A loss evaluation method and system for identifying parameters of an electrochemical model

Abstract

The application discloses a loss evaluation method and system for identifying electrochemical model parameters, and the method comprises the following steps: collecting an actual voltage sequence and an actual current sequence of a lithium battery; substituting the actual current sequence into an electrochemical model to obtain a simulated voltage sequence; obtaining a voltage error sequence according to the actual voltage sequence and the simulated voltage sequence; obtaining a first voltage threshold and a second voltage threshold according to a voltage value of a positive pole inflection point of a preset positive pole OCP curve and a voltage value of a negative pole inflection point of a preset negative pole OCP curve of the lithium battery; obtaining a positive pole inflection point judgment result and a negative pole inflection point judgment result according to the first voltage threshold, the second voltage threshold and the actual voltage sequence; and obtaining a voltage loss function according to the positive pole inflection point judgment result, the negative pole inflection point judgment result, a preset continuous loss weighting logic and the voltage error sequence. The application uses the voltage loss function to accurately evaluate the fitting condition of the simulated voltage sequence obtained by using the current electrochemical parameters relative to the actual voltage sequence.

Description

Technical Field

[0001] This invention relates to the field of electrochemical model parameter identification, and more specifically to a loss assessment method for identifying electrochemical model parameters. Background Technology

[0002] Due to the instability of new energy systems, a Battery Management System (BMS) composed of hardware and software is needed to manage lithium-ion batteries and ensure their long-term safety and reliability. Currently, widely used BMSs are developed based on ECM (Equivalent Circuit Model). However, because ECM has limited predictive power, battery operation strategies are designed based on simple safety constraints, such as charging cut-off voltage, discharging cut-off voltage, and maximum current. However, the terminal voltage cannot fully reflect the internal state of the battery, especially under high current conditions, where large overpotentials can significantly increase or decrease the battery's terminal voltage during charging and discharging.

[0003] Therefore, with the improvement of hardware computing power, more intelligent and advanced new BMS based on electrochemical models will soon be applied. Because electrochemical models can fully reflect the internal state of the battery, they greatly improve the management capabilities of lithium batteries. Electrochemical models involve a large number of coupled partial differential equations, especially dozens of physical parameters, such as the lithium-ion concentration distribution at the positive and negative electrodes, potential distribution, and overpotential. These parameters can be obtained in a data-driven manner using methods such as heuristic algorithms, neural networks, and Kalman filtering.

[0004] Currently, data-driven parameter identification methods primarily use loss functions to compare the simulated voltage values ​​from the model with the actual battery voltage values ​​to optimize the model's electrochemical parameters. Common loss functions include root mean square error (MSE) and mean absolute error (MAE). However, when parameter data is limited or operating conditions are complex, using loss functions like MSE or MAE may yield small values, but the calculated electrochemical parameters may still have a poor fit to the voltage. Therefore, a new loss assessment method is urgently needed to improve the fit of the identified electrochemical parameters to the actual voltage. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a loss assessment method and system for identifying electrochemical model parameters.

[0006] Specifically, the technical solution of the present invention is as follows:

[0007] In a first aspect, the present invention provides a loss assessment method for identifying electrochemical model parameters, comprising:

[0008] Collect the actual voltage and current sequences of the lithium battery during a preset identification time period;

[0009] Substituting the actual current sequence into the electrochemical model, a simulated voltage sequence is obtained;

[0010] Based on the actual voltage sequence and the simulated voltage sequence, a voltage error sequence is obtained;

[0011] Based on the voltage value of the positive inflection point of the preset positive OCP curve of the lithium battery and the voltage value of the negative inflection point of the preset negative OCP curve of the lithium battery, the first voltage threshold and the second voltage threshold of the lithium battery are obtained.

[0012] Based on the first voltage threshold and the actual voltage sequence, the positive electrode inflection point judgment result of the lithium battery during the preset identification time period is obtained; based on the second voltage threshold and the actual voltage sequence, the negative electrode inflection point judgment result of the lithium battery during the preset identification time period is obtained.

[0013] Based on the positive inflection point judgment result, the negative inflection point judgment result, and the preset continuous loss weighting logic of the voltage error sequence, each voltage value in the voltage error sequence is weighted to obtain the voltage loss function.

[0014] This implementation method determines whether there is an inflection point in the actual voltage sequence where the electrode voltage rises or falls rapidly, based on the OCP curves of the positive and negative electrodes of the lithium battery. When an inflection point exists, the actual voltage sequence has a phase of rapid voltage rise or fall. The error values ​​of the upper voltage limit and / or lower voltage limit in the voltage error sequence are weighted to improve the fitting degree of the simulated operating condition sequence identified by the loss function to the phase of rapid voltage rise or fall. In addition, the voltage error sequence is weighted as a whole by a preset continuous loss weighting logic to increase the overall fitting effect of the simulated operating condition sequence identified by the loss function.

[0015] In some electrochemical model parameter identification loss assessment methods, the step of obtaining the positive electrode inflection point judgment result of the lithium battery within a preset identification time period based on the first voltage threshold and the actual voltage sequence, and obtaining the negative electrode inflection point judgment result of the lithium battery within a preset identification time period based on the second voltage threshold and the actual voltage sequence, includes:

[0016] When there is a voltage value higher than the first voltage threshold in the actual voltage sequence, it is determined that the positive electrode of the lithium battery has the positive electrode inflection point in the preset identification time period.

[0017] When there is a voltage value lower than the second voltage threshold in the actual voltage sequence, it is determined that the negative electrode of the lithium battery has a negative electrode inflection point in the preset identification time period.

[0018] This implementation method compares the first voltage threshold, the second voltage threshold, and the actual voltage sequence to obtain the result of determining whether there is a positive / negative inflection point in the actual voltage sequence. This allows for subsequent determination of whether there are rapidly changing voltage values ​​in the actual voltage sequence based on the existence of inflection points, and weighting the error values ​​of the rapidly changing voltage values.

[0019] In the implementation method of some electrochemical model parameter identification loss assessment methods, the step of weighting each voltage value in the voltage error sequence according to the positive electrode inflection point judgment result, the negative electrode inflection point judgment result, and the preset continuous loss weighting logic of the voltage error sequence to obtain a voltage loss function includes:

[0020] When the positive inflection point determination result indicates that the positive inflection point exists, the voltage upper limit error value is weighted using the preset first hyperparameter weight of the voltage upper limit error value to obtain the first loss function of the voltage upper limit error value; the voltage upper limit error value is the error value corresponding to the maximum voltage value of the actual voltage sequence in the voltage error sequence;

[0021] When the negative pole inflection point determination result indicates that the negative pole inflection point exists, the voltage lower limit error value is weighted using the preset second hyperparameter weight of the voltage lower limit value to obtain the second loss function of the voltage lower limit error value; the voltage lower limit error value is the error value corresponding to the minimum voltage value of the actual voltage sequence in the voltage error sequence.

[0022] Based on the preset continuous loss weighting logic of the voltage error sequence, a third hyperparameter weight corresponding to each voltage value in the voltage error sequence is generated; based on the third hyperparameter weight, the voltage error sequence is weighted to obtain the third loss function of the voltage error sequence;

[0023] The voltage loss function is calculated based on the first loss function, the second loss function, and the third loss function.

[0024] This implementation method obtains a first loss function by weighting the upper limit voltage error value corresponding to the positive inflection point, a second loss function by weighting the lower limit voltage error value corresponding to the negative inflection point, and a third loss function by weighting the voltage error sequence according to the preset continuous loss weighting logic. The voltage loss function calculated in the end can better characterize the difference between the voltage operating condition sequence simulated by the current parameters and the actual operating condition sequence.

[0025] In the implementation method of some electrochemical model parameter identification loss assessment methods, the step of weighting each voltage value in the voltage error sequence according to the positive electrode inflection point judgment result, the negative electrode inflection point judgment result, and the preset continuous loss weighting logic of the voltage error sequence to obtain a voltage loss function includes:

[0026] When the positive electrode inflection point determination result is that the positive electrode inflection point does not exist, the first loss function is set to zero;

[0027] When the negative pole inflection point determination result is that the negative pole inflection point does not exist, the second loss function is set to zero;

[0028] Based on the preset continuous loss weighting logic of the voltage error sequence, a third hyperparameter weight corresponding to each voltage value in the voltage error sequence is generated; based on the third hyperparameter weight, the voltage error sequence is weighted to obtain the third loss function of the voltage error sequence;

[0029] The voltage loss function is calculated based on the third loss function.

[0030] This implementation method provides a method to set the loss function corresponding to the inflection point to zero when the inflection point does not exist.

[0031] In the implementation method of some electrochemical model parameter identification loss assessment methods, after the step of weighting each voltage value in the voltage error sequence based on the positive electrode inflection point judgment result, the negative electrode inflection point judgment result, and the preset continuous loss weighting logic of the voltage error sequence to obtain the voltage loss function, the method further includes:

[0032] When the voltage loss function exceeds a preset value, the electrochemical parameters are continuously iterated using a heuristic algorithm or Kalman filtering method.

[0033] Until the voltage loss function is lower than a preset value, the electrochemical parameters of the current iteration are used as the identified electrochemical parameters.

[0034] This implementation method provides a process for iteratively identifying electrochemical parameters using a voltage loss function.

[0035] Secondly, the present invention provides a loss assessment system for identifying electrochemical model parameters, comprising:

[0036] The acquisition unit is used to acquire the actual voltage sequence and actual current sequence of the lithium battery during a preset identification time period; and to send the actual current sequence to the electrochemical model unit and the actual voltage sequence to the central control unit.

[0037] The electrochemical model unit is connected to the acquisition unit and is used to substitute the actual current sequence into the electrochemical model to obtain a simulated voltage sequence; the simulated voltage sequence is then sent to the central control unit.

[0038] The central control unit is connected to the electrochemical model unit and the acquisition unit, and also includes a calculation subunit, which is used to obtain a voltage error sequence based on the actual voltage sequence and the simulated voltage sequence.

[0039] The calculation subunit is further configured to obtain a first voltage threshold and a second voltage threshold of the lithium battery based on the voltage value of the positive inflection point of the preset positive OCP curve of the lithium battery and the voltage value of the negative inflection point of the preset negative OCP curve of the lithium battery.

[0040] The central control unit further includes a judgment subunit, which is further configured to obtain the positive electrode inflection point judgment result of the lithium battery in a preset identification time period based on the first voltage threshold and the actual voltage sequence; and to obtain the negative electrode inflection point judgment result of the lithium battery in a preset identification time period based on the second voltage threshold and the actual voltage sequence.

[0041] The calculation subunit is further configured to weight each voltage value in the voltage error sequence according to the positive inflection point judgment result, the negative inflection point judgment result and the preset continuous loss weighting logic of the voltage error sequence, to obtain the voltage loss function.

[0042] The judgment subunit of this implementation method determines whether there is an inflection point in the actual voltage sequence obtained by the acquisition unit based on the OCP curves of the positive and negative electrodes of the lithium battery. When an inflection point exists, the actual voltage sequence acquired by the acquisition unit has a phase of rapid voltage rise or fall. The calculation subunit weights the error values ​​of the upper voltage limit and / or lower voltage limit in the voltage error sequence to improve the fitting degree of the simulated operating condition sequence identified by the loss function to the phase of rapid voltage rise or fall. In addition, the voltage error sequence is weighted as a whole by the preset continuous loss weighting logic to increase the overall fitting effect of the simulated operating condition sequence identified by the loss function.

[0043] Implementation methods for some electrochemical model parameter identification loss assessment systems

[0044] The judgment subunit is further configured to determine that the positive electrode of the lithium battery has a positive electrode inflection point in the preset identification time period when there is a voltage value higher than the first voltage threshold in the actual voltage sequence; and to determine that the negative electrode of the lithium battery has a negative electrode inflection point in the preset identification time period when there is a voltage value lower than the second voltage threshold in the actual voltage sequence.

[0045] The judgment subunit of this implementation method compares the first voltage threshold and the second voltage threshold with the actual voltage sequence to obtain the result of judging whether there is a positive / negative inflection point in the actual voltage sequence, so as to facilitate the subsequent judgment of whether there is a rapidly changing voltage value in the actual voltage sequence. It is necessary to separately weight its error value.

[0046] Implementation methods for some electrochemical model parameter identification loss assessment systems

[0047] The calculation subunit is further configured to, when the positive inflection point determination result indicates that the positive inflection point exists, use a preset first hyperparameter weight of the upper voltage limit error value to weight the upper voltage limit error value to obtain a first loss function for the upper voltage limit error value; the upper voltage limit error value is the error value corresponding to the maximum voltage value in the actual voltage sequence in the voltage error sequence; when the negative inflection point determination result indicates that the negative inflection point exists, use a preset second hyperparameter weight of the lower voltage limit error value to weight the lower voltage limit error value to obtain a second loss function for the lower voltage limit error value; the lower voltage limit error value is the error value corresponding to the minimum voltage value in the actual voltage sequence in the voltage error sequence;

[0048] The calculation subunit is further configured to generate a third hyperparameter weight corresponding to each voltage value in the voltage error sequence according to a preset continuous loss weighting logic of the voltage error sequence; and to weight the voltage error sequence according to the third hyperparameter weight to obtain a third loss function of the voltage error sequence.

[0049] The calculation subunit is further configured to calculate the voltage loss function based on the first loss function, the second loss function, and the third loss function.

[0050] In this implementation method, the calculation sub-unit weights the upper limit voltage error value corresponding to the positive inflection point to obtain the first loss function, weights the lower limit voltage error value corresponding to the negative inflection point to obtain the second loss function, and weights the voltage error sequence according to the preset continuous loss weighting logic to obtain the third loss function; the voltage loss function finally calculated can better characterize the difference between the voltage operating condition sequence simulated by the current parameters and the actual operating condition sequence.

[0051] Implementation methods for some electrochemical model parameter identification loss assessment systems

[0052] The calculation subunit is further configured to set the first loss function to zero when the positive electrode inflection point determination result is that the positive electrode inflection point does not exist;

[0053] The calculation subunit is further configured to set the second loss function to zero when the negative pole inflection point determination result indicates that the negative pole inflection point does not exist.

[0054] This implementation method provides a method where, when the inflection point does not exist, the calculation sub-unit sets the loss function corresponding to the inflection point to zero.

[0055] Implementation methods for some electrochemical model parameter identification loss assessment systems

[0056] The electrochemical model unit is also used to continuously iterate the electrochemical parameters using a heuristic algorithm or Kalman filtering method when the voltage loss function exceeds a preset value; until the voltage loss function is lower than the preset value, the electrochemical parameters of the current iteration are used as the identified electrochemical parameters.

[0057] This implementation method provides a process for iteratively identifying electrochemical parameters using a voltage loss function within an electrochemical model unit.

[0058] Compared with the prior art, the present invention has at least one of the following beneficial effects:

[0059] 1. This invention determines whether there is an inflection point in the actual voltage sequence where the electrode voltage rises or falls rapidly, based on the OCP curves of the positive and negative electrodes of the lithium battery. When an inflection point exists, the actual voltage sequence has a phase of rapid voltage rise or fall. The error values ​​of the upper and / or lower voltage limits in the voltage error sequence are weighted to improve the fitting degree of the simulated operating condition sequence identified by the loss function to the phase of rapid voltage rise or fall. Furthermore, the voltage error sequence is weighted as a whole by combining a preset continuous loss weighting logic to enhance the overall fitting effect of the simulated operating condition sequence identified by the loss function.

[0060] 2. This invention obtains a first loss function by weighting the upper limit voltage error value corresponding to the positive inflection point, a second loss function by weighting the lower limit voltage error value corresponding to the negative inflection point, and a third loss function by weighting the voltage error sequence according to a preset continuous loss weighting logic; finally, the voltage loss function is calculated based on the first loss function, the second loss function, and the third loss function.

[0061] 3. This invention utilizes the obtained voltage loss function to identify electrochemical parameters, thereby improving the reliability of the identified electrochemical parameters. Attached Figure Description

[0062] The preferred embodiments will now be described in a clear and easy-to-understand manner, in conjunction with the accompanying drawings, to further explain the above-mentioned characteristics, technical features, advantages, and implementation methods of the present invention.

[0063] Figure 1 This is a flowchart of an embodiment of a loss assessment method for identifying electrochemical model parameters provided by the present invention;

[0064] Figure 2 This is a drawing in the specification of an embodiment of a loss assessment method for identifying electrochemical model parameters provided by the present invention;

[0065] Figure 3 This is a drawing in the specification of an embodiment of a loss assessment method for identifying electrochemical model parameters provided by the present invention;

[0066] Figure 4 This is a system block diagram of an embodiment of a loss assessment system for identifying electrochemical model parameters provided by the present invention.

[0067] The following are the definitions of the reference numerals: 10--Acquisition unit; 20--Electrochemical model unit; 30--Central control unit; 31--Calculation subunit; 32--Judgment subunit. Detailed Implementation

[0068] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the specific implementation methods of the present invention will be described below with reference to the accompanying drawings. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings and other implementation methods can be obtained based on these drawings without any creative effort.

[0069] To keep the drawings concise, each figure only schematically shows the parts relevant to the invention, and these do not represent the actual structure of the product. Furthermore, to facilitate understanding, in some figures, only one of components with the same structure or function is schematically depicted, or only one is labeled. In this document, "one" not only means "only one," but can also mean "more than one."

[0070] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0071] In this document, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0072] Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0073] In one embodiment, refer to the appendix to the specification. Figure 1 The present invention provides a loss assessment method for identifying electrochemical model parameters, comprising:

[0074] S110 collects the actual voltage and current sequences of the lithium battery during a preset identification time period.

[0075] S120, by substituting the actual current sequence into the electrochemical model, a simulated voltage sequence is obtained.

[0076] S130, based on the actual voltage sequence and the simulated voltage sequence, obtains the voltage error sequence.

[0077] In step S130, the voltage error sequence can be calculated in various ways. Among them, the more convenient way to calculate the voltage error sequence is as follows:

[0078] V error，i =|V real，i -V sim，i |,

[0079] Among them, V error,i For the voltage error sequence, V real,i For the actual voltage sequence, V sim,i This is a simulated voltage sequence.

[0080] S140. Based on the voltage value of the positive inflection point of the preset positive OCP (open circuit potential) curve of the lithium battery and the voltage value of the negative inflection point of the preset negative OCP curve of the lithium battery, the first voltage threshold and the second voltage threshold of the lithium battery are obtained.

[0081] In step S140, the lithium concentration changes at the positive and negative electrodes of the lithium battery are opposite; that is, when the lithium battery is charging, the lithium concentration at the positive electrode decreases, and the lithium concentration at the negative electrode increases; when the lithium battery is discharging, the lithium concentration at the positive electrode increases, and the lithium concentration at the negative electrode decreases. (See attached instruction manual) Figure 2 This diagram illustrates the relationship between the open-circuit potential of the positive electrode and the lithium concentration in a lithium iron phosphate (LFP) battery with LFP as the positive electrode material. The diagram shows that the voltage at the positive electrode inflection point is 3.4V. The positive electrode potential changes significantly to the left of the inflection point and less so to the right. (See attached instruction manual.) Figure 3The diagram shows the relationship between the open-circuit potential of the negative electrode and the lithium concentration of the negative electrode in a lithium iron phosphate cell with graphite as the negative electrode material. It can be seen that the voltage value at the negative electrode inflection point of the lithium battery is 0.2V; the negative electrode potential changes more on the left side of the negative electrode inflection point and less on the right side. When a lithium battery is charged to the high-voltage range, the lithium concentration at the positive electrode decreases while the lithium concentration at the negative electrode increases. The positive electrode OCP is 3.4V or higher, while the negative electrode OCP stabilizes at around 0.1V. Combining this with other relevant parameters of the lithium battery, we can deduce that the first voltage threshold for the lithium battery in the high-voltage range is 3.3V. That is, when the voltage value is higher than 3.3V, we can determine that there is a positive electrode inflection point in the actual voltage sequence. When a lithium battery is discharged to the low-voltage range, the lithium concentration at the positive electrode increases while the lithium concentration at the negative electrode decreases. The positive electrode OCP stabilizes at around 3.4V, while the negative electrode OCP is higher than 0.2V. Combining this with other relevant parameters of the lithium battery, we can deduce that the second voltage threshold for the lithium battery in the low-voltage range is 3.0V. That is, when the voltage value is lower than 3.0V, we can determine that there is a negative electrode inflection point in the actual voltage sequence.

[0082] S150: Based on the first voltage threshold and the actual voltage sequence, obtain the positive electrode inflection point judgment result of the lithium battery during the preset identification time period; based on the second voltage threshold and the actual voltage sequence, obtain the negative electrode inflection point judgment result of the lithium battery during the preset identification time period.

[0083] In step S150, the first voltage threshold and the second voltage threshold obtained in step S140 are used to determine whether the actual voltage sequence of the obtained lithium battery has a positive electrode inflection point and a negative electrode inflection point.

[0084] S160: Based on the positive inflection point judgment result, the negative inflection point judgment result, and the preset continuous loss weighting logic of the voltage error sequence, weight each voltage value in the voltage error sequence to obtain the voltage loss function.

[0085] In step S160, based on the inflection point judgment result, it can be determined whether there is a rapid voltage change in the high / low voltage range of the battery in the actual voltage sequence. Based on the inflection point judgment result, the voltage error sequence is weighted to improve the fitting degree of the simulated operating condition sequence identified by the loss function to the rapid voltage rise or fall phase.

[0086] This embodiment determines whether there is an inflection point in the actual voltage sequence where the electrode voltage rises or falls rapidly, based on the OCP curves of the positive and negative electrodes of the lithium battery. When an inflection point exists, the actual voltage sequence has a phase of rapid voltage rise or fall. The error values ​​of the upper voltage limit and / or lower voltage limit in the voltage error sequence are weighted to improve the fitting degree of the simulated operating condition sequence identified by the loss function to the phase of rapid voltage rise or fall. In addition, the voltage error sequence is weighted as a whole by a preset continuous loss weighting logic to increase the overall fitting effect of the simulated operating condition sequence identified by the loss function.

[0087] This embodiment provides a method for evaluating the loss of electrochemical model parameter identification based on the previous embodiment. Step S150 specifically includes:

[0088] When there is a voltage value higher than the first voltage threshold in the actual voltage sequence, it is determined that the positive electrode of the lithium battery has a positive electrode inflection point in the preset identification time period.

[0089] When there is a voltage value lower than the second voltage threshold in the actual voltage sequence, it is determined that the negative electrode of the lithium battery has a negative electrode inflection point in the preset identification time period.

[0090] This embodiment provides a specific comparison and judgment method between the first voltage threshold, the second voltage threshold, and the actual voltage sequence to obtain the result of judging whether there are positive / negative inflection points in the actual voltage sequence, so as to weight the error value of the voltage value that changes rapidly in the actual voltage sequence.

[0091] This embodiment provides a method for evaluating the loss of electrochemical model parameter identification based on the previous embodiment. Step S160 specifically includes:

[0092] When the positive inflection point judgment result indicates that the positive inflection point exists, the voltage upper limit error value is weighted using the preset first hyperparameter weight α1 of the voltage upper limit error value to obtain the first loss function of the voltage upper limit error value; the voltage upper limit error value is the error value corresponding to the maximum voltage value of the actual voltage sequence in the voltage error sequence;

[0093] When the negative inflection point determination result indicates that a negative inflection point exists, the voltage lower limit error value is weighted using the preset second hyperparameter weight α2 of the voltage lower limit value to obtain the second loss function of the voltage lower limit error value; the voltage lower limit error value is the error value corresponding to the minimum voltage value of the actual voltage sequence in the voltage error sequence;

[0094] Based on the preset continuous loss weighting logic of the voltage error sequence, the third hyperparameter weight corresponding to each voltage value in the voltage error sequence is generated; based on the third hyperparameter weight β, the voltage error sequence is weighted to obtain the third loss function of the voltage error sequence;

[0095] The voltage loss function is calculated based on the first loss function, the second loss function, and the third loss function.

[0096] Specifically, this embodiment calculates the voltage loss function using the following formula and preset continuous loss weighting logic.

[0097] The formula for calculating the first loss function is: loss1 = α1·V error,max ;

[0098] Where loss1 is the first loss function, Ve rror,max α1 represents the error value of the upper limit of voltage in the voltage error sequence; α1 can be preset according to the sequence length of the actual operating condition sequence.

[0099] The formula for calculating the second loss function is: loss2 = α2·W error,min ;

[0100] Where loss2 is the second loss function, V error,min α2 represents the error value of the lower voltage limit in the voltage error sequence, and can be preset according to the sequence length of the actual operating condition sequence.

[0101] The formula for calculating the third loss function is:

[0102] loss 3,i =loss 3,i-1 +β·V error,i , 1≤i≤N;

[0103] Where, loss 3,i The loss function is the third loss function calculated in the i-th iteration. 3,i-1 V is the third loss function calculated in the (i-1)th iteration. error,i Let i be the i-th error value in the voltage error sequence, i be the current iteration number for calculating the third loss function, and N be the length of the voltage error sequence. 3,N The third loss function is calculated for the Nth iteration, which is the final calculated third loss function.

[0104] The default continuous loss weighting logic is as follows:

[0105] When V error,i Greater than V threshold When , then β=β+1, i=i+1;

[0106] When V error,i Less than V threshold When, then β=1, i=i+1; where, V threshold The preset voltage error threshold can be set to 20mV;

[0107] When calculating the third loss function, first substitute i=1 into the formula for calculating the third loss function to obtain the loss. 3,1 =loss 3,0 +β·V error,1 Among them, loss 3,0 Set to 0; obtain i and β for calculating the third loss function of the next iteration based on the preset continuous loss weighting logic; each iteration uses the error value V of the current iteration. error,i The corresponding third hyperparameter weight β is used to weight the error value V. error,i ; This process is repeated until the final third loss function, loss, is obtained. 3,N .

[0108] The formula for calculating the voltage loss function is: loss = loss1 + loss2 + loss 3,N ; where loss is the voltage loss function.

[0109] In this embodiment, a first loss function, loss1, is obtained by weighting the upper limit voltage error value corresponding to the positive inflection point, a second loss function, loss2, is obtained by weighting the lower limit voltage error value corresponding to the negative inflection point, and a third loss function, loss, is obtained by weighting the voltage error sequence according to a preset continuous loss weighting logic. 3,N The final calculated voltage loss function can better characterize the difference between the voltage operating condition sequence simulated with the current parameters and the actual operating condition sequence.

[0110] This embodiment provides a method for evaluating the loss of electrochemical model parameter identification based on the foregoing embodiments. Step S160 further includes:

[0111] When the positive electrode inflection point determination result is that the positive electrode inflection point does not exist, the first loss function loss1 is set to zero.

[0112] When the negative inflection point determination result is that the negative inflection point does not exist, the second loss function loss2 is set to zero.

[0113] Based on the preset continuous loss weighting logic of the voltage error sequence, the third hyperparameter weight corresponding to each voltage value in the voltage error sequence is generated; based on the third hyperparameter weight, the voltage error sequence is weighted to obtain the third loss function of the voltage error sequence;

[0114] The voltage loss function is calculated based on the third loss function.

[0115] This embodiment provides a method where, when no inflection point exists, the loss function corresponding to the inflection point is set to zero. In this case, the fitting effect between the simulated voltage sequence obtained from the current electrochemical parameters and the actual voltage sequence can be directly determined based on the third loss function. When the error value of the third loss function continuously exceeds a threshold in the voltage error sequence, it indicates that the fitting effect of these voltage points is poor. Compared to MSE, it is more sensitive to such cases of continuous large losses, thus improving the overall fitting effect of the simulated operating condition sequence identified using this loss function. Furthermore, there may only be one inflection point. In this case, the loss function corresponding to the inflection point is set to zero. The fitting effect between the simulated voltage sequence obtained from the current electrochemical parameters and the actual voltage sequence can be determined by using the loss function corresponding to the other inflection point and the third loss function.

[0116] This embodiment provides a method for evaluating the identification loss of electrochemical model parameters based on the foregoing embodiments. After step S160, it further includes:

[0117] When the voltage loss function exceeds the preset value, the electrochemical parameters are continuously iterated using a heuristic algorithm or Kalman filtering method.

[0118] The process continues until the voltage loss function falls below a preset value, at which point the electrochemical parameters of the current iteration are used as the identified electrochemical parameters.

[0119] This embodiment provides a process for iteratively identifying electrochemical parameters using a voltage loss function. Compared to using conventional methods such as MSE and MAE to calculate the fitting between simulated and actual voltage sequences, using the voltage loss function to determine the fitting between simulated and actual voltage sequences improves the reliability of electrochemical parameter identification and the fitting effect of simulated voltage sequences.

[0120] In one embodiment, refer to the appendix to the specification. Figure 4 A loss assessment system for identifying electrochemical model parameters is provided, comprising:

[0121] The acquisition unit 10 is used to acquire the actual voltage sequence and actual current sequence of the lithium battery during a preset identification time period; and to send the actual current sequence to the electrochemical model unit 20 and the actual voltage sequence to the central control unit.

[0122] The electrochemical model unit 20 is connected to the acquisition unit 10 and is used to substitute the actual current sequence into the electrochemical model to obtain the simulated voltage sequence; the simulated voltage sequence is then sent to the central control unit.

[0123] The central control unit 30 is connected to the electrochemical model unit 20 and the acquisition unit 10, and also includes a calculation subunit 31. The calculation subunit 31 is used to obtain the voltage error sequence based on the actual voltage sequence and the simulated voltage sequence.

[0124] The calculation subunit 31 is also used to obtain the first voltage threshold and the second voltage threshold of the lithium battery based on the voltage value of the positive inflection point of the preset positive OCP curve of the lithium battery and the voltage value of the negative inflection point of the preset negative OCP curve of the lithium battery.

[0125] The central control unit 30 also includes a judgment subunit 32, which is further used to obtain the positive electrode inflection point judgment result of the lithium battery in the preset identification time period based on the first voltage threshold and the actual voltage sequence; and to obtain the negative electrode inflection point judgment result of the lithium battery in the preset identification time period based on the second voltage threshold and the actual voltage sequence.

[0126] The calculation subunit 31 is also used to weight each voltage value in the voltage error sequence according to the positive inflection point judgment result, the negative inflection point judgment result and the preset continuous loss weighting logic of the voltage error sequence, so as to obtain the voltage loss function.

[0127] In this embodiment, the judgment subunit 32 determines whether there is an inflection point in the actual voltage sequence obtained by the acquisition unit 10 where the voltage rises or falls rapidly, based on the OCP curves of the positive and negative electrodes of the lithium battery. When an inflection point exists, the actual voltage sequence obtained by the acquisition unit 10 has a phase of rapid voltage rise or fall. The calculation subunit 31 weights the error values ​​of the upper voltage limit and / or the lower voltage limit in the voltage error sequence to improve the fitting degree of the simulated operating condition sequence identified by the loss function to the phase of rapid voltage rise or fall. It also combines the preset continuous loss weighting logic to weight the voltage error sequence as a whole to increase the overall fitting effect of the simulated operating condition sequence identified by the loss function.

[0128] This embodiment, based on the previous embodiment, provides an electrochemical model parameter identification and loss assessment system.

[0129] The judgment subunit 32 is also used to determine that when there is a voltage value higher than the first voltage threshold in the actual voltage sequence, the positive electrode of the lithium battery has a positive electrode inflection point in the preset identification time period; and when there is a voltage value lower than the second voltage threshold in the actual voltage sequence, the negative electrode of the lithium battery has a negative electrode inflection point in the preset identification time period.

[0130] In this embodiment, the judgment subunit 32 compares the first voltage threshold, the second voltage threshold, and the actual voltage sequence to obtain the result of judging whether there is a positive / negative inflection point in the actual voltage sequence, so as to facilitate subsequent judgment on whether there is a rapidly changing voltage value in the actual voltage sequence, and the error value needs to be weighted separately.

[0131] This embodiment, based on the previous embodiment, provides an electrochemical model parameter identification and loss assessment system.

[0132] The calculation subunit 31 is also used to, when the positive inflection point judgment result indicates that a positive inflection point exists, use the preset first hyperparameter weight of the upper voltage limit error value to weight the upper voltage limit error value to obtain the first loss function of the upper voltage limit error value; the upper voltage limit error value is the error value corresponding to the maximum voltage value in the actual voltage sequence in the voltage error sequence; when the negative inflection point judgment result indicates that a negative inflection point exists, use the preset second hyperparameter weight of the lower voltage limit error value to weight the lower voltage limit error value to obtain the second loss function of the lower voltage limit error value; the lower voltage limit error value is the error value corresponding to the minimum voltage value in the actual voltage sequence in the voltage error sequence;

[0133] The calculation subunit 31 is also used to generate the third hyperparameter weight corresponding to each voltage value in the voltage error sequence according to the preset continuous loss weighting logic of the voltage error sequence; and to weight the voltage error sequence according to the third hyperparameter weight to obtain the third loss function of the voltage error sequence.

[0134] The calculation subunit 31 is also used to calculate the voltage loss function based on the first loss function, the second loss function, and the third loss function.

[0135] In this embodiment, the calculation subunit 31 weights the upper limit voltage error value corresponding to the positive inflection point to obtain the first loss function, weights the lower limit voltage error value corresponding to the negative inflection point to obtain the second loss function, and weights the voltage error sequence according to the preset continuous loss weighting logic to obtain the third loss function; the voltage loss function finally calculated can better characterize the difference between the voltage operating condition sequence simulated by the current parameters and the actual operating condition sequence.

[0136] This embodiment, based on the foregoing embodiments, provides an electrochemical model parameter identification and loss assessment system.

[0137] The calculation subunit 31 is also used to set the first loss function to zero when the positive electrode inflection point judgment result is that the positive electrode inflection point does not exist;

[0138] The calculation subunit 31 is also used to set the second loss function to zero when the negative pole inflection point judgment result is that the negative pole inflection point does not exist.

[0139] This embodiment provides a method where, when the inflection point does not exist, the calculation subunit 31 sets the loss function corresponding to the inflection point to zero.

[0140] This embodiment, based on the foregoing embodiments, provides an electrochemical model parameter identification and loss assessment system.

[0141] The electrochemical model unit 20 is also used to continuously iterate the electrochemical parameters using a heuristic algorithm or Kalman filtering method when the voltage loss function exceeds a preset value; until the voltage loss function is lower than the preset value, the electrochemical parameters of the current iteration are used as the identified electrochemical parameters.

[0142] This embodiment provides a process for the electrochemical model unit 20 to iteratively identify electrochemical parameters using the voltage loss function, thereby increasing the reliability of the identified electrochemical parameters.

[0143] It should be noted that the above embodiments can be freely combined as needed. The above are merely preferred embodiments of the present invention. It should be pointed out that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A loss assessment method for identifying electrochemical model parameters, characterized in that, include: Collect the actual voltage and current sequences of the lithium battery during a preset identification time period; Substituting the actual current sequence into the electrochemical model, a simulated voltage sequence is obtained; Based on the actual voltage sequence and the simulated voltage sequence, a voltage error sequence is obtained; Based on the voltage value of the positive inflection point of the preset positive OCP curve of the lithium battery and the voltage value of the negative inflection point of the preset negative OCP curve of the lithium battery, the first voltage threshold and the second voltage threshold of the lithium battery are obtained. Based on the first voltage threshold and the actual voltage sequence, the positive electrode inflection point judgment result of the lithium battery during the preset identification time period is obtained; based on the second voltage threshold and the actual voltage sequence, the negative electrode inflection point judgment result of the lithium battery during the preset identification time period is obtained. Based on the positive inflection point judgment result, the negative inflection point judgment result, and the preset continuous loss weighting logic of the voltage error sequence, each voltage value in the voltage error sequence is weighted to obtain the voltage loss function; The method involves obtaining the positive electrode inflection point judgment result of the lithium battery within a preset identification time period based on the first voltage threshold and the actual voltage sequence. Based on the second voltage threshold and the actual voltage sequence, the negative electrode inflection point determination result of the lithium battery within a preset identification time period is obtained, including: When there is a voltage value higher than the first voltage threshold in the actual voltage sequence, it is determined that the positive electrode of the lithium battery has the positive electrode inflection point in the preset identification time period. When there is a voltage value lower than the second voltage threshold in the actual voltage sequence, it is determined that the negative electrode of the lithium battery has a negative electrode inflection point in the preset identification time period.

2. The loss assessment method for identifying electrochemical model parameters according to claim 1, characterized in that, The method of weighting each voltage value in the voltage error sequence according to the positive electrode inflection point judgment result, the negative electrode inflection point judgment result, and the preset continuous loss weighting logic of the voltage error sequence to obtain the voltage loss function includes: When the positive inflection point determination result indicates that the positive inflection point exists, the voltage upper limit error value is weighted using the preset first hyperparameter weight of the voltage upper limit error value to obtain the first loss function of the voltage upper limit error value; the voltage upper limit error value is the error value corresponding to the maximum voltage value of the actual voltage sequence in the voltage error sequence; When the negative pole inflection point determination result indicates that the negative pole inflection point exists, the voltage lower limit error value is weighted using the preset second hyperparameter weight of the voltage lower limit error value to obtain the second loss function of the voltage lower limit error value; the voltage lower limit error value is the error value corresponding to the minimum voltage value of the actual voltage sequence in the voltage error sequence. Based on the preset continuous loss weighting logic of the voltage error sequence, a third hyperparameter weight corresponding to each voltage value in the voltage error sequence is generated; based on the third hyperparameter weight, the voltage error sequence is weighted to obtain the third loss function of the voltage error sequence; The voltage loss function is calculated based on the first loss function, the second loss function, and the third loss function.

3. The loss assessment method for identifying electrochemical model parameters according to claim 2, characterized in that, The method of weighting each voltage value in the voltage error sequence according to the positive electrode inflection point judgment result, the negative electrode inflection point judgment result, and the preset continuous loss weighting logic of the voltage error sequence to obtain the voltage loss function includes: When the positive electrode inflection point determination result is that the positive electrode inflection point does not exist, the first loss function is set to zero; When the negative pole inflection point determination result is that the negative pole inflection point does not exist, the second loss function is set to zero; Based on the preset continuous loss weighting logic of the voltage error sequence, a third hyperparameter weight corresponding to each voltage value in the voltage error sequence is generated; based on the third hyperparameter weight, the voltage error sequence is weighted to obtain the third loss function of the voltage error sequence; The voltage loss function is calculated based on the third loss function.

4. A loss assessment method for identifying electrochemical model parameters according to any one of claims 1-3, characterized in that, After weighting each voltage value in the voltage error sequence according to the preset continuous loss weighting logic based on the positive electrode inflection point judgment result, the negative electrode inflection point judgment result, and the voltage error sequence to obtain the voltage loss function, the method further includes: When the voltage loss function exceeds the preset value, the electrochemical parameters are continuously iterated using a heuristic algorithm or Kalman filtering method. Until the voltage loss function is lower than a preset value, the electrochemical parameters of the current iteration are used as the identified electrochemical parameters.

5. A loss assessment system for identifying electrochemical model parameters, characterized in that, include: The acquisition unit is used to acquire the actual voltage sequence and actual current sequence of the lithium battery during a preset identification time period; The actual current sequence is sent to the electrochemical model unit, and the actual voltage sequence is sent to the central control unit; The electrochemical model unit is connected to the acquisition unit and is used to substitute the actual current sequence into the electrochemical model to obtain a simulated voltage sequence; the simulated voltage sequence is then sent to the central control unit. The central control unit is connected to the electrochemical model unit and the acquisition unit, and also includes a calculation subunit, which is used to obtain a voltage error sequence based on the actual voltage sequence and the simulated voltage sequence. The calculation subunit is further configured to obtain a first voltage threshold and a second voltage threshold of the lithium battery based on the voltage value of the positive inflection point of the preset positive OCP curve of the lithium battery and the voltage value of the negative inflection point of the preset negative OCP curve of the lithium battery. The central control unit further includes a judgment subunit, which is further configured to obtain the positive electrode inflection point judgment result of the lithium battery in a preset identification time period based on the first voltage threshold and the actual voltage sequence; and to obtain the negative electrode inflection point judgment result of the lithium battery in a preset identification time period based on the second voltage threshold and the actual voltage sequence. The calculation subunit is further configured to weight each voltage value in the voltage error sequence according to the positive inflection point judgment result, the negative inflection point judgment result and the preset continuous loss weighting logic of the voltage error sequence, to obtain the voltage loss function; The judgment subunit is further configured to determine that the positive electrode of the lithium battery has a positive electrode inflection point in the preset identification time period when there is a voltage value higher than the first voltage threshold in the actual voltage sequence; and to determine that the negative electrode of the lithium battery has a negative electrode inflection point in the preset identification time period when there is a voltage value lower than the second voltage threshold in the actual voltage sequence.

6. The loss assessment system for identifying electrochemical model parameters according to claim 5, characterized in that, The calculation subunit is further configured to, when the positive electrode inflection point determination result indicates that the positive electrode inflection point exists, use a preset first hyperparameter weight of the voltage upper limit error value to weight the voltage upper limit error value to obtain a first loss function of the voltage upper limit error value; the voltage upper limit error value is the error value corresponding to the maximum voltage value of the actual voltage sequence in the voltage error sequence; When the negative pole inflection point determination result indicates that the negative pole inflection point exists, the voltage lower limit error value is weighted using the preset second hyperparameter weight of the voltage lower limit error value to obtain the second loss function of the voltage lower limit error value; the voltage lower limit error value is the error value corresponding to the minimum voltage value in the actual voltage sequence in the voltage error sequence. The calculation subunit is further configured to generate a third hyperparameter weight corresponding to each voltage value in the voltage error sequence according to a preset continuous loss weighting logic of the voltage error sequence; and to weight the voltage error sequence according to the third hyperparameter weight to obtain a third loss function of the voltage error sequence. The calculation subunit is further configured to calculate the voltage loss function based on the first loss function, the second loss function, and the third loss function.

7. The loss assessment system for identifying electrochemical model parameters according to claim 6, characterized in that, The calculation subunit is further configured to set the first loss function to zero when the positive electrode inflection point determination result is that the positive electrode inflection point does not exist; The calculation subunit is further configured to set the second loss function to zero when the negative pole inflection point determination result indicates that the negative pole inflection point does not exist.

8. A loss assessment system for identifying electrochemical model parameters according to any one of claims 5-7, characterized in that, The electrochemical model unit is also used to continuously iterate the electrochemical parameters using a heuristic algorithm or Kalman filtering method when the voltage loss function exceeds a preset value; until the voltage loss function is lower than the preset value, the electrochemical parameters of the current iteration are used as the identified electrochemical parameters.

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