A method, device and storage medium for constructing a battery life confidence interval

Abstract

The application relates to a battery life confidence interval construction method and device, equipment and a storage medium. The first ratio of the minimum actual attenuation value to the predicted attenuation value and the second ratio of the maximum actual attenuation value to the predicted attenuation value are calculated; the battery life simulation model established in advance is corrected according to the first ratio and the second ratio, the capacity of the multiple series-connected battery cells in the second attenuation state is predicted according to the corrected battery life simulation model, the first boundary attenuation value and the second boundary attenuation value are obtained, and the confidence interval of the battery life is constructed by using the first boundary attenuation value and the second boundary attenuation value. The application generates a correction coefficient based on the actually obtained battery attenuation data and the predicted battery attenuation data, corrects the battery life simulation model, estimates the life of the battery by using the corrected battery life simulation model, obtains the confidence interval based on the actual battery attenuation data, and improves the credibility of the confidence interval.

Description

Technical Field

[0001] This invention relates to the field of automotive battery evaluation technology, specifically to a method, apparatus, device, and storage medium for constructing a battery life confidence interval. Background Technology

[0002] With the rapid development of new energy vehicles, battery lifespan has become one of the key factors consumers consider when purchasing a car, making the assessment of a vehicle's battery warranty lifespan a crucial task. Traditional battery life simulations, with their built-in battery degradation models or empirical formulas, can only provide a single calculated value.

[0003] To increase the distribution range of lifespan simulation calculation values, as described in patent CN201910420526.8 "A Method for Predicting the Probability of Remaining Lifespan of Lithium Batteries Based on Grey Models", the RVM (Relevance Vector Machine) mathematical model is used to describe the probability range of battery degradation. However, the above technical features are not based on the degradation characteristics distribution of the battery cell itself and lack credibility. Summary of the Invention

[0004] One of the objectives of this invention is to provide a method, apparatus, device, and storage medium for constructing a battery life confidence interval, in order to solve the technical problem of lack of reliability caused by simply using mathematical models to calculate the battery degradation interval in the prior art.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for constructing a battery life confidence interval, the method comprising:

[0007] Obtain the maximum and minimum actual attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state; and obtain the predicted attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state.

[0008] Calculate a first ratio of the minimum actual attenuation value to the predicted attenuation value, and a second ratio of the maximum actual attenuation value to the predicted attenuation value;

[0009] The pre-established battery life simulation model is first corrected according to the first ratio, and the capacity of multiple series-connected cells in the second decay state is predicted according to the first corrected battery life simulation model to obtain the first boundary decay value; the pre-established battery life simulation model is second corrected according to the second ratio, and the capacity of multiple series-connected cells in the second decay state is predicted according to the second corrected battery life simulation model to obtain the second boundary decay value.

[0010] A confidence interval for battery life is constructed using the first boundary decay value and the second boundary decay value.

[0011] In one embodiment of the present invention, obtaining the predicted attenuation values ​​of multiple series-connected cells from an initial state to a first attenuation state includes:

[0012] Based on a pre-established battery life simulation model, the predicted capacity values ​​of multiple series-connected cells in the first decay state are obtained.

[0013] Calculate the capacity difference between the initial capacity value and the predicted capacity value, and calculate the ratio of the capacity difference to the initial capacity value to obtain the predicted attenuation value of the plurality of series-connected cells.

[0014] In one embodiment of the present invention, obtaining the maximum and minimum actual attenuation values ​​of multiple series-connected cells from an initial state to a first attenuation state includes:

[0015] The initial capacity of multiple series-connected cells in an initial state, the remaining capacity of multiple series-connected cells in a first decay state, and the decay time required for multiple series-connected cells to transition from the initial state to the first decay state are obtained.

[0016] The decay rate of the plurality of series-connected cells is calculated based on the initial capacity, the remaining capacity, and the decay time.

[0017] The decay rates of the multiple series-connected cells are screened to obtain the maximum decay rate and the minimum decay rate; and the initial capacity values ​​of the multiple series-connected cells are screened to obtain the maximum cell capacity and the minimum cell capacity value.

[0018] The minimum actual attenuation value of the battery cell is calculated based on the minimum attenuation rate, the minimum cell capacity, and the attenuation time, and the maximum actual attenuation value of the battery cell is calculated based on the maximum attenuation rate, the maximum cell capacity, and the attenuation time.

[0019] In one embodiment of the present invention, obtaining the remaining capacity of multiple series-connected cells when they are in a first attenuation state includes:

[0020] Discharge multiple series-connected cells in the first decay state starting from a fully charged state, and obtain the dynamic voltage value and discharge amount of each cell;

[0021] Discharge is stopped when the dynamic voltage value of any cell drops to the cell cutoff voltage value, and the static voltage value of each cell at the point of stopping discharge is obtained.

[0022] A battery cell with a static voltage value equal to a cutoff voltage value is used as a reference battery cell, and a battery cell with a static voltage value greater than a cutoff voltage value is used as a battery cell to be tested; the stage discharge amount of the reference battery cell when it discharges from the static voltage value to the cutoff voltage value is obtained;

[0023] The total charge of the battery cell under test is obtained by summing the discharged amount and the staged discharge amount of the battery cell under test.

[0024] The remaining capacity of multiple series-connected cells when they are in the first decay state is obtained by summing the discharged amount of the reference cell and the total charge of the cell under test.

[0025] In one embodiment of the present invention, after constructing a confidence interval for battery life using the first boundary decay value and the second boundary decay value, the method further includes:

[0026] The measured capacity of multiple control battery packs in the second decay state was obtained, wherein the control battery packs comprised multiple cells connected in series.

[0027] The measured capacity of the cells in the control battery pack is compared with the confidence interval to obtain the comparison results;

[0028] The confidence rate of the confidence interval is evaluated based on the comparison results.

[0029] The present invention also provides an apparatus for constructing a battery life confidence interval, the apparatus comprising:

[0030] The acquisition module is used to obtain the maximum and minimum actual attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state; and to obtain the predicted attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state.

[0031] The calculation module is used to calculate a first ratio of the minimum actual attenuation value to the predicted attenuation value and a second ratio of the maximum actual attenuation value to the predicted attenuation value;

[0032] The correction and prediction module is used to perform a first correction on the pre-established battery life simulation model according to the first ratio, and predict the capacity of multiple series-connected cells in the second decay state according to the first corrected battery life simulation model to obtain a first boundary decay value; and to perform a second correction on the pre-established battery life simulation model according to the second ratio, and predict the capacity of multiple series-connected cells in the second decay state according to the second corrected battery life simulation model to obtain a second boundary decay value.

[0033] A construction module is used to construct a confidence interval for battery life using the first boundary decay value and the second boundary decay value.

[0034] In one embodiment of the present invention, the acquisition module includes:

[0035] The prediction unit is used to predict the capacity values ​​of multiple series-connected cells in the first degradation state based on a pre-established battery life simulation model.

[0036] The first calculation unit calculates the capacity difference between the initial capacity value and the predicted capacity value, and calculates the ratio of the capacity difference to the initial capacity value to obtain the predicted attenuation value of the plurality of series-connected cells.

[0037] In one embodiment of the present invention, the acquisition module includes:

[0038] The acquisition unit is used to acquire the initial capacity of multiple series-connected cells when they are in an initial state, the remaining capacity of multiple series-connected cells when they are in a first attenuation state, and the attenuation time required for multiple series-connected cells to go from the initial state to the first attenuation state.

[0039] The second calculation unit is used to calculate the decay rate of the plurality of series-connected cells based on the initial capacity, the remaining capacity, and the decay time.

[0040] The screening unit is used to screen the attenuation rate of the plurality of series-connected cells to obtain the maximum attenuation rate and the minimum attenuation rate; and to screen the initial capacity value of the plurality of series-connected cells to obtain the maximum cell capacity and the minimum cell capacity value.

[0041] The third calculation unit is used to calculate the minimum actual attenuation value of the battery cell based on the minimum attenuation rate, the minimum cell capacity, and the attenuation time, and to calculate the maximum actual attenuation value of the battery cell based on the maximum attenuation rate, the maximum cell capacity, and the attenuation time.

[0042] The present invention also provides an electronic device, comprising:

[0043] One or more processors;

[0044] A storage device for storing one or more programs that, when executed by one or more processors, cause the electronic device to implement a method for constructing a battery life confidence interval as described above.

[0045] The present invention also provides a computer-readable storage medium storing computer-readable instructions thereon, which, when executed by a computer's processor, cause the computer to perform a method for constructing a battery life confidence interval as described above.

[0046] The beneficial effects of this invention are as follows: The method, apparatus, device, and storage medium for constructing a battery life confidence interval according to this invention calculate a first ratio of the minimum actual attenuation value to the predicted attenuation value, and a second ratio of the maximum actual attenuation value to the predicted attenuation value. Based on the first ratio, a pre-established battery life simulation model is first corrected, and the capacity of multiple series-connected cells in a second attenuation state is predicted based on the first corrected battery life simulation model to obtain a first boundary attenuation value. Based on the second ratio, a pre-established battery life simulation model is second corrected, and the capacity of multiple series-connected cells in a second attenuation state is predicted based on the second corrected battery life simulation model to obtain a second boundary attenuation value. A confidence interval for battery life is constructed using the first boundary attenuation value and the second boundary attenuation value. This invention generates correction coefficients based on actually acquired battery attenuation data and predicted battery attenuation data, and corrects the battery life simulation model. The battery life is then estimated using the corrected battery life simulation model, resulting in a confidence interval based on actual battery attenuation data, thus improving the reliability of the confidence interval. Attached Figure Description

[0047] Figure 1 An application scenario diagram illustrating a method for constructing a battery life confidence interval, as shown in an exemplary embodiment of this application;

[0048] Figure 2 A flowchart illustrating a method for constructing a battery life confidence interval, as shown in an exemplary embodiment of this application;

[0049] Figure 3 A flowchart illustrating a method for constructing a battery life confidence interval, as shown in another exemplary embodiment of this application;

[0050] Figure 4 A graph showing the relationship between cell voltage and discharge capacity, illustrating an exemplary embodiment of this application;

[0051] Figure 5 This is a schematic diagram illustrating the attenuation rate of multiple series-connected battery cells in an exemplary embodiment of this application.

[0052] Figure 6 A schematic diagram of confidence intervals shown in an exemplary embodiment of this application;

[0053] Figure 7 A structural diagram illustrating an apparatus for constructing a battery life confidence interval, as shown in an exemplary embodiment of this application;

[0054] Figure 8 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0055] The embodiments of this application will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be understood that the preferred embodiments are only for illustrating this application and are not intended to limit the scope of protection of this application.

[0056] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. Therefore, the drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0057] Figure 1 This is an exemplary embodiment of the present application illustrating an application scenario of a method for constructing a battery life confidence interval, as shown in the diagram. Figure 1 As shown, the database stores a large amount of battery experimental data. During the degradation experiment of the automotive power battery, the discharge rate and charge / discharge frequency of the electric vehicle during driving are simulated to make the battery degradation state close to that during driving. The database is connected to a computing device via a data bus. The computing device has a preset battery life simulation model, which is a model of the relationship between battery capacity and degradation state established based on a large amount of battery data, and belongs to existing technology. The computing device obtains battery experimental data from the database, calculates correction coefficients, and corrects the battery life simulation model to obtain a battery degradation confidence interval with a high degree of confidence.

[0058] like Figure 2 As shown, in an exemplary embodiment, a method for constructing a battery life confidence interval includes at least steps S210 to S240, which are described in detail below:

[0059] S210, obtain the maximum actual attenuation value and the minimum actual attenuation value of multiple series-connected cells from the initial state to the first attenuation state; and obtain the predicted attenuation value of multiple series-connected cells from the initial state to the first attenuation state;

[0060] In this embodiment, the multiple series-connected cells can be multiple series-connected cells within a single battery pack, or multiple series-connected cells within multiple battery packs. The first degradation state of the battery pack is a custom degradation state. Taking an electric vehicle battery pack as an example, it can be an intermediate degradation state simulating the battery degradation after 20,000 kilometers of electric vehicle driving, or an aging state simulating the battery degradation after 100,000 kilometers of electric vehicle driving. The maximum and minimum actual degradation values ​​of the multiple series-connected cells from the initial state to the first degradation state are derived from actual battery testing experiments. The predicted degradation values ​​of the multiple series-connected cells from the initial state to the first degradation state are derived from the predictions of the multiple cells by the battery life simulation model.

[0061] S220, calculate the first ratio of the minimum actual attenuation value to the predicted attenuation value, and the second ratio of the maximum actual attenuation value to the predicted attenuation value;

[0062] In step S220, the first ratio and the second ratio are both correction coefficients. If the first degradation state is the intermediate state of battery degradation simulating 20,000 kilometers of electric vehicle driving, then the first ratio and the second ratio are parameters used to describe the relationship between the predicted degradation data and the actual degradation data of the battery pack in the first degradation state.

[0063] S230, the pre-established battery life simulation model is first corrected according to the first ratio, and the capacity of multiple series-connected cells in the second decay state is predicted according to the first corrected battery life simulation model to obtain the first boundary decay value; the pre-established battery life simulation model is second corrected according to the second ratio, and the capacity of multiple series-connected cells in the second decay state is predicted according to the second corrected battery life simulation model to obtain the second boundary decay value.

[0064] In step S230, the battery life simulation model is corrected using a first ratio to obtain the predicted value at the minimum degradation state, and the battery life simulation model is corrected using a second ratio to obtain the predicted value at the maximum degradation state. Specifically, taking a certain model of electric vehicle as an example, the predicted battery degradation value for multiple cells in the battery pack after 50,000 kilometers under target operating conditions is 8%. However, in actual test data, under the same target operating conditions, the maximum actual degradation value after 50,000 kilometers is 16%, and the minimum actual degradation value is 4%. The battery life simulation model predicts a cell life of 20% after 120,000 kilometers under target operating conditions. Therefore, the first ratio is 4% / 8% = 0.5, and the second ratio is 16% / 8% = 2, thus the first boundary degradation value is 0.5. 20% = 10%, the second boundary attenuation value is 2. 20% = 40%.

[0065] S240, construct a confidence interval for battery life using the first boundary decay value and the second boundary decay value.

[0066] In step S240, after obtaining the first boundary attenuation value and the second attenuation boundary value through step S230, the battery life confidence interval (10%, 40%) constructed based on actual data can be obtained.

[0067] In one embodiment of this application, the process of obtaining the predicted attenuation value of multiple series-connected cells from an initial state to a first attenuation state includes steps S310 to S330, which are described in detail below:

[0068] S310, based on a pre-established battery life simulation model, predicts the capacity values ​​of multiple series-connected cells in the first decay state.

[0069] In this embodiment, the battery life simulation model is an existing prediction model, which is generally a prediction formula. The battery life simulation model makes predictions based on the basic data of multiple series-connected cells in the first decay state. The basic data includes data such as initial charge, voltage, and number of charge-discharge cycles.

[0070] S320, calculate the capacity difference between the initial capacity value and the predicted capacity value, and calculate the ratio of the capacity difference to the initial capacity value to obtain the predicted attenuation value of the plurality of series-connected cells.

[0071] In step S320, multiple series-connected cells are treated as a single battery pack for overall prediction to obtain the predicted attenuation value of the multiple series-connected cells.

[0072] In one embodiment of this application, the process of obtaining the maximum and minimum actual attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state may include steps S410 to S440, which are described in detail below:

[0073] S410, obtain the initial capacity of multiple series-connected cells when they are in the initial state, the remaining capacity of multiple series-connected cells when they are in the first decay state, and the decay time required for multiple series-connected cells to go from the initial state to the first decay state.

[0074] In this embodiment, the initial capacity of the internal cells when the multiple series-connected cells are in the initial state, the remaining capacity of the multiple series-connected cells when they are in the first decay state, and the decay time required for the multiple series-connected cells to go from the initial state to the first decay state are all derived from real experimental data. In addition, the time required for the multiple series-connected cells to go from the initial state to the first decay state is different under different operating conditions. To ensure the accuracy of the data, the corresponding operating conditions predicted by the battery life simulation model in this embodiment are consistent with the operating conditions during the experiment.

[0075] S420, calculate the attenuation rate of the plurality of series-connected cells based on the initial capacity value, the remaining capacity, and the attenuation time;

[0076] In step S420, the decay rate = (initial capacity value - remaining capacity) / decay time;

[0077] S430, the attenuation rate of the plurality of series-connected cells is screened to obtain the maximum attenuation rate and the minimum attenuation rate; and the initial capacity value of the plurality of series-connected cells is screened to obtain the maximum cell capacity and the minimum cell capacity value.

[0078] S440, calculate the minimum actual attenuation value of the cell based on the minimum attenuation rate, the minimum cell capacity value, and the attenuation time, and calculate the maximum actual attenuation value of the cell based on the maximum attenuation rate, the maximum cell capacity, and the attenuation time.

[0079] In this embodiment, to maximize the range of the subsequent confidence interval and cover as many battery degradation scenarios as possible, the maximum degradation rate is paired with the maximum cell capacity, and the minimum degradation rate is paired with the minimum cell capacity to obtain data samples. Based on these data samples, the maximum and minimum actual degradation values ​​of the cell are obtained. Specifically, the minimum actual degradation value = minimum degradation rate. Attenuation time / minimum cell capacity; maximum actual attenuation value = maximum attenuation rate Attenuation time / maximum cell capacity;

[0080] In one embodiment of this application, the process of obtaining the remaining capacity of multiple series-connected cells when they are in a first attenuation state may include steps S510 to S550, which are described in detail below:

[0081] S510 discharges multiple series-connected cells in the first decay state from a fully charged state and obtains the dynamic voltage value and discharge amount of each cell.

[0082] In this embodiment, since multiple cells in the battery pack are connected in series and the specifications of each cell are not exactly the same, the voltage value and discharge amount of each cell are different during discharge, and they need to be collected and calculated separately.

[0083] S520 stops discharging when the dynamic voltage value of any cell drops to the cell cutoff voltage value, and obtains the static voltage value of each cell when discharging stops.

[0084] In this embodiment, when the dynamic voltage value of any cell in the battery pack drops to the cell cutoff voltage value, it is not advisable to continue discharging in order to protect the cell. However, at this time, the other cells in the battery pack still have some charge remaining. Therefore, the remaining charge is estimated by obtaining the static voltage value of each cell when it stops discharging.

[0085] S530, a battery cell with a static voltage value equal to a cutoff voltage value is used as a reference battery cell, and a battery cell with a static voltage value greater than a cutoff voltage value is used as a battery cell to be tested; the stage discharge amount of the reference battery cell when it discharges from the static voltage value to the cutoff voltage value is obtained;

[0086] S540, sum the discharged amount of the battery cell under test and the stage discharge amount of the battery cell under test to obtain the total charge of the battery cell under test;

[0087] In steps S530 and S540, since the specifications of each cell in the same battery pack are similar, the specifications of the reference cell and the cell under test are similar. By obtaining the stage discharge amount of the reference cell when it discharges from the static voltage value to the cutoff voltage value, and using the stage discharge amount as the remaining amount of electricity when the cell under test discharges to the static voltage value, the total amount of electricity of the cell under test can be estimated more accurately.

[0088] S550, sum the discharged amount of the reference cell and the total charge of the cell under test to obtain the remaining capacity of multiple series-connected cells when they are in the first decay state.

[0089] In step S550, the remaining capacity of the battery pack when it is in the first state is obtained by summing the discharged amount of the reference cell and the total current of all the cells to be tested.

[0090] In one embodiment of this application, the process after constructing the confidence interval of battery life using the first boundary decay value and the second boundary decay value may further include steps S610 to S630, which are described in detail below:

[0091] S610, Obtain the measured capacity of multiple control battery packs in the second decay state, wherein the control battery packs include multiple cells connected in series;

[0092] S620, compare the measured capacity of the cells in the control battery pack with the confidence interval to obtain the comparison result;

[0093] S630, The confidence rate of the confidence interval is evaluated based on the comparison results.

[0094] In this embodiment, 30 control battery packs were set up, and the measured remaining capacity of the cells was compared with the confidence interval. Finally, the confidence rate of the distribution interval can be evaluated as 99.87% (±3σ).

[0095] Figure 3 A flowchart illustrating a method for constructing a battery life confidence interval, as shown in another exemplary embodiment of this application, includes the following steps:

[0096] a) By statistically analyzing the voltages of multiple series-connected cells in a battery pack, a curve showing the relationship between cell voltage and discharge capacity can be obtained, such as... Figure 4 As shown, Figure 4 A graph showing the relationship between cell voltage and discharge capacity, illustrating an exemplary embodiment of this application;

[0097] b) By processing the cell voltage-discharge capacity data using Matlab, the actual cell capacity when all series-connected cells reach the cutoff voltage can be calculated.

[0098] c) By statistically analyzing the capacity decay of all cells during the process, multiple sets of cell capacity decay curves can be obtained, such as... Figure 5 As shown, Figure 5 This is a schematic diagram illustrating the attenuation rate of multiple series-connected cells as an exemplary embodiment of this application.

[0099] d) From Figure 2 The two cells with the fastest and slowest degradation were selected from the data to obtain the corresponding degradation rates of these two cells. The battery pack sample degradation values ​​were constructed by matching the largest capacity cell with the largest degradation rate and the smallest capacity cell with the smallest degradation rate in the initial state.

[0100] e) The ratio of the battery pack sample attenuation value constructed using the test data to the calculated value of the life simulation model under the corresponding test conditions is used to obtain the correction coefficient of the life simulation model.

[0101] f) Substitute the distribution coefficient into the lifespan simulation model to calculate the lifespan degradation value of the constructed battery pack sample. Use the degradation value as the upper and lower limits of the distribution interval to statistically determine the lifespan simulation confidence interval. Since the number of test data sets for the battery cells is mostly above 30, the confidence rate of the distribution interval can be assessed as 99.87% (±3σ). Figure 6 As shown, Figure 6 A schematic diagram of confidence intervals is shown in an exemplary embodiment of this application.

[0102] Based on battery test data from a large number of new energy vehicle projects, this application calculates the capacity decay of all cells in the battery pack used in the test during the test, obtains the maximum and minimum decay rates of all cells, and constructs the battery life distribution range by using the initial minimum capacity cell with the minimum decay rate and the maximum capacity cell with the maximum decay rate.

[0103] This application discloses a method for constructing a battery life confidence interval. The method involves calculating a first ratio of the minimum actual degradation value to the predicted degradation value, and a second ratio of the maximum actual degradation value to the predicted degradation value. Based on the first ratio, a pre-established battery life simulation model is first corrected, and the capacity of multiple series-connected cells in a second degradation state is predicted using the corrected model to obtain a first boundary degradation value. Based on the second ratio, the pre-established battery life simulation model is second corrected, and the capacity of multiple series-connected cells in a second degradation state is predicted using the corrected model to obtain a second boundary degradation value. A confidence interval for battery life is constructed using the first and second boundary degradation values. This invention generates correction coefficients based on actually acquired battery degradation data and predicted battery degradation data, and corrects the battery life simulation model. The corrected battery life simulation model is then used to estimate battery life, resulting in a confidence interval based on actual battery degradation data, thus improving the reliability of the confidence interval.

[0104] like Figure 7 As shown, this application also provides an apparatus for constructing a battery life confidence interval, the apparatus comprising:

[0105] The acquisition module is used to obtain the maximum and minimum actual attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state; and to obtain the predicted attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state.

[0106] The calculation module is used to calculate a first ratio of the minimum actual attenuation value to the predicted attenuation value and a second ratio of the maximum actual attenuation value to the predicted attenuation value;

[0107] The correction and prediction module is used to perform a first correction on the pre-established battery life simulation model according to the first ratio, and predict the capacity of multiple series-connected cells in the second decay state according to the first corrected battery life simulation model to obtain a first boundary decay value; and to perform a second correction on the pre-established battery life simulation model according to the second ratio, and predict the capacity of multiple series-connected cells in the second decay state according to the second corrected battery life simulation model to obtain a second boundary decay value.

[0108] A construction module is used to construct a confidence interval for battery life using the first boundary decay value and the second boundary decay value.

[0109] In one embodiment of the present invention, the acquisition module includes:

[0110] The prediction unit is used to predict the capacity values ​​of multiple series-connected cells in the first degradation state based on a pre-established battery life simulation model.

[0111] The first calculation unit calculates the capacity difference between the initial capacity value and the predicted capacity value, and calculates the ratio of the capacity difference to the initial capacity value to obtain the predicted attenuation value of the plurality of series-connected cells.

[0112] In one embodiment of the present invention, the acquisition module includes:

[0113] The acquisition unit is used to acquire the initial capacity of multiple series-connected cells when they are in an initial state, the remaining capacity of multiple series-connected cells when they are in a first attenuation state, and the attenuation time required for multiple series-connected cells to go from the initial state to the first attenuation state.

[0114] The second calculation unit is used to calculate the decay rate of the plurality of series-connected cells based on the initial capacity, the remaining capacity, and the decay time.

[0115] The screening unit is used to screen the attenuation rate of the plurality of series-connected cells to obtain the maximum attenuation rate and the minimum attenuation rate; and to screen the initial capacity value of the plurality of series-connected cells to obtain the maximum cell capacity and the minimum cell capacity value.

[0116] The third calculation unit is used to calculate the minimum actual attenuation value of the battery cell based on the minimum attenuation rate, the minimum cell capacity, and the attenuation time, and to calculate the maximum actual attenuation value of the battery cell based on the maximum attenuation rate, the maximum cell capacity, and the attenuation time.

[0117] This application discloses a device for constructing a battery life confidence interval. The device calculates a first ratio of the minimum actual degradation value to the predicted degradation value and a second ratio of the maximum actual degradation value to the predicted degradation value. Based on the first ratio, a pre-established battery life simulation model is first corrected, and the capacity of multiple series-connected cells in a second degradation state is predicted based on the first corrected battery life simulation model to obtain a first boundary degradation value. Based on the second ratio, the pre-established battery life simulation model is second corrected, and the capacity of multiple series-connected cells in a second degradation state is predicted based on the second corrected battery life simulation model to obtain a second boundary degradation value. A confidence interval for battery life is constructed using the first boundary degradation value and the second boundary degradation value. This invention generates correction coefficients based on actually acquired battery degradation data and predicted battery degradation data, and corrects the battery life simulation model. The battery life is then estimated using the corrected battery life simulation model, resulting in a confidence interval based on actual battery degradation data, thus improving the reliability of the confidence interval.

[0118] It should be noted that the battery life confidence interval construction device provided in the above embodiments and the battery life confidence interval construction method provided in the above embodiments belong to the same concept. The specific operation methods of each module and unit have been described in detail in the method embodiments and will not be repeated here. In practical applications, the battery life confidence interval construction device provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. This is not a limitation here.

[0119] Embodiments of this application also provide an electronic device, including: one or more processors; and a storage device for storing one or more programs, which, when executed by one or more processors, cause the electronic device to implement a method for constructing a battery life confidence interval provided in the above embodiments.

[0120] Figure 8 A schematic diagram of a computer system suitable for implementing the embodiments of this application is shown. It should be noted that... Figure 8 The computer system 800 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0121] like Figure 8 As shown, the computer system 800 includes a Central Processing Unit (CPU) 801, which can perform various appropriate actions and processes, such as executing the methods described in the above embodiments, based on a program stored in Read-Only Memory (ROM) 802 or a program loaded from storage portion 808 into Random Access Memory (RAM) 803. The RAM 803 also stores various programs and data required for system operation. The CPU 801, ROM 802, and RAM 803 are interconnected via a bus 804. An Input / Output (I / O) interface 805 is also connected to the bus 804.

[0122] The following components are connected to I / O interface 805: an input section 806 including a keyboard, mouse, etc.; an output section 807 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 88 is also connected to I / O interface 805 as needed. A removable medium 811, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 88 as needed so that computer programs read from it can be installed into storage section 808 as needed.

[0123] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 809, and / or installed from removable medium 811. When the computer program is executed by central processing unit (CPU) 801, it performs various functions defined in the system of this application.

[0124] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0125] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0126] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0127] Another aspect of this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a computer's processor, causes the computer to perform a method for constructing a battery life confidence interval as described above. This computer-readable storage medium may be included in the electronic device described in the above embodiments, or it may exist independently and not assembled into the electronic device.

[0128] Another aspect of this application provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform a method for constructing a battery life confidence interval provided in the various embodiments described above.

[0129] The above embodiments are merely preferred embodiments provided to fully illustrate this application, and the scope of protection of this application is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on this application are all within the scope of protection of this application.

Claims

1. A method for constructing a confidence interval for battery life, characterized in that, The method includes: The maximum and minimum actual attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state are obtained; and the predicted attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state are obtained; wherein, the predicted attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state are derived from the predictions of multiple cells by the battery life simulation model. Calculate a first ratio of the minimum actual attenuation value to the predicted attenuation value, and a second ratio of the maximum actual attenuation value to the predicted attenuation value; The battery life simulation model is first corrected according to the first ratio, and the capacity of multiple series-connected cells in the second decay state is predicted according to the first corrected battery life simulation model to obtain the first boundary decay value; the battery life simulation model is second corrected according to the second ratio, and the capacity of multiple series-connected cells in the second decay state is predicted according to the second corrected battery life simulation model to obtain the second boundary decay value. A confidence interval for battery life is constructed using the first boundary decay value and the second boundary decay value.

2. The method for constructing a battery life confidence interval according to claim 1, characterized in that: Obtain the predicted attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state, including: Based on a pre-established battery life simulation model, the predicted capacity values ​​of multiple series-connected cells in the first decay state are obtained. Calculate the capacity difference between the initial capacity value and the predicted capacity value, and calculate the ratio of the capacity difference to the initial capacity value to obtain the predicted attenuation value of the plurality of series-connected cells.

3. The method for constructing a battery life confidence interval according to claim 1, characterized in that: Obtain the maximum and minimum actual attenuation values ​​of multiple series-connected cells from the initial state to the first attenuation state, including: The initial capacity value of multiple series-connected cells in the initial state, the remaining capacity of multiple series-connected cells in the first decay state, and the decay time required for multiple series-connected cells to go from the initial state to the first decay state are obtained. The decay rate of the plurality of series-connected cells is calculated based on the initial capacity value, the remaining capacity, and the decay time. The decay rates of the multiple series-connected cells are screened to obtain the maximum decay rate and the minimum decay rate; and the initial capacity values ​​of the multiple series-connected cells are screened to obtain the maximum cell capacity and the minimum cell capacity value. The minimum actual attenuation value of the battery cell is calculated based on the minimum attenuation rate, the minimum cell capacity, and the attenuation time, and the maximum actual attenuation value of the battery cell is calculated based on the maximum attenuation rate, the maximum cell capacity, and the attenuation time.

4. The method for constructing a battery life confidence interval according to claim 3, characterized in that: Obtain the remaining capacity of multiple series-connected cells when they are in the first decay state, including: Discharge multiple series-connected cells in the first decay state starting from a fully charged state, and obtain the dynamic voltage value and discharge amount of each cell; Discharge is stopped when the dynamic voltage value of any cell drops to the cell cutoff voltage value, and the static voltage value of each cell at the point of stopping discharge is obtained. A battery cell with a static voltage value equal to a cutoff voltage value is used as a reference battery cell, and a battery cell with a static voltage value greater than a cutoff voltage value is used as a battery cell to be tested; the discharge amount of the reference battery cell when it discharges from the static voltage value to the cutoff voltage value is obtained; The total charge of the battery cell under test is obtained by summing the discharged amount and the staged discharge amount of the battery cell under test. The remaining capacity of multiple series-connected cells when they are in the first decay state is obtained by summing the discharged amount of the reference cell and the total charge of the cell under test.

5. The method for constructing a battery life confidence interval according to claim 1, characterized in that: After constructing the confidence interval for battery life using the first boundary decay value and the second boundary decay value, the method further includes: The measured capacity of multiple control battery packs in the second decay state was obtained, wherein the control battery packs comprised multiple cells connected in series. The measured capacity of the cells in the control battery pack is compared with the confidence interval to obtain the comparison results; The confidence rate of the confidence interval is evaluated based on the comparison results.

6. An apparatus for constructing a confidence interval for battery life, characterized in that, The device includes: The acquisition module is used to obtain the maximum and minimum actual decay values ​​of multiple series-connected cells from the initial state to the first decay state; and to obtain the predicted decay values ​​of multiple series-connected cells from the initial state to the first decay state; wherein, the predicted decay values ​​of multiple series-connected cells from the initial state to the first decay state are derived from the predictions of the multiple cells by the battery life simulation model. The calculation module is used to calculate a first ratio of the minimum actual attenuation value to the predicted attenuation value and a second ratio of the maximum actual attenuation value to the predicted attenuation value; The correction and prediction module is used to perform a first correction on the pre-established battery life simulation model according to the first ratio, and predict the capacity of multiple series-connected cells in the second decay state according to the first corrected battery life simulation model to obtain a first boundary decay value; and to perform a second correction on the pre-established battery life simulation model according to the second ratio, and predict the capacity of multiple series-connected cells in the second decay state according to the second corrected battery life simulation model to obtain a second boundary decay value. A construction module is used to construct a confidence interval for battery life using the first boundary decay value and the second boundary decay value.

7. The apparatus for constructing a battery life confidence interval according to claim 6, characterized in that, The acquisition module includes: The prediction unit is used to predict the capacity values ​​of multiple series-connected cells in the first degradation state based on a pre-established battery life simulation model. The first calculation unit calculates the capacity difference between the initial capacity value and the predicted capacity value, and calculates the ratio of the capacity difference to the initial capacity value to obtain the predicted attenuation value of the plurality of series-connected cells.

8. The apparatus for constructing a battery life confidence interval according to claim 6, characterized in that: The acquisition module includes: The acquisition unit is used to acquire the initial capacity value of multiple series-connected cells when they are in the initial state, the remaining capacity of multiple series-connected cells when they are in the first decay state, and the decay time required for multiple series-connected cells to go from the initial state to the first decay state. The second calculation unit is used to calculate the decay rate of the plurality of series-connected cells based on the initial capacity value, the remaining capacity, and the decay time. The screening unit is used to screen the attenuation rate of the plurality of series-connected cells to obtain the maximum attenuation rate and the minimum attenuation rate; and to screen the initial capacity value of the plurality of series-connected cells to obtain the maximum cell capacity and the minimum cell capacity value. The third calculation unit is used to calculate the minimum actual attenuation value of the battery cell based on the minimum attenuation rate, the minimum cell capacity, and the attenuation time, and to calculate the maximum actual attenuation value of the battery cell based on the maximum attenuation rate, the maximum cell capacity, and the attenuation time.

9. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, cause the electronic device to implement a method for constructing a battery life confidence interval as described in any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that, It stores computer-readable instructions that, when executed by the computer's processor, cause the computer to perform a method for constructing a battery life confidence interval according to any one of claims 1 to 5.

Images