. ah= 8.7 Ah / (0.92 - 0.63) = 8.7 / 0.29 ≈ 30.0Ah.

[0029] Step S200, the method for obtaining the second battery capacity value by relating the battery internal resistance to the battery temperature is shown in the following formula: ; In the formula, C r This is the second battery capacity value; C rated R0 is the battery's rated capacity; R0 is the battery's initial internal resistance; R is the battery's current internal resistance; k is the battery's empirical degradation coefficient; λ is the temperature influence coefficient; α and β are weighting coefficients; ΔT is the difference between the current ambient temperature and the standard temperature.

[0030] Specifically, let R0 = 5.0 mΩ, R = 7.5 mΩ, the baseline value at 50% SOC; k = 0.8; ΔT = 25 - 10 = 15℃, standard temperature 25℃, current ambient temperature 10℃; λ = 0.015; α = 0.7, β = 0.3.

[0031] Therefore, based on the above parameter values, the calculation is as follows: This is the internal resistance-temperature correlation method. Internal resistance term: (R0 / R)^k = (5.0 / 7.5)^0.8 = (0.6667)^0.8 ≈ 0.724; Temperature term: exp(-λ) ΔT) = exp(-0.015 15) = exp(-0.225) ≈ 0.799; Weighted combination: 0.7 0.724 + 0.3 0.799 = 0.5068 + 0.2397 ≈ 0.7465 Final second battery capacity value C r = 60 Ah × 0.7465 ≈ 44.8 Ah.

[0032] Step S300, the method for obtaining the third battery capacity value obtained from the associated battery voltage is shown in the following formula: ; In the formula, C v This is the third battery capacity value; C rated γ is the rated capacity of the battery; γ is the curvature factor; V m V is the current terminal voltage of the battery. fullThis is the virtual full-charge voltage, representing the terminal voltage a "new battery" with a 100% SOC should have under the current discharge current and temperature. (This value is higher than the open-circuit voltage OCV because it includes the ohmic dropout); V cutoff This is the operating condition cutoff voltage, which represents the terminal voltage at the current discharge current and temperature when the capacity is depleted (typically SOC≈10-15%).

[0033] Specifically, let V m = 12.2 V; V full = 12.9 V; V cutoff = 10.8 V; γ = 1.3.

[0034] Therefore, based on the above parameter values, the calculation is as follows: This is the voltage correlation method. Voltage difference ratio: (12.2 - 10.8) / (12.9 - 10.8) = 1.4 / 2.1 ≈ 0.6667; Curvature correction: 0.6667 ^ 1.3 ≈ 0.6667^1.3, calculation: first find ln(0.6667)≈ -0.4055, then multiply by 1.3 to get -0.5271, finally exp(-0.5271)≈0.590.

[0035] Final third battery capacity value C v = 60 Ah × 0.590 ≈ 35.4 Ah.

[0036] Step S400: Adjust the first battery capacity value, the second battery capacity value and the third battery capacity value respectively, and obtain the current maximum usable capacity of the battery based on the adjusted first battery capacity value, second battery capacity value and third battery capacity value; The adjustment of the first battery capacity value, the second battery capacity value, and the third battery capacity value respectively includes: Obtain the battery capacity value corresponding to each day from the current time period to the previous n days, and calculate the average value of the first battery capacity value and all battery capacity values ​​to obtain the adjusted first battery capacity value. Obtain the battery capacity value corresponding to each day from the current time period to the previous n days, and calculate the average value of the second battery capacity value and all battery capacity values ​​to obtain the adjusted second battery capacity value. Obtain the battery capacity value corresponding to each day from the current time period to the previous n days, and calculate the average value of the third battery capacity value with all battery capacity values ​​to obtain the adjusted third battery capacity value.

[0037] Specifically, for the first battery capacity value: the actual calculated value is C. ah =30.0Ah, which requires the fusion of historical data. The system memory needs to retrieve the values ​​calculated using the ampere-hour integration method for the previous 6 days (42.1, 41.2, 42.5, 40.5, 40.8, 41.9, 30.0 (this time)), and then fuse the historical values ​​with the newly calculated and predicted values. The logic is: trust the long-term trend, be cautious about short-term drastic fluctuations (this time an anomaly of 30.0Ah), and can remove them. Therefore, the fusion formula is: Adjusted C ah = (42.1+41.2+42.5+40.5+40.8+41.9) / 6=41.5Ah, which is the adjusted first battery capacity value.

[0038] For the second battery capacity value: the actual calculated value is C. r =44.8Ah, it is necessary to integrate historical data and retrieve the capacity calculation values ​​of the previous 6 days from the system memory (36.3, 34.2, 43.0, 39.5, 38.8, 34.9, 44.8 (this time)). The capacity calculation method of these previous 6 days is the same as the calculation method of the second battery capacity value. Then, the historical value and the current newly calculated prediction value are integrated. The logic is: trust the long-term trend, and retain all data if there are no abnormalities. Therefore, the fusion formula is: Adjusted C r = (36.2+34.2+43.0+39.5+38.8+34.9+44.8) / 7=38.2Ah, which is the adjusted first battery capacity value.

[0039] For the third battery capacity: the actual calculated value is C. v =35.4Ah, it is necessary to integrate historical data and retrieve the capacity calculation values ​​of the previous 6 days from the system memory (33.6, 32.2, 35.0, 31.5, 31.8, 33.6, 35.4 (this time)). The capacity calculation method of these previous 6 days is the same as the calculation method of the third battery capacity value. Then, the historical value and the current newly calculated prediction value are integrated. The logic is: trust the long-term trend, and retain all data if there are no abnormalities. Therefore, the fusion formula is: Adjusted C v =(33.6+32.2+35.0+31.5+31.8+33.6+35.4) / 7=33.3Ah.

[0040] The method for obtaining the current maximum usable capacity of the battery based on the adjusted first battery capacity value, second battery capacity value, and third battery capacity value is shown in the following formula: ; In the formula, C currentThis represents the battery's current maximum usable capacity; w1, w2, and w3 are weighting coefficients. This is the adjusted first battery capacity value; This is the adjusted second battery capacity value; This is the adjusted third battery capacity value.

[0041] Specifically, dynamic weights are assigned based on the current state, as shown in Table (1) below: Table (1)

[0042] Therefore, the final weighted fusion calculation of the battery's current maximum usable capacity is as follows:

[0043] = 0.35 41.5 + 0.45 38.2 + 0.20 33.3 = 38.375 Ah.

[0044] Step S500, providing a battery life warning based on the current maximum usable capacity of the battery, including: Step S600: Calculate the current SOH value of the battery based on the current maximum usable capacity and the rated capacity of the battery; When the current SOH value of the battery is detected to exceed the SOH threshold, an early warning is issued regarding the current battery life.

[0045] Specifically, in this embodiment of the invention, the degradation of lead-acid batteries is mainly manifested in two aspects: capacity decay and internal resistance increase. The state of health is typically quantified using SOH (State of Health), and its calculation formula is as follows: SOH = (C current / C rated )×100%, C rated This refers to the battery's rated capacity (Ah).

[0046] When the SOH drops to 60%-80% (usually 70% is the critical point), the battery is considered to be degraded and needs to be replaced.

[0047] Therefore, the current SOH value of the battery is: SOH now = (C current / C rated (38.375 / 60) × 100% = (38.375 / 60) × 100% ≈ 63.96%. Therefore, the current SOH value of the battery is close to the critical line and has entered the warning range, thus providing an early warning for the current battery life.

[0048] The early warning threshold can be adjusted as follows: The general thresholds (70% / 60% / 50%) are too lenient for short-distance users and are adjusted to: Green: SOH > 75% (pay attention to capacity degradation earlier); Yellow: 65% < SOH ≤ 75% (recommend changing usage habits); Orange: 55% < SOH ≤ 65% (plan to replace); Red: SOH ≤ 55% (replace immediately); Therefore, when the current SOH value of the battery is 63.96%, an orange early warning is triggered, and it is recommended to: plan to replace and avoid long-term parking at low temperatures.

[0049] After the battery life early warning is performed according to the current maximum available capacity of the battery in step S500, it includes: The method for calculating the target SOH value of the battery in the future target period according to the current SOH value of the battery is shown in the following formula: ; In the formula, SOH future is the target SOH value of the battery in the future target period; SOH now is the current SOH value of the battery; d SOH / d Cycle is the SOH value corresponding to the average full-cycle attenuation value each time; d SOH / d Time is the static vulcanization attenuation rate; ΔTime is the difference between the current time and the future target period; ΔCycle is the equivalent cycle number in the future target period. In actual vehicle use, the battery rarely undergoes a complete charge and discharge, but experiences complex working conditions such as shallow charge and discharge, large current pulses, and different temperatures. The "equivalent cycle number" is to convert the complex and irregular actual vehicle use into the equivalent number of "standard cycles" according to the cumulative aging damage degree it causes to the battery.

[0050] Specifically, let d SOH / d Cycle = -0.05% / cycle, which is fitted according to the historical 180-cycle data, and the SOH of the average full-cycle attenuation is 0.05% each time.

[0051] ΔCycle = 7 times, predicting the next 7 days, the equivalent cycle number estimated according to the daily driving mode.

[0052] d SOH / d Time = -0.1% / day, the static vulcanization attenuation rate, which can be estimated according to the battery having been used for 18 months.

[0053] ΔTime = 7 days.

[0054] Therefore, based on the specific parameter values ​​mentioned above, the calculation is as follows: SOH_future = 63.96% - (0.05%) 7) - (0.1%) 7) = 62.91%.

[0055] Therefore, the prediction is that SOH will drop to about 62.9% in 7 days, triggering a "warning state".

[0056] See also Figure 2 As shown, this embodiment of the invention also provides a vehicle battery life prediction and early warning system, including: The first capacity calculation module is used to obtain the first battery capacity value based on the ampere-hour integration method. The second capacity calculation module is used to obtain the second battery capacity value obtained by relating the battery internal resistance and battery temperature. The third capacity calculation module is used to obtain the third battery capacity value obtained from the associated battery voltage. A battery capacity adjustment calculation module, communicatively connected to the first capacity calculation module, the second capacity calculation module, and the third capacity calculation module, is used to adjust the first battery capacity value, the second battery capacity value, and the third battery capacity value respectively, and to obtain the current maximum usable battery capacity based on the adjusted first battery capacity value, second battery capacity value, and third battery capacity value; and, The early warning module is communicatively connected to the battery capacity adjustment calculation module and is used to provide early warning of battery life based on the current maximum usable capacity of the battery.

[0057] In summary, the main innovations of this invention are as follows: 1. This invention overcomes the limitations of single-method battery capacity characterization by integrating three independent dimensions: the ampere-hour integration method, the internal resistance-temperature correlation method, and the voltage correlation method. These methods are susceptible to operating condition interference (such as the cumulative error of the ampere-hour integration method and the environmental sensitivity of single-parameter methods). The adjusted and integrated maximum usable capacity of the battery provides a more comprehensive picture of its actual health, significantly improving the accuracy of capacity prediction and providing a reliable basis for subsequent life assessment.

[0058] 2. This invention not only provides real-time early warning based on the current capacity, but also calculates the target SOH value for a future target period based on the current SOH value, and combines the SOH threshold to determine the future lifespan trend. This dual-layer early warning mechanism of current status monitoring + future trend prediction can identify potential accelerated aging risks of batteries in advance, avoiding vehicle breakdowns or safety accidents caused by a sudden drop in capacity.

[0059] 3. By adjusting the three original capacity values, the validity of the input data is ensured; the warning logic is dynamically adjusted based on the actual vehicle usage scenarios, making the warning results more consistent with the actual aging process of the battery and reducing false alarms and missed alarms. Users can take timely maintenance measures based on the warning information to extend battery life and reduce maintenance costs.

[0060] 4. Traditional methods often rely on single-parameter threshold alarms, which are reactive measures. This invention quantifies the maximum usable capacity of the battery by fusing multi-source data and predicts future states based on SOH trends, thus achieving a quantitative assessment of battery life.

[0061] 5. The internal resistance-temperature correlation method can compensate for the impact of temperature changes on battery performance, while the voltage correlation method can help correct the cumulative error of the ampere-hour integration method. The three methods are highly complementary. Even under complex operating conditions (such as frequent start-stop and extreme temperatures), it can still output reliable capacity assessment results stably, improving the universality of the method in different vehicle models and usage environments.

[0062] In summary, this invention solves the problems of insufficient accuracy, delayed warning, and poor environmental adaptability in traditional battery life prediction by multi-dimensional data fusion, current-future state collaborative early warning, and dynamic parameter adjustment, providing key technical support for the safe operation and efficient maintenance of vehicle batteries.

[0063] Specifically, this embodiment corresponds one-to-one with the above method embodiments. The functions of each module have been described in detail in the corresponding method embodiments, so they will not be repeated here.

[0064] Based on the same inventive concept, embodiments of this application also provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements all or part of the method steps of the above method.

[0065] The present invention can implement all or part of the processes in the above methods, or it can be accomplished by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content contained in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0066] Based on the same inventive concept, embodiments of this application also provide an electronic device, including a memory and a processor. The memory stores a computer program that runs on the processor. When the processor executes the computer program, it implements all or part of the method steps described above.

[0067] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the computer device, connecting all parts of the computer device through various interfaces and lines.

[0068] Memory can be used to store computer programs and / or modules. The processor performs various functions of the computer device by running or executing the computer programs and / or modules stored in the memory, and by accessing data stored in the memory. Memory can primarily include a program storage area and a data storage area. The program storage area can store the operating system and application programs required for at least one function (e.g., sound playback, image playback, etc.); the data storage area can store data created based on mobile usage (e.g., audio data, video data, etc.). Furthermore, memory can include high-speed random access memory, and can also include non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital cards (SD cards), flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0069] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, servers, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0070] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), servers, and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0071] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0072] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0073] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for predicting and warning the lifespan of a vehicle battery, characterized in that, include: Obtain the first battery capacity value based on the ampere-hour integration method; The second battery capacity value is obtained by relating the battery internal resistance to the battery temperature. Obtain the third battery capacity value from the associated battery voltage; The first battery capacity value, the second battery capacity value, and the third battery capacity value are adjusted respectively, and the current maximum usable capacity of the battery is obtained based on the adjusted first battery capacity value, second battery capacity value, and third battery capacity value. Battery life warning is given based on the current maximum available capacity of the battery.

2. The vehicle battery life prediction and early warning method as described in claim 1, characterized in that, The method for obtaining the first battery capacity value based on the ampere-hour integration method is shown in the following formula: ； In the formula, C ah t is the first battery capacity value; I(t) is the instantaneous current; SOC1 is the SOC value obtained by measuring the open-circuit voltage after the vehicle has been stationary for the first time; SOC2 is the SOC value obtained by measuring the open-circuit voltage after the vehicle has been stationary for the second time.

3. The vehicle battery life prediction and early warning method as described in claim 1, characterized in that, The method for obtaining the second battery capacity value by relating the battery internal resistance to the battery temperature is shown in the following formula: ； In the formula, C r This is the second battery capacity value; C rated R0 is the battery's rated capacity; R0 is the battery's initial internal resistance; R is the battery's current internal resistance; k is the battery's empirical degradation coefficient; λ is the temperature influence coefficient; α and β are weighting coefficients; ΔT is the difference between the current ambient temperature and the standard temperature.

4. The vehicle battery life prediction and early warning method as described in claim 1, characterized in that, The method for obtaining the third battery capacity value by acquiring the associated battery voltage is shown in the following formula: ； In the formula, C v This is the third battery capacity value; C rated γ is the rated capacity of the battery; γ is the curvature factor; V m V is the current terminal voltage of the battery. full This is the virtual full-charge voltage; V cutoff This is the operating condition cutoff voltage.

5. The vehicle battery life prediction and early warning method as described in claim 1, characterized in that, The adjustment of the first battery capacity value, the second battery capacity value, and the third battery capacity value respectively includes: Obtain the battery capacity value corresponding to each day from the current time period to the previous n days, and calculate the average value of the first battery capacity value and all battery capacity values ​​to obtain the adjusted first battery capacity value. Obtain the battery capacity value corresponding to each day from the current time period to the previous n days, and calculate the average value of the second battery capacity value and all battery capacity values ​​to obtain the adjusted second battery capacity value. Obtain the battery capacity value corresponding to each day from the current time period to the previous n days, and calculate the average value of the third battery capacity value with all battery capacity values ​​to obtain the adjusted third battery capacity value.

6. The vehicle battery life prediction and early warning method as described in claim 1, characterized in that, The method for obtaining the current maximum usable capacity of the battery based on the adjusted first battery capacity value, second battery capacity value, and third battery capacity value is shown in the following formula: ； In the formula, C current This represents the battery's current maximum usable capacity; w1, w2, and w3 are weighting coefficients. This is the adjusted first battery capacity value; This is the adjusted second battery capacity value; This is the adjusted third battery capacity value.

7. The vehicle battery life prediction and early warning method as described in claim 1, characterized in that, The battery life warning based on the current maximum usable capacity of the battery includes: Calculate the current SOH value of the battery based on the current maximum usable capacity and the battery's rated capacity; When the current SOH value of the battery is detected to exceed the SOH threshold, an early warning is issued regarding the current battery life.

8. The vehicle battery life prediction and early warning method as described in claim 7, characterized in that, After issuing a battery life warning based on the current maximum usable capacity of the battery, the following steps are included: Calculate the target SOH value of the battery for the future target period based on the current SOH value of the battery; When the target SOH value of the battery is detected to exceed the SOH threshold, an early warning is issued for the battery life in the future target period.

9. The vehicle battery life prediction and early warning method as described in claim 8, characterized in that, The method for calculating the target SOH value of the battery for a future target period based on the current SOH value of the battery is shown in the following formula: ； In the formula, SOH future The target SOH value for the battery in the future target period; SOH now This represents the current SOH value of the battery; d SOH / d Cycle The SOH value corresponding to the average full-cycle decay value; d SOH / d Time ΔTime is the static sulfur decay rate; ΔTime is the difference between the current time and the future target time period; ΔCycle is the equivalent number of cycles for the future target time period.

10. A vehicle battery life prediction and early warning system, characterized in that, include: The first capacity calculation module is used to obtain the first battery capacity value based on the ampere-hour integration method. The second capacity calculation module is used to obtain the second battery capacity value obtained by relating the battery internal resistance and battery temperature. The third capacity calculation module is used to obtain the third battery capacity value obtained from the associated battery voltage. A battery capacity adjustment calculation module is communicatively connected to the first capacity calculation module, the second capacity calculation module, and the third capacity calculation module. It is used to adjust the first battery capacity value, the second battery capacity value, and the third battery capacity value respectively, and to obtain the current maximum usable capacity of the battery based on the adjusted first battery capacity value, second battery capacity value, and third battery capacity value. as well as, The early warning module is communicatively connected to the battery capacity adjustment calculation module and is used to provide early warning of battery life based on the current maximum usable capacity of the battery.

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