Solid-state battery capacity grading method and system based on sampling resistor temperature compensation

Abstract

The invention belongs to the technical field of battery capacity grading detection, and particularly relates to a solid-state battery capacity grading method and system based on sampling resistor temperature compensation, and the method comprises the steps: collecting the local temperature of a sampling resistor and the voltages at the two ends of the sampling resistor in a capacity grading detection loop in real time; the actual resistance value of the sampling resistor is dynamically corrected through a resistance value-temperature model integrating first-order and second-order temperature coefficients and a self-heating power effect, so that high-precision real current is calculated, and the accurate capacity of the solid-state battery is determined according to the real current. The system correspondingly comprises a temperature sensor, a temperature compensation processing module and other hardware. By directly monitoring and compensating the temperature drift of the sampling resistor, the problem of capacity calculation error caused by self-heating of the resistor under large current is effectively solved, and the precision and reliability of solid-state battery capacity grading detection are remarkably improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of battery capacity grading detection, and particularly relates to a solid-state battery capacity grading method and system based on sampling resistor temperature compensation. BACKGROUND

[0002] In the manufacturing process of solid-state batteries, capacity grading detection is a crucial process, which aims to accurately measure the actual charge and discharge capacity of the battery, and then perform performance screening and grade division, so as to ensure the consistency of the batteries leaving the factory. At present, the capacity grading system generally adopts the method of connecting a sampling resistor (shunt) in series in the charge and discharge circuit, measures the voltage across the resistor to obtain the current, and then integrates the current in time to calculate the battery capacity. However, this technology has an inherent error source that has not been effectively solved for a long time: the resistance value of the sampling resistor will drift with temperature changes. In the working condition of large current (usually ≥ 50A) and long time charge and discharge, the current flowing through the sampling resistor will generate significant Joule heat, causing the local temperature to rise rapidly by 10-20℃. Since the sampling resistor generally has a non-negligible temperature coefficient (usually ±20~±100ppm / ℃), its resistance value will change by 0.1%~0.4%. This change is directly introduced into the current sampling link and ultimately transmitted to the capacity calculation result, causing a non-negligible measurement error.

[0003] In the prior art, in order to alleviate this problem, an environmental temperature sensor or a battery body temperature sensor is used to compensate for the temperature of the sampling resistor. However, the heating of the sampling resistor is highly localized and transient, and there is a significant lag and deviation between its actual temperature and the environmental temperature or the battery temperature. This "indirect" compensation method cannot accurately and timely reflect the real temperature state of the sampling resistor body, so it is difficult to completely eliminate the temperature drift error introduced by the self-heating of the resistor.

[0004] Therefore, there is an urgent need in the art for a high-precision capacity grading detection method and system that can directly and timely monitor and compensate for the temperature of the sampling resistor body. SUMMARY

[0005] The purpose of the present application is to provide a solid-state battery capacity grading method and system based on sampling resistor temperature compensation, aiming to solve the technical problem of introducing current sampling and capacity calculation errors due to the resistance value temperature drift of the sampling resistor caused by self-heating in the capacity grading detection of solid-state batteries.

[0006] The present application achieves the above-mentioned purpose by the following technical solutions: In a first aspect, the present application provides a solid-state battery capacity grading method based on sampling resistor temperature compensation, which comprises the following steps: connecting a solid-state battery to be tested into a capacity grading detection circuit with a sampling resistor, the sampling resistor having a known nominal resistance value ; During the charging and discharging process of the battery, the voltage signal V across the sampling resistor and the local temperature T of the sampling resistor are synchronously collected; According to the preset resistance-temperature model , the actual resistance value of the sampling resistor at the current temperature is determined ; Wherein, is the reference temperature, is the first-order temperature coefficient, is the second-order temperature coefficient, is the self-heating power coefficient, is the instantaneous self-heating power of the sampling resistor; According to the actual resistance value , the voltage signal V is converted into the current value I; According to the current value I, the actual charging and discharging capacity of the solid-state battery is determined.

[0007] Further, the instantaneous self-heating power is obtained by the following formula: ; Wherein is the sampling interval, and are the current value and resistance value at the previous sampling time, respectively.

[0008] Further, before the to-be-tested solid-state battery is connected to the capacity-detecting circuit with the sampling resistor, the method further comprises calibrating the nominal resistance value of the sampling resistor, comprising: Making the capacity-detecting circuit in an open circuit state and lasting for a first preset time length, so as to cool the sampling resistor to a cold state balanced with the ambient temperature; When the loop current is less than a set threshold, collecting the average initial voltage across the sampling resistor and the average local temperature of the sampling resistor at this time; Injecting a calibration current with a known size into the loop , and collecting the voltage across the sampling resistor at this time ; According to the formula = / , the calibrated cold resistance value is calculated, and the is updated to the nominal resistance value in the resistance-temperature model .

[0009] Further, the updating a nominal resistance in the resistance-temperature model , comprising: based on the calibrated cold resistance , a corresponding local temperature at the time of measurement , the first-order temperature coefficient , and a predetermined reference temperature , determining a standard resistance at the reference temperature , and updating the resistance-temperature model in the . . .

[0010] Further, the determination of the standard resistance at the reference temperature is achieved by a first-order temperature compensation model as follows: = / .

[0011] Further, the determination of the standard resistance at the reference temperature is achieved by a second-order temperature compensation model as follows: = / . .

[0012] Further, the predetermined reference temperature is 25℃.

[0013] Further, when the local temperature T of the sampling resistor is collected in real time, the local temperature T is collected by a temperature sensor arranged on the surface of the sampling resistor body or in the adjacent area within a distance of not more than 5mm from the surface; the temperature sensor is fixed by a heat-conducting material, and the thermal resistance between the temperature sensor and the sampling resistor is <5 K / W.

[0014] In a second aspect, the present application provides a solid-state battery capacity grading system based on sampling resistor temperature compensation, which is used to implement the solid-state battery capacity grading method as described above, and the system comprises: a charging and discharging module for connecting with a solid-state battery to be tested and performing programmable charging and discharging operation; a sampling resistor connected in series in a main loop composed of the charging and discharging module and the solid-state battery, having a known nominal resistance and a first-order temperature coefficient ; a temperature sensor arranged in the adjacent area of the sampling resistor for collecting the local temperature T of the sampling resistor in real time; ​a voltage sampling circuit for collecting a voltage signal V across the sampling resistor; a temperature compensation processing module connected to the temperature sensor and the voltage sampling circuit, configured to: receive the voltage signal V and the local temperature T synchronously collected; according to a preset resistance-temperature model calculate an actual resistance value of the sampling resistor ; use the actual resistance value convert the voltage signal V into a current value I; a capacity calculation module for determining the actual charge-discharge capacity of the solid-state battery according to the current value I.

[0015] Further, the system further comprises an online calibration module configured to automatically perform a calibration process of the nominal resistance value of the sampling resistor when the system is powered on or the battery to be measured is replaced, the process comprising: controlling the capacity detection circuit to be in an open circuit state for a first preset duration; collecting an average initial voltage across the sampling resistor when the circuit current is less than a set threshold and the average local temperature of the sampling resistor at this time ; controlling a known size of calibration current to be injected into the circuit and collecting the voltage across the sampling resistor at this time ; according to the formula = / calculate a calibrated cold resistance value update the nominal resistance value in the resistance-temperature model .

[0016] The beneficial effects of the present application are: 1. The present application solves the core technical problem of current sampling and capacity calculation error caused by resistance value drift due to self-heating of the resistor under large current conditions by directly monitoring the local temperature of the sampling resistor body and using a dynamic model that integrates first and second order temperature coefficients and self-heating power effects to correct the resistance value in real time.

[0017] 2. The capacity detection system in the present application has online calibration and self-learning life tracking functions, can automatically correct the long-term drift of the reference resistance value and realize predictive maintenance, ensuring the long-term stability and reliability of the measurement system. The present application has small hardware changes and low cost, only needs to add a temperature sensor and upgrade the control algorithm, and can be compatible with existing capacity detection equipment for upgrading and modification.​​ Attached Figure Description

[0018] Figure 1 This is a flowchart of a solid-state battery capacity testing method based on sampling resistor temperature compensation according to an embodiment of the present invention; Figure 2 The nominal resistance value of the sampling resistor in this embodiment of the invention. A flowchart for the calibration process; Figure 3 This is a system block diagram of a solid-state battery capacity testing system based on temperature compensation of sampling resistor, according to an embodiment of the present invention. Detailed Implementation

[0019] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.

[0020] In the manufacturing process of solid-state batteries, capacity testing is a core step in evaluating their actual capacity, screening performance levels, and ensuring batch consistency. Currently, traditional capacity testing methods mainly rely on high-precision sampling resistors (shunts) to measure the charge and discharge current and calculate the capacity through integration. However, this method has an inherent technical bottleneck: during high-current, long-term charge and discharge tests, the sampling resistor generates significant heat due to the Joule effect, causing its resistance value to drift with temperature. Existing technologies mostly use monitoring of ambient temperature or battery temperature for indirect compensation, but because the heating of the sampling resistor is localized and transient, its actual temperature lags significantly behind and deviates from the ambient temperature, making it impossible to effectively eliminate temperature drift errors, thus directly limiting the accuracy of the final capacity calculation.

[0021] To address the aforementioned issues, this disclosure provides a solid-state battery capacity testing method and system based on temperature compensation of sampling resistors. Please refer to [link to relevant documentation]. Figure 1 and Figure 3 The method can be applied to solid-state battery capacity testing systems and corresponding computer program products. This embodiment uses an integrated system including a charge / discharge module, a sampling resistor, a temperature sensor, and a signal processing module as an example. The following will focus on... Figure 1 The process illustrated here is detailed. The solid-state battery capacity testing method based on sampling resistor temperature compensation may include the following steps: S100. Connect the solid-state battery under test to the capacitance detection circuit with a sampling resistor, the sampling resistor having a known nominal resistance value. .

[0022] In an embodiment, the capacity detection circuit provides a current path for the battery charging and discharging, and the sampling resistor is connected in series in the circuit to convert the circuit current into a voltage signal for measurement.

[0023] It should be noted that in the field of capacity detection, the capacity detection circuit is a mature current measurement infrastructure. Its core component is to connect a sampling resistor with a known resistance value in series in the charging and discharging main circuit of the battery. According to Ohm's law (V = IR), when the charging and discharging current flows through the resistor, a small voltage drop proportional to the current will be generated across the resistor. By measuring this voltage signal through a voltage sampling circuit (usually including a differential amplifier and an analog-to-digital converter ADC), the real-time current value in the circuit can be indirectly calculated. Finally, the system obtains the charging and discharging capacity of the battery by time integration of the current, and completes the capacity evaluation. The capacity detection circuit is a general and mainstream technical means for current sampling.

[0024] S200, synchronously collecting the voltage signal V across the sampling resistor and the local temperature T of the sampling resistor during the battery charging and discharging process.

[0025] In an embodiment, when the local temperature T of the sampling resistor is collected in real time, the local temperature T is collected by a temperature sensor arranged on the surface of the sampling resistor body or in a neighboring area within a distance of not more than 5 mm from the surface of the sampling resistor body; the temperature sensor is fixed by a heat-conducting material (heat-conducting silicone grease or heat-conducting glue), and the thermal resistance between the temperature sensor and the sampling resistor is <5 K / W.

[0026] Optionally, the temperature sensor is a PT100 platinum resistor, an NTC thermistor, or a digital temperature chip, and the measurement accuracy is better than ±0.2℃, which can be realized by two-point calibration or a digital temperature chip.

[0027] In an embodiment, the sampling frequency of the voltage signal V and the temperature signal T is ≥1 kHz, and both are triggered by the clock domain of the same MCU or FPGA to ensure that the sampling clock jitter is <50 ns, and the phase difference is <0.1 ms, realizing high-precision time alignment. The voltage sampling circuit includes a differential amplifier and a high-precision ADC (analog-to-digital converter) to accurately collect the small voltage drop across the sampling resistor.

[0028] S300, determining the actual resistance value of the sampling resistor at the current temperature according to a preset resistance-temperature model , wherein is the reference temperature, is the first-order temperature coefficient, is the second-order temperature coefficient, is the self-heating power coefficient, is the instantaneous self-heating power of the sampling resistor. ​

[0029] It should be noted that the parameters set in the present application are obtained by the following method: The first-order temperature coefficient (ppm / ℃) α is factory calibration, which is written once by model calibration method.

[0030] The second-order temperature coefficient (ppm / ℃ 2 ) β is obtained by multi-point fitting in a temperature chamber, for example, the sampling resistor is placed in a temperature chamber, the platform temperature is 25 → 85 ℃, and each 5 ℃ is kept constant for 20 min; the data of R(T) and T are recorded under a small current such as 5A, and the least square method is used to fit R(T) = R0[1 + αΔT + βΔT 2 ], requiring R 2 ≥ 0.999, and the obtained β is written into EEPROM, which does not change in the product life cycle.

[0031] The self-heating power coefficient (ppm / W) γ is specifically obtained by applying a constant current (such as 50 A) to the resistor for 60 s under the condition of 25 ℃ environment, recording the steady-state temperature rise ΔT_ss and the average power P = I 2 ·R0; calculating the thermal resistance R_th = ΔT_ss / P (℃ / W); γ = α× R_th (ppm / W), and writing into EEPROM, which does not change in the product life cycle.

[0032] In one embodiment, the instantaneous self-heating power is obtained by the following formula: ; Wherein is the sampling interval, and are the current value and resistance value at the previous sampling time, respectively; wherein .

[0033] This iterative method uses the known information at the previous time to approximate the self-heating effect at the current time, realizing real-time and dynamic compensation of resistance value change.

[0034] S400, according to the actual resistance value , the voltage signal V is converted into a current value I, that is = / .

[0035] This step uses the resistance value after accurate compensation of temperature and self-heating effect to calculate the current, which fundamentally eliminates the current measurement error introduced by resistance value drift.

[0036] S500, determining the actual charge and discharge capacity of the solid-state battery according to the current value I.

[0037] The corrected high-precision current value I is integrated, and the integration range covers the complete charging, discharging or test conditions. Finally, the battery capacity is output in ampere-hours (Ah) or milliampere-hours (mAh) to complete the capacity test.

[0038] In one implementation, combined with Figure 2 Before connecting the solid-state battery under test to the capacitance detection circuit with a sampling resistor, the method also includes setting the nominal resistance value of the sampling resistor. Calibration includes: The capacitance detection circuit is kept in an open state for a first preset time (e.g., at least 5 minutes) to allow the sampling resistor to cool to a cold state that is in equilibrium with the ambient temperature. The purpose of this operation is to ensure that no current flows through the sampling resistor so that the self-generated heat generated by its previous operation can be fully dissipated.

[0039] Subsequently, it was verified and ensured that the loop current was less than a set threshold (e.g., less than 0.001C, which is extremely small and can be considered as zero current background noise). In this state, the average initial voltage across the sampling resistor was acquired. and the average local temperature of the sampling resistor at this time, which is obtained in real time by the temperature sensor. This step is used to measure the system's zero drift and obtain the ambient temperature during calibration.

[0040] Next, a reference current source (e.g., with an accuracy of 0.1%) is controlled to inject a calibration current of known magnitude and with a very short duration (e.g., 20 ms) into the capacity detection circuit. (e.g., 1A). This current pulse should be short enough to avoid causing significant self-heating of the sampling resistor. Simultaneously with injecting the calibration current, the system synchronously acquires the voltage across the sampling resistor. .

[0041] Finally, according to Ohm's law, using the formula... = / The cold-state resistance value after calibration at the current ambient temperature was calculated. Use this immediately. The value directly updates the nominal resistance used in the resistance-temperature model. .

[0042] In one implementation, Update the nominal resistance in the resistance-temperature model. This includes: based on the calibrated cold-state resistance value The corresponding local temperature during its measurement First-order temperature coefficient and the predetermined reference temperature Determine the reference temperature the standard resistance value at the reference temperature , and updating the resistance-temperature model with . .

[0043] It is understood that the determination of the standard resistance value at the reference temperature , can eliminate the resistance deviation caused by the difference between the environmental temperature at the calibration moment and the reference temperature preset by the system. Subsequently, the resistance-temperature model is updated with the calculated . After this step, the model is established on a unified and accurate reference point, and the compensation calculation of the model is based on this reference point regardless of the subsequent change of the environmental temperature. .

[0044] Preferably, the determination of the standard resistance value at the reference temperature is achieved by a first-order temperature compensation model as follows: = / .

[0045] The term in the formula represents the relative resistance change amount caused by the temperature difference ; by the division operation, the measured value is "compensated" back to the resistance value at the reference temperature . This model has the advantages of simple calculation and fast response when the difference between and is not large and the accuracy requirement is not extremely harsh.

[0046] As an example, it is assumed that the local temperature of the sampling resistor is 30°C during calibration, and the cold resistance value obtained by calibration is 1.0002 mΩ. It is known that the first-order temperature coefficient is 50 ppm / °C, and the reference temperature is 25°C. The first-order temperature compensation model is used for calculation: The 0.99995 mΩ after the conversion will be used as the new reference in the resistance-temperature model. This process eliminates the reference deviation of about 25 ppm caused by the difference between the calibration temperature (30°C) and the reference temperature (25°C).

[0047] The 0.99995 mΩ after the conversion will be used as the new reference in the resistance-temperature model. This process eliminates the reference deviation of about 25 ppm caused by the difference between the calibration temperature (30°C) and the reference temperature (25°C).

[0048] ​​​​​​​​In one embodiment, the predetermined reference temperature is 25℃. This is the general industry standard temperature for electronic component parameter calibration. Setting the reference temperature to 25℃ makes the updated model reference to the nominal value in the sampling resistor factory specification book is usually under the same temperature condition, which facilitates the unified comparison and initial calibration of the data.

[0049] In an alternative embodiment, the method further comprises a self-learning life tracking step. The standard resistance value obtained after each online calibration and its corresponding calibration timestamp are recorded. When the cumulative operating time reaches a preset maintenance period (e.g. 1000 hours), a new online calibration process (i.e. the aforementioned cooling, measuring, injecting a calibration current, calculating and converting steps) is automatically triggered and performed to obtain the latest .

[0050] The latest value obtained this time is linearly regressed with the recorded multiple values based on their corresponding calibration times to extrapolate and predict the resistance value change trend at a future time point (e.g. the next maintenance period). If the prediction result shows that the drift of the sampling resistor's resistance value relative to its initial value will exceed the preset maintenance threshold (e.g. ≥0.1%), a maintenance warning signal is generated and issued to prompt the user to check or replace the sampling resistor, thereby achieving predictive maintenance.

[0051] According to the above embodiments, the present application directly monitors the local temperature of the sampling resistor body, uses a dynamic model that integrates the first-order, second-order temperature coefficients and self-heating power effects to correct the resistance value in real time, and simultaneously uses an online calibration mechanism to maintain the long-term accuracy of the reference, thereby systematically improving the accuracy of current sampling and battery capacity calculation.

[0052] Embodiment 2 Based on embodiment 1, this embodiment provides a calibration resistance conversion scheme with higher precision. Specifically, in the online calibration process, the standard resistance value at the reference temperature is determined, which is achieved by the following second-order temperature compensation model, as follows: = / .

[0053] The second-order model adds a compensation term This setting corrects for the non-linearity (curvature effect) of the sampling resistor's resistance changing with temperature. The ambient temperature during calibration is also considered. Compared with reference temperature When the difference is large, or when the temperature characteristics of the sampling resistor material are significantly nonlinear, this second-order model can more accurately represent the sampled resistor than the first-order model. Converted to standard reference temperature This further reduces the conversion error of the reference resistance value.

[0054] Understandably, the second-order temperature coefficient It is an inherent parameter of the sampling resistor. Its value is usually obtained at the factory by placing the resistor in a temperature chamber, measuring its resistance at multiple different temperature points, performing quadratic curve fitting, and pre-stored in the system.

[0055] As an example, suppose the ambient temperature was high during a calibration, and the local temperature of the sampling resistor was measured. The cold resistance value obtained during calibration at 45℃ The first-order temperature coefficient of the sampling resistor is 1.0008 mΩ. It has a concentration of 40 ppm / ℃, and its nonlinear characteristics are quite obvious, with a second-order temperature coefficient. The factory specification is 0.8 ppm / ℃. 2 Reference temperature The temperature is 25°C. If the first-order model of Example 1 is used at this time: ; The second-order model used in this embodiment is employed for calculation: ; The two models yielded calculation results differing by 0.00032 mΩ (i.e., 320 ppm), a difference that reflects the compensation effect of the second-order model on nonlinear temperature drift. When the difference between the ambient temperature during calibration and the reference temperature reaches 20℃, the nonlinear term... The contribution reached 0.00032, accounting for 28.6% of the total compensation. At this point, using a second-order model can more accurately restore the true resistance value of the sampling resistor at the reference temperature, establishing a more reliable benchmark for subsequent high-precision temperature compensation.

[0056] In one implementation, a predetermined reference temperature The temperature is 25℃.

[0057] Example 3 The same technical concept as in Embodiment 1 or 2, combined with Figure 3 This embodiment proposes a solid-state battery capacity assessment system based on sampling resistor temperature compensation, used to implement the solid-state battery capacity assessment method as described in Embodiment 1 or 2. The system includes: A charge-discharge module for connecting with the solid-state battery under test and performing programmable charge-discharge operation; the module is usually composed of a programmable power supply and an electronic load, supporting constant current (CC), constant voltage (CV), constant power (CP) and multi-stage charge-discharge working conditions, for simulating the actual working state of the battery or performing standard capacity test procedures.

[0058] A sampling resistor connected in series in the main circuit composed of the charge-discharge module and the solid-state battery, with a known nominal resistance value and a first-order temperature coefficient .

[0059] A temperature sensor arranged in the vicinity of the sampling resistor for real-time acquisition of the local temperature T of the sampling resistor.

[0060] A voltage sampling circuit for acquiring the voltage signal V across the sampling resistor.

[0061] A temperature compensation processing module connected with the temperature sensor and the voltage sampling circuit, configured to: receive the synchronously acquired voltage signal V and local temperature T; according to a pre-set resistance-temperature model calculate the actual resistance value of the sampling resistor ; convert the voltage signal V to a current value I using the actual resistance value .

[0062] A capacity calculation module for determining the actual charge-discharge capacity of the solid-state battery according to the current value I. This module is usually a software functional unit in the temperature compensation processing module, which calculates the battery capacity in ampere-hours (Ah) or milliampere-hours (mAh) by numerically integrating the compensated current value I.

[0063] In an embodiment, the system further comprises an online calibration module configured to automatically perform a calibration process (cold calibration) of the nominal resistance value of the sampling resistor when the system is powered on for the first time each day or when the battery under test is replaced, the process including: controlling the capacity detection circuit to be in an open circuit state for a first pre-set duration; when the circuit current is less than a set threshold, acquiring the average initial voltage across the sampling resistor and the average local temperature of the sampling resistor at this time ; controlling the injection of a known size of calibration current into the circuit , and acquiring the voltage across the sampling resistor at this time ; calculating the calibrated cold resistance value = / according to the formula , and Updating the nominal resistance in the resistance-temperature model . Subsequently, the nominal resistance in the resistance-temperature model is updated (or converted) according to the temperature compensation model described in Embodiment 1 or 2 . .

[0064] Optionally, when the system cumulative running time is greater than or equal to a second preset time length (such as 1000h), the online calibration module automatically executes the calibration process of the nominal resistance of the sampling resistance. .

[0065] The online calibration module is also configured to perform a self-learning life tracking function. This function includes a non-volatile memory for storing the standard resistance and the corresponding system cumulative running time obtained from previous calibrations.

[0066] When the system cumulative running time reaches a preset maintenance period (for example, 1000 hours), the online calibration module automatically triggers and executes a complete calibration process. Subsequently, the module calls the embedded algorithm to perform linear extrapolation analysis on the stored historical data to predict the future trend of the sampling resistance value. If the prediction result shows that the resistance drift will exceed the preset threshold (for example, ≥0.1%), the data output module sends an explicit maintenance alarm information to the outside.

[0067] It should be noted that the above-mentioned modules in the solid-state battery capacity grading system correspond to the steps in the above-mentioned solid-state battery capacity grading method. The instances and application scenarios realized by the multiple modules and the corresponding steps are the same, but are not limited to the contents disclosed in Embodiments 1 and 2.

[0068] In another embodiment provided by the present application, a computer readable storage medium is also provided, which stores a computer program. When the computer program is executed by a processor, the steps of any of the above-mentioned solid-state battery capacity grading methods based on sampling resistance temperature compensation are realized.

[0069] In another embodiment provided by the present application, a computer program product containing instructions is also provided, which, when running on a computer, causes the computer to execute the steps of any of the above-mentioned solid-state battery capacity grading methods based on sampling resistance temperature compensation.

[0070] Those skilled in the art can understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software manner depends on the specific application and design constraints of the technical solutions. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0071] In addition, each functional module in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0072] The above embodiments are only used to illustrate the technical solutions of the present application, but not to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not drive the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for sorting solid-state batteries based on sampling resistance temperature compensation, characterized in that, The method comprises the following steps: The solid-state battery to be tested is connected to a capacity detection circuit with a sampling resistor, which has a known nominal resistance value ; During the charging and discharging process of the battery, the voltage signal V across the sampling resistor and the local temperature T of the sampling resistor are synchronously collected; According to a preset resistance-temperature model , determine the actual resistance value of the sampling resistor at the current temperature ; wherein, Tref is a reference temperature, T1 is a first order temperature coefficient, T2 is a second order temperature coefficient, Pth is a self-heating power coefficient, Pth is an instantaneous self-heating power of the sampling resistor; According to the actual resistance value convert the voltage signal V into a current value I; The actual charging and discharging capacity of the solid-state battery is determined according to the current value I.

2. The method of claim 1, wherein the method is a method of sampling resistance-based temperature compensation for sorting solid-state batteries, and wherein the method further comprises: The instantaneous self-heating power By the following formula: ； wherein is a sampling interval, and is the current value and the resistance value at the previous sampling time, respectively.

3. The method of claim 1, wherein the method is a method of sampling resistance-based temperature compensation for sorting solid-state batteries, and wherein the method further comprises: Before the method of connecting the to-be-tested solid-state battery into the capacity detection circuit with a sampling resistor, the method further comprises setting a nominal resistance value of the sampling resistor Carrying out calibration, comprising: The capacity detection circuit is kept in an open circuit state for a first preset time duration, so that the sampling resistor is cooled to a cold state balanced with the ambient temperature; acquiring an average initial voltage across the sampling resistor when the loop current is less than a set threshold and an average local temperature of the sampling resistor at that time ; Injecting a known size of calibration current into the loop and capturing the voltage across the sampling resistor at that time ; According to the formula = / The calibrated cold resistance value is calculated based on the The nominal resistance value in the resistance-temperature model is updated .

4. The method of claim 3, wherein the sampling resistance temperature compensation-based solid-state battery capacity sorting method is characterized by, The method comprises the following steps: updating the nominal resistance value in the resistance-temperature model , comprising: Based on the calibrated cold resistance value The corresponding local temperature during its measurement The first-order temperature coefficient and the predetermined reference temperature Determining at the reference temperature Standard resistance value and with the stated Update the resistance-temperature model .

5. The method of claim 4, wherein the sampling resistance temperature compensation-based solid-state battery capacity sorting method is characterized by, The determining of the standard resistance value at the reference temperature is achieved by a first order temperature compensation model as follows:​ = / 。 6. The method of claim 4, wherein the sampling resistance temperature compensation-based solid-state battery capacity sorting method is characterized by, The determining of the standard resistance value at the reference temperature is achieved by a second order temperature compensation model as follows:​ = / 。 7. The method of claim 4, 5 or 6, wherein the method is based on sampling resistance temperature compensation for solid-state battery sorting. the predetermined reference temperature 25 °C.

8. The method of claim 1, wherein the method is a method of sampling resistance-based temperature compensation for solid-state battery cell balancing. When the local temperature T of the sampling resistor is collected in real time, the local temperature T is collected by a temperature sensor arranged on the surface of the sampling resistor body or in a neighboring area within a distance of not more than 5 mm from the surface of the sampling resistor; the temperature sensor is fixed by a heat-conducting material, and the thermal resistance between the temperature sensor and the sampling resistor is less than 5 K / W.

9. A solid-state battery cell sorting system based on sampling resistance temperature compensation for implementing a solid-state battery cell sorting method according to any one of claims 1-8, characterized in that, The system comprises: A charging and discharging module for connecting with the solid-state battery to be tested and performing programmable charging and discharging operations; a sampling resistor, in series in a main circuit constituted by the charge-discharge module and the solid-state battery, having a known nominal resistance value and a first order temperature coefficient ; A temperature sensor arranged in a neighboring area of the sampling resistor for collecting the local temperature T of the sampling resistor in real time; A voltage sampling circuit for collecting the voltage signal V across the sampling resistor; A temperature compensation processing module connected with the temperature sensor and the voltage sampling circuit and configured to: Receive the synchronously collected voltage signal V and local temperature T; According to a preset resistance-temperature model Calculating an actual resistance value of the sampling resistor ; using the actual resistance value converting the voltage signal V into a current value I; A capacity calculation module for determining the actual charging and discharging capacity of the solid-state battery according to the current value I.

10. The sampling resistance temperature compensation based solid state battery cell balancing system of claim 9, wherein, The system also includes an online calibration module, configured to automatically perform a calibration of the nominal resistance of the sampling resistor when the system is powered on or the battery under test is replaced. The calibration process includes: The capacity detection circuit is kept in an open circuit state for a first preset time duration; acquiring an average initial voltage across the sampling resistor when the loop current is less than a set threshold and an average local temperature of the sampling resistor at that time ; Controlling injection of a known size of calibration current into the loop and capturing the voltage across the sampling resistor at that time ; The calibrated cold resistance value is calculated according to the formula = / The calibrated cold resistance value is calculated according to the formula The nominal resistance value in the resistance-temperature model is updated The nominal resistance value in the resistance-temperature model is updated .

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