A lithium battery parameter identification method, device and electronic equipment

Abstract

The application provides a lithium battery parameter identification method and device and electronic equipment, an SP electrochemical model of a lithium battery is established through an FPGA, and to-be-identified parameters in the SP electrochemical model are obtained; the to-be-identified parameters in the SP electrochemical model are iteratively processed through a heuristic algorithm, a candidate solution set of the to-be-identified parameters is obtained, then parallel calculation of data is performed through an IP core of Vivado HLS deployed in the FPGA itself, a voltage-time curve of the candidate solution set of the to-be-identified parameters is obtained, and when the voltage-time curve of the candidate solution set of the to-be-identified parameters meets a preset condition, the candidate solution set of the to-be-identified parameters is determined as an output result of lithium battery parameter identification, the process of identifying parameters in an electrochemical model realized through a heuristic algorithm is accelerated through an IP core of Vivado HLS software running in the FPGA hardware, and the parameter identification period of the parameter identification process is shortened.

Description

Technical Field

[0001] This application relates to the field of battery technology, and more specifically, to a method, apparatus, and electronic device for identifying lithium battery parameters. Background Technology

[0002] Given the frequent safety incidents involving lithium batteries and their dominant position in short-term energy storage, lithium battery parameter identification methods are of great significance for the management and operation of energy storage power stations. Currently, parameter identification devices using FPGAs developed with RTL-level languages ​​have long parameter identification cycles and low efficiency. Summary of the Invention

[0003] To address the aforementioned problems, the purpose of this application is to provide a lithium battery parameter identification method, apparatus, and electronic device.

[0004] In a first aspect, embodiments of this application provide a method for identifying lithium battery parameters, including:

[0005] The FPGA acquires the correspondence between multiple time, voltage, and current data collected.

[0006] Using the correspondence between the multiple times, voltages, and currents, a SP electrochemical model of a lithium battery is established, and the parameters to be identified in the SP electrochemical model are obtained.

[0007] The parameters to be identified in the SP electrochemical model are iteratively processed using a heuristic algorithm to obtain a candidate solution set for the parameters to be identified.

[0008] The voltage-time curve of the candidate solution set of the parameter to be identified is obtained by using the IP core of Vivado HLS deployed on the FPGA itself to calculate the time and current recorded in the correspondence of the multiple time, voltage and current, as well as the candidate solution set of the parameter to be identified.

[0009] When the voltage-time curve of the candidate solution set of the parameter to be identified does not meet the preset conditions, a heuristic algorithm is used to perform cross-mutation on the candidate solution set of the parameter to be identified to generate a new candidate solution set of the parameter to be identified, and then the step of using the IP core of Vivado HLS deployed on the FPGA itself to calculate the time and current recorded in the correspondence of multiple time, voltage and current, as well as the candidate solution set of the parameter to be identified, to obtain the voltage-time curve of the candidate solution set of the parameter to be identified is returned.

[0010] When the voltage-time curve of the candidate solution set of the parameter to be identified meets the preset conditions, the candidate solution set of the parameter to be identified is determined as the output result of lithium battery parameter identification.

[0011] Secondly, embodiments of this application also provide a lithium battery parameter identification device, comprising:

[0012] The acquisition module is used to acquire the correspondence between multiple collected time, voltage, and current data.

[0013] A module is established to utilize the correspondence between the multiple times, voltages, and currents to establish a SP electrochemical model of a lithium battery and obtain the parameters to be identified in the SP electrochemical model.

[0014] The iterative module is used to iteratively process the parameters to be identified in the SP electrochemical model using a heuristic algorithm to obtain a candidate solution set for the parameters to be identified.

[0015] The calculation module is used to calculate the time and current recorded in the correspondence of the multiple time, voltage and current, as well as the candidate solution set of the parameter to be identified, to obtain the voltage-time curve of the candidate solution set of the parameter to be identified.

[0016] The first processing module is used to perform crossover mutation on the candidate solution set of the parameter to be identified using a heuristic algorithm when the voltage-time curve of the candidate solution set of the parameter to be identified does not meet the preset conditions, generate a new candidate solution set of the parameter to be identified, and return to the function of executing the calculation module.

[0017] The second processing module is used to determine the candidate solution set of the parameter to be identified as the output result of lithium battery parameter identification when the voltage-time curve of the candidate solution set of the parameter to be identified meets the preset conditions.

[0018] Thirdly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the method described in the first aspect above.

[0019] Fourthly, embodiments of this application also provide an electronic device, the electronic device including a memory, a processor and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor using the steps of the method described in the first aspect above.

[0020] In the solutions provided in the first to fourth aspects of this application, an SP electrochemical model of a lithium battery is established using an FPGA with multiple time, voltage, and current correspondences, and the parameters to be identified in the SP electrochemical model are obtained. A heuristic algorithm is used to iteratively process the parameters to be identified in the SP electrochemical model to obtain a candidate solution set. Then, the Vivado HLS IP core deployed on the FPGA is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solution set of the parameters to be identified, to obtain the voltage-time curve of the candidate solution set of the parameters to be identified. When the voltage-time curve of the candidate solution set of the parameters to be identified meets preset conditions, the candidate solution set of the parameters to be identified is determined as the output result of lithium battery parameter identification. Compared with the parameter identification method using FPGA parameter identification devices developed with RTL-level languages ​​in related technologies, this method, based on FPGA hardware and Vivado running on the FPGA, provides a more efficient approach. The IP core of the HLS software accelerates the parameter identification process in the electrochemical model implemented by heuristic algorithms, shortening the parameter identification cycle; moreover, the output results can provide guidance for the battery management system of energy storage power stations.

[0021] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart of a lithium battery parameter identification method provided in Embodiment 1 of this application is shown;

[0024] Figure 2 A schematic diagram of parallel computation of multiple candidate subsets provided in Embodiment 1 of this application is shown;

[0025] Figure 3 This paper shows a schematic diagram of the structure of a lithium battery parameter identification device provided in Embodiment 2 of this application;

[0026] Figure 4 A schematic diagram of the structure of an electronic device provided in Embodiment 3 of this application is shown. Detailed Implementation

[0027] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0028] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0029] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0030] Given the frequent safety incidents involving lithium batteries and their dominant position in short-term energy storage, lithium battery parameter identification methods are of great significance for the management and operation of energy storage power stations. Currently, parameter identification devices using FPGAs developed with RTL-level languages ​​have long parameter identification cycles and low efficiency.

[0031] Based on this, the following embodiments of this application propose a lithium battery parameter identification method, device, and electronic device. Using an FPGA, a SP electrochemical model of the lithium battery is established based on multiple time, voltage, and current correspondences, and the parameters to be identified in the SP electrochemical model are obtained. A heuristic algorithm is used to iteratively process the parameters to be identified in the SP electrochemical model to obtain a candidate solution set. Then, the Vivado HLS IP core deployed on the FPGA is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solution set of the parameters to be identified, to obtain the voltage-time curve of the candidate solution set of the parameters to be identified. When the voltage-time curve of the candidate solution set of the parameters to be identified meets preset conditions, the candidate solution set of the parameters to be identified is determined as the output result of lithium battery parameter identification. Compared with the parameter identification method using FPGA parameter identification devices developed using RTL-level languages ​​in related technologies, this method uses FPGA hardware and Vivado HLS running on the FPGA. HLS software accelerates the parameter identification process in electrochemical models implemented by heuristic algorithms, shortening the parameter identification cycle; moreover, the output results can provide guidance for the battery management system of energy storage power stations.

[0032] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and embodiments.

[0033] Example 1

[0034] This embodiment proposes a lithium battery parameter identification method, with the FPGA as the execution entity.

[0035] See Figure 1 The flowchart shown illustrates a lithium battery parameter identification method. This application proposes a lithium battery parameter identification method, which includes the following specific steps:

[0036] Step 100: Obtain the correspondence between multiple collected time, voltage and current data.

[0037] The correspondence between the multiple time, voltage, and current data collected in step 100 above can be represented as follows:

[0038]

[0039]

[0040] The correspondences between multiple times, voltages, and currents are collected during the charging and discharging process of the lithium battery and stored in the FPGA.

[0041] Step 102: Using the correspondence between the multiple times, voltages and currents, establish the SP electrochemical model of the lithium battery and obtain the parameters to be identified in the SP electrochemical model.

[0042] In step 102 above, the SP electrochemical model of the lithium battery includes: solid-phase mass transfer equation, charge conservation equation and Bullter-Volmer equation.

[0043] The specific process of establishing the SP electrochemical model of lithium battery using the aforementioned correspondences of multiple times, voltages, and currents is existing technology and will not be elaborated here.

[0044] After establishing the SP electrochemical model of the lithium battery, the parameters to be identified in the SP electrochemical model can be obtained.

[0045] The parameters to be identified in the SP electrochemical model include, but are not limited to, solid phase concentration and solid phase coefficient.

[0046] In one embodiment, the SP electrochemical model of a lithium battery can be represented as follows:

[0047] U = f(X0,X1,...,Xn,I,t)

[0048] Where U is the battery terminal voltage, I is the external circuit current, t is time, and X0, X1, ..., Xn are the parameters to be identified.

[0049] Step 104: Use a heuristic algorithm to iteratively process the parameters to be identified in the SP electrochemical model to obtain a candidate solution set for the parameters to be identified.

[0050] In step 104 above, heuristic algorithms include, but are not limited to, genetic algorithms, particle swarm optimization, and ant colony optimization.

[0051] The specific process of using a heuristic algorithm to iteratively process the parameters to be identified in the SP electrochemical model to obtain the candidate solution set of the parameters to be identified is existing technology and will not be described in detail here.

[0052] In the candidate solution set of the parameter to be identified, the first candidate solution set obtained is called the initial solution set.

[0053] Step 106: Calculate the time and current recorded in the correspondence between the multiple time, voltage and current, as well as the candidate solution set of the parameter to be identified, using the IP core of Vivado HLS deployed on the FPGA itself, to obtain the voltage-time curve of the candidate solution set of the parameter to be identified.

[0054] In step 106 above, the calculation of the voltage-time curve uses time and current from multiple time, voltage and current correspondences. Therefore, the time in the voltage-time curve is the time 1, time 2, ..., time n recorded in the multiple time, voltage and current correspondences mentioned above.

[0055] Specifically, in order to perform parallel calculations on the time and current recorded in multiple time, voltage and current correspondences, as well as the candidate solution set of the parameter to be identified, and shorten the period of parameter identification, step 106 above can perform the following steps (1) to (7):

[0056] (1) The Vivado HLS IP core in the FPGA divides the candidate solution set of the parameter to be identified into multiple candidate subsets, wherein each candidate subset in the multiple candidate subsets has a preset number of candidate solutions for the parameter to be identified.

[0057] (2) When the number of candidate subsets is N, at time τ0, the IP core of Vivado HLS deployed on the FPGA itself is used to calculate the time and current recorded in the correspondence between the multiple time, voltage and current, and the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, and to obtain the U0 of each candidate solution in the first candidate subset at time τ0 in the voltage-time curve corresponding to each candidate solution in the first candidate subset.

[0058] (3) At time τ1, the IP core of Vivado HLS deployed on the FPGA itself is used to calculate the time and current recorded in the correspondence between the multiple time, voltage and current, and the candidate solutions in the preset number of groups in the first candidate subset of the candidate solution set of the parameter to be identified, so as to obtain the U1 of each candidate solution in the voltage-time curve corresponding to each candidate solution in the first candidate subset at time τ1; and the IP core of Vivado HLS deployed on the FPGA itself is used to calculate the time and current recorded in the correspondence between the multiple time, voltage and current, and the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, so as to obtain the U0 of each candidate solution in the voltage-time curve corresponding to each candidate solution in the second candidate subset at time τ0.

[0059] (4) At time τ2, the IP core of Vivado HLS deployed on the FPGA is used to calculate the time and current recorded in the multiple time, voltage and current correspondences, and the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, based on a preset number of groups, to obtain U2 of each candidate solution in the first candidate subset at time τ2 in the voltage-time curve corresponding to each candidate solution in the first candidate subset; and the IP core of Vivado HLS deployed on the FPGA is used to calculate the time and current recorded in the multiple time, voltage and current correspondences, and the candidate solutions in the second candidate subset of the candidate solution set of the parameter to be identified, based on a preset number of groups, to obtain U1 of each candidate solution in the second candidate subset at time τ1 in the voltage-time curve corresponding to each candidate solution in the second candidate subset; simultaneously, the IP core of Vivado HLS deployed on the FPGA is used to calculate U1 of each candidate solution in the second candidate subset at time τ1 in the voltage-time curve corresponding to each candidate solution in the second candidate subset; The IP core of HLS calculates the time and current recorded in the correspondence of the multiple time, voltage and current, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, to obtain the U0 of each candidate solution in the third candidate subset at time τ0 in the voltage-time curve corresponding to each candidate solution in the third candidate subset.

[0060] (5) After τ3, τ4,...,τ n-1 After parallel processing at time τ, n At any given time, the IP core of Vivado HLS deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, within the preset number of groups. This yields the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the time-current curves of each candidate solution in the first candidate subset at τ. n U of time n Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each group of candidate solutions in the second candidate subset, and the τ values ​​of each group of candidate solutions in the second candidate subset. n-1 U of time n-1Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each group of candidate solutions in the third candidate subset, and the τ values ​​of each group of candidate solutions in the third candidate subset. n-2 U of time n-2 ...Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage and current correspondences, and the candidate solutions in the preset number of groups in the (n-1)th candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain U1 of each candidate solution in the (n-1)th candidate subset at time τ1 in the voltage-time curve corresponding to each candidate solution; using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage and current correspondences, and the candidate solutions in the preset number of groups in the nth candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain U0 of each candidate solution in the nth candidate subset at time τ0 in the voltage-time curve corresponding to each candidate solution;

[0061] (6) In τ n+1 At time τ, the Vivado HLS IP core deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, to obtain the voltage-time curves corresponding to each group of candidate solutions in the second candidate subset, and the time and current of each group of candidate solutions in the second candidate subset at τ. n U of time n Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each group of candidate solutions in the third candidate subset, and the τ values ​​of each group of candidate solutions in the third candidate subset. n-1 U of time n-1...Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage and current correspondences, and the candidate solutions in the preset number of groups in the (n-1)th candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the U2 of each candidate solution in the (n-1)th candidate subset at time τ2 in the voltage-time curve corresponding to each candidate solution; using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage and current correspondences, and the candidate solutions in the preset number of groups in the nth candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the U1 of each candidate solution in the nth candidate subset at time τ1 in the voltage-time curve corresponding to each candidate solution;

[0062] (7) After τ n+2 τ n+3 ... τ n+N-2 After parallel processing at time τ, n+N-1 At any given time, the Vivado HLS IP core deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the predetermined number of groups in the nth candidate subset of the candidate solution set of the parameter to be identified, to obtain the voltage-time curves corresponding to each group of candidate solutions in the nth candidate subset, and the time-current curves of each group of candidate solutions in the nth candidate subset at τ. n U of time n Thus, N*preset number of voltage-time curves are calculated, and the calculated N*preset number of voltage-time curves are determined as the voltage-time curves of the candidate solution set of the parameter to be identified.

[0063] In step (1) above, in one embodiment, the preset quantity is 6.

[0064] Therefore, each candidate subset has 6 sets of candidate solutions for the parameters to be identified.

[0065] In step (2) above, the number of candidate subsets is obtained by dividing the candidate solution set of the parameter to be identified into multiple candidate subsets and then counting the number of candidate subsets. See [link to relevant documentation]. Figure 2 The diagram shows the parallel computation of multiple candidate subsets. Time τ0 is the initial time when the Vivado HLS IP core in the FPGA performs parallel computation of multiple candidate subsets.

[0066] like Figure 1As shown, at time τ0, the time and current recorded in the correspondence of the multiple time, voltage and current, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the U0 of each candidate solution in the first candidate subset at time τ0 in the voltage-time curve corresponding to each candidate solution in the first candidate subset.

[0067] During the calculation process, it is necessary to input the time and current recorded in multiple time, voltage, and current correspondences, as well as the candidate solutions from the first candidate subset of the candidate solution set to be identified into the SP electrochemical model of the lithium battery, to complete the calculation of the battery terminal voltage at time τ0 for each candidate solution in the first candidate subset. Since the calculation process for each candidate solution in the first candidate subset within the pre-defined number of sets is the same in the SP electrochemical model of the lithium battery, only the calculated parameters differ, in order to further optimize the calculation process, the charge conservation equation, the solid-state mass transfer equation, and the Bullter-Volmer equation formed by each candidate solution can be solved separately to further shorten the calculation time.

[0068] Specifically, in order to calculate the battery terminal voltage at time τ0 for each candidate solution in the first candidate subset, the following steps (21) to (24) can be performed:

[0069] (21) At time τ0, the charge conservation equations formed by each group of candidate solutions in the first candidate subset are solved to obtain the solution results of the charge conservation equations for each group of candidate solutions.

[0070] (22) Solve the solid mass transfer equations formed by each group of candidate solutions in the first candidate subset to obtain the solution results of the solid mass transfer equations of each group of candidate solutions.

[0071] (23) Solve the Bulter-Volmer equations formed by each group of candidate solutions in the first candidate subset to obtain the solution results of the Bulter-Volmer equations for each group of candidate solutions;

[0072] (24) Based on the solution results of the charge conservation equation, the solid mass transfer equation and the Bullter-Volmer equation of each candidate solution, the U0 of each candidate solution in the first candidate subset at time τ0 is obtained in the voltage-time curves corresponding to each candidate solution in the first candidate subset.

[0073] In step (21) above, the process of solving the charge conservation equation is existing technology and will not be described in detail here.

[0074] In step (22) above, the process of solving the solid-phase mass transfer equation is existing technology and will not be described in detail here.

[0075] In step (23) above, the process of solving the Bullter-Volmer equation is existing technology and will not be described in detail here.

[0076] In step (24) above, the specific process of obtaining the voltage-time curves corresponding to each group of candidate solutions in the first candidate subset and the U0 of each group of candidate solutions at time τ0 based on the solution results of the charge conservation equation, the solid mass transfer equation and the Bullter-Volmer equation of each group of candidate solutions is the prior art and will not be repeated here.

[0077] As can be seen from the above steps (21) to (24), the charge conservation equation formed by each set of candidate solutions can be solved, the solid mass transfer equation formed by each set of candidate solutions can be solved, and the Butler-Volmer equation formed by each set of candidate solutions can be solved. In this way, the time consumption of solving the charge conservation equation, the solid mass transfer equation, and the Butler-Volmer equation is similar, so that the same equation calculation tasks can be processed together to further shorten the calculation time.

[0078] In step (3) above, at time τ1, the voltage-time curves corresponding to each group of candidate solutions in the first candidate subset and the U1 of each group of candidate solutions in the first candidate subset at time τ1, and the voltage-time curves corresponding to each group of candidate solutions in the second candidate subset and the U0 of each group of candidate solutions in the second candidate subset at time τ0 are calculated in parallel.

[0079] The calculation process of U1 at time τ1 for each group of candidate solutions in the first candidate subset and the calculation process of U0 at time τ0 for each group of candidate solutions in the second candidate subset are similar to the specific calculation process of U0 at time τ0 for each group of candidate solutions in the first candidate subset as recorded in step (2) above. They will not be repeated here.

[0080] In step (4) above, at time τ2, the following are calculated in parallel: the voltage-time curves corresponding to each group of candidate solutions in the first candidate subset at time τ2; the voltage-time curves corresponding to each group of candidate solutions in the second candidate subset at time τ1; and the voltage-time curves corresponding to each group of candidate solutions in the third candidate subset at time τ0. The specific process is similar to that described in step (3) above, and will not be repeated here.

[0081] In step (5) above, τ3, τ4, ..., τ n-1 The parallel processing at each time point is similar to the parallel calculation process described in step (4) above, which involves calculating the U2 of each candidate solution in the first candidate subset at time τ2, the U1 of each candidate solution in the second candidate subset at time τ1, and the U0 of each candidate solution in the third candidate subset at time τ0, based on the voltage-time curves corresponding to each candidate solution in the first candidate subset at time τ2. Therefore, it will not be repeated here.

[0082] In τ n At time τ, for each candidate solution in the first candidate subset, the voltage-time curves corresponding to each candidate solution in the first candidate subset are... n U of time n The voltage-time curves corresponding to each candidate solution in the second candidate subset, and the values ​​of each candidate solution in the second candidate subset at τ n-1 U of time n-1 The voltage-time curves corresponding to each candidate solution in the third candidate subset, and the values ​​of each candidate solution in the third candidate subset at τ n-2 U of time n-2 ... The voltage-time curves corresponding to each group of candidate solutions in the (n-1)th candidate subset, and the U1 of each group of candidate solutions in the (n-1)th candidate subset at time τ1; and the voltage-time curves corresponding to each group of candidate solutions in the nth candidate subset, and the U0 of each group of candidate solutions in the nth candidate subset at time τ0 are calculated in parallel. The specific process is similar to the process described in step (3) above, and will not be repeated here.

[0083] In τ n At time τ, for each candidate solution in the first candidate subset, the voltage-time curves corresponding to each candidate solution in the first candidate subset are... n U of time nIf the calculation is complete, it means that the voltage-time curves corresponding to each group of candidate solutions in the first candidate subset have been calculated, and the voltage-time curves corresponding to each group of candidate solutions in the first candidate subset have been obtained.

[0084] In step (6) above, at τ n+1 At that time, the specific process of parallel computing is similar to the process described in step (4) above, and will not be repeated here.

[0085] In τ n+1 At time 1, the voltage-time curves corresponding to each group of candidate solutions in the second candidate subset were obtained.

[0086] In step (7) above, the specific parallel computing process is similar to that described in step (5) above, and will not be repeated here.

[0087] In steps (1) to (7) above, U0 at time τ0 represents U0 calculated at time τ0. The time corresponding to U0 is time 1; U1 at time τ1 represents U1 calculated at time τ1. The time corresponding to U1 is time 2; ...; the above at τ n U of time n , used to represent in τ n U0 is calculated at time step U. n The corresponding time is time n.

[0088] As can be seen from the process described in steps (1) to (7) above, since the voltage-time curve calculation accumulates over time, the voltage calculation results at previous times in time 1, time 2, ..., time n of the voltage-time curve will affect the voltage calculation results at subsequent times. Parallel calculations cannot be performed between the times in time 1, time 2, ..., time n. Here, parallel processing is adopted between the calculations at each time in time 1, time 2, ..., time n. Each time in time 1, time 2, ..., time n is iteratively calculated according to N sets of candidate parameters, thereby improving the calculation efficiency and reducing the resource consumption of the FPGA while shortening the parameter identification cycle.

[0089] Here, shortening the parameter identification cycle means shortening the parameter identification time.

[0090] After performing step 106 above, in order to determine whether the voltage-time curve of the candidate solution set of the parameter to be identified meets the preset conditions, the following steps (1) to (4) can also be performed:

[0091] (1) Subtract the voltage value at the same time from the voltage-time curve and the voltage value at the same time in the correspondence between the multiple time, voltage and current to obtain multiple voltage difference values;

[0092] (2) Calculate the square of each voltage difference in the multiple voltage differences, and sum the squares of each voltage difference to obtain the sum of the squares of each voltage difference;

[0093] (3) When the sum of the squares of the obtained voltage differences is greater than the preset voltage difference threshold, it is determined that the voltage-time curve of the candidate solution set of the parameter to be identified does not meet the preset condition, and step 108 is executed.

[0094] (4) When the sum of the squares of the obtained voltage differences is less than or equal to the preset voltage difference threshold, the voltage-time curve of the candidate solution set of the parameter to be identified is determined to meet the preset condition, and step 110 is executed.

[0095] Step 108: When the voltage-time curve of the candidate solution set of the parameter to be identified does not meet the preset conditions, a heuristic algorithm is used to perform crossover mutation on the candidate solution set of the parameter to be identified to generate a new candidate solution set of the parameter to be identified, and then the process returns to step 106.

[0096] In step 108 above, the specific process of using a heuristic algorithm to perform crossover mutation on the candidate solution set of the parameter to be identified to generate a new candidate solution set of the parameter to be identified is existing technology and will not be described in detail here.

[0097] Step 110: When the voltage-time curve of the candidate solution set of the parameter to be identified meets the preset conditions, the candidate solution set of the parameter to be identified is determined as the output result of lithium battery parameter identification.

[0098] For simplicity, this embodiment uses the SP model for illustration, but it should not be limited to the SP model. For the application of heuristic algorithms in the field of lithium battery parameter identification, some simple deductions or substitutions can be made without departing from the inventive concept of this embodiment, and all of them should be considered to fall within the protection scope of this embodiment.

[0099] The lithium battery parameter identification method proposed in this embodiment has the following characteristics:

[0100] 1. Based on FPGA hardware and Vivado HLS software, a scheme for accelerating electrochemical identification using heuristic algorithms is provided, and the calculation results can provide guidance for the battery management system of energy storage power stations.

[0101] 2. The Vivado HLS tool is written in C++, which improves the accuracy of the calculation results, increases the ease of calculation, speeds up the algorithm development process, and the generated IP core can be directly called by FPGA, making the algorithm highly portable.

[0102] 3. By using the Vivado HLS tool to generate IP cores for parallel computation of data, resource consumption is reduced and the parameter identification cycle is shortened.

[0103] In summary, this embodiment proposes a lithium battery parameter identification method. It establishes a SP electrochemical model of the lithium battery using multiple time, voltage, and current correspondences via an FPGA, and obtains the parameters to be identified within the SP electrochemical model. A heuristic algorithm iteratively processes these parameters to obtain a candidate solution set. Then, the Vivado HLS IP core deployed on the FPGA is used to calculate the time and current data recorded in the multiple time, voltage, and current correspondences, as well as the candidate solution set, to obtain the voltage-time curve of the candidate solution set. When the voltage-time curve of the candidate solution set meets preset conditions, the candidate solution set is determined as the output result of the lithium battery parameter identification. Compared with related technologies that use FPGA parameter identification devices developed using RTL-level languages ​​for parameter identification, this method, based on FPGA hardware and Vivado running on the FPGA, offers a superior approach. The IP core of the HLS software accelerates the parameter identification process in the electrochemical model implemented by heuristic algorithms, shortening the parameter identification cycle; moreover, the output results can provide guidance for the battery management system of energy storage power stations.

[0104] Example 2

[0105] This embodiment proposes a lithium battery parameter identification device for executing the lithium battery parameter identification method proposed in Embodiment 1 above.

[0106] See Figure 3 The diagram shows a structural schematic of a lithium battery parameter identification device. This embodiment proposes a lithium battery parameter identification device, comprising:

[0107] The acquisition module 300 is used to acquire the correspondence between multiple time, voltage and current data collected.

[0108] Module 302 is used to establish an SP electrochemical model of a lithium battery by utilizing the correspondence between the multiple times, voltages and currents, and to obtain the parameters to be identified in the SP electrochemical model.

[0109] The iteration module 304 is used to iteratively process the parameters to be identified in the SP electrochemical model using a heuristic algorithm to obtain a candidate solution set for the parameters to be identified.

[0110] The calculation module 306 is used to calculate the time and current recorded in the correspondence of the multiple time, voltage and current, as well as the candidate solution set of the parameter to be identified, to obtain the voltage-time curve of the candidate solution set of the parameter to be identified.

[0111] The first processing module 308 is used to perform crossover mutation on the candidate solution set of the parameter to be identified using a heuristic algorithm when the voltage-time curve of the candidate solution set of the parameter to be identified does not meet the preset conditions, generate a new candidate solution set of the parameter to be identified, and return to the function of executing the calculation module.

[0112] The second processing module 310 is used to determine the candidate solution set of the parameter to be identified as the output result of lithium battery parameter identification when the voltage-time curve of the candidate solution set of the parameter to be identified meets the preset conditions.

[0113] Specifically, the computing module 306 is used for:

[0114] The candidate solution set of the parameter to be identified is divided into multiple candidate subsets, wherein each candidate subset in the multiple candidate subsets has a preset number of candidate solutions for the parameter to be identified;

[0115] When the number of candidate subsets is N, at time τ0, the time and current recorded in the correspondence of the multiple time, voltage and current, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the U0 of each candidate solution in the first candidate subset at time τ0 in the voltage-time curve corresponding to each candidate solution in the first candidate subset.

[0116] At time τ1, the time and current recorded in the multiple time, voltage and current correspondences, as well as the candidate solutions in the preset number of groups in the first candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain U1 of each candidate solution in the first candidate subset at time τ1 in the voltage-time curve corresponding to each candidate solution in the first candidate subset; and the time and current recorded in the multiple time, voltage and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated using the IP core of Vivado HLS deployed on the FPGA itself to obtain U0 of each candidate solution in the second candidate subset at time τ0 in the voltage-time curve corresponding to each candidate solution in the second candidate subset;

[0117] At time τ2, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the first candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain U2 of each candidate solution in the first candidate subset at time τ2 in the voltage-time curve corresponding to each candidate solution in the first candidate subset; and using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain U1 of each candidate solution in the second candidate subset at time τ1 in the voltage-time curve corresponding to each candidate solution in the second candidate subset; simultaneously, using the Vivado HLS IP core deployed on the FPGA itself... The IP core of HLS calculates the time and current recorded in the correspondence of the multiple time, voltage and current, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, to obtain the U0 of each candidate solution in the third candidate subset at time τ0 in the voltage-time curve corresponding to each candidate solution in the third candidate subset.

[0118] After τ3, τ4, ..., τ n-1 After parallel processing at time τ, n At time τ, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the time curves of each candidate solution in the first candidate subset at τ. n U of time n Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each group of candidate solutions in the second candidate subset, and the τ values ​​of each group of candidate solutions in the second candidate subset. n-1 U of time n-1Using the VivadoHLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each group of candidate solutions in the third candidate subset, and the τ values ​​of each group of candidate solutions in the third candidate subset. n-2 U of time n-2 ...Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage and current correspondences, and the candidate solutions in the preset number of groups in the (n-1)th candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain U1 of each candidate solution in the (n-1)th candidate subset at time τ1 in the voltage-time curve corresponding to each candidate solution; using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage and current correspondences, and the candidate solutions in the preset number of groups in the nth candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain U0 of each candidate solution in the nth candidate subset at time τ0 in the voltage-time curve corresponding to each candidate solution;

[0119] In τ n+1 At time τ, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each candidate solution in the second candidate subset, and the time of each candidate solution in the second candidate subset at τ. n U of time n Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each group of candidate solutions in the third candidate subset, and the τ values ​​of each group of candidate solutions in the third candidate subset. n-1 U of time n-1...Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage and current correspondences, and the candidate solutions in the preset number of groups in the (n-1)th candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the U2 of each candidate solution in the (n-1)th candidate subset at time τ2 in the voltage-time curve corresponding to each candidate solution; using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage and current correspondences, and the candidate solutions in the preset number of groups in the nth candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the U1 of each candidate solution in the nth candidate subset at time τ1 in the voltage-time curve corresponding to each candidate solution;

[0120] After τ n+2 τ n+3 ... τ n+N-2 After parallel processing at time τ, n+N-1 At time τ, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the predetermined number of groups in the nth candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each group of candidate solutions in the nth candidate subset, and the time curves of each group of candidate solutions in the nth candidate subset at τ. n U of time n Thus, N*preset number of voltage-time curves are calculated, and the calculated N*preset number of voltage-time curves are determined as the voltage-time curves of the candidate solution set of the parameter to be identified.

[0121] The SP electrochemical model of the lithium battery includes: solid-phase mass transfer equation, charge conservation equation and Butler-Volmer equation.

[0122] Specifically, the calculation module 306 is used to calculate, at time τ0, the time and current recorded in the multiple time, voltage and current correspondences, and each group of candidate solutions in the preset number of groups in the first candidate subset of the candidate solution set of the parameter to be identified, to obtain U0 of each group of candidate solutions in the first candidate subset at time τ0 in the voltage-time curves corresponding to each group of candidate solutions in the first candidate subset, including:

[0123] At time τ0, the charge conservation equations formed by each group of candidate solutions in the first candidate subset are solved to obtain the solution results of the charge conservation equations for each group of candidate solutions.

[0124] Solve the solid-phase mass transfer equations formed by each group of candidate solutions in the first candidate subset to obtain the solution results of the solid-phase mass transfer equations for each group of candidate solutions.

[0125] Solve the Bullter-Volmer equations formed by each group of candidate solutions in the first candidate subset to obtain the solution results of the Bullter-Volmer equations for each group of candidate solutions;

[0126] Based on the solutions to the charge conservation equation, the solid-state mass transfer equation, and the Butler-Volmer equation for each group of candidate solutions, the U0 of each group of candidate solutions in the first candidate subset at time τ0 is obtained from the voltage-time curves corresponding to each group of candidate solutions in the first candidate subset.

[0127] In summary, this embodiment proposes a lithium battery parameter identification device. It establishes a SP electrochemical model of the lithium battery using multiple time, voltage, and current correspondences via an FPGA, and obtains the parameters to be identified in the SP electrochemical model. A heuristic algorithm iteratively processes the parameters in the SP electrochemical model to obtain a candidate solution set. Then, the Vivado HLS IP core deployed on the FPGA is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solution set of the parameters to be identified, to obtain the voltage-time curve of the candidate solution set. When the voltage-time curve of the candidate solution set of the parameters meets preset conditions, the candidate solution set of the parameters to be identified is determined as the output result of lithium battery parameter identification. Compared with the parameter identification method of FPGA-based parameter identification devices developed using RTL-level languages ​​in related technologies, this method, based on FPGA hardware and Vivado running on the FPGA, provides a superior solution. The IP core of the HLS software accelerates the parameter identification process in the electrochemical model implemented by heuristic algorithms, shortening the parameter identification cycle; moreover, the output results can provide guidance for the battery management system of energy storage power stations.

[0128] Example 3

[0129] This embodiment proposes a computer-readable storage medium storing a computer program. When the computer program is run by a processor, it executes the steps of the lithium battery parameter identification method described in Embodiment 1. For a detailed implementation, please refer to Embodiment 1, which will not be repeated here.

[0130] In addition, see Figure 4The diagram shows the structure of an electronic device. This embodiment also proposes an electronic device, which includes a bus 51, a processor 52, a transceiver 53, a bus interface 54, a memory 55, and a user interface 56. The electronic device includes a memory 55.

[0131] In this embodiment, the electronic device further includes: one or more programs stored in the memory 55 and executable on the processor 52, configured to be executed by the processor to perform the one or more programs for the following steps (1) to (6):

[0132] (1) The FPGA acquires the correspondence between multiple time, voltage and current data collected;

[0133] (2) Using the correspondence between the multiple times, voltages and currents, establish the SP electrochemical model of the lithium battery and obtain the parameters to be identified in the SP electrochemical model;

[0134] (3) The parameters to be identified in the SP electrochemical model are iteratively processed using a heuristic algorithm to obtain a candidate solution set for the parameters to be identified;

[0135] (4) Using the IP core of Vivado HLS deployed on the FPGA itself, the time and current recorded in the correspondence of the multiple time, voltage and current, as well as the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curve of the candidate solution set of the parameter to be identified.

[0136] (5) When the voltage-time curve of the candidate solution set of the parameter to be identified does not meet the preset conditions, the candidate solution set of the parameter to be identified is cross-mutated using a heuristic algorithm to generate a new candidate solution set of the parameter to be identified, and the process returns to step (4).

[0137] (6) When the voltage-time curve of the candidate solution set of the parameter to be identified meets the preset conditions, the candidate solution set of the parameter to be identified is determined as the output result of lithium battery parameter identification.

[0138] Transceiver 53 is used to receive and send data under the control of processor 52.

[0139] The bus architecture (represented by bus 51) can include any number of interconnected buses and bridges, linking various circuits including one or more processors represented by processor 52 and memory represented by memory 55. Bus 51 can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be further described in this embodiment. Bus interface 54 provides an interface between bus 51 and transceiver 53. Transceiver 53 can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. For example, transceiver 53 receives external data from other devices. Transceiver 53 is used to transmit data processed by processor 52 to other devices. Depending on the nature of the computing system, a user interface 56 may also be provided, such as a keypad, display, speaker, microphone, or joystick.

[0140] Processor 52 is responsible for managing bus 51 and general processing, such as running general-purpose operating system 551 as described above. Memory 55 can be used to store data used by processor 52 during operation.

[0141] Optionally, the processor 52 may be, but is not limited to, a central processing unit, a microcontroller, a microprocessor, or a programmable logic device.

[0142] It is understood that the memory 55 in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate Synchronous DRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 55 of the systems and methods described in this embodiment is intended to include, but is not limited to, these and any other suitable types of memory.

[0143] In some implementations, memory 55 stores elements such as executable modules or data structures, or subsets thereof, or extended sets thereof: operating system 551 and application programs 552.

[0144] The operating system 551 includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application program 552 includes various applications, such as a media player and a browser, used to implement various application functions. Programs implementing the methods of the embodiments of this application can be included in the application program 552.

[0145] In summary, this embodiment proposes a computer-readable storage medium and electronic device. It establishes a SP electrochemical model of a lithium battery using multiple time, voltage, and current correspondences via an FPGA, and obtains the parameters to be identified in the SP electrochemical model. A heuristic algorithm is used to iteratively process the parameters to be identified in the SP electrochemical model, obtaining a candidate solution set. Then, the Vivado HLS IP core deployed on the FPGA is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solution set of the parameters to be identified, to obtain the voltage-time curve of the candidate solution set. When the voltage-time curve of the candidate solution set of the parameters to be identified meets preset conditions, the candidate solution set of the parameters to be identified is determined as the output result of lithium battery parameter identification. Compared with the parameter identification method using FPGA parameter identification devices developed using RTL-level languages ​​in related technologies, this embodiment, based on FPGA hardware and Vivado running on the FPGA, provides a superior approach. The IP core of the HLS software accelerates the parameter identification process in the electrochemical model implemented by heuristic algorithms, shortening the parameter identification cycle; moreover, the output results can provide guidance for the battery management system of energy storage power stations.

[0146] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for identifying lithium battery parameters, characterized in that, include: The FPGA acquires the correspondence between multiple time, voltage, and current data collected. Using the correspondence between the multiple times, voltages, and currents, a SP electrochemical model of a lithium battery is established, and the parameters to be identified in the SP electrochemical model are obtained. The parameters to be identified in the SP electrochemical model are iteratively processed using a heuristic algorithm to obtain a candidate solution set for the parameters to be identified. The voltage-time curve of the candidate solution set of the parameter to be identified is obtained by using the IP core of Vivado HLS deployed on the FPGA itself to calculate the time and current recorded in the correspondence of the multiple time, voltage and current, as well as the candidate solution set of the parameter to be identified. When the voltage-time curve of the candidate solution set of the parameter to be identified does not meet the preset conditions, a heuristic algorithm is used to perform cross-mutation on the candidate solution set of the parameter to be identified to generate a new candidate solution set of the parameter to be identified, and then the step of using the IP core of Vivado HLS deployed on the FPGA itself to calculate the time and current recorded in the correspondence of multiple time, voltage and current, as well as the candidate solution set of the parameter to be identified, to obtain the voltage-time curve of the candidate solution set of the parameter to be identified is returned. When the voltage-time curve of the candidate solution set of the parameter to be identified meets the preset conditions, the candidate solution set of the parameter to be identified is determined as the output result of lithium battery parameter identification. The step of using the Vivado HLS IP core deployed on the FPGA itself to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solution set of the parameter to be identified, to obtain the voltage-time curve of the candidate solution set of the parameter to be identified, includes: The Vivado HLS IP core in the FPGA divides the candidate solution set of the parameter to be identified into multiple candidate subsets, wherein each candidate subset in the multiple candidate subsets has a preset number of candidate solutions for the parameter to be identified; When the number of candidate subsets is N, At any given time, the Vivado HLS IP core deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, within the preset number of groups. This yields the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the results of the calculations for each candidate solution in the first candidate subset. Moment ; exist At any given time, the Vivado HLS IP core deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, within the preset number of groups. This yields the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the results of the calculations for each candidate solution in the first candidate subset. Moment The Vivado HLS IP core deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, to obtain the voltage-time curves corresponding to each group of candidate solutions in the second candidate subset, and the results of the calculations for each group of candidate solutions in the second candidate subset. Moment ; exist At any given time, the Vivado HLS IP core deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, within the preset number of groups. This yields the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the results of calculations for each candidate solution in the first candidate subset at [time value missing]. Moment The Vivado HLS IP core deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, to obtain the voltage-time curves corresponding to each group of candidate solutions in the second candidate subset, and the results of the calculations for each group of candidate solutions in the second candidate subset. Moment Simultaneously, using the Vivado HLS IP core deployed on the FPGA itself, calculations are performed on the time and current recorded in the multiple time, voltage, and current correspondences, as well as on each set of candidate solutions in the preset number of groups within the third candidate subset of the candidate solution set for the parameters to be identified. This yields the voltage-time curves corresponding to each set of candidate solutions in the third candidate subset, and the calculations for each set of candidate solutions in the third candidate subset. Moment ; go through , ... After parallel processing at each time step, At any given time, the Vivado HLS IP core deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, within the preset number of groups. This yields the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the results of calculations for each candidate solution in the first candidate subset at [time value missing]. Moment Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each candidate solution in the second candidate subset, and the results of the calculations for each candidate solution in the second candidate subset. Moment Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the third candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each group of candidate solutions in the third candidate subset, and the results of the calculations for each group of candidate solutions in the third candidate subset. Moment ...using the Vivado HLS IP core deployed on the FPGA itself to record the time and current in the correspondence between the multiple time, voltage, and current parameters, and the candidate solution set of the parameter to be identified... The candidate solutions in each of the preset number of groups in the candidate subset are calculated to obtain the first... The voltage-time curves corresponding to each group of candidate solutions in the candidate subsets, specifically the first... Each candidate solution in the candidate subset is Moment Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the correspondence between the multiple time, voltage, and current parameters, as well as the candidate solution set of the parameter to be identified, are analyzed. The candidate solutions in each of the preset number of groups in the candidate subset are calculated to obtain the first... The voltage-time curves corresponding to each group of candidate solutions in the candidate subsets, specifically the first... Each candidate solution in the candidate subset is Moment ; exist At any given time, the Vivado HLS IP core deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, to obtain the voltage-time curves corresponding to each group of candidate solutions in the second candidate subset, and the results of the calculations for each group of candidate solutions in the second candidate subset. Moment Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the third candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each group of candidate solutions in the third candidate subset, and the results of the calculations for each group of candidate solutions in the third candidate subset. Moment ...using the Vivado HLS IP core deployed on the FPGA itself to record the time and current in the correspondence between the multiple time, voltage, and current parameters, and the candidate solution set of the parameter to be identified... The candidate solutions in each of the preset number of groups in the candidate subset are calculated to obtain the first... The voltage-time curves corresponding to each group of candidate solutions in the candidate subsets, specifically the first... Each candidate solution in the candidate subset is Moment Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the correspondence between the multiple time, voltage, and current parameters, as well as the candidate solution set of the parameter to be identified, are analyzed. The candidate solutions in each of the preset number of groups in the candidate subset are calculated to obtain the first... The voltage-time curves corresponding to each group of candidate solutions in the candidate subsets, specifically the first... Each candidate solution in the candidate subset is Moment ; go through , ... After parallel processing at each time step, At any given time, the time and current recorded in the correspondence between the multiple time, voltage, and current parameters, as well as the candidate solution set of the parameter to be identified, are determined using the IP core of Vivado HLS deployed on the FPGA itself. The candidate solutions in each of the preset number of groups in the candidate subset are calculated to obtain the first... The voltage-time curves corresponding to each group of candidate solutions in the candidate subsets, specifically the first... Each candidate solution in the candidate subset is Moment Thus, N*preset number of voltage-time curves are calculated, and the calculated N*preset number of voltage-time curves are determined as the voltage-time curves of the candidate solution set of the parameter to be identified.

2. The method according to claim 1, characterized in that, The SP electrochemical model of the lithium battery includes: solid-phase mass transfer equation, charge conservation equation and Butler-Volmer equation. The above At any given time, the Vivado HLS IP core deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, within the preset number of groups. This yields the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the results of the calculations for each candidate solution in the first candidate subset. Moment ,include: exist At time 1, the charge conservation equations formed by each group of candidate solutions in the first candidate subset are solved to obtain the solution results of the charge conservation equations for each group of candidate solutions. Solve the solid-phase mass transfer equations formed by each group of candidate solutions in the first candidate subset to obtain the solution results of the solid-phase mass transfer equations for each group of candidate solutions. Solve the Butler-Volmer equations formed by each group of candidate solutions in the first candidate subset to obtain the solution results of the Butler-Volmer equations for each group of candidate solutions. Based on the solutions to the charge conservation equation, the solid-state mass transfer equation, and the Butler-Volmer equation for each group of candidate solutions, the voltage-time curves corresponding to each group of candidate solutions in the first candidate subset are obtained. Moment .

3. The method according to claim 1, characterized in that, After the step of using the VivadoHLS IP core deployed on the FPGA itself to calculate the time and current recorded in the correspondence of the multiple time, voltage and current, and the candidate solution set of the parameter to be identified, to obtain the voltage-time curve of the candidate solution set of the parameter to be identified, the method further includes: Subtract the voltage value at the same time from the voltage-time curve in the multiple time, voltage and current correspondences to obtain multiple voltage difference values; Calculate the square of each voltage difference among multiple voltage differences, and sum the squares of each voltage difference to obtain the sum of the squares of each voltage difference; When the sum of the squares of the obtained voltage differences is greater than a preset voltage difference threshold, it is determined that the voltage-time curve of the candidate solution set of the parameter to be identified does not meet the preset condition. Then, the step of using a heuristic algorithm to perform cross-mutation on the candidate solution set of the parameter to be identified to generate a new candidate solution set of the parameter to be identified is executed when the voltage-time curve of the candidate solution set of the parameter to be identified does not meet the preset condition. Then, the step of using the IP core of Vivado HLS deployed on the FPGA itself to calculate the time and current recorded in the correspondence of multiple time, voltage and current, as well as the candidate solution set of the parameter to be identified, to obtain the voltage-time curve of the candidate solution set of the parameter to be identified is executed.

4. The method according to claim 3, characterized in that, After the step of using the VivadoHLS IP core deployed on the FPGA itself to calculate the time and current recorded in the correspondence of the multiple time, voltage and current, and the candidate solution set of the parameter to be identified, to obtain the voltage-time curve of the candidate solution set of the parameter to be identified, the method further includes: When the sum of the squares of the obtained voltage differences is less than or equal to a preset voltage difference threshold, it is determined that the voltage-time curve of the candidate solution set of the parameter to be identified meets the preset condition, and the step of determining the candidate solution set of the parameter to be identified as the output result of lithium battery parameter identification when the voltage-time curve of the candidate solution set of the parameter to be identified meets the preset condition is executed.

5. A lithium battery parameter identification device, characterized in that, include: The acquisition module is used to acquire the correspondence between multiple time, voltage, and current data collected. A module is established to utilize the correspondence between the multiple times, voltages, and currents to establish a SP electrochemical model of a lithium battery and obtain the parameters to be identified in the SP electrochemical model. The iterative module is used to iteratively process the parameters to be identified in the SP electrochemical model using a heuristic algorithm to obtain a candidate solution set for the parameters to be identified. The calculation module is used to calculate the time and current recorded in the correspondence of the multiple time, voltage and current, as well as the candidate solution set of the parameter to be identified, to obtain the voltage-time curve of the candidate solution set of the parameter to be identified. The first processing module is used to perform crossover mutation on the candidate solution set of the parameter to be identified using a heuristic algorithm when the voltage-time curve of the candidate solution set of the parameter to be identified does not meet the preset conditions, generate a new candidate solution set of the parameter to be identified, and return to the function of executing the calculation module. The second processing module is used to determine the candidate solution set of the parameter to be identified as the output result of lithium battery parameter identification when the voltage-time curve of the candidate solution set of the parameter to be identified meets the preset conditions. The computing module is specifically used for: The candidate solution set of the parameter to be identified is divided into multiple candidate subsets, wherein each candidate subset in the multiple candidate subsets has a preset number of candidate solutions for the parameter to be identified. When the number of candidate subsets is N, At a given time, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the results of the calculations for each candidate solution in the first candidate subset. Moment ; exist At a given time, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the results of the calculations for each candidate solution in the first candidate subset. Moment The Vivado HLS IP core deployed on the FPGA is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, to obtain the voltage-time curves corresponding to each group of candidate solutions in the second candidate subset, and the results of the calculations for each group of candidate solutions in the second candidate subset. Moment ; exist At any given time, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the results of the calculations for each candidate solution in the first candidate subset. Moment The Vivado HLS IP core deployed on the FPGA itself is used to calculate the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the second candidate subset of the candidate solution set of the parameter to be identified, to obtain the voltage-time curves corresponding to each group of candidate solutions in the second candidate subset, and the results of the calculations for each group of candidate solutions in the second candidate subset. Moment Simultaneously, using the Vivado HLS IP core deployed on the FPGA itself, calculations are performed on the time and current recorded in the multiple time, voltage, and current correspondences, as well as on each set of candidate solutions in the preset number of groups within the third candidate subset of the candidate solution set for the parameters to be identified. This yields the voltage-time curves corresponding to each set of candidate solutions in the third candidate subset, and the calculations for each set of candidate solutions in the third candidate subset. Moment ; go through , ... After parallel processing at each time step, At any given time, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the results of the calculations for each candidate solution in the first candidate subset. Moment Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each candidate solution in the second candidate subset, and the results of the calculations for each candidate solution in the second candidate subset. Moment Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the third candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each group of candidate solutions in the third candidate subset, and the results of the calculations for each group of candidate solutions in the third candidate subset. Moment ...using the Vivado HLS IP core deployed on the FPGA itself to record the time and current in the correspondence between the multiple time, voltage, and current parameters, and the candidate solution set of the parameter to be identified... The candidate solutions in each of the preset number of groups in the candidate subset are calculated to obtain the first... The voltage-time curves corresponding to each group of candidate solutions in the candidate subsets, specifically the first... Each candidate solution in the candidate subset is Moment Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the correspondence between the multiple time, voltage, and current parameters, as well as the candidate solution set of the parameter to be identified, are analyzed. The candidate solutions in each of the preset number of groups in the candidate subset are calculated to obtain the first... The voltage-time curves corresponding to each group of candidate solutions in the candidate subsets, specifically the first... Each candidate solution in the candidate subset is Moment ； exist At a given time, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the second candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each candidate solution in the second candidate subset, and the results of the calculations for each candidate solution in the second candidate subset. Moment Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the preset number of groups in the third candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each group of candidate solutions in the third candidate subset, and the results of the calculations for each group of candidate solutions in the third candidate subset. Moment ...using the Vivado HLS IP core deployed on the FPGA itself to record the time and current in the correspondence between the multiple time, voltage, and current parameters, and the candidate solution set of the parameter to be identified... The candidate solutions in each of the preset number of groups in the candidate subset are calculated to obtain the first... The voltage-time curves corresponding to each group of candidate solutions in the candidate subsets, specifically the first... Each candidate solution in the candidate subset is Moment Using the Vivado HLS IP core deployed on the FPGA itself, the time and current recorded in the correspondence between the multiple time, voltage, and current parameters, as well as the candidate solution set of the parameter to be identified, are analyzed. The candidate solutions in each of the preset number of groups in the candidate subset are calculated to obtain the first... The voltage-time curves corresponding to each group of candidate solutions in the candidate subsets, specifically the first... Each candidate solution in the candidate subset is Moment ; go through , ... After parallel processing at each time step, At time, the time and current recorded in the correspondence of the multiple times, voltages and currents, and the first time in the candidate solution set of the parameter to be identified. The candidate solutions in each of the preset number of groups in the candidate subset are calculated to obtain the first... The voltage-time curves corresponding to each group of candidate solutions in the candidate subsets, specifically the first... Each candidate solution in the candidate subset is Moment Thus, N*preset number of voltage-time curves are calculated, and the calculated N*preset number of voltage-time curves are determined as the voltage-time curves of the candidate solution set of the parameter to be identified.

6. The apparatus according to claim 5, characterized in that, The SP electrochemical model of the lithium battery includes: solid-phase mass transfer equation, charge conservation equation and Butler-Volmer equation. The computing module is used to perform... At a given time, the time and current recorded in the multiple time, voltage, and current correspondences, as well as the candidate solutions in the first candidate subset of the candidate solution set of the parameter to be identified, are calculated to obtain the voltage-time curves corresponding to each candidate solution in the first candidate subset, and the results of the calculations for each candidate solution in the first candidate subset. Moment ,include: exist At time 1, the charge conservation equations formed by each group of candidate solutions in the first candidate subset are solved to obtain the solution results of the charge conservation equations for each group of candidate solutions. Solve the solid-phase mass transfer equations formed by each group of candidate solutions in the first candidate subset to obtain the solution results of the solid-phase mass transfer equations for each group of candidate solutions. Solve the Butler-Volmer equations formed by each group of candidate solutions in the first candidate subset to obtain the solution results of the Butler-Volmer equations for each group of candidate solutions. Based on the solutions to the charge conservation equation, the solid-state mass transfer equation, and the Butler-Volmer equation for each group of candidate solutions, the voltage-time curves corresponding to each group of candidate solutions in the first candidate subset are obtained. Moment .

7. A computer-readable storage medium storing a computer program thereon, characterized in that, When the computer program is run by the processor, it performs the steps of the method described in any one of claims 1-4.

8. An electronic device, characterized in that, The electronic device includes a memory, a processor, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor of the steps of the method according to any one of claims 1-4.

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