Method for detecting life of power battery, computer readable storage medium and vehicle

Abstract

The application discloses a kind of life detection methods of power battery, computer readable storage medium and vehicle.Therein, the method involves field, and the method includes: obtaining the target signal parameter of power battery and preset decision parameter, wherein, target signal parameter is the signal parameter of power battery in the process of using power battery by vehicle, and preset decision parameter is used to indicate the use habit of target object using power battery;Based on target signal parameter, determine the safety score value of power battery, energy score value, power score value, wherein, energy score value is used to indicate the value obtained by scoring the capacity of power battery, and power score value is used to indicate the value obtained by scoring the peak power of power battery;Based on preset decision parameter, safety score value, energy score value, power score value are processed, and the life detection result of power battery is obtained.The application solves the technical problem that the user acceptance of battery life detection result is relatively low.

Description

Technical Field

[0001] This invention relates to the field of power battery testing, and more specifically, to a method for testing the lifespan of a power battery, a computer-readable storage medium, and a vehicle. Background Technology

[0002] Currently, new energy vehicles are an important measure to achieve high-quality development in the automotive industry. As a key component of new energy vehicles, the reliability and long lifespan of power batteries are one of the bottlenecks in their promotion and application. However, traditional methods for evaluating power battery lifespan quantitatively assess battery degradation based on changes in battery capacity, internal resistance, or a combination of both. This approach is not well understood by users, resulting in low user acceptance of battery life test results.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This invention provides a method for testing the lifespan of a power battery, a computer-readable storage medium, and a vehicle, to at least address the technical problem of low user acceptance of battery lifespan test results.

[0005] According to one aspect of the present invention, a method for detecting the lifespan of a power battery is provided, comprising: acquiring target signal parameters and preset decision parameters of the power battery, wherein the target signal parameters are signal parameters of the power battery during vehicle use, and the preset decision parameters are used to represent the usage habits of the target object when using the power battery; determining a safety score, an energy score, and a power score of the power battery based on the target signal parameters, wherein the energy score represents a value obtained by scoring the capacity of the power battery, and the power score represents a value obtained by scoring the peak power of the power battery; and processing the safety score, energy score, and power score based on the preset decision parameters to obtain a lifespan detection result of the power battery.

[0006] Optionally, the safety score, energy score, and power score are processed based on preset decision parameters to obtain the life evaluation result of the power battery. This includes: adjusting the weight ratio of the first initial weight of the energy score and the second initial weight of the power score based on the preset decision parameters to obtain the first target weight of the energy score and the second target weight of the power score; determining the first product of the first target weight and the energy score; determining the second product of the second target weight and the power score; and determining the product of the third target weight and the target sum to obtain the life evaluation result. The target sum is the sum of the first product and the second product, and the third target weight is determined based on the safety score.

[0007] Optionally, the method further includes: determining a third target weight as a first preset weight in response to a security score value being greater than or equal to a preset security threshold; and determining a third target weight as a second preset weight in response to a security score value being less than the preset security threshold.

[0008] Optionally, the safety score, energy score, and power score of the power battery are determined based on the target signal parameters, including: determining the power battery's historical fault handling information, risk warning information, power battery capacity, and peak power based on the target signal parameters; detecting the power battery's safety based on the historical fault handling information and risk warning information to obtain the power battery's safety score; detecting the power battery's energy based on its capacity to obtain the power battery's energy score; and detecting the power battery's power based on its peak power to obtain the power battery's power score.

[0009] Optionally, the safety of the power battery is tested based on historical fault handling information and risk warning information to obtain a safety score for the power battery. This includes: determining the fault modes of the power battery that occurred within a preset time period based on historical fault handling information, as well as the corresponding fault repair degree and fault impact degree. The fault repair degree is used to represent the complexity of repairing the faulty power battery, and the fault impact degree is used to represent the impact on the power battery when it fails. The residual risk information of the power battery is determined based on the fault repair degree and fault impact degree. The safety score of the power battery is determined based on the residual risk information and risk warning information.

[0010] Optionally, the safety score of the power battery is determined based on residual risk information and risk warning information, including: assigning weights to the residual risk information and risk warning information based on the number of fault handling operations of the power battery to obtain a fourth target weight for the residual risk information and a fifth target weight for the risk warning information; determining the product of the fourth target weight and the residual risk information to obtain the residual risk value; determining the product of the fifth target weight and the risk warning information to obtain the risk warning value; and obtaining the safety score based on the first preset value, the residual risk value, and the risk warning value.

[0011] Optionally, determining the power battery capacity based on target signal parameters includes: determining the first charge and the second charge of the power battery during a charging cycle based on the target signal parameters, wherein the first charge is the charge of the power battery at the start of charging during the charging cycle, and the second charge is the charge of the power battery at the end of charging during the charging cycle; and determining the power battery capacity based on the ratio of a target difference to a preset difference, wherein the target difference is the difference between the first charge and the second charge.

[0012] Optionally, obtaining the target signal parameters of the power battery includes: obtaining the initial signal parameters of the power battery and the signal type of the initial signal parameters; filtering the initial signal parameters based on the preset filtering conditions corresponding to the signal type to obtain the target signal parameters.

[0013] Optionally, the initial signal parameters are filtered based on preset filtering conditions corresponding to the signal type to obtain target signal parameters, including: filtering the initial signal parameters based on preset filtering conditions corresponding to the signal type to obtain filtered signal parameters; removing the first signal parameter and / or the second signal parameter from the filtered signal parameters to obtain target signal parameters, wherein the first signal parameter is used to represent the parameter with missing values ​​in the filtered signal parameters, and the second signal parameter is used to represent the parameter in the filtered signal parameters that does not conform to preset logic.

[0014] Optionally, the energy of the power battery is detected based on the power battery capacity to obtain the energy score value of the power battery, including: determining the energy score value based on the ratio of the power battery capacity to the preset battery capacity.

[0015] Optionally, the power of the power battery is tested based on the peak power of the power battery to obtain a power score value of the power battery, including: determining the power score value based on the ratio of the peak power of the power battery to the preset peak power of the battery.

[0016] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the execution of the power battery life detection method of the above embodiment in the processor of the device.

[0017] According to another aspect of the present invention, a vehicle is also provided, comprising: one or more processors; a storage device for storing one or more programs; and, when the one or more programs are executed by the one or more processors, causing the one or more processors to perform the power battery life detection method of the above embodiments.

[0018] In this embodiment of the invention, target signal parameters and preset decision parameters of the power battery are acquired; based on the target signal parameters, the safety score, energy score, and power score of the power battery are determined; based on the preset decision parameters, the safety score, energy score, and power score are processed to obtain the power battery life test result. It is important to note that by using user perception as a preset decision parameter and processing the safety score, energy score, and power score, the obtained power battery life test result takes into account both user perception and the scores of the power battery's safety, energy performance, and power performance dimensions. This achieves the goal of improving the user acceptance of the battery life test result, thereby filling the technical gap in battery life evaluation technology based on user perception, and ultimately solving the technical problem of low user acceptance of battery life test results. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0020] Figure 1 This is a flowchart of a life testing method for a power battery according to an embodiment of the present invention;

[0021] Figure 2 This is a schematic diagram of an optional user-perceived battery life evaluation system according to an embodiment of the present invention;

[0022] Figure 3 This is a flowchart of an optional power battery life detection method according to an embodiment of the present invention;

[0023] Figure 4 This is a schematic diagram of a power battery life testing device according to an embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] Example 1

[0027] According to an embodiment of the present invention, an embodiment of a life detection method for a power battery 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.

[0028] Figure 1 This is a flowchart of a power battery life testing method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0029] Step S102: Obtain the target signal parameters and preset decision parameters of the power battery. The target signal parameters are the signal parameters of the power battery during the vehicle's use of the power battery, and the preset decision parameters are used to represent the target object's usage habits of the power battery.

[0030] The aforementioned power batteries can be rechargeable batteries used to drive electric vehicles, typically composed of multiple lithium-ion or nickel-metal hydride chemical elements. They feature high energy density, long lifespan, and rapid charge / discharge characteristics, providing a long-lasting and stable energy source for automobiles, and are relatively environmentally friendly.

[0031] The target signal parameters mentioned above can be signal parameters generated and cleaned during the use of the power battery, or power battery signal parameters after invalid signal parameters have been removed, including but not limited to: the position, time, voltage, current and temperature of the power battery during use.

[0032] The aforementioned preset decision parameters can be decision parameters set in advance based on the specific usage conditions of the power battery, or decision parameters set based on the power battery usage habits of the target audience. The target audience can be the driver of the vehicle.

[0033] In one optional embodiment, real-time signal parameters such as location, time, voltage, current, and temperature of the vehicle-mounted power battery during its use are collected. These real-time collected power battery signal parameters are cleaned, removing those exceeding threshold ranges. Furthermore, invalid data is filtered out based on the completeness of each frame of data. For example, if one or more cell voltage data values ​​are missing, it is considered invalid and the frame is discarded. Invalid data is further filtered out based on the logical consistency of each frame's acquisition. For instance, if the current value is valid and the battery's state of charge (SOC) changes, but the cell voltage value remains unchanged, the cell voltage data in that frame is considered potentially unreliable due to sampling anomalies or data delays, and is also discarded. This process obtains accurate, valid, complete, and logically consistent signal parameters. Preset decision parameters are then obtained using the periodic power battery signal parameters.

[0034] Step S104: Determine the safety score, energy score, and power score of the power battery based on the target signal parameters. The energy score represents the value obtained by scoring the capacity of the power battery, and the power score represents the value obtained by scoring the peak power of the power battery.

[0035] The aforementioned safety rating can be a numerical value used to assess the safety of a power battery. Based on the rating, the safety of the power battery can be accurately and clearly understood. The rating can be from small to large to indicate either weak to strong or strong to weak safety.

[0036] The energy rating mentioned above is a numerical score that assesses the capacity of a power battery, and can be based on the size of the battery capacity. It reflects the performance and efficiency of the power battery. A higher energy rating generally means a longer driving range and better performance.

[0037] The aforementioned power rating is a numerical score given for the peak power of the power battery. Peak power is the maximum power the battery can output, usually measured in kilowatts (kW). It varies between different models and brands of power batteries, depending on factors such as battery design, materials, and size. Generally, the higher the peak power of the power battery, the better its performance will be when the vehicle needs acceleration, hill climbing, and other similar tasks.

[0038] In one optional embodiment, all fault modes of the battery are obtained based on the target signal parameters. These fault modes can be power battery fault modes, including but not limited to: on-board battery management system faults and cloud-based battery management system faults. The fault modes are categorized according to whether they have been processed, and the processing status of each fault mode is analyzed. A safety score is determined based on the power battery's fault processing status and the current safety risk situation. Specific segments of data from the battery charging and discharging process are selected to calculate the battery capacity, thereby obtaining an energy score. The target signal parameters are constrained based on factors such as the power battery's voltage, SOC, temperature, and lifespan to obtain the current peak power of the power battery, further calculating the power battery's power evaluation value.

[0039] In one optional embodiment, the fault mode of the power battery, historical fault handling information, risk warning information, power battery capacity, and peak power of the power battery are determined based on target signal parameters. The fault modes of the power battery are analyzed to determine the complexity and status of fault handling, and residual risk information and risk warning information of the power battery are analyzed. The residual risk information can be related to the degree of fault repair and the severity of the fault, determined after the power battery fault has been repaired. The risk warning information can be related to identifying potential risks of the power battery, with experts determining the current risk of the battery based on the severity of the fault through a scoring method. A safety score is determined based on the residual risk information and risk warning information, thereby determining whether the power battery can handle faults in a timely manner and whether there are any safety hazards. Target signal parameters are filtered to determine the changes in power battery data during the charging process. The capacity of the power battery is determined based on the changes in power battery data before and after charging, thereby determining the energy score of the power battery. Data on different battery monitoring conditions (SOH, State of Health), SOC, temperature, etc., are obtained from the database to determine the equivalent circuit model parameter library. After obtaining the model parameters of the power battery under the current state, the equivalent circuit model parameters of the power battery under the current state are determined according to the equivalent circuit model parameter library, thereby obtaining the peak power of the current power battery and determining the power performance score of the power battery.

[0040] Step S106: Based on preset decision parameters, the safety score, energy score, and power score are processed to obtain the life test results of the power battery.

[0041] The above-mentioned life test results can be the test results corresponding to the life test of the power battery.

[0042] In one optional embodiment, a safety score is used as a prerequisite, and weighted matching is performed based on the energy score and power score of the power battery. First, the discharge segments of the power battery are classified according to the user's driving conditions and habits to determine the weight ratio of the energy dimension and the power dimension. Then, the energy score is adjusted using the weight of the energy dimension, the power score is adjusted using the weight of the power dimension, and the battery life test result is obtained by combining the safety score.

[0043] Through the above steps, the target signal parameters and preset decision parameters of the power battery can be obtained; the safety score, energy score, and power score of the power battery can be determined based on the target signal parameters; and the safety score, energy score, and power score can be processed based on the preset decision parameters to obtain the power battery life test results. It is important to note that by using user perception as a preset decision parameter and processing the safety score, energy score, and power score, the resulting power battery life test results take into account both user perception and the scores for the power battery's safety, energy performance, and power performance dimensions. This improves the user acceptance of the battery life test results, thus filling the technical gap in battery life evaluation technology based on user perception, and ultimately solving the technical problem of low user acceptance of battery life test results.

[0044] It should be noted that, Figure 2 This is a schematic diagram of an optional user-perceived battery life evaluation system according to an embodiment of the present invention, such as... Figure 2 As shown, the system includes a cloud computing system, a vehicle-to-cloud communication system, and a vehicle-side execution system. The vehicle-side execution system further includes: a data acquisition module for real-time data collection of the vehicle's power battery's location, time, voltage, current, and temperature during driving; and a notification module for receiving and displaying battery life evaluation results. The cloud computing system includes: a data cleaning module for removing data exceeding thresholds or exhibiting illogical changes; a user perception dimension quantification evaluation module for determining scores across three user perception dimensions; an influence weight calculation module for calculating the weight coefficients of the three user perception dimensions; and a battery life evaluation module for calculating the final battery life evaluation result. The vehicle-to-cloud communication system also includes: a data upload module for uploading collected signals to the cloud-based big data platform according to specific encoding rules; and a notification delivery module for sending battery life evaluation results to the user.

[0045] This invention considers three user-perceived dimensions: safety, energy, and power. With safety evaluation as a premise, user habits are used as decision factors, and the influence weights of energy and power are matched to construct a comprehensive battery life evaluation system that takes into account both safety and user habits, filling the technical gap in battery life evaluation based on user perception dimensions.

[0046] Optionally, the safety score, energy score, and power score are processed based on preset decision parameters to obtain the life evaluation result of the power battery. This includes: adjusting the weight ratio of the first initial weight of the energy score and the second initial weight of the power score based on the preset decision parameters to obtain the first target weight of the energy score and the second target weight of the power score; determining the first product of the first target weight and the energy score; determining the second product of the second target weight and the power score; and determining the product of the third target weight and the target sum to obtain the life evaluation result. The target sum is the sum of the first product and the second product, and the third target weight is determined based on the safety score.

[0047] The aforementioned first initial weight can be the initial evaluation weight of the power battery's energy dimension, or it can be the evaluation weight of the power battery's energy dimension before it is used by the user.

[0048] The aforementioned second initial weight can be the initial evaluation weight of the power battery's power performance dimension, or it can be the evaluation weight of the power battery's power performance dimension before user use.

[0049] The aforementioned first target weight can be an adjusted weight based on the initial weight, or it can be determined by identifying user driving habits through battery history, labeling all battery discharge segments according to mileage and power preferences, and statistically analyzing the proportion of the two types of discharge segments to determine the weight proportion of the energy dimension. This can be expressed as η. e express.

[0050] The aforementioned second target weight can be an adjusted weight based on the second initial weight, or it can be determined by identifying user driving habits through battery history, labeling all battery discharge segments according to mileage and power preferences, and statistically analyzing the proportion of the two types of discharge segments to determine the weight proportion of the power dimension. This can be expressed as η. p express.

[0051] The first product mentioned above can be the product of the first objective weight and the energy score value. This can be represented by η. e score energy express.

[0052] The second product mentioned above can be the product of the second objective weight and the dynamic score, which can be represented by η. p score power express.

[0053] The aforementioned third objective weight can be an evaluation weight for the safety dimension of the power battery, which can be represented by η. s express.

[0054] In one optional embodiment, the user's driving habits are determined by identifying historical battery usage based on preset decision parameters. All battery discharge segments are then tagged with habitual preferences based on mileage and power preferences. The weighting of the energy and power dimensions is determined by statistically analyzing the proportions of the two types of discharge segments. This allows for the adjustment of the weighting of the first initial weight of the energy score and the second initial weight of the power score, resulting in the first target weight η for the energy score. e The second objective weight η of the dynamic score p The third objective weight for the safety dimension is determined based on the safety score. Battery life is then evaluated from three aspects: safety, power, and energy. The life evaluation result is calculated based on the energy score, power score, first objective weight, second objective weight, and third objective weight, using the following formula:

[0055] f(x) = η s ·[η e score energy +η p score power ]

[0056] It should be noted that the sum of the weights of the first objective and the second objective is 1, denoted as η. e +η p =1, where η e ∈(0,1).

[0057] Optionally, the method further includes: determining a third target weight as a first preset weight in response to a security score value being greater than or equal to a preset security threshold; and determining a third target weight as a second preset weight in response to a security score value being less than the preset security threshold.

[0058] The aforementioned preset security threshold can be a security scoring threshold set in advance according to specific circumstances, and can be represented by TBD.

[0059] The aforementioned first preset weight can be a security evaluation weight threshold set in advance according to specific circumstances, used to indicate the situation where the security score threshold is greater than or equal to the preset security threshold, and can be, but is not limited to: 1.

[0060] The aforementioned second preset weight can be a preset security evaluation weight threshold set according to specific circumstances, used to indicate the situation where the security score threshold is less than the preset security threshold, and can be, but is not limited to, 0.

[0061] In one optional embodiment, the third objective weight of the security dimension is determined based on the security score. The evaluation weight of the security dimension is either 1 or 0. The security score threshold when the security dimension weight is 0 can be set to 60 points. The third objective weight is obtained according to the following formula:

[0062]

[0063] Optionally, the safety score, energy score, and power score of the power battery are determined based on the target signal parameters, including: determining the power battery's historical fault handling information, risk warning information, power battery capacity, and peak power based on the target signal parameters; detecting the power battery's safety based on the historical fault handling information and risk warning information to obtain the power battery's safety score; detecting the power battery's energy based on its capacity to obtain the power battery's energy score; and detecting the power battery's power based on its peak power to obtain the power battery's power score.

[0064] The aforementioned historical fault handling information can be related to the historical handling of faults in the power battery, including but not limited to: information corresponding to the fault occurrence, the severity of the fault, the fault handling method, and the degree of fault repair.

[0065] The aforementioned power battery capacity can be the current capacity of the power battery, which can be expressed as Q. est_result express.

[0066] In one optional embodiment, historical fault handling information of the power battery is identified based on the target signal parameters, and potential risks of the power battery are identified based on the historical fault handling information. Risk warning information is determined by experts scoring the risks based on the degree of harm. The historical fault handling information and risk warning information are weighted and adjusted to determine the safety score of the power battery.

[0067] Filter out specific segments of data during the battery charging and discharging process. These characteristic segments can be defined as those where the state of charge (SOC) increases by at least 60%, using the formula:

[0068] Q est =ΔQ / ΔSOC

[0069] The battery capacity is calculated, and the density clustering (DBSCAN) algorithm is used to perform cluster analysis on the battery capacity calculation results within the mileage window to identify inflection points of change. The stable output after the inflection point is used to correct the battery capacity calculation results, and the power battery capacity Q is obtained. est_result Therefore, an energy rating system is calculated using the rated capacity and capacity of the power battery. The specific formula is as follows:

[0070]

[0071] Among them, Q est_result Q0 represents the current capacity of the power battery, while Q0 represents the rated capacity.

[0072] The battery equivalent circuit model parameters are identified using the forgetting factor least squares method, resulting in a parameter library for the equivalent circuit model under different SOH, SOC, and temperatures. Online identification methods, such as the dual extended Kalman filter algorithm, are used to calculate the model parameters for the battery in its current state. Using the equivalent circuit model parameter library as boundary conditions, the battery's equivalent circuit model parameters are optimized. With voltage, SOC, temperature, and lifespan as constraints, the current peak power P of the power battery is obtained. est_result The power battery power score is calculated using the peak power of the power battery. The specific formula is as follows:

[0073]

[0074] Among them, P est_result P0 is the currently estimated peak power of the power battery, while P0 is the initial peak power value under the same SOC, temperature, and other conditions.

[0075] Optionally, the safety of the power battery is tested based on historical fault handling information and risk warning information to obtain a safety score for the power battery. This includes: determining the fault modes of the power battery that occurred within a preset time period based on historical fault handling information, as well as the corresponding fault repair degree and fault impact degree. The fault repair degree is used to represent the complexity of repairing the faulty power battery, and the fault impact degree is used to represent the impact on the power battery when it fails. The residual risk information of the power battery is determined based on the fault repair degree and fault impact degree. The safety score of the power battery is determined based on the residual risk information and risk warning information.

[0076] The aforementioned preset time period can be a time period set in advance according to specific circumstances, and can be, but is not limited to, 1 month, 6 months, or 12 months.

[0077] The aforementioned degree of fault repair can refer to the degree of repair performed on the battery fault, and can include, but is not limited to: no repair, partial repair, and complete repair.

[0078] The aforementioned degree of fault impact can be categorized as the magnitude of the fault's effect on the battery, and can be, but is not limited to, a significant impact, a minor impact, or a negligible impact.

[0079] In one optional embodiment, all failure modes of the power battery that occurred within a preset time period are determined based on historical fault handling information. These failure modes are categorized into two groups based on whether they have been addressed. For addressed faults, the degree of impact is determined based on fault occurrence information (e.g., the battery's cumulative throughput, temperature, temperature difference, SOC, duration, etc.). The degree of fault repair is determined based on the handling method (partial repair, global repair, component replacement, etc.). Thus, residual risk information of the power battery is determined based on the degree of fault repair and the degree of fault impact. Potential risks identified can be used to determine battery risk warning information through expert scoring. An analytic hierarchy process (AHP) can be used to assign weight coefficients to residual risk information and risk warning information respectively to determine the power battery's safety score.

[0080] Optionally, the safety score of the power battery is determined based on residual risk information and risk warning information, including: assigning weights to the residual risk information and risk warning information based on the number of fault handling operations of the power battery to obtain a fourth target weight for the residual risk information and a fifth target weight for the risk warning information; determining the product of the fourth target weight and the residual risk information to obtain the residual risk value; determining the product of the fifth target weight and the risk warning information to obtain the risk warning value; and obtaining the safety score based on the first preset value, the residual risk value, and the risk warning value.

[0081] The fourth objective weight mentioned above can be the weight of residual risk information, which can be represented by ρ. i express.

[0082] The fifth objective weight mentioned above can be the weight of risk warning information, which can be represented by μ. j express.

[0083] The aforementioned residual risk value can be a numerical value used to assess the residual risk of the power battery, and can be used as... express.

[0084] The aforementioned risk warning value can be a numerical value used to assess the risk warning of power batteries, and can be used... express.

[0085] The first preset value mentioned above can be a threshold set in advance according to specific circumstances, used to calculate the safety score value of the power battery, and can be, but is not limited to, 100.

[0086] In one optional embodiment, residual risk information and risk warning information are weighted according to the number of times the power battery has been handled, and a fourth target weight ρ for residual risk information is determined. i The fifth objective weight μ of risk warning information jThe safety score is calculated using the weights of the fourth and fifth objectives, the residual risk value, the risk warning value, and the first preset value. The specific formula is as follows:

[0087]

[0088] Among them, fault i ρ represents the residual risk score of the i-th historical failure handling. i Indicates fault i The impact weighting coefficient, n represents the total number of historically processed faults, warning j μ represents the score of the j-th potential risk currently identified, m represents the total number of risks currently identified, and μ j Indicates warning j The influence weighting coefficient.

[0089] Optionally, determining the power battery capacity based on target signal parameters includes: determining the first charge and the second charge of the power battery during a charging cycle based on the target signal parameters, wherein the first charge is the charge of the power battery at the start of charging during the charging cycle, and the second charge is the charge of the power battery at the end of charging during the charging cycle; and determining the power battery capacity based on the ratio of a target difference to a preset difference, wherein the target difference is the difference between the first charge and the second charge.

[0090] The charging cycle mentioned above can be the charging cycle of the power battery, which can be, but is not limited to: 1 week, 3 days, or 2 days.

[0091] The aforementioned first charge quantity can be the charge quantity of the power battery before charging.

[0092] The aforementioned second charge quantity can be the charge quantity of the power battery at the end of charging.

[0093] The target difference mentioned above can be the difference between the first charge and the second charge.

[0094] The aforementioned preset difference can be the difference in charge before and after charging of the power battery, which can be set in advance according to specific circumstances.

[0095] In one optional embodiment, the first charge amount at the start of charging and the second charge amount at the end of charging are determined according to the target signal parameters in the most recent charging cycle of the power battery. The difference between the first charge amount and the second charge amount is calculated as the target difference. The charge amount before and after charging of the power battery under the same conditions is determined as the preset difference based on the data of the power battery simulation experiment. The ratio of the target difference to the preset difference is calculated as the power battery capacity.

[0096] In another optional embodiment, the first charge and the second charge before and after charging in multiple charging cycles of the power battery are determined according to the target signal parameters, multiple target differences are calculated, and the average value of the multiple target differences is the power battery capacity.

[0097] Optionally, obtaining the target signal parameters of the power battery includes: obtaining the initial signal parameters of the power battery and the signal type of the initial signal parameters; filtering the initial signal parameters based on the preset filtering conditions corresponding to the signal type to obtain the target signal parameters.

[0098] The aforementioned initial signal parameters can be real-time acquired power battery signal parameters or unprocessed power battery signal parameters, including but not limited to: power battery position, battery voltage, current, temperature, and capacity.

[0099] The above-mentioned signal types can be broad categories of power battery signals, including but not limited to: cell voltage, default voltage output, battery module temperature, current value, SOC value, and vehicle mileage.

[0100] The aforementioned preset filtering conditions can be conditions for setting the filtering signal parameters in advance according to specific circumstances, or rules for judging the accuracy of power battery signal parameters in advance, removing data that exceeds a reasonable range, including but not limited to cell voltage, voltage default value, battery module temperature, current value, SOC value, and vehicle mileage.

[0101] In one optional embodiment, data such as location, time, voltage, current, and temperature of the on-board power battery during its use are collected in real time and uploaded to a cloud-based big data platform. The uploaded dynamic data undergoes data cleaning. Initial signal parameters from the real-time train arrival are classified to determine the corresponding signal type. Based on preset filtering conditions corresponding to the signal type, the initial signal parameters are filtered to remove variable values ​​exceeding a reasonable range. Furthermore, based on the completeness and logic of the power battery's signal parameters for each frame, invalid data is further extracted to obtain the target signal parameters.

[0102] Optionally, the initial signal parameters are filtered based on preset filtering conditions corresponding to the signal type to obtain target signal parameters, including: filtering the initial signal parameters based on preset filtering conditions corresponding to the signal type to obtain filtered signal parameters; removing the first signal parameter and / or the second signal parameter from the filtered signal parameters to obtain target signal parameters, wherein the first signal parameter is used to represent the parameter with missing values ​​in the filtered signal parameters, and the second signal parameter is used to represent the parameter in the filtered signal parameters that does not conform to preset logic.

[0103] The aforementioned filtered signal parameters can be signal parameters after filtering the initial signal parameters, or signal parameters that meet preset filtering conditions.

[0104] The first signal parameter mentioned above can be data where the filter signal parameters have missing values, and the first signal parameter ensures the integrity of each frame of data. The second signal parameter mentioned above can be data that does not conform to the data change logic, and the second signal parameter judges the logic of each frame of data.

[0105] The target signal parameters mentioned above can be signal parameters that meet preset filtering conditions and have completeness and logic.

[0106] The aforementioned preset logic can be a logical relationship that is pre-set based on the changes in the power battery signal parameters.

[0107] In one optional embodiment, the initial signal parameters are filtered according to preset filtering conditions to obtain filtered signal parameters. The preset filtering conditions are shown in Table 1 below.

[0108] Table 1 shows the rules for judging signal accuracy.

[0109] Cell voltage [0,5V], values ​​outside this range will be filtered out. Voltage default value exclusion All individual unit voltages are set to 0 or default values; this invention uses 3.65V as an example. Battery module temperature [-40℃, 210℃], filters out temperatures outside this range. Current value [-1500A, 1500A], filters out values ​​outside this range. SOC value [0, 100%], filtering out values ​​outside the range. Vehicle mileage [0,1000000km], filtering out values ​​outside this range.

[0110] Signal parameters that do not meet the preset filtering conditions are deleted to obtain filtered signal parameters. The completeness of the filtered signal parameters is then assessed, and the first signal parameter is deleted. For example, if one or more battery module temperature data values ​​are missing, it is considered invalid data and the frame is discarded. Simultaneously, the logical consistency of the filtered signal parameters is assessed, and the second signal parameter is deleted. For example, if the current value is valid and the SOC (or mileage, etc.) changes, but the cell voltage value does not change, the cell voltage data frame is considered to have sampling abnormalities or data delays leading to unreliable data, and is also marked as invalid data and discarded. The filtered signal parameters, after removing the first and / or second signal parameters, are determined as the target signal parameters.

[0111] Optionally, the energy of the power battery is detected based on the power battery capacity to obtain the energy score value of the power battery, including: determining the energy score value based on the ratio of the power battery capacity to the preset battery capacity.

[0112] The aforementioned preset battery capacity can be a rated capacity value set in advance based on the power battery capacity, which can be represented by Q0.

[0113] In one optional embodiment, the energy score is determined according to a formula based on the power battery capacity and a preset battery capacity, as follows:

[0114]

[0115] Among them, Q est_result Q0 represents the current battery capacity, while Q0 represents the preset battery capacity.

[0116] Optionally, the power of the power battery is tested based on the peak power of the power battery to obtain a power score value of the power battery, including: determining the power score value based on the ratio of the peak power of the power battery to the preset peak power of the battery.

[0117] The aforementioned preset battery peak power can be an initial peak power value determined in advance based on the state of the power battery, wherein it can be an initial peak power value under the same SOC, temperature, and other conditions.

[0118] In one optional embodiment, the power score is calculated based on the peak power of the power battery and the preset peak power of the battery according to a formula, the specific formula of which is as follows:

[0119]

[0120] Among them, P est_result P0 is the current peak power of the power battery, while P0 is the preset peak power of the battery.

[0121] Figure 3 This is a flowchart of an optional power battery life detection method according to an embodiment of the present invention, such as... Figure 3 As shown, the steps of this method are as follows:

[0122] Step S301: Acquisition and cleaning of power battery signal parameters.

[0123] Step S302: Determine the safety score of the power battery.

[0124] Step S303: Determine the energy score value of the power battery.

[0125] Step S304: Determine the power performance score of the power battery.

[0126] Step S305, battery life evaluation.

[0127] Example 2

[0128] According to another aspect of the present invention, a life testing device for a power battery is also provided. This device can perform the life testing method for the power battery of a vehicle in the above embodiments. The specific implementation and preferred application scenarios are the same as those in the above embodiments, and will not be repeated here.

[0129] Figure 4 This is a schematic diagram of a power battery life testing device according to an embodiment of the present invention, as shown below. Figure 4As shown, the device includes the following components: an acquisition module 40, a first determination module 42, and a processing module 44.

[0130] The acquisition module 40 is used to acquire the target signal parameters and preset decision parameters of the power battery. The target signal parameters are the signal parameters of the power battery during the use of the power battery by the vehicle, and the preset decision parameters are used to represent the usage habits of the target object when using the power battery.

[0131] The first determining module 42 is used to determine the safety score, energy score, and power score of the power battery based on the target signal parameters. The energy score is used to represent the value obtained by scoring the capacity of the power battery, and the power score is used to represent the value obtained by scoring the peak power of the power battery.

[0132] The processing module 44 is used to process the safety score, energy score, and power score based on preset decision parameters to obtain the life test results of the power battery.

[0133] Optionally, the processing module includes: a first adjustment unit, configured to adjust the weight ratio of the first initial weight of the energy score value and the second initial weight of the power score value based on preset decision parameters, to obtain the first target weight of the energy score value and the second target weight of the power score value; a first determination unit, configured to determine the first product of the first target weight and the energy score value; a second determination unit, configured to determine the second product of the second target weight and the power score value; and a third determination unit, configured to determine the product of the third target weight and the target sum value, to obtain the life evaluation result, wherein the target sum value is the sum of the first product and the second product, and the third target weight is determined based on the safety score value.

[0134] Optionally, the device further includes: a second determining module, configured to determine a third target weight as a first preset weight in response to a security score value being greater than or equal to a preset security threshold; and a third determining module, configured to determine a third target weight as a second preset weight in response to a security score value being less than a preset security threshold.

[0135] Optionally, the first determining module includes: a fourth determining unit, used to determine the historical fault handling information, risk warning information, power battery capacity, and power battery peak power of the power battery based on the target signal parameters; a first detection unit, used to detect the safety of the power battery based on the historical fault handling information and risk warning information, and obtain a safety score value for the power battery; a second detection unit, used to detect the energy of the power battery based on the power battery capacity, and obtain an energy score value for the power battery; and a third detection unit, used to detect the power of the power battery based on the peak power of the power battery, and obtain a power score value for the power battery.

[0136] Optionally, the first detection unit includes: a fifth determining unit, used to determine, based on historical fault handling information, the fault mode of the power battery within a preset time period and the corresponding fault repair degree and fault impact degree, wherein the fault repair degree is used to represent the complexity of repairing the faulty power battery, and the fault impact degree is used to represent the impact on the power battery when the power battery fails; a sixth determining unit, used to determine the residual risk information of the power battery based on the fault repair degree and fault impact degree; and a seventh determining unit, used to determine the safety score value of the power battery based on the residual risk information and risk warning information.

[0137] Optionally, the seventh determining unit includes: a weight allocation subunit, used to allocate weights to residual risk information and risk warning information based on the number of times the power battery has been handled, to obtain a fourth target weight for residual risk information and a fifth target weight for risk warning information; a first determining subunit, used to determine the product of the fourth target weight and residual risk information to obtain a residual risk value; a second determining subunit, used to determine the product of the fifth target weight and risk warning information to obtain a risk warning value; and an acquisition subunit, used to obtain a safety score value based on a first preset value, the residual risk value, and the risk warning value.

[0138] Optionally, the fourth determining unit includes: a third determining subunit, configured to determine the first charge and the second charge of the power battery during a charging cycle based on target signal parameters, wherein the first charge is the charge of the power battery at the start of charging during the charging cycle, and the second charge is the charge of the power battery at the end of charging during the charging cycle; and a fourth determining subunit, configured to determine the capacity of the power battery according to the ratio of a target difference to a preset difference, wherein the target difference is the difference between the first charge and the second charge.

[0139] Optionally, the acquisition module includes: a first acquisition unit, used to acquire the initial signal parameters of the power battery and the signal type of the initial signal parameters; and a filtering unit, used to filter the initial signal parameters based on preset filtering conditions corresponding to the signal type to obtain the target signal parameters.

[0140] Optionally, the filtering unit includes: a first filtering subunit, used to filter the initial signal parameters based on preset filtering conditions corresponding to the signal type to obtain filtered signal parameters; and a rejection subunit, used to reject the first signal parameter and / or the second signal parameter in the filtered signal parameters to obtain target signal parameters, wherein the first signal parameter is used to represent the parameter in the filtered signal parameters that has missing values, and the second signal parameter is used to represent the parameter in the filtered signal parameters that does not conform to preset logic.

[0141] Optionally, the second detection unit includes: a fifth determining subunit, used to determine an energy score value based on the ratio of the power battery capacity to a preset battery capacity.

[0142] Optionally, the third detection unit includes: a sixth determining subunit, used to determine a power score value based on the ratio of the peak power of the power battery to the preset peak power of the battery.

[0143] Example 3

[0144] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the execution of the power battery life detection method of the above embodiment in the processor of the device.

[0145] Example 4

[0146] According to another aspect of the present invention, a vehicle is also provided, comprising: one or more processors; a storage device for storing one or more programs; and, when the one or more programs are executed by the one or more processors, causing the one or more processors to perform the power battery life detection method of the above embodiments.

[0147] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0148] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0149] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0150] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0151] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0152] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0153] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for testing the lifespan of a power battery, characterized in that, include: The target signal parameters and preset decision parameters of the power battery are obtained. The target signal parameters are the signal parameters of the power battery during the use of the power battery by the vehicle. The preset decision parameters are used to represent the usage habits of the target object when using the power battery. Based on the target signal parameters, the safety score, energy score, and power score of the power battery are determined, wherein the energy score represents the value obtained by scoring the capacity of the power battery, and the power score represents the value obtained by scoring the peak power of the power battery. The safety score, energy score, and power score are processed based on the preset decision parameters to obtain the life test results of the power battery.

2. The life testing method for power batteries according to claim 1, characterized in that, Based on the preset decision parameters, the safety score, energy score, and power score are processed to obtain the life evaluation result of the power battery, including: Based on the preset decision parameters, the weight ratios of the first initial weight of the energy score and the second initial weight of the power score are adjusted to obtain the first target weight of the energy score and the second target weight of the power score. Determine the first product of the first target weight and the energy score value; Determine the second product of the second target weight and the dynamic score value; The product of the third objective weight and the objective sum is determined to the lifetime assessment result, wherein the objective sum is the sum of the first product and the second product, and the third objective weight is determined based on the safety score value.

3. The life testing method for power batteries according to claim 1, characterized in that, The safety score, energy score, and power score of the power battery are determined based on the target signal parameters, including: Based on the target signal parameters, determine the historical fault handling information, risk warning information, power battery capacity, and power battery peak power of the power battery; The safety of the power battery is tested based on the historical fault handling information and the risk warning information to obtain the safety score value of the power battery. The energy of the power battery is detected based on its capacity to obtain the energy score value of the power battery. The power of the power battery is tested based on its peak power to obtain the power battery's power score value.

4. The life testing method for power batteries according to claim 3, characterized in that, The safety of the power battery is tested based on the historical fault handling information and the risk warning information to obtain the safety score of the power battery, including: Based on the historical fault handling information, the fault mode of the power battery that malfunctions within a preset time period is determined, along with the fault repair degree and fault impact degree corresponding to the fault mode. The fault repair degree is used to indicate the complexity of repairing the faulty power battery, and the fault impact degree is used to indicate the impact on the power battery when it malfunctions. The residual risk information of the power battery is determined based on the degree of fault repair and the degree of fault impact. The safety score of the power battery is determined based on the residual risk information and the risk warning information.

5. The life testing method for a power battery according to claim 4, characterized in that, The safety score of the power battery is determined based on the residual risk information and the risk warning information, including: The residual risk information and the risk warning information are weighted according to the number of times the power battery has been handled, resulting in a fourth target weight for the residual risk information and a fifth target weight for the risk warning information. The residual risk value is obtained by multiplying the fourth objective weight and the residual risk information. The risk warning value is obtained by multiplying the weight of the fifth objective with the risk warning information. The safety score is obtained based on the first preset value, the residual risk value, and the risk warning value.

6. The life testing method for a power battery according to claim 3, characterized in that, Determining the power battery capacity based on the target signal parameters includes: The first charge and the second charge of the power battery in the charging cycle are determined based on the target signal parameters, wherein the first charge is the charge of the power battery when it starts charging in the charging cycle, and the second charge is the charge of the power battery when it ends charging in the charging cycle. The capacity of the power battery is determined based on the ratio of the target difference to the preset difference, wherein the target difference is the difference between the first charge and the second charge.

7. The life testing method for a power battery according to claim 1, characterized in that, Obtain the target signal parameters of the power battery, including: Obtain the initial signal parameters of the power battery and the signal type of the initial signal parameters; The initial signal parameters are filtered based on the preset filtering conditions corresponding to the signal type to obtain the target signal parameters.

8. The life testing method for a power battery according to claim 7, characterized in that, The initial signal parameters are filtered based on preset filtering conditions corresponding to the signal type to obtain the target signal parameters, including: The initial signal parameters are filtered based on the preset filtering conditions corresponding to the signal type to obtain the filtered signal parameters; The first signal parameter and / or the second signal parameter in the filtered signal parameters are removed to obtain the target signal parameters, wherein the first signal parameter is used to represent the parameter in the filtered signal parameters that has a missing value, and the second signal parameter is used to represent the parameter in the filtered signal parameters that does not conform to the preset logic.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the execution of the power battery life detection method according to any one of claims 1 to 8 in the processor of the device.

10. A vehicle, characterized in that, include: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors perform the life detection method for a power battery as described in any one of claims 1 to 8.

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