All-solid-state battery mechanical stress equivalent modeling and parameter identification method

Abstract

The invention discloses an all-solid-state battery mechanical stress equivalent modeling and parameter identification method. The method comprises the steps of obtaining test data of a battery; the test data comprises a first stress, a second stress and a total mechanical stress of the battery under various test conditions; the battery is an all-solid-state battery and is fixed by a preset clamp; the first stress comprises thermal stress and initial pre-tightening force, and the second stress comprises thermal stress, mechanical static stress and initial pre-tightening force; the battery and the clamp are equivalent to an equivalent mechanical model composed of a pull rod-spring-elastic damping system; based on an equivalent mechanism of an equivalent mechanical model, the total mechanical stress between the battery and the clamp is decoupled into a coupling model related to pull rod characteristics, spring characteristics and elastic damping system characteristics; based on the coupling model and the generation mechanism of the mechanical static stress, the mechanical dynamic stress and the thermal stress of the battery, related parameters in the equivalent mechanical model are identified by using test data. The coupling model constructed by the invention can accurately calculate the mechanical stress of the solid-state battery.

Description

Technical Field

[0001] The present invention relates to the technical field of battery testing, and in particular to a method for equivalent modeling and parameter identification of mechanical stress of an all-solid-state battery. Background Art

[0002] With the rapid development of new energy vehicles and energy storage, all-solid-state batteries are considered a core development direction for next-generation power batteries due to their ultra-high energy density, excellent power performance, wide temperature adaptability, and high safety. However, during the charge and discharge process, all-solid-state batteries generate complex mechanical stresses due to factors such as lithium ion migration at the interface between the solid electrolyte and electrode materials, volume expansion / contraction effects, and temperature changes. This mechanical stress can lead to deterioration of the electrode-electrolyte interface, material crack propagation, and even battery structural failure, seriously affecting the battery's cycle life and safety.

[0003] However, the existing mechanical stress modeling methods are mainly based on liquid lithium battery systems, which are difficult to apply directly to solid-state batteries. They cannot accurately calculate the mechanical stress of solid-state batteries, and thus cannot support the life prediction and safety warning of solid-state batteries. Summary of the Invention

[0004] This invention provides a method for equivalent modeling and parameter identification of mechanical stress in all-solid-state batteries. The constructed coupling model can accurately calculate the mechanical stress of solid-state batteries. The technical solution is as follows:

[0005] On the one hand, a method for equivalent modeling and parameter identification of mechanical stress of an all-solid-state battery is provided, the method comprising:

[0006] Obtaining test data of a battery; the test data including a first stress, a second stress, and a total mechanical stress of the battery under various test conditions; the battery being an all-solid-state battery and being secured by a preset fixture; the first stress including thermal stress and an initial preload, and the second stress including thermal stress, mechanical static stress, and an initial preload;

[0007] Equivalently treating the battery and the fixture as an equivalent mechanical model consisting of a pull rod-spring-elastic damping system;

[0008] Based on the equivalent mechanism of the equivalent mechanical model, the total mechanical stress between the battery and the fixture is decoupled into a coupling model related to the characteristics of the pull rod, the spring and the elastic damping system;

[0009] Based on the coupling model and the generation mechanism of the mechanical static stress, mechanical dynamic stress and thermal stress of the battery, the test data is used to identify relevant parameters in the equivalent mechanical model.

[0010] On the other hand, a device for equivalent modeling and parameter identification of mechanical stress of an all-solid-state battery is provided, the device comprising:

[0011] an acquisition unit, configured to acquire test data of a battery; the test data including a first stress, a second stress, and a total mechanical stress of the battery under various test conditions; the battery being an all-solid-state battery and being secured by a preset fixture; the first stress including thermal stress and an initial preload, and the second stress including thermal stress, mechanical static stress, and an initial preload;

[0012] An equivalent unit, used to equate the battery and the fixture to an equivalent mechanical model consisting of a pull rod-spring-elastic damping system;

[0013] a decoupling unit, configured to decouple the total mechanical stress between the battery and the fixture into a coupling model related to pull rod characteristics, spring characteristics, and elastic damping system characteristics based on an equivalent mechanism of the equivalent mechanical model;

[0014] An identification unit is used to identify relevant parameters in the equivalent mechanical model using the test data based on the coupling model and the generation mechanism of the mechanical static stress, mechanical dynamic stress and thermal stress of the battery.

[0015] On the other hand, a computer device is provided, which includes a memory and a processor, the memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory to implement the steps of the above-mentioned all-solid-state battery mechanical stress equivalent modeling and parameter identification method.

[0016] On the other hand, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the steps of the above-mentioned all-solid-state battery mechanical stress equivalent modeling and parameter identification method are implemented.

[0017] On the other hand, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for equivalent modeling and parameter identification of mechanical stress of all-solid-state batteries.

[0018] The embodiment of the present invention provides an equivalent modeling and parameter identification method for the mechanical stress of an all-solid-state battery. First, the battery and the fixture are equivalent to an equivalent mechanical model consisting of a pull rod-spring-elastic damping system, which can simulate the mechanical dynamic force generated by the diffusion of lithium ions at the electrode-electrolyte interface and the transmission process in the electrolyte. Then, based on the equivalent mechanism, the total mechanical stress between the battery and the fixture is decoupled into a coupling model related to the pull rod characteristics, spring characteristics and elastic damping system characteristics, and the relevant parameters in the coupling model are identified in combination with the test data to obtain the identified coupling model. In this way, after determining the specific parameters of the battery and the fixture, the total mechanical stress of the battery can be accurately calculated using the coupling model. It can be seen that the coupling model constructed by the present application can more accurately reflect the complex stress changes of the all-solid-state battery during the charging and discharging process, can meet the mechanical stress detection and monitoring requirements of the all-solid-state battery, provide an efficient health management basis for the operation of the all-solid-state battery, and help to extend the cycle life of the battery and improve safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 This is a flow chart of a method for equivalent modeling and parameter identification of mechanical stress of an all-solid-state battery provided by one embodiment of the present invention;

[0021] Figure 2 This is a structural diagram of an all-solid-state battery mechanical stress equivalent modeling and parameter identification device provided by one embodiment of the present invention;

[0022] Figure 3 This is a hardware architecture diagram of a computer device provided by one embodiment of the present invention;

[0023] Figure 4 It is an equivalent mechanical model of a pull rod-spring-elastic damping system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0025] The specific implementation of the above concept is described below.

[0026] Please refer to Figure 1 , an embodiment of the present invention provides an all-solid-state battery mechanical stress equivalent modeling and parameter identification method, the method comprising:

[0027] Step 100, obtaining test data of the battery; the test data includes a first stress, a second stress, and a total mechanical stress of the battery under various test conditions; the battery is an all-solid-state battery and is fixed by a preset fixture; the first stress includes thermal stress and initial preload, and the second stress includes thermal stress, mechanical static stress, and initial preload;

[0028] Step 102 , equating the battery and the fixture to an equivalent mechanical model consisting of a pull rod-spring-elastic damping system;

[0029] Step 104 , based on the equivalent mechanism of the equivalent mechanical model, decoupling the total mechanical stress between the battery and the fixture into a coupling model related to the characteristics of the pull rod, the spring, and the elastic damping system;

[0030] Step 106 : Based on the coupling model and the generation mechanism of the mechanical static stress, mechanical dynamic stress, and thermal stress of the battery, relevant parameters in the equivalent mechanical model are identified using the test data.

[0031] In an embodiment of the present invention, first, the battery and the fixture are equivalent to an equivalent mechanical model consisting of a pull rod-spring-elastic damping system, so that the mechanical dynamic force generated by the diffusion of lithium ions at the electrode-electrolyte interface and the transmission process in the electrolyte can be simulated using the equivalent mechanical model, thereby improving the accuracy and practicality of the model. Then, based on the equivalent mechanism, the total mechanical stress between the battery and the fixture is decoupled into a coupling model related to the pull rod characteristics, spring characteristics and elastic damping system characteristics, and the relevant parameters in the coupling model are identified in combination with the test data, and the identified coupling model can be obtained. In this way, after determining the specific parameters of the battery and the fixture, the total mechanical stress of the battery can be accurately calculated using the coupling model. It can be seen that the coupling model constructed by the present application can more accurately reflect the complex stress changes of the all-solid-state battery during the charging and discharging process, can meet the mechanical stress detection and monitoring requirements of the all-solid-state battery, provide an efficient health management basis for the operation of the all-solid-state battery, and help to extend the cycle life of the battery and improve safety.

[0032] Described below Figure 1 How to perform the steps shown.

[0033] First, for step 100, the test conditions include:

[0034] Different SOH, different SOC, different charge and discharge conditions, different oven temperatures, different ambient temperatures and different initial preload forces of the battery.

[0035] The following describes the testing processes of the first stress, second stress and total mechanical stress respectively.

[0036] First, the first stress testing process.

[0037] For each initial preload, execute A1 to A3:

[0038] A1. Place the battery in a constant temperature box and let it rest at 25°C.

[0039] A2, discharge the battery with constant current to the cut-off voltage and let it rest for a long time;

[0040] A3. Adjust the temperature of the incubator in sequence. At each temperature, adjust the preload force of the battery fixture to the current initial preload force. Allow the battery to stand for a long time to allow it to reach full thermal equilibrium. Record the mechanical stress value of the battery at each temperature, i.e., the first stress value.

[0041] After steps A1 to A3, the first stress measurement value of the battery at each initial preload force and each set temperature can be obtained, and the corresponding relationship between the initial preload force, temperature, and the first stress measurement value can be obtained.

[0042] In addition, by subtracting the corresponding initial preload force from each first stress measurement value, the thermal stress measurement value of the battery at each set temperature can be obtained, that is, the corresponding relationship between initial preload force, temperature, and thermal stress measurement value.

[0043] Second, the second stress testing process.

[0044] For each initial preload force, execute B1 to B3:

[0045] B1. Place the battery in a constant temperature box and let it rest at 25°C.

[0046] B2, discharge the battery at a constant current to the cut-off voltage, let it rest for a long time, and set the battery preload to the current initial preload;

[0047] B3, constant current constant voltage charging, is performed at each SOC: the incubator temperature is adjusted sequentially. At each temperature, the battery is allowed to stand for a sufficient period of time to achieve full thermal equilibrium. The mechanical stress value of the battery at each temperature is recorded, i.e., the second stress value. Repeat the second stress test of the battery until the battery SOC reaches 100%.

[0048] After steps B1 to B3, the second stress measurement value of the battery at each initial preload force, each SOC and each set temperature can be obtained, and the corresponding relationship between initial preload force-SOC-temperature-second stress measurement value can be obtained.

[0049] Furthermore, by subtracting the first stress measurement under the corresponding condition from each second stress measurement value, the mechanical static stress measurement value of the battery at each SOC can be obtained. This indicates the correspondence between initial preload, SOC, temperature, and mechanical static stress measurement value. Furthermore, after obtaining each mechanical static stress measurement value, a correspondence table between SOC and mechanical static stress can be generated. This correspondence table can be used to determine the mechanical static stress at any SOC through interpolation.

[0050] Third, the testing process of total mechanical stress.

[0051] For each initial preload, execute C1 to C3:

[0052] C1, place the battery in a constant temperature box and let it rest at 25℃.

[0053] C2, discharge the battery at a constant current to the cut-off voltage, let it rest for a long time, and set the battery preload to the current initial preload;

[0054] C3, adjust the temperature of the incubator in sequence. At each temperature, perform constant current and constant voltage charging. At preset intervals, test the total mechanical stress of the battery during charging until the battery SOC reaches 100%. Repeat this process until the test results at each temperature are obtained.

[0055] After steps C1 to C3, the total mechanical stress measurement value of the battery at each initial preload force, each set temperature and charging process can be obtained, and the corresponding relationship between the initial preload force-each SOC charging stage-temperature-total mechanical stress measurement value can be obtained.

[0056] In addition, the present application can also construct a battery aging mechanical stress experimental data set, perform constant current and constant voltage charge and discharge on the battery, repeat the above-mentioned first stress, second stress and total mechanical stress test steps, record the battery mechanical stress data under different SOH, and construct a battery mechanical stress experimental data set Z, where Z = {[Z1Z2Z3] 100 ,[Z1Z2Z3] 99 …[Z1Z2Z3] x}, where x is the cutoff SOH value; Z1, Z2, and Z3 represent the first stress set, the second stress set, and the total mechanical stress set, respectively.

[0057] For step 102, if Figure 4As shown, the clamp consists of an upper clamping plate, a lower clamping plate and two second pull rods. The battery is arranged between the upper clamping plate and the lower clamping plate. The two ends of the two second pull rods are respectively connected to the upper clamping plate and the lower clamping plate to apply an initial preload force to the battery.

[0058] Step 102 includes:

[0059] D1. Determine the equivalent conditions, which include: uniform intercalation and deintercalation of the battery at the positive and negative electrodes; uniform diffusion of lithium ions at the interface and in the electrolyte; and the mechanical stress on the battery being perpendicular to the large surface of the battery, i.e., the positive electrode-electrolyte-negative electrode direction.

[0060] D2, based on the equivalent conditions, the battery is equivalent to the first pull rod, so as to characterize the mechanical behavior of the battery volume change based on the first pull rod; the mechanical behavior of the solid electrolyte, the clamp and the force sensor between the clamps in the battery is equivalent to the first spring, one end of the first spring is connected to the top of the first pull rod, and the other end is connected to the inner wall of the upper clamp; the mechanical behavior generated by the diffusion of lithium ions at the solid-solid interface between the electrode and the electrolyte is equivalent to a spring damping system, and the spring damping system includes a second spring and a damper arranged in parallel; the mechanical connection of the clamp device is equivalent to the second pull rod.

[0061] In step D1, by adopting the above equivalent conditions, it can be obtained that the total mechanical stress of the battery mainly includes the mechanical static force F generated by the change of the porous electrode structure caused by the lithium ion insertion and extraction at the positive and negative electrodes. e , the mechanical dynamic force F caused by the diffusion of lithium ions across the solid-solid interface and in the electrolyte d , and the thermal stress F caused by thermal expansion due to the overall temperature change of the battery T .

[0062] Therefore, the total stress F generated during the battery operation is total It can be calculated by the following formula:

[0063] F total =F T +F d +F e +F in (1)

[0064] Where, F in is the initial preload.

[0065] For step 104 , the coupling model is constructed in the following manner.

[0066] In this step, if Figure 4As shown, when the battery is charged and discharged and the SOC changes, an equivalent force is applied to point A of the battery, and the resulting displacement is u1. When lithium ions diffuse at the solid-solid interface, an equivalent force is applied to point B, and the displacement is u2. At this time, the force on point C is the interaction force between the first spring and the fixture, which is the same as the value measured by the force sensor, both F total .

[0067] At this time, the force sensor measured value F total is the coupling value of the stress change between the battery and the fixture, and its calculation formula is as follows:

[0068] F total =k s (ΔL1+ΔL2)=σA (2)

[0069] Where k s is the equivalent elastic coefficient of the first spring, ΔL1 is the deformation of the first rod, and ΔL2 is the deformation of the second rod, where ΔL1=u1+u2, σ is the stress value of the battery, and A is the contact area between the battery and the fixture. The deformation of L2 is defined as caused by the thermal expansion of the fixture. Therefore, when the fixture temperature changes ΔT s When , the strain of the second rod is:

[0070]

[0071] According to the principle of mechanical stress generation, the strain of the first tie rod is:

[0072]

[0073] In formula 4, the right sides of the equation are the thermal strain, mechanical static strain, mechanical dynamic strain and resistance strain of the battery.

[0074] Combining formulas 2 to 4, we can get the expression of the total mechanical stress of the battery, that is, the expression of the coupling model is:

[0075]

[0076] The following is a detailed description of the process of determining the parameters in the above formula:

[0077] 1. When the solid-state battery-fixture system reaches thermal equilibrium, its mechanical dynamic stress and fixture thermal equilibrium can be ignored. At this time, by simplifying Equations 1 and 5, the mechanical static strain of the battery can be obtained as:

[0078]

[0079] In formula 6, F eThe mechanical static stress at any SOC can be obtained by interpolation according to the corresponding relationship table between SOC and mechanical static stress.

[0080] 2. When the battery mechanical stress fixture is in a static state after charging, the temperature difference between the core temperature and the surface temperature of the battery can be ignored. Therefore, by simplifying Equations 1 and 5, the mechanical dynamic strain of the battery can be obtained as:

[0081]

[0082] 3. Since the mechanical dynamic stress of solid-state batteries is generated inside the battery and has a long relaxation time, a spring damping system is used to simulate this process.

[0083] Assuming that the battery only generates mechanical dynamic stress, then in the constant current state, the force at point B is:

[0084]

[0085] At this time, the strain generated by dynamic diffusion is The state equation of mechanical dynamic stress can be expressed as:

[0086]

[0087] Where, σ d is the mechanical dynamic stress per unit area; k b is the equivalent elastic coefficient of the second spring, D b is the equivalent damping coefficient of the damper.

[0088] 4. During the actual operation of the battery, the current will change. Therefore, it is necessary to add the calculation part of the mechanical dynamic stress related to the battery rate. At this time, the state equation of the mechanical dynamic stress can be expressed as:

[0089]

[0090] Where, F d The derivative of; λ2 is the battery rate factor; C n is the battery capacity; I is the current.

[0091] Through the above deduction process, in the coupling model shown in Formula 5, A, l1, and l2 involved can be directly obtained by measurement, α F is the battery material characteristic, and parameter k s 、k b 、D b , λ2 cannot be calculated directly, so parameter identification is required.

[0092] For step 106, the relevant parameters in the coupling model are identified in the following manner:

[0093] First, the identification process of the equivalent elastic coefficient of the first spring.

[0094] Based on the coupling model, the first calculation formula for the battery thermal stress experimental value when the battery has no current input and reaches thermal equilibrium is determined as follows:

[0095]

[0096] Construct the first objective function related to the battery thermal stress experimental value and the measured value:

[0097]

[0098] Where, is the first objective function, N T is the number of thermal stress points, F T,exp (j) and F T,cal (j) are the measured and experimental values of the jth thermal stress point, respectively;

[0099] Calculate the difference between each first stress and the initial preload force to obtain the thermal stress measurement value of each thermal stress point of the battery;

[0100] For each thermal stress measurement value, based on the test conditions corresponding to the measurement value, a preset algorithm is used to optimize the equivalent elastic coefficient of the first spring, and the optimization result is substituted into the first calculation formula to obtain the corresponding thermal stress experimental value; and a first objective function is calculated based on each thermal stress experimental value and the corresponding thermal stress measurement value;

[0101] The same process is repeated until the optimization result satisfies the convergence condition of the first objective function, and the identification result of the equivalent elastic coefficient of the first spring is obtained.

[0102] In this step, only k in Formula 11 s is an unknown number, for each round of k s Substitute it and other parameters corresponding to the data points into Formula 11 to obtain the experimental value of thermal stress. Substitute the experimental value and the test value into Formula 12 to obtain the corresponding first objective function until the objective function converges to obtain the final equivalent elastic coefficient of the first spring.

[0103] Second, the identification process of the equivalent elastic coefficient of the second spring and the equivalent damping coefficient of the damper.

[0104] Based on the working mechanism of the coupling model and the spring damping system, the second calculation formula for the mechanical dynamic stress of the battery when the battery is fully charged and in a stationary state is determined:

[0105]

[0106] Construct the second objective function related to the experimental and measured values of the battery mechanical dynamic stress:

[0107]

[0108] Where, is the second objective function, N d is the number of mechanical dynamic stress points, F d,exp (m) and F d,cal (m) are the measured and experimental values of the mth mechanical dynamic stress point, respectively;

[0109] Calculating the difference between each mechanical total stress measurement value and the corresponding second stress respectively to obtain the mechanical dynamic stress measurement value of each mechanical dynamic stress point of the battery;

[0110] For each mechanical dynamic stress measurement value, based on the test conditions corresponding to the measurement value, a preset algorithm is used to optimize the equivalent elastic coefficient of the second spring and the equivalent damping coefficient of the damper, and the optimization result is substituted into the second calculation formula to obtain the corresponding mechanical dynamic stress experimental value; and a second objective function is calculated based on each mechanical dynamic stress experimental value and the corresponding mechanical dynamic stress measurement value;

[0111] The same process is repeated until the optimization result satisfies the convergence condition of the second objective function, and the identification results of the equivalent elastic coefficient of the second spring and the equivalent damping coefficient of the damper are obtained.

[0112] In this step, only k in Formula 13 b and D b is an unknown number, for each round of k b and D b Substituting it and the other parameters corresponding to the data points into Formula 13, we can obtain the experimental value of the mechanical dynamic stress. Substituting the experimental value and the test value into Formula 14, we can obtain the corresponding second objective function. Until the objective function converges, we can obtain the final equivalent elastic coefficient of the second spring and the equivalent damping coefficient of the damper.

[0113] Third, the identification process of battery rate factor.

[0114] The third calculation formula for determining the mechanical dynamic stress of the battery during variable current charging is:

[0115]

[0116] Construct the third objective function related to the experimental and measured values of the total mechanical stress of the battery:

[0117]

[0118] Where, is the third objective function, N F is the number of total mechanical stress points, F total,exp (n) and F total,cal (n) are the measured and experimental values of the nth total mechanical stress point, respectively;

[0119] For each total mechanical stress measurement value in the test data, a preset algorithm is used to optimize the battery rate factor based on the test conditions corresponding to the measurement value, and the optimization result is substituted into the third calculation formula to obtain the corresponding mechanical dynamic stress experimental value. The experimental value is substituted into the coupling model to obtain the mechanical total stress experimental value; and the third objective function is calculated based on each mechanical total stress experimental value and the corresponding mechanical total stress measurement value;

[0120] The process is deduced in this way until the optimization result meets the convergence condition of the third objective function, and the identification result of the battery rate factor is obtained.

[0121] In this step, only λ2 is an unknown in Formula 15. For each round of λ2, it and the other parameters corresponding to the data points are substituted into Formulas 15, 8, 7, 6, and 5, respectively, to obtain the experimental value of the total mechanical stress. The experimental and test values are substituted into Formula 16 to obtain the corresponding third objective function, and the final battery rate factor is obtained until the objective function converges. In addition, the battery rate factor is a parameter related to the current. Different currents will result in different battery rate factors.

[0122] It should be noted that, in the above identification process, the preset algorithm may be recursive least squares method, particle swarm optimization method, genetic algorithm, etc., and this application does not make any specific limitation.

[0123] After identifying the unknown parameters through the above process, the final coupling model is obtained. Once the battery temperature, temperature variation, SOC, SOH, initial preload, current, and fixture parameters are determined, the final total mechanical stress can be calculated according to Equations 5-10. This calculated total mechanical stress can then be used to assess battery life and safety, facilitating battery health management.

[0124] like Figure 2 、 Figure 3 As shown, the embodiment of the present invention provides an all-solid-state battery mechanical stress equivalent modeling and parameter identification device. The device embodiment can be implemented by software, hardware, or a combination of software and hardware. From the hardware level, such as Figure 2 As shown in FIG. 1 , a hardware architecture diagram of a computing device where an all-solid-state battery mechanical stress equivalent modeling and parameter identification device is located is provided in an embodiment of the present invention. Figure 2In addition to the processor, memory, network interface, and non-volatile memory shown, the computing device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing messages, etc. Taking software implementation as an example, Figure 3 As shown, as a device in a logical sense, it is formed by the CPU of the computing device in which it is located reading the corresponding computer program in the non-volatile memory into the internal memory and running it.

[0125] Please refer to Figure 3 , the embodiment of the present application provides an all-solid-state battery mechanical stress equivalent modeling and parameter identification device, comprising:

[0126] An acquisition unit 300 is configured to acquire test data of the battery; the test data includes a first stress, a second stress, and a total mechanical stress of the battery under various test conditions; the battery is an all-solid-state battery and is secured by a preset fixture; the first stress includes thermal stress and an initial preload, and the second stress includes thermal stress, mechanical static stress, and an initial preload;

[0127] An equivalent unit 302 is used to equate the battery and the fixture to an equivalent mechanical model consisting of a pull rod-spring-elastic damping system;

[0128] a decoupling unit 304 for decoupling the total mechanical stress between the battery and the fixture into a coupling model related to the characteristics of the pull rod, the spring, and the elastic damping system based on an equivalent mechanism of the equivalent mechanical model;

[0129] The identification unit 306 is used to identify relevant parameters in the equivalent mechanical model using the test data based on the coupling model and the generation mechanism of the mechanical static stress, mechanical dynamic stress and thermal stress of the battery.

[0130] In some embodiments, the test conditions include:

[0131] Different SOH, different SOC, different charge and discharge conditions, different oven temperatures, different ambient temperatures and different initial preload forces of the battery.

[0132] In some embodiments, the clamp comprises an upper clamping plate, a lower clamping plate, and two second pull rods. The battery is disposed between the upper clamping plate and the lower clamping plate. The two second pull rods are connected to the upper clamping plate and the lower clamping plate at both ends, respectively, for applying an initial preload force to the battery. The equivalent unit 302 is configured to perform the following operations:

[0133] Determine the equivalent conditions, which include: uniform intercalation and deintercalation of the battery at the positive and negative electrodes; uniform diffusion of lithium ions at the interface and in the electrolyte; and the mechanical stress on the battery being perpendicular to the large surface of the battery.

[0134] Based on the equivalent conditions, the battery is equivalent to the first pull rod, and the mechanical behavior of the battery volume change is characterized based on the first pull rod; the mechanical behavior of the solid electrolyte, the clamp and the force sensor between the clamps in the battery is equivalent to the first spring, one end of the first spring is connected to the top of the first pull rod, and the other end is connected to the inner wall of the upper clamp; the mechanical behavior generated by the diffusion of lithium ions at the solid-solid interface between the electrode and the electrolyte is equivalent to a spring damping system, and the spring damping system includes a second spring and a damper arranged in parallel; the mechanical connection of the clamp device is equivalent to the second pull rod.

[0135] In some embodiments, the coupling model is:

[0136]

[0137] When constant current charging and discharging,

[0138] When the variable current is charged and discharged,

[0139] Where, F total is the total mechanical stress of the battery; k s is the equivalent elastic coefficient of the first spring; α b is the thermal expansion coefficient of the battery; ε e is the mechanical static strain of the battery; ε d is the mechanical dynamic strain of the battery; α F is the thermal expansion coefficient of the fixture; ΔT i is the change in battery core temperature; ΔT s is the temperature change of the fixture; L1 is the length of the first pull rod; L2 is the length of the second pull rod; A is the contact area between the battery and the fixture; E is the equivalent elastic modulus of the first pull rod; T i is the core temperature of the battery; F in is the initial preload force of the fixture; F e and F d are the mechanical static stress and mechanical dynamic stress of the battery respectively; k b is the equivalent elastic coefficient of the second spring, D b is the equivalent damping coefficient of the damper; F d The derivative of; λ2 is the battery rate factor; C n is the battery capacity; I is the current.

[0140] In some embodiments, the relevant parameters include an equivalent elastic coefficient of the first spring; the equivalent elastic coefficient of the first spring is identified as follows:

[0141] Based on the coupling model, the first calculation formula for the battery thermal stress experimental value when the battery has no current input and reaches thermal equilibrium is determined as follows:

[0142]

[0143] Construct the first objective function related to the battery thermal stress experimental value and the measured value:

[0144]

[0145] Where, is the first objective function, N T is the number of thermal stress points, F T,exp (j) and F T,cal (j) are the measured and experimental values of the jth thermal stress point, respectively;

[0146] Calculate the difference between each first stress and the initial preload force to obtain the thermal stress measurement value of each thermal stress point of the battery;

[0147] For each thermal stress measurement value, based on the test conditions corresponding to the measurement value, a preset algorithm is used to perform optimal calculation on the equivalent elastic coefficient of the first spring, and the optimization result is substituted into the first calculation formula to obtain the corresponding thermal stress experimental value; the first objective function is calculated based on each thermal stress experimental value and the corresponding thermal stress measurement value; and it is determined whether the convergence condition is met. If so, the optimization is stopped; if not, the next round of calculation is entered until the optimization result meets the convergence condition of the first objective function, and the identification result of the equivalent elastic coefficient of the first spring is obtained.

[0148] In some embodiments, the relevant parameters further include an equivalent elastic coefficient of the second spring and an equivalent damping coefficient of the damper; the equivalent elastic coefficient of the second spring and the equivalent damping coefficient of the damper are identified as follows:

[0149] Based on the working mechanism of the coupling model and the spring damping system, the second calculation formula for the mechanical dynamic stress of the battery when the battery is fully charged and in a stationary state is determined:

[0150]

[0151] Construct the second objective function related to the experimental and measured values of the battery mechanical dynamic stress:

[0152]

[0153] Where, is the second objective function, N d is the number of mechanical dynamic stress points, F d,exp (m) and F d,cal (m) are the measured and experimental values of the mth mechanical dynamic stress point, respectively;

[0154] Calculating the difference between each mechanical total stress measurement value and the corresponding second stress respectively to obtain the mechanical dynamic stress measurement value of each mechanical dynamic stress point of the battery;

[0155] For each mechanical dynamic stress measurement value, based on the test conditions corresponding to the measurement value, a preset algorithm is used to perform optimal calculation on the equivalent elastic coefficient of the second spring and the equivalent damping coefficient of the damper, and the optimization result is substituted into the second calculation formula to obtain the corresponding mechanical dynamic stress experimental value; the second objective function is calculated based on each mechanical dynamic stress experimental value and the corresponding mechanical dynamic stress measurement value; and it is judged whether the convergence condition is met. If so, the optimization is stopped; if not, the next round of calculation is entered until the optimization result meets the convergence condition of the second objective function, and the identification results of the equivalent elastic coefficient of the second spring and the equivalent damping coefficient of the damper are obtained.

[0156] In some embodiments, when the battery is in a variable current operating condition, the relevant parameters also include a battery rate factor, which is identified as follows:

[0157] The third calculation formula for determining the mechanical dynamic stress of the battery during variable current charging is:

[0158]

[0159] Construct the third objective function related to the experimental and measured values of the total mechanical stress of the battery:

[0160]

[0161] Where, is the third objective function, N F is the number of total mechanical stress points, F total,exp (n) and F total,cal (n) are the measured and experimental values of the nth total mechanical stress point, respectively;

[0162] For each mechanical total stress measurement value in the test data, a preset algorithm is used to optimize the battery rate factor based on the test conditions corresponding to the measurement value, and the optimization result is substituted into the third calculation formula to obtain the corresponding mechanical dynamic stress experimental value, and the experimental value is substituted into the coupling model to obtain the mechanical total stress experimental value; the third objective function is calculated based on each mechanical total stress experimental value and the corresponding mechanical total stress measurement value; and it is judged whether the convergence condition is met. If so, the optimization is stopped; if not, the next round of calculation is entered until the optimization result meets the convergence condition of the third objective function, and the identification result of the battery rate factor is obtained.

[0163] It should be noted that the all-solid-state battery mechanical stress equivalent modeling and parameter identification device provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the all-solid-state battery mechanical stress equivalent modeling and parameter identification device provided in the above embodiment and the all-solid-state battery mechanical stress equivalent modeling and parameter identification method embodiment are of the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0164] The embodiment of the present application also provides a computer device, please refer to Figure 3 The computer device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor to implement the all-solid-state battery mechanical stress equivalent modeling and parameter identification method provided by the above-mentioned method embodiments.

[0165] An embodiment of the present application also provides a computer-readable storage medium, which stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by a processor to implement the all-solid-state battery mechanical stress equivalent modeling and parameter identification method provided by the above-mentioned method embodiments.

[0166] An embodiment of the present application also provides a computer program product, which includes a computer program. The processor of a computer device reads the computer program from a computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the all-solid-state battery mechanical stress equivalent modeling and parameter identification method described in any of the above embodiments.

[0167] For the convenience of description, the above systems or devices are described as being divided into various modules or units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0168] Through the description of the above embodiments, it can be seen that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present application or certain parts of the embodiments.

[0169] Finally, it should be noted that, in this document, relational terms such as first, second, third, and fourth are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus comprising the element.

[0170] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for equivalent modeling and parameter identification of mechanical stress of all-solid-state batteries, characterized in that: The method comprises: Obtaining test data of a battery; the test data including a first stress, a second stress, and a total mechanical stress of the battery under various test conditions; the battery being an all-solid-state battery and being secured by a preset fixture; the first stress including thermal stress and an initial preload, and the second stress including thermal stress, mechanical static stress, and an initial preload; Equivalently treating the battery and the fixture as an equivalent mechanical model consisting of a pull rod-spring-elastic damping system; Based on the equivalent mechanism of the equivalent mechanical model, the total mechanical stress between the battery and the fixture is decoupled into a coupling model related to the characteristics of the pull rod, the spring and the elastic damping system; Based on the coupling model and the generation mechanism of the mechanical static stress, mechanical dynamic stress and thermal stress of the battery, the test data is used to identify relevant parameters in the equivalent mechanical model.

2. The method according to claim 1, characterized in that The test conditions include: The battery has different SOH, different SOC, different charge and discharge conditions, different oven temperatures, different ambient temperatures and different initial preload forces.

3. The method according to claim 1, characterized in that The clamp consists of an upper clamping plate, a lower clamping plate and two second pull rods. The battery is arranged between the upper clamping plate and the lower clamping plate. The two ends of the two second pull rods are respectively connected to the upper clamping plate and the lower clamping plate to apply an initial preload force to the battery. The battery and the fixture are equivalent to an equivalent mechanical model consisting of a pull rod-spring-elastic damping system, including: Determine equivalent conditions, which include: uniform intercalation and deintercalation of the battery at the positive and negative electrodes; uniform diffusion of lithium ions at the interface and in the electrolyte; and mechanical stress on the battery perpendicular to the large surface of the battery. Based on the equivalent condition, the battery is equivalent to a first pull rod, so as to characterize the mechanical behavior of the volume change of the battery based on the first pull rod; the mechanical behavior of the solid electrolyte, the clamp and the force sensor between the clamps in the battery is equivalent to a first spring, one end of the first spring is connected to the top of the first pull rod, and the other end is connected to the inner wall of the upper clamp; the mechanical behavior generated by the diffusion of lithium ions at the solid-solid interface between the electrode and the electrolyte is equivalent to a spring damping system, and the spring damping system includes a second spring and a damper arranged in parallel; the mechanical connection of the clamp device is equivalent to a second pull rod.

4. The method according to claim 3, characterized in that The expression of the coupling model is: When constant current charging and discharging, When the variable current is charged and discharged, Where, F total is the total mechanical stress of the battery; k s is the equivalent elastic coefficient of the first spring; α b is the thermal expansion coefficient of the battery; ε e is the mechanical static strain of the battery; ε d is the mechanical dynamic strain of the battery; α F is the thermal expansion coefficient of the fixture; ΔT i is the change in battery core temperature; ΔT s is the temperature change of the fixture; L1 is the length of the first pull rod; L2 is the length of the second pull rod; A is the contact area between the battery and the fixture; E is the equivalent elastic modulus of the first pull rod; T i is the core temperature of the battery; F e and F d are the mechanical static stress and mechanical dynamic stress of the battery respectively; k b is the equivalent elastic coefficient of the second spring, D b is the equivalent damping coefficient of the damper; F d The derivative of; λ2 is the battery rate factor; C n is the battery capacity; I is the current.

5. The method according to claim 4, characterized in that The relevant parameters include the equivalent elastic coefficient of the first spring; the equivalent elastic coefficient of the first spring is obtained by identification in the following manner: Based on the coupling model, a first calculation formula for the battery thermal stress experimental value when the battery has no current input and reaches thermal equilibrium is determined: Construct the first objective function related to the battery thermal stress experimental value and the measured value: Where, is the first objective function, N T is the number of thermal stress points, F T,exp (j) and F T,cal (j) are the measured and experimental values of the jth thermal stress point, respectively; Calculate the difference between each first stress and the initial preload force to obtain the thermal stress measurement value of each thermal stress point of the battery; For each thermal stress measurement value, based on the test conditions corresponding to the measurement value, a preset algorithm is used to optimize the equivalent elastic coefficient of the first spring, and the optimization result is substituted into the first calculation formula to obtain the corresponding thermal stress experimental value; Calculating the first objective function based on each thermal stress experimental value and the corresponding thermal stress measurement value; The same process is repeated until the optimization result satisfies the convergence condition of the first objective function, thereby obtaining the identification result of the equivalent elastic coefficient of the first spring.

6. The method according to claim 4, characterized in that The relevant parameters also include an equivalent elastic coefficient of the second spring and an equivalent damping coefficient of the damper; the equivalent elastic coefficient of the second spring and the equivalent damping coefficient of the damper are obtained by identification in the following manner: Based on the working mechanism of the coupling model and the spring damping system, a second calculation formula for the mechanical dynamic stress of the battery when the battery is fully charged and in a stationary state is determined: Construct the second objective function related to the experimental and measured values of the battery mechanical dynamic stress: Where, is the second objective function, N d is the number of mechanical dynamic stress points, F d,exp (m) and F d,cal (m) are the measured and experimental values of the mth mechanical dynamic stress point, respectively; Calculating the difference between each mechanical total stress measurement value and the corresponding second stress respectively to obtain the mechanical dynamic stress measurement value of each mechanical dynamic stress point of the battery; For each mechanical dynamic stress measurement value, based on the test conditions corresponding to the measurement value, a preset algorithm is used to optimize the equivalent elastic coefficient of the second spring and the equivalent damping coefficient of the damper, and the optimization result is substituted into the second calculation formula to obtain the corresponding mechanical dynamic stress experimental value; Calculating the second objective function based on each mechanical dynamic stress experimental value and the corresponding mechanical dynamic stress measurement value; The same process is repeated until the optimization result satisfies the convergence condition of the second objective function, and the identification results of the equivalent elastic coefficient of the second spring and the equivalent damping coefficient of the damper are obtained.

7. The method according to claim 6, characterized in that When the battery is in a variable current operating condition, the relevant parameters also include a battery rate factor, which is obtained by identifying: The third calculation formula for determining the mechanical dynamic stress of the battery during variable current charging is: Construct the third objective function related to the experimental and measured values of the total mechanical stress of the battery: Where, is the third objective function, N F is the number of total mechanical stress points, F total,exp (n) and F total,cal (n) are the measured and experimental values of the nth total mechanical stress point, respectively; For each total mechanical stress measurement value in the test data, based on the test conditions corresponding to the measurement value, a preset algorithm is used to optimize the battery rate factor, and the optimization result is substituted into the third calculation formula to obtain a corresponding mechanical dynamic stress experimental value, and the experimental value is substituted into the coupling model to obtain a total mechanical stress experimental value; Calculating the third objective function based on each mechanical total stress experimental value and the corresponding mechanical total stress measurement value; The process is deduced in this way until the optimization result satisfies the convergence condition of the third objective function, thereby obtaining the identification result of the battery rate factor.

8. A device for equivalent modeling and parameter identification of mechanical stress of all-solid-state batteries, characterized in that: The device comprises: an acquisition unit, configured to acquire test data of a battery; the test data including a first stress, a second stress, and a total mechanical stress of the battery under various test conditions; the battery being an all-solid-state battery and being secured by a preset fixture; the first stress including thermal stress and an initial preload, and the second stress including thermal stress, mechanical static stress, and an initial preload; An equivalent unit, used to equate the battery and the fixture to an equivalent mechanical model consisting of a pull rod-spring-elastic damping system; a decoupling unit, configured to decouple the total mechanical stress between the battery and the fixture into a coupling model related to pull rod characteristics, spring characteristics, and elastic damping system characteristics based on an equivalent mechanism of the equivalent mechanical model; An identification unit is used to identify relevant parameters in the equivalent mechanical model using the test data based on the coupling model and the generation mechanism of the mechanical static stress, mechanical dynamic stress and thermal stress of the battery.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to implement the steps of any one of the methods described in claims 1-7.

10. A computer-readable storage medium, characterized in that The storage medium stores a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 7.

Images