A method and system for identifying electrochemical parameters of a lithium battery

Abstract

The application discloses a lithium battery electrochemical parameter identification method and system, wherein the method comprises the following steps: performing iterative circulation on an initialization parameter set of an electrochemical model; generating a disturbance parameter set by disturbing the initialization parameter set during the iteration process; calculating the difference value between the simulated battery working condition and the real battery working condition generated by the initialization parameter set / disturbance parameter set; judging whether the initialization parameter set is a local optimal parameter set according to the difference value of the initialization parameter set / disturbance parameter set; setting a global optimal parameter set according to the local optimal parameter set; judging whether the global optimal parameter set is less than a preset value; if not, entering a loop, that is, iteratively performing the initialization parameter set until the global optimal parameter set is less than the preset value, and outputting the global optimal parameter set as the electrochemical parameter; and limiting the value range of the initialization parameter set through a tabu stack and a medium-term table, so that the number of iterations is reduced, and the efficiency of electrochemical parameter evaluation is improved.

Description

Technical Field

[0001] This invention relates to the field of batteries, and specifically to a method and system for identifying electrochemical parameters of lithium batteries. Background Technology

[0002] There are two main approaches to modeling the state of lithium-ion batteries. One approach treats the battery as a connection of abstract circuit elements, known as the equivalent circuit model. The other approach uses coupled partial differential equations to describe the physicochemical processes within the lithium-ion battery; this is the electrochemical model. The equivalent circuit model offers simple numerical simulations but low accuracy; the electrochemical model, on the other hand, is highly accurate, predictive, and better helps in understanding the true internal state of the battery. For example, the P2D (pseudo-two-dimensional) electrochemical model for lithium-ion batteries can accurately simulate the electrochemical processes during charging and discharging, but it requires dozens of electrochemical parameters with real physicochemical significance to characterize the internal material states of the battery. Obtaining these parameters is extremely difficult. Experimentally, different methods yield different values ​​for the same electrochemical parameter, and many experimental methods are destructive to lithium-ion batteries. Summary of the Invention

[0003] To address the difficulty in determining the electrochemical parameters of lithium batteries, this invention provides a method and system for identifying lithium battery electrochemical parameters.

[0004] Specifically, the technical solution of the present invention is as follows:

[0005] In a first aspect, the present invention discloses a method for identifying electrochemical parameters of lithium batteries, comprising:

[0006] Initialize the tabu stack, intermediate table, and global optimal parameter set;

[0007] Sample the battery control condition sequence and select a set of initial lithium battery electrochemical parameters to generate a first initial parameter set in vector form;

[0008] When the first initial parameter set is not within the range limited by the taboo stack, each parameter in the first initial parameter set is iteratively perturbed to generate several first perturbation parameter sets;

[0009] The first initial parameter set / several first disturbance parameter sets and the battery control condition sequence are substituted into the electrochemical model for evaluation to generate a simulated battery condition sequence.

[0010] Sample the actual battery operating condition sequence and calculate the difference between the simulated battery operating condition sequence and the actual battery operating condition sequence;

[0011] When the difference values ​​calculated using the aforementioned first perturbation parameter sets are all greater than the difference values ​​calculated using the first initial parameter set, the first initial parameter set is taken as the local optimal parameter set.

[0012] Update the difference values ​​calculated for the global optimal parameter set based on the difference values ​​of the local optimal parameter set;

[0013] When the difference value calculated by the global optimal parameter set is greater than the preset value, a second initial parameter set is generated according to the first initial parameter set. The first initial parameter set in the previous step is replaced with the second initial parameter set, and the previous steps are repeated to update the global optimal parameter set again.

[0014] The process is repeated until the difference value calculated from the global optimal parameter set is less than the preset value or the number of repetitions corresponding to the repeated execution of the aforementioned steps reaches the preset maximum number of cycles. Then, the global optimal parameter set is output as the final electrochemical parameters of the lithium battery.

[0015] This implementation method determines the electrochemical parameters of lithium batteries by iteratively analyzing the initial electrochemical parameters without being limited by the taboo stack.

[0016] In some implementations of lithium battery electrochemical parameter identification methods, the control condition sequence is one of the battery condition sequences, which includes a voltage condition sequence, a current condition sequence, and a temperature condition sequence. The simulated battery condition sequence is the battery condition sequence other than the control condition sequence generated by the electrochemical model.

[0017] This implementation method provides examples of the different operating conditions of lithium batteries, specifically illustrating the types of control operating conditions incorporated into the electrochemical model and the types of battery operating condition sequences output by the electrochemical model.

[0018] In some implementations of lithium battery electrochemical parameter identification methods, the difference value is calculated using a difference quantification formula. Where MSE is the difference value, n is the number of sampling time points, i is a positive integer, and u sim,i U is the battery condition value at time point i in the simulated battery condition sequence. real,i It is the battery condition value at time point i in the actual battery condition sequence, a i It is the battery operating condition weight at time point i.

[0019] This implementation method uses a difference quantification calculation formula to calculate the difference value of lithium batteries. The difference values ​​at different time points are weighted and then summed and averaged. The weighted value can be determined by the curvature of the change of operating conditions and time. The faster the operating conditions change with time, the larger the weighted value. This formula can converge to obtain the electrochemical parameters of lithium batteries more quickly.

[0020] In some implementations of lithium battery electrochemical parameter identification methods, after using the first initial parameter set as a locally optimal parameter set, the method further includes:

[0021] If the difference value calculated by the local optimal parameter set is greater than the difference value calculated by the global optimal parameter set, then the local optimal parameter set is written into the taboo stack, and the parameter set at the tail of the taboo stack is popped from the stack.

[0022] This implementation method uses a tabu stack. When the local optimal parameter set is not the optimal solution, the local optimal parameter set is pushed onto the stack, and the parameter set at the end of the tabu list is popped from the stack. This method can avoid repeated searches around the local optimal parameter set that is not the optimal solution in a short period of time.

[0023] In some implementations of lithium battery electrochemical parameter identification methods, after the step of writing the local optimal parameter set into the taboo stack, the method further includes:

[0024] In the multidimensional space of electrochemical parameters, determine whether the distance between the local optimal parameter set and the parameter set in the intermediate table is less than a preset value;

[0025] When the distance between the local optimal parameter set and the parameter set in the intermediate table is less than a preset value, the parameter set in the intermediate table is selected, and the geometric center point of the local optimal parameter set and the parameter set in the intermediate table in the multidimensional space of electrochemical parameters is calculated.

[0026] Write the parameter set corresponding to the geometric center point into the intermediate table;

[0027] The intermediate table is equipped with penalty logic, which sets penalty items for the parameter set neighborhood in the intermediate table.

[0028] This implementation method uses an intermediate table. In the multidimensional space of electrochemical parameters, when the parameter set added to the tabu stack is within a certain range of the parameter set in the intermediate table, the geometric center point is taken between the parameter set added to the tabu stack and the parameter set in the intermediate table. The parameter set corresponding to the geometric center point is written into the intermediate table. Based on the penalty term for the parameter set in the intermediate table, the method can effectively avoid obtaining the same local optimum multiple times.

[0029] Secondly, this invention discloses a lithium battery electrochemical parameter identification system, comprising:

[0030] Initialization module: Used to initialize the tabu stack, intermediate table, and global optimal parameter set;

[0031] Sampling control module: used to sample the battery control condition sequence and select a set of initial lithium battery electrochemical parameters to generate a first initial parameter set in vector form;

[0032] Iterative perturbation module: used to iteratively perturb each parameter in the first initial parameter set when the first initial parameter set is not within the range limited by the taboo stack, and generate several first perturbation parameter sets;

[0033] Electrochemical model module: used to input the first initial parameter set / several first perturbation parameter sets and the battery control condition sequence into the electrochemical model for evaluation, and generate a simulated battery operating condition sequence;

[0034] The sampling control module is further configured to sample the actual battery operating condition sequence and calculate the difference between the simulated battery operating condition sequence and the actual battery operating condition sequence.

[0035] Judgment module: When the difference values ​​calculated using the plurality of first disturbance parameter sets are all greater than the difference values ​​calculated using the first initial parameter set, the first initial parameter set is taken as the local optimal parameter set;

[0036] The parameter update module is used to update the difference value calculated from the global optimal parameter set based on the difference value of the local optimal parameter set.

[0037] The judgment module is further configured to determine that when the difference value calculated by the global optimal parameter set is greater than a preset value, generate a second initial parameter set based on the first initial parameter set, and update the global optimal parameter set again through the aforementioned module in a loop.

[0038] Output module: Repeat the loop until the difference value calculated by the global optimal parameter set is less than the preset value or the number of repetitions corresponding to the repeated execution of the aforementioned steps reaches the preset maximum number of loops, and then output the global optimal parameter set as the final electrochemical parameters of the lithium battery.

[0039] This system rapidly determines the electrochemical parameters of a lithium battery by iteratively searching the initial electrochemical parameters within the limited range of the taboo stack.

[0040] In some implementation methods of lithium battery electrochemical parameter identification systems, the difference value in the sampling control module is calculated using a difference quantification formula. Calculate, where MSE is the difference value, n is the number of sampling time points, i is a positive integer, and u sim,i U is the battery condition value at time point i in the simulated battery condition sequence.real,i It is the battery condition value at time point i in the actual battery condition sequence, a i It is the battery operating condition weight at time point i.

[0041] The sampling control module of this system uses a difference quantification calculation formula to calculate the difference value of lithium batteries. The difference values ​​at different time points are weighted and then summed and averaged to obtain the electrochemical parameters of lithium batteries more quickly.

[0042] In some implementations of lithium battery electrochemical parameter identification systems, the calculation module further includes a taboo stack processing submodule: when the difference value calculated by the local optimal parameter set is greater than the difference value calculated by the global optimal parameter set, the local optimal parameter set is written into the taboo stack, and the parameter set at the tail of the taboo stack is popped from the stack.

[0043] The computation module of this system uses a tabu stack. When the local optimal parameter set is not the optimal solution, the local optimal parameter set is pushed onto the stack, and the parameter set at the end of the tabu list is popped off the stack. This method can avoid repeated searches around the local optimal parameter set that is not the optimal solution in a short period of time.

[0044] In some implementations of lithium battery electrochemical parameter identification systems, the calculation module further includes an intermediate table processing submodule: when the distance between the locally optimal parameter set in the multidimensional space of electrochemical parameters and the parameter set in the intermediate table is less than a preset value, the submodule selects the parameter set in the intermediate table, calculates the geometric center point between the several locally optimal parameter sets and the parameter set in the intermediate table, and writes the parameter set corresponding to the geometric center point into the intermediate table. The intermediate table processing submodule is equipped with penalty logic to set a penalty term for the neighborhood of the parameter set in the intermediate table.

[0045] The calculation module of this system uses an intermediate table. In the multidimensional space of electrochemical parameters, when the parameter set added to the tabu stack is within a certain range of the parameter set in the intermediate table, the geometric center point is taken between the parameter set added to the tabu stack and the parameter set in the intermediate table. The parameter set corresponding to the geometric center point is written into the intermediate table. Based on the penalty term of the parameter set in the intermediate table, the system can effectively avoid obtaining the same local optimum multiple times.

[0046] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements a lithium battery electrochemical parameter identification method as described in any of the preceding claims.

[0047] Compared with the prior art, the method for identifying electrochemical parameters of lithium batteries provided by the present invention has at least one of the following advantages:

[0048] 1. This invention iterates over the first initial parameter set of the electrochemical model, and during the iteration process, calculates the difference between the simulated battery conditions and the real battery conditions generated by the first initial parameter set and several first perturbation parameter sets after iteration. It determines the relationship between the magnitudes of the difference values ​​of the several first perturbation parameter sets and the first initial parameter set, obtains the locally optimal parameter set, and updates the tabu stack and intermediate table. The difference value of the locally optimal parameter set with the smallest difference value is set as the difference value of the globally optimal parameter set. Then, a second initial parameter set is randomly generated within a certain range around the first initial parameter set, and this process is repeated until the globally optimal parameter set is less than a preset value. This globally optimal parameter set is then used as the obtained lithium battery electrochemical parameters. This invention solves the problem of difficulty in calculating electrochemical parameters by iteratively substituting the first initial parameter set into the sequence obtained from the electrochemical model to calculate the difference value, and by selecting the one with the smallest difference value as the globally optimal parameter set. Furthermore, it allows for a good balance between the accuracy of the obtained electrochemical parameters and the parameter calculation time by adjusting the preset value.

[0049] 2. The present invention performs a weighted average of different time points on the differential quantification calculation formula. The weighting value can be determined by the curvature of the change of operating conditions and time. The faster the operating conditions change with time, the larger the weighting value. The weighted calculation formula can make the electrochemical parameters converge faster.

[0050] 3. This invention limits the selection range of the initial parameter set by using a taboo stack and an intermediate table, avoiding the selection of adjacent initial parameter sets multiple times within a preset range in a short period of time, thus helping to converge and lock in electrochemical parameter values ​​more quickly. Attached Figure Description

[0051] The preferred embodiments will now be described in a clear and easy-to-understand manner, in conjunction with the accompanying drawings, to further explain the above-mentioned characteristics, technical features, advantages, and implementation methods of the present invention.

[0052] Figure 1 This is a flowchart of an embodiment of a lithium battery electrochemical parameter identification method according to the present invention;

[0053] Figure 2 This is a flowchart of an embodiment of a lithium battery electrochemical parameter identification method according to the present invention;

[0054] Figure 3 This is a structural block diagram of an embodiment of a lithium battery electrochemical parameter identification system of the present invention.

[0055] The diagram numbers are explained as follows: 10--Initialization module, 20--Sampling control module, 30--Iterative perturbation module, 40--Electrochemical model module, 50--Judgment module, 51--Taboo stack sub-module, 52--Interim table sub-module, 60--Output module. Detailed Implementation

[0056] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the specific implementation methods of the present invention will be described below with reference to the accompanying drawings. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings and other implementation methods can be obtained based on these drawings without any creative effort.

[0057] To keep the drawings concise, each figure only schematically shows the parts relevant to the invention, and these do not represent the actual structure of the product. Furthermore, to facilitate understanding, in some figures, only one of components with the same structure or function is schematically depicted, or only one is labeled. In this document, "one" not only means "only one," but can also mean "more than one."

[0058] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0059] In this document, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0060] Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0061] In one embodiment, refer to the appendix to the specification. Figure 1 An embodiment of a lithium battery electrochemical parameter identification method provided by the present invention includes:

[0062] S101 initializes the tabu stack, intermediate table, and global optimal parameter set, and assigns the loop variable k the value 1.

[0063] In step S101, the taboo stack prohibits the selection of parameter sets in the neighborhood of the parameter sets in the taboo stack from being substituted into the model and for calculating the difference value. The neighborhood range can be set by the user. The intermediate table adds a penalty term to the neighborhood of the parameter sets in the intermediate table. The globally optimal parameter set is the parameter set with the smallest difference value calculated in the current loop.

[0064] S102 samples the battery control condition sequence.

[0065] The type of battery control condition sequence in step S102 is determined by the actual battery control method. For example, if the actual battery is controlled by voltage, then the battery control condition sequence is a voltage-time sequence.

[0066] S103 selects a set of initial lithium battery electrochemical parameters to generate the k-th initial parameter set in vector form.

[0067] In step S103, when k = 1, the first initial parameter set can be selected from the factory battery parameter set or the previous electrochemical parameter identification result. When k > 1, the k-th initial parameter set is randomly selected from a preset range around the (k-1)-th initial parameter set. Other methods can also be used to select the initial parameter set.

[0068] S104 determines whether the k-th initial parameter set is within the range defined by the taboo stack. If the k-th initial parameter set is within the range defined by the taboo stack, it is necessary to return to S103 and re-evaluate the k-th initial parameter set.

[0069] Step S104 avoids selecting adjacent parameter sets multiple times in a short period of time during the loop process, reduces the number of iterations, and speeds up the calculation efficiency of electrochemical parameters.

[0070] S105 perturbs the k-th initial parameter set to generate several k-th perturbation parameter sets.

[0071] The several sets of perturbation parameters generated in step S105 are obtained by perturbing each parameter of the initial set of parameters k one by one.

[0072] S106 inputs the k-th initial parameter set / several k-th perturbation parameter sets and the battery control condition sequence into the electrochemical model for evaluation, generating a simulated battery condition sequence.

[0073] S107 samples the actual battery operating condition sequence and calculates the difference between the simulated battery operating condition sequence and the actual battery operating condition sequence;

[0074] The difference value in step S107 is the criterion for judging whether the currently selected k-th initial parameter set is a local optimum, a global optimum, or the final electrochemical parameter. The smaller the difference value, the better the k-th initial parameter.

[0075] S108 When the difference values ​​calculated using the kth perturbation parameter set are all greater than the difference values ​​calculated using the kth initial parameter set, the kth initial parameter set is taken as the local optimal parameter set.

[0076] Step S108 selects the k-th initial parameter set that satisfies the condition of being better than all k-th perturbation parameter sets as the local optimal parameter set.

[0077] The difference value calculated by the local optimal parameter set S109 is compared with the difference value calculated by the global optimal parameter set;

[0078] S110 When the difference value calculated by the local optimal parameter set is less than the difference value calculated by the global optimal parameter set, the difference value calculated by the global optimal parameter set is replaced with the difference value calculated by the local optimal parameter set;

[0079] In step S110, the difference value of the global optimal solution is continuously updated in the loop, so that the difference value of the global optimal solution is kept to be the difference value of the local optimal solution with the smallest historical value.

[0080] S111 When the number of iterations is within the preset maximum number of iterations, and the difference value calculated by the global optimal parameter set is greater than the preset value, generate the (k+1)th initial parameter set according to the kth initial parameter set, replace the kth initial parameter set in the previous step with the (k+1)th initial parameter set, and repeat the previous step to update the global optimal parameter set again.

[0081] Step S111 sets the loop conditions in the lithium battery parameter identification method: the difference value converges to the preset value or the number of loops reaches the upper limit. In each loop, the loop variable k is incremented by 1, and the k-th initial parameter set is randomly generated within a preset range around the (k-1)-th initial parameter set.

[0082] S112 repeats the loop until the difference value calculated by the global optimal parameter set is less than the preset value or the number of repetitions corresponding to the repeated execution of the aforementioned steps exceeds the preset maximum number of loops. Then, the global optimal parameter set is output as the final electrochemical parameters of the lithium battery.

[0083] When the loop conditions of step S111 are met, the output of the global optimal parameter set of the current loop in step S112 is the lithium battery electrochemical parameter that this method needs to calculate.

[0084] This embodiment iterates over the k-th initial parameter set of the electrochemical model, calculating the difference between the k-th initial parameter set and several k-th perturbation parameter sets after iteration. It then determines the relationship between the differences between these k-th perturbation parameter sets and the k-th initial parameter set, obtaining a locally optimal parameter set. The tabu stack and intermediate table are updated, and the difference value of the locally optimal parameter set with the smallest historical difference is set as the difference value of the globally optimal parameter set. Next, a (k+1)-th initial parameter set is randomly generated within a certain range around the k-th initial parameter set, and this process is repeated until the globally optimal parameter set is less than a preset value or reaches a preset maximum number of iterations. The globally optimal parameter set is then used as the obtained lithium-ion battery electrochemical parameters. This embodiment solves the problem of difficulty in calculating electrochemical parameters by iteratively substituting the first initial parameter set into the sequence obtained from the electrochemical model and calculating the difference value, finding the set with the smallest difference value as the globally optimal parameter set. Furthermore, by adjusting the preset value, a good balance can be achieved between the accuracy of the obtained electrochemical parameters and the parameter calculation time. In addition, the tabu stack limits the search range, reducing the number of iterations.

[0085] This embodiment, based on the previous embodiment, provides a method for identifying electrochemical parameters of lithium batteries. The control condition sequence is one of the battery condition sequences, which includes a voltage condition sequence, a current condition sequence, and a temperature condition sequence. The simulated battery condition sequence is the battery condition sequence other than the control condition sequence generated by the electrochemical model.

[0086] This embodiment compares multiple battery operating condition sequences with multiple sampled actual battery operating condition sequences to obtain multiple difference values. Different local optimal parameter sets and different global optimal parameter sets are obtained through different calculation methods for these difference values, ultimately leading to more accurate electrochemical parameters. For example, the control operating condition sequence for a lithium battery is a voltage operating condition sequence, while the battery operating condition sequence consists of a current operating condition sequence and a temperature operating condition sequence. The difference value calculation method involves comparing the simulated voltage operating condition sequence with the actual voltage operating condition sequence to determine the local optimal parameter set and the global optimal parameter set for voltage. Similarly, the difference value calculation method involves comparing the simulated temperature operating condition sequence with the actual temperature operating condition sequence to determine the local optimal parameter set and the global optimal parameter set for temperature.

[0087] This embodiment, based on the above embodiments, provides a method for identifying electrochemical parameters of lithium batteries. The difference values ​​in the above embodiments are calculated using a difference quantification formula. Where MSE is the difference value, n is the number of sampling time points, i is a positive integer, and u sim,i U is the battery condition value at time point i in the simulated battery condition sequence. real,iIt is the battery condition value at time point i in the actual battery condition sequence, a i It is the battery operating condition weight at time point i.

[0088] This embodiment calculates the difference value of lithium battery using a difference quantification calculation formula. The difference values ​​at different time points are weighted and then summed and averaged. The weighted value can be determined by the curvature of the change in operating conditions and time. The faster the operating conditions change with time, the larger the weighted value. This formula can converge to obtain the electrochemical parameters of lithium battery more quickly.

[0089] This embodiment is based on the above embodiment, and refers to the appendix to the specification. Figure 2 A method for identifying electrochemical parameters of lithium batteries is provided, which, after step S109, further includes the following step:

[0090] S210: When the difference value calculated by the local optimal parameter set is greater than the difference value calculated by the global optimal parameter set, the local optimal parameter set is written into the taboo stack.

[0091] S211: Pop the parameter set from the tail of the taboo stack.

[0092] This embodiment avoids unnecessary and repetitive searches by adding locally optimal parameter sets that are not globally optimal to the tabu stack. This is done by adding such sets to the tabu stack. Only when new locally optimal parameter sets are continuously added to the tabu stack and the locally optimal parameter sets are popped from the end of the stack can searches be performed on the parameter sets adjacent to the locally optimal parameter sets.

[0093] This embodiment, based on the previous embodiment, provides a method for identifying electrochemical parameters of lithium batteries. Following step S211 of the previous embodiment, the method further includes: determining whether the distance between the locally optimal parameter set and the parameter set in the intermediate table is less than a preset value in the multidimensional space of electrochemical parameters; if the distance between the locally optimal parameter set and the parameter set in the intermediate table is less than the preset value, selecting the parameter set in the intermediate table, calculating the geometric center point of the locally optimal parameter set and the parameter set in the intermediate table in the multidimensional space of electrochemical parameters; writing the parameter set corresponding to the geometric center point into the intermediate table; the intermediate table is equipped with penalty logic, setting penalty terms for the neighborhood of the parameter set in the intermediate table.

[0094] In this embodiment, in addition to restricting the k-th initial parameter set through the tabu stack, an intermediate table is added. The parameter update method of the intermediate table is to take the geometric center point of the parameter set in the intermediate table and the locally optimal parameter set that meets the conditions as the parameter set in the new intermediate table. The intermediate table serves to set penalty logic for the k-th initial parameter set that is close to the parameter set in the intermediate table.

[0095] Specifically, if the local optimal parameter set is near a parameter set in the intermediate table, the penalty variable n of this parameter set in the intermediate table is incremented by 1, and the weighted geometric center of this parameter set and the local optimal parameter set in the intermediate table is calculated to replace the previous parameter set. When the size of n meets certain conditions, the neighborhood of the replaced intermediate table parameter set is set as a region where the search of the k-th initial parameter set is prohibited.

[0096] In one embodiment, refer to the appendix to the specification. Figure 3 The present invention provides a lithium battery electrochemical parameter identification system, comprising:

[0097] Initialization module 10: Used to initialize the tabu stack, intermediate table, and global optimal parameter set;

[0098] Sampling control module 20: used to sample the battery control condition sequence and select a set of initial lithium battery electrochemical parameters to generate the k-th initial parameter set in vector form;

[0099] Iterative perturbation module 30: When the k-th initial parameter set is not within the range limited by the taboo stack, iteratively perturb each parameter in the k-th initial parameter set to generate several k-th perturbation parameter sets;

[0100] Electrochemical model module 40: used to input the k-th initial parameter set / several k-th perturbation parameter sets and the battery control condition sequence into the electrochemical model for evaluation, and generate a simulated battery operating condition sequence;

[0101] The sampling control module is further configured to sample the actual battery operating condition sequence and calculate the difference between the simulated battery operating condition sequence and the actual battery operating condition sequence.

[0102] Judgment module 50: When it is determined that the difference values ​​calculated using the plurality of k-th perturbation parameter sets are all greater than the difference values ​​calculated using the k-th initial parameter set, the k-th initial parameter set is taken as the local optimal parameter set;

[0103] The judgment module 50 is used to update the difference value calculated from the global optimal parameter set based on the difference value of the local optimal parameter set.

[0104] The judgment module 50 is further configured to: when the difference value calculated by the global optimal parameter set is greater than the preset value, generate the (k+1)th initial parameter set according to the kth initial parameter set, and cyclically update the global optimal parameter set through the aforementioned module;

[0105] Output module 60: Repeat the loop until the difference value calculated by the global optimal parameter set is less than the preset value or the number of repetitions corresponding to the repeated execution of the aforementioned steps reaches the preset maximum number of loops, and then output the global optimal parameter set as the final electrochemical parameters of the lithium battery.

[0106] This embodiment calculates the difference values ​​of the sequence obtained by iteratively iterating the initial parameter set through the electrochemical model module, and selects the one with the smallest difference value as the global optimal parameter set, which solves the problem of difficulty in calculating electrochemical parameters. It can also achieve a good balance between the accuracy of the calculated electrochemical parameters and the parameter calculation time by adjusting the size of the preset value.

[0107] This embodiment, based on the previous embodiment, provides a lithium battery electrochemical parameter identification system, including:

[0108] The difference value in the sampling control module is calculated using a difference quantization formula. Calculate, where MSE is the difference value, n is the number of sampling time points, i is a positive integer, and u sim,i U is the battery condition value at time point i in the simulated battery condition sequence. real,i It is the battery condition value at time point i in the actual battery condition sequence, a i It is the battery operating condition weight at time point i.

[0109] This embodiment calculates the difference value of lithium battery using a difference quantification calculation formula. The difference values ​​at different time points are weighted and then summed and averaged. The weighted value can be determined by the curvature of the change in operating conditions and time. The faster the operating conditions change with time, the larger the weighted value. This formula can converge to obtain the electrochemical parameters of lithium battery more quickly.

[0110] Based on the above embodiments, this embodiment provides a lithium battery electrochemical parameter identification system, including:

[0111] The judgment module 50 further includes a taboo stack processing submodule 51: when the difference value calculated by the local optimal parameter set is greater than the difference value calculated by the global optimal parameter set, the local optimal parameter set is written into the taboo stack, and the parameter set at the tail of the taboo stack is popped from the stack.

[0112] This embodiment uses a tabu stack processing submodule to add locally optimal parameter sets that are not globally optimal to the tabu stack. This avoids repeatedly selecting parameter sets adjacent to the locally optimal parameter set in a short period of time and performing unnecessary repetitive searches. Only when new locally optimal parameter sets are continuously added to the tabu stack and the locally optimal parameter set is popped from the end of the stack is it allowed to search the parameter sets adjacent to the locally optimal parameter set.

[0113] This embodiment, based on the previous embodiment, provides a lithium battery electrochemical parameter identification system, including:

[0114] The judgment module 50 further includes an intermediate table processing submodule 52: when the distance between the local optimal parameter set in the multidimensional space of electrochemical parameters and the parameter set in the intermediate table is less than a preset value, the parameter set in the intermediate table is selected, the geometric center point between the several local optimal parameter sets and the parameter set in the intermediate table is calculated, and the parameter set corresponding to the geometric center point is written into the intermediate table. The intermediate table processing submodule is equipped with penalty logic to set a penalty item for the neighborhood of the parameter set in the intermediate table.

[0115] This embodiment, based on the taboo stack processing submodule added in the previous embodiment, adds an intermediate table processing submodule. The parameter update method in the intermediate table is to take the geometric center point of the parameter set in the intermediate table and the locally optimal parameter set that meets the conditions as the parameter set in the new intermediate table. The intermediate table sets a penalty logic for the k-th initial parameter set that is close to the parameter set in the intermediate table. This reduces the number of iterations and helps to lock the electrochemical parameter values ​​more quickly.

[0116] In one embodiment of the present invention, a computer-readable storage medium stores a computer program thereon. When executed by a processor, the computer program can implement a lithium battery electrochemical parameter identification method as described in the foregoing embodiments. That is, when part or all of the technical solutions contributing to the prior art in the foregoing embodiments of the present invention are embodied in the form of a computer software product, the aforementioned computer software product is stored in a computer-readable storage medium. The computer-readable storage medium can be any physical device or apparatus capable of carrying computer program code. For example, the computer-readable storage medium can be a USB flash drive, a portable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, etc.

[0117] It should be noted that the above embodiments can be freely combined as needed. The above are merely preferred embodiments of the present invention. It should be pointed out that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for identifying electrochemical parameters of lithium batteries, characterized in that, include: Initialize the tabu stack, intermediate table, and global optimal parameter set; Sample the battery control condition sequence and select a set of initial lithium battery electrochemical parameters to generate the first initial parameter set; When the first initial parameter set is not within the range limited by the taboo stack, each parameter in the first initial parameter set is iteratively perturbed to generate several first perturbation parameter sets; The first initial parameter set / several first disturbance parameter sets and the battery control condition sequence are substituted into the electrochemical model for evaluation to generate a simulated battery condition sequence. Sample the actual battery operating condition sequence and calculate the difference between the simulated battery operating condition sequence and the actual battery operating condition sequence; The difference value is calculated using the difference quantification formula. Where MSE is the difference value, n is the number of sampling time points, and i is a positive integer. It is the battery condition value at the i-th time point of the simulated battery condition sequence. It is the battery condition value at the i-th time point of the actual battery condition sequence. It is the battery condition weight at time point i; The control condition sequence is one of the battery condition sequences, which includes a voltage condition sequence, a current condition sequence, and a temperature condition sequence. The simulated battery condition sequence is the battery condition sequence other than the control condition sequence generated by the electrochemical model. When the difference values ​​calculated using the aforementioned first perturbation parameter sets are all greater than the difference values ​​calculated using the first initial parameter set, the first initial parameter set is taken as the local optimal parameter set. Update the difference values ​​calculated for the global optimal parameter set based on the difference values ​​of the local optimal parameter set; When the loop is within the preset maximum number of loops, and the difference value calculated by the global optimal parameter set is greater than the preset value, a second initial parameter set is generated based on the first initial parameter set. The first initial parameter set in the previous steps is replaced with the second initial parameter set, and the previous steps are repeated to update the global optimal parameter set again. The process is repeated until the difference value calculated by the global optimal parameter set is less than the preset value or the number of repetitions corresponding to the repeated execution of the aforementioned steps reaches the preset maximum number of cycles. Then, the global optimal parameter set is output as the final electrochemical parameters of the lithium battery. After using the first initial parameter set as the local optimal parameter set, the method further includes: If the difference value calculated by the local optimal parameter set is greater than the difference value calculated by the global optimal parameter set, then the local optimal parameter set is written into the taboo stack, and the parameter set at the tail of the taboo stack is popped from the stack. In the multidimensional space of electrochemical parameters, determine whether the distance between the local optimal parameter set and the parameter set in the intermediate table is less than a preset value; When the distance between the local optimal parameter set and the parameter set in the intermediate table is less than a preset value, the parameter set in the intermediate table is selected, and the geometric center point of the local optimal parameter set and the parameter set in the intermediate table in the multidimensional space of electrochemical parameters is calculated. Write the parameter set corresponding to the geometric center point into the intermediate table; The intermediate table is equipped with penalty logic, which sets penalty items for the parameter set neighborhood in the intermediate table.

2. A lithium battery electrochemical parameter identification system, characterized in that, include: Initialization module: Used to initialize the tabu stack, intermediate table, and global optimal parameter set; Sampling control module: used to sample the battery control condition sequence and select a set of initial lithium battery electrochemical parameters to generate a first initial parameter set in vector form; Iterative perturbation module: used to iteratively perturb each parameter in the first initial parameter set when the first initial parameter set is not within the range limited by the taboo stack, and generate several first perturbation parameter sets; Electrochemical model module: used to input the first initial parameter set / several first perturbation parameter sets and the battery control condition sequence into the electrochemical model for evaluation, and generate a simulated battery operating condition sequence; The sampling control module is further configured to sample the actual battery operating condition sequence and calculate the difference between the simulated battery operating condition sequence and the actual battery operating condition sequence. Judgment module: When the difference values ​​calculated using the plurality of first disturbance parameter sets are all greater than the difference values ​​calculated using the first initial parameter set, the first initial parameter set is taken as the local optimal parameter set; The parameter update module is used to update the difference value calculated from the global optimal parameter set based on the difference value of the local optimal parameter set. The judgment module is further configured to: when the difference value calculated by the global optimal parameter set is greater than a preset value, generate a second initial parameter set based on the first initial parameter set, and cyclically update the global optimal parameter set through the aforementioned module; Output module: Repeat the loop until the difference value calculated by the global optimal parameter set is less than the preset value or the number of repetitions corresponding to the repeated execution of the aforementioned steps reaches the preset maximum number of loops, and then output the global optimal parameter set as the final electrochemical parameters of the lithium battery. The difference value in the sampling control module is calculated using a difference quantization formula. Calculate, where MSE is the difference value, n is the number of sampling time points, and i is a positive integer. It is the battery condition value at the i-th time point of the simulated battery condition sequence. It is the battery condition value at the i-th time point of the actual battery condition sequence. It is the battery condition weight at time point i; The control condition sequence is one of the battery condition sequences, which includes a voltage condition sequence, a current condition sequence, and a temperature condition sequence. The simulated battery condition sequence is the battery condition sequence other than the control condition sequence generated by the electrochemical model. The calculation module further includes a taboo stack processing submodule: when the difference value calculated by the local optimal parameter set is greater than the difference value calculated by the global optimal parameter set, the local optimal parameter set is written into the taboo stack, and the parameter set at the tail of the taboo stack is popped from the stack. The calculation module further includes an intermediate table processing submodule: when it is determined that the distance between the local optimal parameter set in the multidimensional space of electrochemical parameters and the parameter set in the intermediate table is less than a preset value, the parameter set in the intermediate table is selected, the geometric center point between the several local optimal parameter sets and the parameter set in the intermediate table is calculated, and the parameter set corresponding to the geometric center point is written into the intermediate table. The intermediate table processing submodule is equipped with penalty logic to set a penalty term for the neighborhood of the parameter set in the intermediate table.

3. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the lithium battery electrochemical parameter identification method according to claim 1.

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