Power battery health degree assessment method and device and electronic equipment

Abstract

The invention provides a power battery health degree assessment method and apparatus, and an electronic device. The method comprises the steps of obtaining operation data of a vehicle power battery; dividing step length based on a preset state of charge interval, dividing the operation data into a plurality of SOC intervals, and obtaining sub-operation data corresponding to each SOC interval; calculating the capacity retention ratio of the vehicle power battery according to the sub-operation data; calculating the relative voltage deviation ratio of the vehicle power battery according to the operation data; and calculating the health state of the vehicle power battery according to the capacity retention ratio and the relative voltage deviation ratio. According to the method, the capacity retention ratio and the relative voltage deviation ratio are respectively calculated in different SOC intervals, so that the refined segmented evaluation of the health state of the battery is realized, the accuracy and the local sensitivity of the evaluation result are improved, and the decline difference and the aging characteristics of the battery in different working intervals can be more effectively reflected.

Description

Technical Field

[0001] This invention relates to the field of power battery technology, and in particular to a method, apparatus, and electronic device for assessing the health status of power batteries. Background Technology

[0002] In the field of power battery health status assessment, accurate and reliable testing methods are of great significance for the safe operation and life prediction of battery systems. Among traditional assessment methods, the open-circuit voltage method (OCV-based method) is widely used in the estimation of battery capacity and health status due to its simplicity and ease of implementation. However, this method relies on the empirical relationship between the open-circuit voltage measured in a static state and the SOC (State of Charge), neglecting the dynamic changes in battery voltage response characteristics within different SOC ranges.

[0003] Therefore, there is an urgent need to propose a new health status assessment method that can adapt to changes in battery aging characteristics and take into account the dynamic voltage response in different SOC ranges, so as to improve the intelligence level and reliability of the power battery management system. Summary of the Invention

[0004] The purpose of this invention is to provide a method, device, and electronic device for assessing the health status of a power battery. This method calculates the capacity retention rate and relative voltage deviation rate in different SOC ranges, thereby achieving a refined segmented assessment of the battery's health status. This improves the accuracy and local sensitivity of the assessment results and can more effectively reflect the degradation differences and aging characteristics of the battery in different operating ranges, thus enhancing the intelligence level and reliability of the power battery management system.

[0005] In a first aspect, embodiments of the present invention provide a method for assessing the health of a power battery, comprising: acquiring operational data of a vehicle power battery; dividing the operational data into multiple SOC intervals based on a preset state of charge interval division step size, thereby obtaining sub-operational data corresponding to each SOC interval; calculating the capacity retention rate of the vehicle power battery based on the sub-operational data; calculating the relative voltage deviation rate of the vehicle power battery based on the operational data; and calculating the health status of the vehicle power battery based on the capacity retention rate and the relative voltage deviation rate.

[0006] In a preferred embodiment of the present invention, the aforementioned operating data includes: the displayed SOC data of the vehicle power battery; the step of dividing the operating data into multiple SOC intervals based on a preset state of charge interval division step size to obtain sub-operating data corresponding to each SOC interval includes: dividing the operating data into multiple SOC intervals based on the aforementioned state of charge interval division step size and the aforementioned displayed SOC data to obtain sub-operating data corresponding to each SOC interval; the aforementioned sub-operating data further includes: the operating voltage, operating current, and operating temperature of each individual cell in the vehicle power battery; the step of calculating the capacity retention rate of the vehicle power battery based on the aforementioned sub-operating data includes: statistically analyzing the target operating temperature of each individual cell. The first target operating voltage within the temperature range is set as a reasonable voltage mapping range for the true SOC range; the first target operating voltage conforms to a preset confidence interval; the highest value of the operating voltage of the vehicle's power battery corresponding to a preset number of charging cycles is statistically analyzed, and the average value of the highest operating voltage is calculated; based on the average value of the highest operating voltage and its corresponding time, a voltage-time baseline of the vehicle's power battery is plotted; the voltage-time baseline is corrected based on the reasonable voltage mapping range, and a true SOC-time relationship curve is output; based on the true SOC-time relationship curve, the usable capacity of the vehicle's power battery is calculated; based on the usable capacity, the capacity retention rate of the vehicle's power battery is calculated.

[0007] In a preferred embodiment of the present invention, the step of correcting the voltage and time baseline based on the above-mentioned reasonable voltage mapping range and outputting the true SOC and time relationship curve includes: filtering out points where the above-mentioned reasonable voltage mapping range does not match the above-mentioned voltage and time baseline; replacing the displayed SOC of the above-mentioned mismatched points with the closest above-mentioned true SOC; and outputting the true SOC and time relationship curve.

[0008] In a preferred embodiment of the present invention, the step of calculating the relative voltage deviation rate of the vehicle power battery based on the above-mentioned operating data includes: calculating the first average voltage of all the individual cells at a preset first time point and the second average voltage at a preset second time point based on the above-mentioned operating voltage; calculating the first difference between the starting voltage of all the individual cells at the first time point and the first average voltage; and calculating the second difference between the ending voltage of all the individual cells at the second time point and the second average voltage; taking the absolute value of the difference between the first difference and the second difference; calculating the absolute value and the duration of the first time point and the second time point to obtain the unit time voltage deviation of each individual cell; and calculating the relative voltage deviation rate of the vehicle power battery based on the unit time voltage deviation of each individual cell.

[0009] In a preferred embodiment of the present invention, the step of calculating the relative voltage deviation rate of the vehicle power battery based on the unit time voltage deviation of each of the aforementioned individual cells includes: screening the maximum value of the unit time voltage deviation of each of the aforementioned individual cells; and determining the relative voltage deviation rate based on the maximum value and the rated voltage of the vehicle power battery.

[0010] In a preferred embodiment of the present invention, the step of determining the relative voltage deviation rate based on the maximum value and the rated voltage of the vehicle power battery includes: calculating the ratio of the maximum value to the rated voltage of the vehicle power battery to obtain the relative voltage deviation rate.

[0011] In a preferred embodiment of the present invention, the step of calculating the health status of the vehicle power battery based on the capacity retention rate and the relative voltage deviation rate includes: determining whether the capacity retention rate is less than a first threshold or whether the relative voltage deviation rate is greater than a second threshold; if yes, outputting the health status value as zero; if no, calculating the health status according to the following formula: SOH = (α * +β*(1- *100))*100%; where α is the first weighting coefficient, β is the second weighting coefficient, and CR is the capacity retention rate mentioned above. The above-mentioned relative voltage deviation rate is given, and SOH is the value of the above-mentioned health status.

[0012] In a preferred embodiment of the present invention, after calculating the health status of the vehicle power battery based on the capacity retention rate and the relative voltage deviation rate, the method further includes: determining whether the value of the health status is less than a third threshold; if so, outputting a life-end prompt message for the vehicle power battery.

[0013] Secondly, embodiments of the present invention also provide a power battery health assessment device, comprising: a data acquisition module for acquiring operating data of a vehicle power battery; a division module for dividing the operating data into sub-operating data corresponding to multiple SOC intervals based on a preset SOC step size; a calculation module for calculating the capacity retention rate of the vehicle power battery based on the sub-operating data; and calculating the relative voltage deviation rate of the vehicle power battery based on the operating data; and a result output module for calculating the health status of the vehicle power battery based on the capacity retention rate and the relative voltage deviation rate.

[0014] Thirdly, embodiments of the present invention also provide an electronic device, which includes a processor and a memory. The memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the above-mentioned power battery health assessment method.

[0015] The embodiments of the present invention have the following beneficial technical effects: This invention provides a method, apparatus, and electronic device for assessing the health of a power battery, comprising: acquiring operational data of a vehicle power battery; dividing the operational data into multiple SOC intervals based on a preset state of charge (SOC) interval step size, obtaining sub-operational data corresponding to each SOC interval; calculating the capacity retention rate of the vehicle power battery based on the sub-operational data; calculating the relative voltage deviation rate of the vehicle power battery based on the operational data; and calculating the health status of the vehicle power battery based on the capacity retention rate and the relative voltage deviation rate. This method achieves a refined segmented assessment of battery health status by calculating the capacity retention rate and relative voltage deviation rate separately within different SOC intervals, improving the accuracy and local sensitivity of the assessment results, and more effectively reflecting the degradation differences and aging characteristics of the battery in different operating intervals. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating a method for assessing the health of a power battery, provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the voltage distribution of a single battery cell provided in an embodiment of the present invention; Figure 3 A schematic diagram illustrating the correction process of a voltage and time reference line provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a power battery health assessment device provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0018] Icons: 21 - Displayed SOC and time relationship curve; 22 - Actual SOC and time relationship curve; 31 - Data acquisition module; 32 - Partitioning module; 33 - Calculation module; 34 - Result output module; 41 - Processor; 42 - Memory; 43 - Bus; 44 - Communication interface. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0020] In the field of power battery health status assessment, accurate and reliable testing methods are of great significance for the safe operation and life prediction of battery systems. Among traditional assessment methods, the open-circuit voltage method (OCV-based method) is widely used in the estimation of battery capacity and health status due to its simplicity and ease of implementation. However, this method relies on the empirical relationship between the open-circuit voltage measured in a static state and the SOC (State of Charge), neglecting the dynamic changes in battery voltage response characteristics within different SOC ranges.

[0021] Based on this, embodiments of the present invention provide a method, apparatus, and electronic device for assessing the health status of a power battery. This method achieves a refined, segmented assessment of the battery's health status by calculating the capacity retention rate and relative voltage deviation rate within different SOC ranges, improving the accuracy and local sensitivity of the assessment results, and more effectively reflecting the degradation differences and aging characteristics of the battery in different operating ranges. For ease of understanding, a method for assessing the health status of a power battery is first introduced.

[0022] Example 1 In this embodiment, Figure 1 This is a flowchart illustrating a method for assessing the health of a power battery, as provided in an embodiment of the present invention.

[0023] Depend on Figure 1 As seen, the method includes: Step S101: Obtain the operating data of the vehicle's power battery.

[0024] The aforementioned operational data refers to a series of key parameters reflecting the battery's status, performance, and operating environment, collected and recorded by sensors and the Battery Management System (BMS) during the actual operation of the battery. This data can reflect the battery's operating status and health condition in real time or periodically.

[0025] Step S102: Based on the preset state of charge interval division step size, the above operating data is divided into multiple SOC intervals to obtain the sub-operating data corresponding to each SOC interval.

[0026] In this embodiment, the battery operating data is first divided into several non-overlapping SOC intervals according to a preset state of charge (SOC) interval. Then, for each SOC interval, a corresponding sub-operating dataset is extracted from the original operating data to ensure that each sub-dataset contains only data points within the corresponding SOC range.

[0027] Step S103: Calculate the capacity retention rate of the vehicle power battery based on the above sub-operation data; and calculate the relative voltage deviation rate of the vehicle power battery based on the above operation data.

[0028] Step S104: Calculate the health status of the vehicle power battery based on the above-mentioned capacity retention rate and the above-mentioned relative voltage deviation rate.

[0029] In this embodiment, the capacity retention rate of the vehicle's power battery at different usage stages is acquired through data acquisition. This indicator reflects the ratio between the battery's current usable capacity and its initial nominal capacity, and is one of the key parameters for measuring the degree of battery aging. Secondly, the voltage changes in each SOC range during multiple charge-discharge cycles are statistically calculated to obtain the relative voltage deviation rate, which characterizes the stability and consistency of the battery's internal electrochemical performance. Subsequently, the two key parameters, capacity retention rate and relative voltage deviation rate, are weighted and fused to construct a battery health status assessment model. The weights can be adjusted according to the sensitivity to capacity decay and voltage fluctuations in actual application scenarios to ensure that the assessment results accurately reflect the overall health status of the battery. Finally, the comprehensive index calculated based on this model is the battery's state of health (SOH), which can be used to assess the battery's remaining service life, determine whether replacement or maintenance is needed, and provide a decision-making basis for the battery management system.

[0030] This invention provides a method for assessing the health of a power battery, comprising: acquiring operational data of a vehicle power battery; dividing the operational data into multiple SOC intervals based on a preset state of charge (SOC) interval step size, obtaining sub-operational data corresponding to each SOC interval; calculating the capacity retention rate of the vehicle power battery based on the sub-operational data; calculating the relative voltage deviation rate of the vehicle power battery based on the operational data; and calculating the health status of the vehicle power battery based on the capacity retention rate and the relative voltage deviation rate. This method achieves a refined segmented assessment of battery health status by calculating the capacity retention rate and relative voltage deviation rate separately within different SOC intervals, improving the accuracy and local sensitivity of the assessment results, and more effectively reflecting the degradation differences and aging characteristics of the battery in different operating intervals.

[0031] Example 2 Based on the above embodiments, this invention provides another method for assessing the health of a power battery, the method comprising: Step S201: Obtain the operating data of the vehicle's power battery.

[0032] Step S202: Based on the preset state of charge interval division step size, the above operating data is divided into multiple SOC intervals to obtain the sub-operating data corresponding to each SOC interval.

[0033] In one embodiment, the above-mentioned operating data includes: the displayed SOC data of the vehicle's power battery; the step of dividing the above-mentioned operating data into multiple SOC intervals based on a preset state of charge interval division step size, and obtaining sub-operating data corresponding to each SOC interval, includes: dividing the above-mentioned operating data into multiple SOC intervals based on the above-mentioned state of charge interval division step size and the above-mentioned displayed SOC data, and obtaining sub-operating data corresponding to each SOC interval.

[0034] Step S203: Calculate the capacity retention rate of the vehicle power battery based on the above sub-operation data; and calculate the relative voltage deviation rate of the vehicle power battery based on the above operation data.

[0035] In this embodiment, the aforementioned sub-operational data further includes: the operating voltage, operating current, and operating temperature of each individual cell in the vehicle power battery; the step of calculating the capacity retention rate of the vehicle power battery based on the aforementioned sub-operational data includes: statistically analyzing the first target operating voltage within the target temperature range of the operating temperature of each individual cell, setting it as a reasonable voltage mapping range for the true SOC range; the aforementioned first target operating voltage conforms to a preset confidence interval; statistically analyzing the highest value of the operating voltage of the vehicle power battery corresponding to a preset number of charging cycles, and calculating the average value of the highest operating voltage; plotting a voltage-time baseline of the vehicle power battery based on the average value of the highest operating voltage and its corresponding time; correcting the voltage-time baseline based on the aforementioned reasonable voltage mapping range, and outputting a true SOC-time relationship curve; calculating the available capacity of the vehicle power battery based on the aforementioned true SOC-time relationship curve; and calculating the capacity retention rate of the vehicle power battery based on the available capacity.

[0036] Furthermore, the step of correcting the voltage and time baseline based on the above reasonable voltage mapping range and outputting the true SOC and time relationship curve includes: filtering out points where the above reasonable voltage mapping range does not match the above voltage and time baseline; replacing the displayed SOC of the above mismatched points with the closest above true SOC, and outputting the true SOC and time relationship curve.

[0037] In practical implementation, firstly, the operating data of the power batteries of 1000 new energy vehicles in the same batch are read. Each power battery consists of multiple individual cells. This operating data includes the voltage (V), current (I), displayed SOC, temperature (T), and other data items for each individual cell, along with their corresponding timestamps (T). Then, the data for each individual cell is divided into multiple SOC intervals (e.g., 0-10%, 10-20%, etc.) according to the state of charge range. Next, 25... For all individual cells within each SOC interval of a 5˚C temperature range, statistical distribution analysis was performed, and the 90% confidence interval voltage was selected as the reasonable voltage mapping range for that SOC interval. Next, a specific charging process or segment of the charging process was selected as the time interval for calculating the usable capacity of the battery system. The highest voltage data of individual cells in the battery system under evaluation for the 10 days prior to the selected charging process were statistically analyzed, and a curve was plotted between the average highest voltage and time to obtain the voltage-time baseline for that specific charging process. Then, based on the reasonable voltage mapping range for different SOC intervals, the dynamic voltage baseline of the selected charging process or segment of the charging process was adjusted for SOC, resulting in the aforementioned true SOC-time relationship curve.

[0038] For ease of understanding, Figure 2 This is a schematic diagram of the voltage distribution of a single battery cell provided in an embodiment of the present invention. Wherein, Figure 2 The horizontal axis represents the voltage range, and the vertical axis represents the number of samples.

[0039] Furthermore, Figure 3 This is a schematic diagram illustrating the correction process of a voltage and time reference line provided in an embodiment of the present invention.

[0040] Depend on Figure 3 As observed, when the horizontal axis of the voltage and time baseline represents the time point, the voltage at time point 7000 falls outside the mapped range (the displayed SOC is 89%, but based on the reasonable voltage mapping range of 90-92% SOC, the displayed SOC at this point is underestimated; its true SOC should be at least 90%). Therefore, the SOC at this point should be adjusted to the lowest SOC value within the reasonable voltage mapping range, to 90%. Figure 3 The curves depicting the relationship between apparent SOC and time are shown in Figure 21, as well as the curves depicting the relationship between actual SOC and time are shown in Figure 22.

[0041] Furthermore, the step of calculating the relative voltage deviation rate of the vehicle power battery based on the aforementioned operating data includes: calculating the first average voltage of all individual cells at a preset first time point and the second average voltage at a preset second time point based on the aforementioned operating voltage; calculating the first difference between the starting voltage of all individual cells at the aforementioned first time point and the aforementioned first average voltage; and calculating the second difference between the ending voltage of all individual cells at the aforementioned second time point and the aforementioned second average voltage; taking the absolute value of the difference between the aforementioned first difference and the aforementioned second difference; calculating the absolute value and the duration of the aforementioned first time point and the aforementioned second time point to obtain the unit time voltage deviation of each individual cell; and calculating the relative voltage deviation rate of the vehicle power battery based on the unit time voltage deviation of each individual cell.

[0042] Furthermore, the step of calculating the relative voltage deviation rate of the vehicle power battery based on the unit time voltage deviation of each of the aforementioned individual cells includes: screening the maximum value of the unit time voltage deviation of each of the aforementioned individual cells; and determining the relative voltage deviation rate based on the maximum value and the rated voltage of the vehicle power battery.

[0043] Here, the step of determining the relative voltage deviation rate based on the maximum value and the rated voltage of the vehicle power battery includes: calculating the ratio of the maximum value to the rated voltage of the vehicle power battery to obtain the relative voltage deviation rate.

[0044] In practice, firstly, the operating data of the vehicle's power battery for the past three months is read, including the voltage (V) of each individual battery cell and the timestamp (T) of the battery voltage (V), etc. Then, a required calculation period ∆t is defined, and the average voltage of each battery cell at the start time is calculated. and the average voltage at the end time Then, based on the following formula, the difference between the relative average voltage deviation of the starting voltage Vi,start and the ending voltage Vi,end of each battery cell within the cycle duration ∆t is calculated, and then normalized with ∆t to obtain the relative voltage deviation rate Δ for each battery cell. The unit is mV / month: Δ =∣( - )-( - )∣ / ∆t Where i represents the number of the battery cell.

[0045] =Max(Δ ) / Where Max(Δ () represents the maximum value of the voltage deviation per unit time for each battery cell during the aforementioned cycle duration. This refers to the rated voltage of the vehicle's power battery.

[0046] Step S204: Determine whether the above-mentioned capacity retention rate is less than the first threshold or whether the above-mentioned relative voltage deviation rate is greater than the second threshold.

[0047] Here, the first threshold is 60 percent and the second threshold is 0.2 percent.

[0048] Step S205: If yes, output the value of the above health status as zero; if no, calculate the above health status according to the following formula: SOH=(α* +β*(1- *100))*100% Where α is the first weighting coefficient, β is the second weighting coefficient, and CR is the capacity retention rate mentioned above. The above-mentioned relative voltage deviation rate is given, and SOH is the value of the above-mentioned healthy state, with α=0.7 and β=0.3.

[0049] Here, when the value of the above health status is zero, it indicates that the life of the vehicle's power battery has ended.

[0050] Furthermore, after calculating the health status of the vehicle power battery based on the aforementioned capacity retention rate and relative voltage deviation rate, the method further includes: determining whether the value of the health status is less than a third threshold; if so, outputting a lifespan termination warning message for the vehicle power battery.

[0051] Here, the third threshold mentioned above is 70%. That is, if SOH < 70%, the vehicle's power battery life is considered to have ended, and SOH = 0; if SOH ≥ 70%, the value of SOH is output.

[0052] Assume a vehicle's power battery =65%, =0.18%, according to the SOH calculation formula, SOH = (0.7*) +0.3*(1- ))*100=(0.7*0.65+0.3*(1-0.18))*100%=70.1%.

[0053] This invention provides a method for assessing the health status of a power battery, comprising: acquiring operational data of a vehicle power battery; dividing the operational data into multiple SOC intervals based on a preset state of charge interval step size, obtaining sub-operational data corresponding to each SOC interval; calculating the capacity retention rate of the vehicle power battery based on the sub-operational data; and calculating the relative voltage deviation rate of the vehicle power battery based on the operational data; if the value is zero, outputting a health status value of zero; if not, calculating the health status according to a formula: when the health status value is zero, it indicates that the lifespan of the vehicle power battery has ended. This method, by combining the capacity retention rate and the relative voltage deviation rate to comprehensively calculate the battery health status, can accurately determine the battery's lifespan status and output a zero-value signal in a timely manner when the battery fails, achieving a refined assessment of the power battery's health status and effective identification of lifespan termination.

[0054] Example 3 Based on the above implementation, Figure 4 This is a schematic diagram of a power battery health assessment device provided in an embodiment of the present invention.

[0055] Depend on Figure 4 As seen, the device includes: The data acquisition module 31 is used to acquire the operating data of the vehicle's power battery.

[0056] The partitioning module 32 is used to divide the above running data into sub-running data corresponding to multiple SOC intervals based on a preset SOC step size.

[0057] The calculation module 33 is used to calculate the capacity retention rate of the vehicle power battery based on the above sub-operation data; and to calculate the relative voltage deviation rate of the vehicle power battery based on the above operation data.

[0058] The result output module 34 is used to calculate the health status of the vehicle power battery based on the capacity retention rate and the relative voltage deviation rate.

[0059] The data acquisition module 31, the partitioning module 32, the calculation module 33, and the result output module 34 are connected in sequence.

[0060] In one embodiment, the operating data includes: the displayed SOC data of the vehicle power battery; the division module 32 is further configured to divide the operating data into multiple SOC intervals based on the step size of the state of charge interval and the displayed SOC data, to obtain sub-operating data corresponding to each SOC interval; the sub-operating data also includes: the operating voltage, operating current, and operating temperature of each individual cell in the vehicle power battery; the calculation module 33 is further configured to: statistically analyze the first target operating voltage of the target temperature interval for each individual cell, and set it as a reasonable voltage mapping range for the real SOC interval; the first target operating voltage conforms to a preset confidence interval; statistically analyze the highest value of the operating voltage of the vehicle power battery corresponding to a preset number of charging cycles, and calculate the average value of the highest value of the operating voltage; plot the voltage and time baseline of the vehicle power battery based on the average value of the highest value of the operating voltage and its corresponding time; correct the voltage and time baseline based on the reasonable voltage mapping range, and output the real SOC and time relationship curve; calculate the available capacity of the vehicle power battery based on the real SOC and time relationship curve; calculate the capacity retention rate of the vehicle power battery based on the available capacity.

[0061] In one embodiment, the calculation module 33 is further configured to filter out points where the voltage reasonable mapping range does not match the voltage and time baseline; replace the displayed SOC of the mismatched points with the closest real SOC, and output the real SOC and time relationship curve.

[0062] In one embodiment, the calculation module 33 is further configured to: calculate the first average voltage of all the individual cells at a preset first time point and the second average voltage at a preset second time point based on the operating voltage; calculate the first difference between the starting voltage of all the individual cells at the first time point and the first average voltage; and calculate the second difference between the ending voltage of all the individual cells at the second time point and the second average voltage; take the absolute value of the difference between the first difference and the second difference; calculate the absolute value and the duration of the first time point and the second time point to obtain the unit time voltage deviation of each individual cell; and calculate the relative voltage deviation rate of the vehicle power battery based on the unit time voltage deviation of each individual cell.

[0063] In one embodiment, the calculation module 33 is further configured to filter the maximum value of the voltage deviation per unit time for each of the aforementioned individual cells; and determine the relative voltage deviation rate based on the maximum value and the rated voltage of the vehicle power battery.

[0064] In one embodiment, the calculation module 33 is further used to calculate the ratio of the maximum value to the rated voltage of the vehicle power battery to obtain the relative voltage deviation rate.

[0065] In one embodiment, the result output module 34 is further configured to determine whether the capacity retention rate is less than a first threshold or whether the relative voltage deviation rate is greater than a second threshold; if yes, output the health status value as zero; if no, calculate the health status according to the following formula: SOH=(α* +β*(1- *100))*100% Where α is the first weighting coefficient, β is the second weighting coefficient, and CR is the capacity retention rate mentioned above. The above-mentioned relative voltage deviation rate is given, and SOH is the value of the above-mentioned health status.

[0066] In one embodiment, the result output module 34 is further used to determine whether the value of the health status is less than a third threshold; if so, it outputs the life end reminder information of the vehicle power battery.

[0067] The power battery health assessment device provided in this embodiment of the invention has the same implementation principle and technical effect as the aforementioned power battery health assessment method embodiment. For the sake of brevity, any parts not mentioned in the embodiments of the power battery health assessment device can be referred to the corresponding content in the aforementioned method embodiment.

[0068] This invention also provides an electronic device, such as... Figure 5 The diagram shows the structure of the electronic device, which includes a processor 41 and a memory 42. The memory 42 stores machine-executable instructions that can be executed by the processor 41. The processor 41 executes the machine-executable instructions to implement the above-mentioned power battery health assessment method.

[0069] exist Figure 5 In the illustrated embodiment, the electronic device further includes a bus 43 and a communication interface 44, wherein the processor 41, the communication interface 44, and the memory 42 are connected via the bus.

[0070] The memory 42 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 44 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus can be an ISA bus, PCI bus, or EISA bus, etc. The aforementioned bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0071] Processor 41 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 41 or by software instructions. Processor 41 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in the memory. The processor 41 reads the information in the memory 42 and, in conjunction with its hardware, completes the steps of the power battery health assessment method of the aforementioned embodiment.

[0072] This invention also provides a machine-readable storage medium storing machine-executable instructions. When these machine-executable instructions are called and executed by a processor, they cause the processor to implement the aforementioned power battery health assessment method. For specific implementation details, please refer to the foregoing method embodiments, which will not be repeated here.

[0073] The computer program products of the power battery health assessment method, power battery health assessment device, and electronic device provided in the embodiments of the present invention include a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the power battery health assessment method described in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0074] Unless otherwise specifically stated, the relative steps, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0075] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion 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 this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0076] Finally, it should be noted that the above embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the scope of the technology disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention.

Claims

1. A method for assessing the health status of a power battery, characterized in that, include: Obtain operational data of the vehicle's power battery; Based on a preset state of charge interval division step size, the running data is divided into multiple SOC intervals to obtain sub-running data corresponding to each SOC interval. Based on the sub-operation data, calculate the capacity retention rate of the vehicle's power battery; and based on the operation data, calculate the relative voltage deviation rate of the vehicle's power battery. The health status of the vehicle's power battery is calculated based on the capacity retention rate and the relative voltage deviation rate.

2. The method for assessing the health of a power battery according to claim 1, characterized in that, The operating data includes: the displayed SOC data of the vehicle's power battery; The steps of dividing the operating data into multiple SOC intervals based on a preset state of charge interval division step size, and obtaining sub-operating data corresponding to each SOC interval, include: Based on the step size of the state of charge interval and the displayed SOC data, the running data is divided into multiple SOC intervals to obtain sub-running data corresponding to each SOC interval. The sub-operational data further includes: the operating voltage, operating current, and operating temperature of each individual cell in the vehicle's power battery; the step of calculating the capacity retention rate of the vehicle's power battery based on the sub-operational data includes: The first target operating voltage within the target temperature range of each individual unit is statistically analyzed and set as a reasonable voltage mapping range for the actual SOC range; the first target operating voltage conforms to a preset confidence level range; The highest value of the operating voltage of the vehicle's power battery corresponding to a preset number of charging cycles is statistically analyzed, and the average value of the highest operating voltage is calculated. Based on the average value of the highest operating voltage and its corresponding time, a voltage-time baseline of the vehicle's power battery is plotted. Based on the reasonable voltage mapping range, the voltage and time baseline are corrected, and the true SOC and time relationship curve is output. The usable capacity of the vehicle's power battery is calculated based on the actual SOC and time relationship curve. The capacity retention rate of the vehicle's power battery is calculated based on the available capacity.

3. The method for assessing the health of a power battery according to claim 2, characterized in that, The steps of correcting the voltage and time baseline based on the reasonable voltage mapping range and outputting the true SOC and time relationship curve include: Filter the points where the voltage and time baseline do not match within the reasonable voltage mapping range; Replace the displayed SOC of the mismatched points with the closest real SOC, and output the real SOC and time relationship curve.

4. The method for assessing the health of a power battery according to claim 2, characterized in that, The step of calculating the relative voltage deviation rate of the vehicle's power battery based on the operating data includes: Based on the operating voltage, calculate the first average voltage of all the individual cells at a preset first time point and the second average voltage at a second time point; Calculate the first difference between the initial voltage and the first average voltage of all individual cells at the first time point; and calculate the second difference between the final voltage and the second average voltage of all individual cells at the second time point; Take the absolute value of the difference between the first difference and the second difference; The absolute value is calculated along with the duration of the first time point and the second time point to obtain the unit time voltage deviation of each individual battery cell; The relative voltage deviation rate of the vehicle power battery is calculated based on the voltage deviation per unit time of each of the individual cells.

5. The method for assessing the health of a power battery according to claim 4, characterized in that, The step of calculating the relative voltage deviation rate of the vehicle power battery based on the unit time voltage deviation of each of the individual cells includes: Filter the maximum value of the voltage deviation per unit time for each of the individual cells; The relative voltage deviation rate is determined based on the maximum value and the rated voltage of the vehicle's power battery.

6. The method for assessing the health of a power battery according to claim 5, characterized in that, The step of determining the relative voltage deviation rate based on the maximum value and the rated voltage of the vehicle's power battery includes: The ratio of the maximum value to the rated voltage of the vehicle's power battery is calculated to obtain the relative voltage deviation rate.

7. The method for assessing the health of a power battery according to claim 1, characterized in that, The step of calculating the health status of the vehicle's power battery based on the capacity retention rate and the relative voltage deviation rate includes: Determine whether the capacity retention rate is less than a first threshold or whether the relative voltage deviation rate is greater than a second threshold; If so, output the value of the health status as zero; If not, calculate the health status according to the following formula: SOH=(α* +β*(1- *100))*100% Wherein, α is the first weighting coefficient, β is the second weighting coefficient, and CR is the capacity retention rate. The relative voltage deviation rate is denoted as , and SOH is the value of the health status.

8. The method for assessing the health of a power battery according to claim 7, characterized in that, After calculating the health status of the vehicle power battery based on the capacity retention rate and the relative voltage deviation rate, the method further includes: Determine whether the value of the health status is less than a third threshold; If so, output a lifespan termination warning message for the vehicle's power battery.

9. A power battery health assessment device, characterized in that, include: The data acquisition module is used to acquire the operating data of the vehicle's power battery; The partitioning module is used to divide the running data into sub-running data corresponding to multiple SOC intervals based on a preset SOC step size; The calculation module is used to calculate the capacity retention rate of the vehicle power battery based on the sub-operation data; and to calculate the relative voltage deviation rate of the vehicle power battery based on the operation data. The result output module is used to calculate the health status of the vehicle power battery based on the capacity retention rate and the relative voltage deviation rate.

10. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, the processor executing the computer-executable instructions to implement the power battery health assessment method according to any one of claims 1 to 8.

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