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

Abstract

The present application belongs to the technical field of battery capacity detection, and particularly relates to a solid-state battery capacity detection method and system based on sampling resistor temperature compensation, which comprises the following steps: in the capacity detection circuit, the local temperature and the voltage across the sampling resistor are collected in real time; through a resistance-temperature model integrating the first-order and second-order temperature coefficients and the self-heating power effect, the actual resistance value of the sampling resistor is dynamically corrected, so as to calculate the real current with high precision, 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 the like hardware. By directly monitoring and compensating the temperature drift of the sampling resistor, the present application effectively solves the capacity calculation error problem caused by the self-heating of the resistor under large current, and significantly improves the precision and reliability of the solid-state battery capacity detection.

Description

Technical Field

[0001] This invention belongs to the field of battery capacity testing technology, specifically relating to a solid-state battery capacity testing method and system based on temperature compensation of sampling resistor. Background Technology

[0002] In the manufacturing process of solid-state batteries, capacity grading is a crucial step. Its purpose is to accurately determine the actual charge / discharge capacity of the battery, enabling performance screening and grading to ensure consistency of batteries leaving the factory. Currently, capacity grading systems commonly use a sampling resistor (shunt) connected in series in the charge / discharge circuit. The current is obtained by measuring the voltage across the resistor, and then the current is integrated over time to calculate the battery capacity. However, this technology has a long-standing, unresolved inherent source of error: the resistance of the sampling resistor drifts with temperature. Under high current (typically ≥50A) and long-term charge / discharge conditions, the current flowing through the sampling resistor generates significant Joule heating, causing its local temperature to rise rapidly by 10-20°C. Since sampling resistors generally have a non-negligible temperature coefficient (typically ±20~±100ppm / °C), their resistance will change by 0.1%~0.4%. This change is directly introduced into the current sampling stage and ultimately transmitted to the capacity calculation result, causing a non-negligible measurement error.

[0003] In existing technologies, to alleviate this problem, ambient temperature sensors or battery body temperature sensors are often 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 ambient temperature or battery temperature. This "indirect" compensation method cannot accurately and in real time reflect the true temperature state of the sampling resistor itself, and therefore it is difficult to completely eliminate the temperature drift error introduced by the resistor's self-heating.

[0004] Therefore, there is an urgent need in this field for a high-precision capacitance detection method and system that can directly and in real time monitor and compensate the temperature of the sampling resistor body. Summary of the Invention

[0005] The purpose of this invention is to provide a solid-state battery capacity assessment method and system based on sampling resistor temperature compensation, aiming to solve the technical problem of resistance drift caused by self-heating of the sampling resistor in solid-state battery capacity assessment, which introduces errors in current sampling and capacity calculation.

[0006] The present invention achieves the above objectives through the following technical solutions:

[0007] In a first aspect, the present invention proposes a solid-state battery capacity assessment method based on sampling resistor temperature compensation, the method comprising the following steps:

[0008] The solid-state battery under test is connected to a capacitance testing circuit with a sampling resistor having a known nominal resistance value. ;

[0009] During the battery charging and discharging process, the voltage signal V across the sampling resistor and the local temperature T of the sampling resistor are simultaneously acquired.

[0010] Based on the preset resistance-temperature model Determine the actual resistance value of the sampling resistor at the current temperature. ;

[0011] in, As the reference temperature, It is a first-order temperature coefficient. It is a second-order temperature coefficient. The self-heating power coefficient, The instantaneous self-heating power of the sampling resistor;

[0012] Based on the actual resistance value This converts the voltage signal V into a current value I.

[0013] The actual charge / discharge capacity of the solid-state battery is determined based on the current value I.

[0014] Furthermore, the instantaneous self-heating power Obtained through the following formula:

[0015] ;

[0016] in The sampling interval is... and These are the current and resistance values ​​at the previous sampling time, respectively.

[0017] Furthermore, before connecting the solid-state battery under test to the capacitance detection circuit with a sampling resistor, the method further includes setting the nominal resistance value of the sampling resistor. Calibration includes:

[0018] The capacitance detection circuit is kept in an open circuit state for a first preset duration to allow the sampling resistor to cool to a cold state that is in equilibrium with the ambient temperature.

[0019] When the loop current is less than a set threshold, the average initial voltage across the sampling resistor is collected. and the average local temperature of the sampling resistor at this time ;

[0020] Inject a known calibration current into the circuit. And collect the voltage across the sampling resistor at this time. ;

[0021] According to the formula = / The calibrated cold resistance value was calculated. , will the Update the nominal resistance in the resistance-temperature model. .

[0022] Furthermore, the aforementioned Update the nominal resistance in the resistance-temperature model. ,include:

[0023] 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 .

[0024] Furthermore, the determination at the reference temperature Standard resistance value This is achieved through the following first-order temperature compensation model, as shown in the following equation:

[0025] = / .

[0026] Furthermore, the determination at the reference temperature Standard resistance value This is achieved through the following second-order temperature compensation model, as shown in the following equation:

[0027] = / .

[0028] Furthermore, the predetermined reference temperature The temperature is 25℃.

[0029] Furthermore, when acquiring the local temperature T of the sampling resistor in real time, the local temperature T is acquired by a temperature sensor arranged on the surface of the sampling resistor body or in an adjacent area at a distance of no more than 5 mm from its surface; the temperature sensor is fixed by a thermally conductive material, and its thermal resistance with the sampling resistor is <5 K / W.

[0030] Secondly, this invention proposes a solid-state battery capacity assessment system based on sampling resistor temperature compensation, used to implement the solid-state battery capacity assessment method described above. The system includes:

[0031] A charge / discharge module is used to connect to the solid-state battery under test and perform programmable charge / discharge operations;

[0032] The sampling resistor, connected in series in the main circuit consisting of the charging / discharging module and the solid-state battery, has a known nominal resistance value. and first-order temperature coefficient ;

[0033] A temperature sensor is arranged in the vicinity of the sampling resistor to collect the local temperature T of the sampling resistor in real time.

[0034] A voltage sampling circuit is used to acquire the voltage signal V across the sampling resistor;

[0035] The temperature compensation processing module, connected to the temperature sensor and the voltage sampling circuit, is configured as follows:

[0036] Receive the synchronously acquired voltage signal V and local temperature T;

[0037] Based on the preset resistance-temperature model Calculate the actual resistance value of the sampling resistor ;

[0038] Using the actual resistance value Convert the voltage signal V into a current value I;

[0039] The capacity calculation module is used to determine the actual charge and discharge capacity of the solid-state battery based on the current value I.

[0040] Furthermore, the system also includes an online calibration module, configured to automatically perform a calibration of the nominal resistance value of the sampling resistor when the system is powered on or the battery under test is replaced. The calibration process includes:

[0041] The capacity detection circuit is kept in an open circuit state for a first preset duration.

[0042] When the loop current is less than a set threshold, the average initial voltage across the sampling resistor is collected. and the average local temperature of the sampling resistor at this time ;

[0043] Control the injection of a known calibration current into the loop. And collect the voltage across the sampling resistor at this time. ;

[0044] According to the formula = / The calibrated cold resistance value was calculated. , will the Update the nominal resistance in the resistance-temperature model. .

[0045] The beneficial effects of this invention are as follows:

[0046] 1. This invention solves the core technical problem of resistance drift caused by resistor self-heating under high current conditions, which leads to errors in current sampling and capacity calculation, by directly monitoring the local temperature of the sampling resistor body and using a dynamic model that integrates first-order and second-order temperature coefficients and self-heating power effects to correct its resistance value in real time.

[0047] 2. The capacitance testing system in this invention features online calibration and self-learning lifetime tracking functions, automatically correcting long-term drift of the reference resistance and enabling predictive maintenance, thus ensuring the long-term stability and reliability of the measurement system. This invention requires minimal hardware modifications and is low-cost; it only requires adding a temperature sensor and upgrading the control algorithm to be compatible with existing capacitance testing equipment for upgrades. Attached Figure Description

[0048] 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;

[0049] Figure 2 The nominal resistance value of the sampling resistor in this embodiment of the invention. A flowchart for the calibration process;

[0050] 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

[0051] 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.

[0052] 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.

[0053] 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:

[0054] 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. .

[0055] In one embodiment, the capacity detection circuit provides a current path for 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.

[0056] It's important to note that in the field of capacity assessment, the capacity assessment circuit is a mature current measurement infrastructure. Its core component is a sampling resistor of known resistance connected in series in the battery's main charging and discharging circuit. According to Ohm's law (V=IR), when the charging and discharging current flows through this resistor, a small voltage drop proportional to the current is generated across it. By measuring this voltage signal through a voltage sampling circuit (typically 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 battery's charging and discharging capacity by integrating this current over time, thus completing the capacity assessment. The capacity assessment circuit is a common and mainstream technique for implementing current sampling.

[0057] S200. During the battery charging and discharging process, the voltage signal V across the sampling resistor and the local temperature T of the sampling resistor are simultaneously acquired.

[0058] In one embodiment, when the local temperature T of the sampling resistor is acquired in real time, the local temperature T is acquired by a temperature sensor arranged on the surface of the sampling resistor body or in an adjacent area at a distance of no more than 5 mm from its surface; the temperature sensor is fixed by a thermally conductive material (thermal grease or thermal adhesive), and the thermal resistance between the sensor and the sampling resistor is <5 K / W.

[0059] Optionally, the temperature sensor can be a PT100 platinum resistance thermometer, an NTC thermistor, or a digital temperature chip, with a measurement accuracy better than ±0.2℃, which can be achieved through two-point calibration or a digital temperature chip.

[0060] In one implementation, the sampling frequencies of the voltage signal V and the temperature signal T are ≥1 kHz, and both are triggered by the same clock domain of the MCU or FPGA to ensure that the sampling clock jitter is <50 ns and the phase difference between the two is <0.1 ms, achieving high-precision time alignment. The voltage sampling circuit includes a differential amplifier and a high-precision ADC (analog-to-digital converter) to accurately acquire the small voltage drop across the sampling resistor.

[0061] S300, based on the preset resistance-temperature model Determine the actual resistance value of the sampling resistor at the current temperature. .in, As the reference temperature, It is a first-order temperature coefficient. It is a second-order temperature coefficient. The self-heating power coefficient, This represents the instantaneous self-heating power of the sampling resistor.

[0062] It should be noted that the parameters set in this invention are obtained in the following ways:

[0063] The first-order temperature coefficient (ppm / ℃) α is the factory calibration value, which is written once through the model calibration method.

[0064] Second-order temperature coefficient (ppm / ℃) 2 β is obtained by multi-point fitting of the temperature chamber. For example, the sampling resistor is placed in the temperature chamber, and the platform temperature is kept constant at 25 ℃ to 85 ℃ for 20 min at every 5 ℃. The data of R(T) and T are recorded under a small current such as 5A. The least squares fitting method is used to fit R(T) = R0[1 + αΔT + βΔT]. 2 ], requires R 2 If the result is ≥ 0.999, the β value is written into the EEPROM and remains unchanged throughout the product's lifecycle.

[0065] The self-heating power coefficient (ppm / W) γ is specifically determined by applying a constant current (e.g., 50 A) to a resistor at 25 °C for 60 s, and recording the steady-state temperature rise ΔT_ss and the average power P = I.2 • R0; Calculate the thermal resistance R_th = ΔT_ss / P (℃ / W); γ = α× R_th (ppm / W), write it into EEPROM, and it remains unchanged throughout the product's life cycle.

[0066] In one implementation, instantaneous self-heating power Obtained through the following formula:

[0067] ;

[0068] in The sampling interval is... and These are the current and resistance values ​​at the previous sampling time, respectively; where... .

[0069] This iterative method uses known information from the previous moment to approximate the self-heating effect at the current moment, achieving real-time, dynamic compensation for resistance changes.

[0070] S400, based on actual resistance value This converts the voltage signal V into a current value I, i.e. = / .

[0071] This step uses the resistance value, which has been precisely compensated for by temperature and self-heating effects, to calculate the current, fundamentally eliminating the current measurement error caused by resistance drift.

[0072] S500. Determine the actual charge / discharge capacity of the solid-state battery based on the current value I.

[0073] 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.

[0074] 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:

[0075] 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.

[0076] 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.

[0077] 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. .

[0078] 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. .

[0079] 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 Standard resistance value and with Update the resistance-temperature model .

[0080] Understandably, this is determined at the reference temperature. Standard resistance value This can eliminate the influence of ambient temperature during calibration. With the system's preset reference temperature The resistance deviation caused by the difference. Then, the calculated... Update the resistance-temperature model After this step, the model is established on a unified and accurate benchmark. No matter how the ambient temperature changes subsequently, the model's compensation calculations will be carried out based on this benchmark.

[0081] Preferably, the reference temperature is determined. Standard resistance value This is achieved through the following first-order temperature compensation model, as shown in the following equation:

[0082] = / .

[0083] In the formula The item represents the difference due to temperature. The resulting relative resistance change; by division, the measured value... "Compensation" returns to the reference temperature Required resistance value under the given conditions This model is in and When the differences are not significant and the accuracy requirements are not extremely stringent, it has the advantages of simple calculation and fast response.

[0084] As an example, suppose during a calibration, the local temperature of the sampling resistor was measured. The cold resistance value obtained during calibration at 30℃. It is 1.0002 mΩ. The first-order temperature coefficient is known. 50 ppm / ℃, reference temperature The temperature is 25℃. A first-order temperature compensation model is used for calculation.

[0085]

[0086] This converted 0.99995 mΩ will be used as the new benchmark in the resistance-temperature model. This process eliminates a reference deviation of approximately 25 ppm caused by the difference between the calibration temperature (30°C) and the reference temperature (25°C).

[0087] In one implementation, the predetermined reference temperature The temperature is 25℃. This is the general industrial standard temperature for calibrating electronic components. Setting it to 25℃ makes the updated model baseline... The sampling resistor is usually at the same temperature as the nominal value in the manufacturer's specifications, which is beneficial for data comparison and initial calibration.

[0088] In an optional implementation, the method further includes a self-learning lifetime tracking step, recording the standard resistance value obtained after each online calibration. And its corresponding calibration timestamp. When the cumulative running time reaches the preset maintenance cycle (e.g., 1000 hours), a new online calibration process is automatically triggered and executed (i.e., the aforementioned cooling, measurement, injection of calibration current, calculation and conversion steps) to obtain the latest... .

[0089] The latest obtained this time Values ​​and multiple historical records The resistance value is analyzed using linear regression based on its corresponding calibration time, and extrapolated to predict the resistance change trend at a future point in time (the next maintenance cycle). If the prediction result indicates that the drift of the sampling resistor's resistance value relative to its initial value will exceed a preset maintenance threshold (e.g., ≥0.1%), a maintenance alarm signal is generated and issued to prompt the user to check or replace the sampling resistor, thereby achieving predictive maintenance.

[0090] According to the above embodiments, the present invention directly monitors the local temperature of the sampling resistor body and uses a dynamic model that integrates first-order and second-order temperature coefficients and self-heating power effects to correct its resistance value in real time. At the same time, it is supplemented by 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.

[0091] Example 2

[0092] Based on Example 1, this example provides a more accurate calibration resistance conversion scheme. Specifically, in the online calibration process, the reference temperature is determined. Standard resistance value This is achieved through the following second-order temperature compensation model, as shown in the following equation:

[0093] = / .

[0094] This second-order model, based on the first-order linear model used in Example 1, adds a compensation term proportional to the square of the temperature difference. 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.

[0095] 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.

[0096] 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:

[0097] ;

[0098] The second-order model used in this embodiment is employed for calculation:

[0099] ;

[0100] 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.

[0101] In one implementation, a predetermined reference temperature The temperature is 25℃.

[0102] Example 3

[0103] 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:

[0104] The charge / discharge module is used to connect to the solid-state battery under test and perform programmable charge / discharge operations. This module typically consists of a programmable power supply and an electronic load, and supports constant current (CC), constant voltage (CV), constant power (CP) and multi-stage charge / discharge conditions to simulate the actual working state of the battery or to perform standard capacity testing procedures.

[0105] The sampling resistor, connected in series in the main circuit consisting of the charging / discharging module and the solid-state battery, has a known nominal resistance value. and first-order temperature coefficient .

[0106] A temperature sensor is placed in the vicinity of the sampling resistor to collect the local temperature T of the sampling resistor in real time.

[0107] The voltage sampling circuit is used to acquire the voltage signal V across the sampling resistor.

[0108] The temperature compensation processing module, connected to the temperature sensor and voltage sampling circuit signals, is configured as follows:

[0109] Receive synchronously acquired voltage signal V and local temperature T; based on a preset resistance-temperature model... Calculate the actual resistance value of the sampling resistor ; Using actual resistance value Convert the voltage signal V into a current value I.

[0110] The capacity calculation module determines the actual charge / discharge capacity of the solid-state battery based on the current value I. This module is typically a software function unit within the temperature compensation processing module. It calculates the battery capacity in ampere-hours (Ah) or milliampere-hours (mAh) by numerically integrating the compensated current value I.

[0111] In one implementation, the system further includes an online calibration module configured to automatically perform a calibration of the nominal resistance of the sampling resistor upon the system's first power-on each day or upon replacement of the battery under test. The calibration procedure (cold calibration) includes:

[0112] The control circuit for capacity detection is kept in an open-circuit state for a first preset duration; when the circuit current is less than a set threshold, the average initial voltage across the sampling resistor is collected. and the average local temperature of the sampling resistor at this time ; Control the injection of a known calibration current into the circuit And collect the voltage across the sampling resistor at this time. According to the formula = / The calibrated cold resistance value was calculated. ,Will Update the nominal resistance in the resistance-temperature model. Subsequently, according to the temperature compensation model described in Example 1 or 2, the following will be performed: Update (or convert and update) to the nominal resistance in the resistance-temperature model. .

[0113] Optionally, when the system's cumulative running time is ≥ a second preset duration (e.g., 1000 hours), the online calibration module automatically performs calibration on the nominal resistance of the sampling resistor. The calibration process.

[0114] The online calibration module is also configured to perform a self-learning lifetime tracking function. This function includes a non-volatile memory for storing standard resistance values ​​obtained from previous calibrations. and its corresponding cumulative system uptime.

[0115] When the system's cumulative operating time reaches a preset maintenance cycle (e.g., 1000 hours), the online calibration module automatically triggers and executes a complete calibration process. Subsequently, the module calls the embedded algorithm to perform a calibration on the stored data. Historical data is used for linear extrapolation analysis to predict the future trend of the sampling resistor value. If the prediction result shows that the resistance drift will exceed a preset threshold (e.g., ≥0.1%), a clear maintenance alarm message is sent to the outside through the data output module.

[0116] It should be noted that each module in the above solid-state battery capacity testing system corresponds to a step in implementing the above solid-state battery capacity testing method. Multiple modules and their corresponding steps are implemented in the same instances and application scenarios, but are not limited to the content disclosed in Embodiments 1 and 2 above.

[0117] In another embodiment of the present invention, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps of any of the above-described solid-state battery capacity assessment methods based on sampling resistor temperature compensation.

[0118] In another embodiment of the present invention, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to perform the steps of any of the solid-state battery capacity assessment methods based on sampling resistor temperature compensation in the above embodiments.

[0119] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0120] In addition, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0121] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A solid-state battery capacity assessment method based on temperature compensation of sampling resistor, characterized in that, The method includes the following steps: The solid-state battery under test is connected to a capacitance testing circuit with a sampling resistor having a known nominal resistance value. ; During the battery charging and discharging process, the voltage signal V across the sampling resistor and the local temperature T of the sampling resistor are simultaneously acquired. Based on the preset resistance-temperature model Determine the actual resistance value of the sampling resistor at the current temperature. ; in, As the reference temperature, It is a first-order temperature coefficient. It is a second-order temperature coefficient. The self-heating power coefficient, The instantaneous self-heating power of the sampling resistor; the first-order temperature coefficient The second-order temperature coefficient is written once for factory calibration and model calibration methods; The sampling resistor is obtained by performing multi-point fitting within a temperature chamber; specifically, measurements are taken and recorded at multiple temperature points. R ( T ) Fitting by least squares method Solving for β minimizes the fitting error, yielding the second-order temperature coefficient. Where ΔT is the temperature difference at different temperature points; the self-heating power coefficient By applying a constant current I to the sampling resistor for a set duration at an ambient temperature of 25°C, the steady-state temperature rise ΔT_ss and average power were recorded. Calculate thermal resistance The instantaneous self-heating power Obtained through the following formula: ； in The sampling interval is... and These are the current and resistance values ​​at the previous sampling time, respectively; Based on the actual resistance value This converts the voltage signal V into a current value I. The actual charge / discharge capacity of the solid-state battery is determined based on the current value I.

2. The solid-state battery capacity assessment method based on sampling resistor temperature compensation according to claim 1, characterized in that, Before connecting the solid-state battery under test to the capacity testing circuit with a sampling resistor, the method further includes setting the nominal resistance value of the sampling resistor. Calibration includes: The capacitance detection circuit is kept in an open circuit state for a first preset duration to allow the sampling resistor to cool to a cold state that is in equilibrium with the ambient temperature. When the loop current is less than a set threshold, the average initial voltage across the sampling resistor is collected. and the average local temperature of the sampling resistor at this time ; Inject a known rated current into the circuit. And collect the voltage across the sampling resistor at this time. ; According to the formula = / The calibrated cold resistance value was calculated. Based on the above Update the nominal resistance in the resistance-temperature model. .

3. The solid-state battery capacity assessment method based on sampling resistor temperature compensation according to claim 2, characterized in that, The basis of Update the nominal resistance in the resistance-temperature model. ,include: 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 .

4. The solid-state battery capacity assessment method based on sampling resistor temperature compensation according to claim 3, characterized in that, The determination is made at the reference temperature. Standard resistance value This is achieved through the following first-order temperature compensation model, as shown in the following equation: = / 。 5. The solid-state battery capacity assessment method based on sampling resistor temperature compensation according to claim 3, characterized in that, The determination is made at the reference temperature. Standard resistance value This is achieved through the following second-order temperature compensation model, as shown in the following equation: = / 。 6. The solid-state battery capacity assessment method based on sampling resistor temperature compensation according to claim 3, 4, or 5, characterized in that, The predetermined reference temperature The temperature is 25℃.

7. The solid-state battery capacity assessment method based on sampling resistor temperature compensation according to claim 1, characterized in that, When acquiring the local temperature T of the sampling resistor in real time, the local temperature T is acquired by a temperature sensor arranged on the surface of the sampling resistor body or in an adjacent area at a distance of no more than 5 mm from its surface; the temperature sensor is fixed by a thermally conductive material, and its thermal resistance with the sampling resistor is <5 K / W.

8. 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 any one of claims 1-7, characterized in that, The system includes: A charge / discharge module is used to connect to the solid-state battery under test and perform programmable charge / discharge operations; The sampling resistor, connected in series in the main circuit consisting of the charging / discharging module and the solid-state battery, has a known nominal resistance value. and first-order temperature coefficient ; A temperature sensor is arranged in the vicinity of the sampling resistor to collect the local temperature T of the sampling resistor in real time. A voltage sampling circuit is used to acquire the voltage signal V across the sampling resistor; The temperature compensation processing module, connected to the temperature sensor and the voltage sampling circuit, is configured as follows: Receive the synchronously acquired voltage signal V and local temperature T; Based on the preset resistance-temperature model Calculate the actual resistance value of the sampling resistor ; Using the actual resistance value Convert the voltage signal V into a current value I; The capacity calculation module is used to determine the actual charge and discharge capacity of the solid-state battery based on the current value I.

9. The solid-state battery capacity assessment system based on temperature compensation of sampling resistor according to claim 8, characterized in that, 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 duration. When the loop current is less than a set threshold, the average initial voltage across the sampling resistor is collected. and the average local temperature of the sampling resistor at this time ; Control the injection of a known calibration current into the loop. And collect the voltage across the sampling resistor at this time. ; According to the formula = / The calibrated cold resistance value was calculated. , will the Update the nominal resistance in the resistance-temperature model. .

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