Thermal hysteresis correction method and system for heat generation power measurement of battery isothermal calorimetry

Abstract

The application discloses a kind of battery isothermal calorimetry heat production power measurement thermal hysteresis correction method and system, belong to battery thermal management technical field.The method is by obtaining test original data, based on the exponential decay section of thermal power after charge and discharge end fitting battery thermal time constant, and then using the constant to original measurement data is carried out deconvolution correction, to eliminate thermal hysteresis effect, reconstructs the real transient heat production power in battery.The system includes data acquisition, parameter fitting, power correction and data output module.The application is based on RC thermal circuit model, converts the useful parameter of the signal of measurement " tailing " into the thermal inertia, effectively solves the problem of power curve distortion in traditional method, peak underestimation, significantly improves the accuracy of heat production power measurement, provides more accurate data basis for battery thermal management design, state evaluation and safety warning.

Description

Technical Field

[0001] This invention relates to the field of battery technology, and in particular to a method and system for correcting thermal hysteresis in the measurement of heat generation power by isothermal calorimetry of batteries, as well as a storage medium. Background Technology

[0002] The thermal characteristics of lithium-ion batteries are key factors affecting their performance, safety, and lifespan. Accurate measurement of heat generation power during battery charging and discharging is crucial for thermal management system design, safety warnings, and condition assessment. Isothermal calorimetry is one of the main methods for experimentally measuring battery heat generation power. It obtains the battery's heat generation power by maintaining the battery at a constant temperature and measuring the compensation power required to maintain that temperature.

[0003] However, existing isothermal calorimetry has an inherent drawback: due to the internal heat capacity and thermal resistance of the battery, it takes time for the heat generated inside the battery to be transferred to the measurement interface, resulting in a thermal hysteresis effect. Specifically, after the charging and discharging process is completed, the instrument still detects a continuous heat flow signal, causing a "tailing" phenomenon. This distorts the measured heat generation power curve on the time axis, underestimates the peak power, and smooths out the power change process, failing to accurately reflect the true instantaneous heat generation inside the battery.

[0004] In existing technologies, raw data measured by isothermal calorimeters are typically used directly for analysis, or the tail portion is simply truncated. These methods do not fundamentally solve the measurement distortion problem caused by thermal hysteresis, affecting the accuracy of battery thermal characteristic analysis and thus limiting the reliability of battery state assessment and safety warnings based on thermal characteristics. Summary of the Invention

[0005] The present invention aims to solve the problem of heat generation power measurement distortion caused by thermal hysteresis in existing battery isothermal calorimetry, and provides a method, system and storage medium that can correct the thermal hysteresis effect and obtain the true instantaneous heat generation power inside the battery.

[0006] This invention, based on the lumped-parameter thermal model of a battery, namely the RC thermal circuit model, transforms the thermal hysteresis effect from a source of measurement error into an information source for solving the battery's thermal characteristics. By extracting the battery's thermal time constant from the tail portion of the measurement data and performing deconvolution processing on the original measurement data based on a physical model, the true internal heat generation power time-series curve of the battery is reconstructed. The "deconvolution processing" described in this invention is a classic method in signal processing, namely, recovering the original signal from the measurement signal blurred by the system response.

[0007] According to a first aspect of the present invention, a method for correcting thermal hysteresis in the measurement of heat generation power by isothermal calorimetry of a battery is provided, comprising the following steps:

[0008] S1. Obtain data on the change of the original thermal power P_meas of the battery with time t as measured in the isothermal calorimetry test, and determine the end time t_end of charging and discharging;

[0009] S2. Based on the data segment with original thermal power t≥t_end, the thermal time constant τ of the battery is obtained by fitting;

[0010] S3. Based on the thermal time constant τ and the original thermal power-time data P_meas(t), calculate the corrected internal true heat generation power P_int(t);

[0011] S4. Output the corrected internal true heat generation power-time data P_int(t).

[0012] Optionally, the fitting of the battery's thermal time constant τ in step S2 specifically includes:

[0013] Assuming the actual internal heat generation power of the battery is zero after charging and discharging, establish the original heat power decay expression for the data segment t≥t_end:

[0014] P_meas(t)=P0*exp[-(t-t_end) / τ];

[0015] Based on the above expression, a nonlinear least squares fit is performed on the data segment t≥t_end to obtain the thermal time constant τ and the initial value of the original thermal power decay P0.

[0016] Optionally, the calculation of the corrected internal true heat production power P_int(t) in step S3 uses the following formula:

[0017] P_int(t)=P_meas(t)+τ*dP_meas(t) / dt, t∈[0, t_end];

[0018] Where dP_meas(t) / dt is the first derivative of the original thermal power-time data P_meas(t) with respect to time, and t=0 and t=t_end are the start and end times of battery charging and discharging, respectively.

[0019] Optionally, before calculating the first derivative dP_meas(t) / dt, the original thermal power-time data P_meas(t) is smoothed and filtered to suppress the influence of measurement noise on the numerical derivative.

[0020] Optionally, the thermal hysteresis correction method for measuring the heat generation power of a battery using isothermal calorimetry further includes a verification step:

[0021] Calculate the original total heat measurement Q_meas=∫P_meas(t)dt and the corrected total heat measurement Q_int=∫P_int(t)dt, where the start and end times of the integration of Q_meas are the start time of charging and discharging and the end time of the entire measurement, respectively, and the start and end times of the integration of Q_int are the start time of charging and discharging and the end time of charging and discharging, respectively.

[0022] Verify that |Q_int-Q_meas| / Q_meas≤ε, where ε is a preset error threshold.

[0023] According to a second aspect of the present invention, a thermal hysteresis correction system for measuring the heat generation power of a battery isothermal calorimeter is provided, comprising:

[0024] The data acquisition module is used to acquire the raw thermal power-time data P_meas(t) of the battery measured in the isothermal calorimetry test, and to determine the end time t_end of charging and discharging.

[0025] The parameter fitting module is used to fit the battery's thermal time constant τ from the data segment t≥t_end in the original thermal power-time data;

[0026] The power correction module is used to calculate the corrected internal true heat generation power P_int(t) based on the thermal time constant τ and the original thermal power-time data P_meas(t);

[0027] The data output module is used to output the corrected internal true heat generation power-time data P_int(t).

[0028] Optionally, the parameter fitting module performs the following operations:

[0029] Based on the expression P_meas(t)=P0*exp[-(t-t_end) / τ], a nonlinear least squares fit is performed on the data segment t≥t_end to obtain the thermal time constant τ and the initial value of the original thermal power decay P0.

[0030] Optionally, the power correction module calculates the corrected internal true heat generation power using the following formula:

[0031] P_int(t)=P_meas(t)+τ*dP_meas(t) / dt, t∈[0, t_end];

[0032] Where dP_meas(t) / dt is the first derivative of the original thermal power-time data P_meas(t) with respect to time, and t=0 and t=t_end are the start and end times of battery charging and discharging, respectively.

[0033] Optionally, the thermal hysteresis correction system for measuring the heat generation power of the battery isothermal calorimetry described above further includes a data preprocessing module for smoothing and filtering the original heat power-time data P_meas(t) to suppress the influence of measurement noise on the numerical derivative.

[0034] According to a third aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the thermal hysteresis correction method for measuring the heat generation power of a battery isothermal calorimeter as described above.

[0035] The beneficial effects of this invention will be described below in conjunction with the principles of its technical solution.

[0036] This paper focuses on introducing the thermal hysteresis correction method for measuring the heat generation power of batteries using isothermal calorimetry. The core physical basis of this method is the lumped parameter thermal model, also known as the RC thermal circuit model.

[0037] To simplify the complex heat generation and heat conduction processes inside the battery, the model makes the following assumptions: heat generation inside the battery is uniform, and the temperature T_bat inside the battery (core) is uniform at any time; the process of heat transfer from the uniform battery interior to the constant-temperature instrument measurement interface (shell) is characterized by a concentrated thermal resistance.

[0038] Based on the above assumptions, three thermophysical parameters are constructed to describe the thermal characteristics of the battery: heat capacity C_th, thermal resistance R_th, and thermal time constant τ.

[0039] (1) Heat capacity C_th: Represents the overall thermal energy storage capacity of the battery. Its physical meaning is the amount of heat required to raise the overall temperature of the battery by 1 Kelvin (or 1 degree Celsius). The unit is joules per Kelvin (J / K) or joules per degree Celsius (J / ℃). The calculation formula is C_th = m * c p Where m is the battery mass (kg), c p The average specific heat capacity of the battery is (J / (kg·K)).

[0040] (2) Thermal resistance R_th: This indicates the degree of resistance to heat transfer from the inside of the battery to the surface (isothermal interface). Physically, it represents the temperature difference required between the inside and surface of the battery to generate 1 watt of heat flux. The unit is Kelvin per watt (K / W) or degrees Celsius per watt (°C / W).

[0041] (3) Thermal time constant τ: Defined as the product of thermal resistance R_th and thermal capacity C_th, i.e., τ = R_th * C_th. Its unit derivation is as follows: [τ] = [R_th] * [C_th] = (K / W) * (J / K) = J / W = s. Therefore, the unit of the thermal time constant is seconds (s). It is a key dynamic parameter characterizing the response speed of the battery thermal system to disturbances (such as the start or stop of heat generation). The larger the value of τ, the slower the temperature change and the more significant the thermal hysteresis effect.

[0042] The overall theoretical basis of this invention is the energy conservation law in the charging and discharging process of the above-mentioned battery RC thermal circuit model. Treating the battery as a whole, the actual internal heat generation power P_int(t) to be solved is used for two parts: 1) increasing the internal temperature of the battery itself, that is, increasing its internal energy; 2) overcoming thermal resistance and transferring heat to the surface.

[0043] 1. According to the law of conservation of energy, the following energy conservation equation holds at any given time:

[0044] P_int(t)=C_th*(dT_bat(t) / dt)+P_meas(t) (1)

[0045] In the above, t represents time, C_th represents the battery heat capacity, T_bat(t) represents the internal temperature of the battery at time t, P_meas(t) and P_int(t) represent the original heat power and the actual internal heat generation power of the battery at time t, respectively. That is, P_meas(t) is the heat flow power lost through thermal resistance as measured and output by the isothermal calorimeter, while P_int(t) is the actual heat generation power generated by the battery.

[0046] 2. According to the definition of thermal resistance, the relationship between the measured power, i.e., the original heat power P_meas(t), and the temperature difference is as follows:

[0047] P_meas(t)=[T_bat(t)-T_set] / R_th (2)

[0048] Where T_set is the constant temperature set by the isothermal calorimeter, which is the surface temperature of the battery.

[0049] 3. Substituting equation (2) into equation (1), we get:

[0050] P_int(t)=C_th*d[T_set+R_th*P_meas(t)] / dt+P_meas(t) (3)

[0051] Since T_set is a constant, its derivative is zero; based on this, substituting τ=R_th*C_th into equation (3) simplifies to obtain the internal real heat generation power correction model adopted in this invention:

[0052] P_int(t)=P_meas(t)+τ*[dP_meas(t) / dt] (4)

[0053] In equation (4), t∈[0, t_end], where dP_meas(t) / dt is the first derivative of the original thermal power-time data P_meas(t) with respect to time, and t=0 and t=t_end are the start and end times of battery charging and discharging, respectively.

[0054] 4. Let t_end be the moment when the battery stops charging and discharging. Correspondingly, the battery stops generating heat at this moment. Then, for the data segment t≥t_end, P_int(t)=0. Equation (4) can be rewritten as:

[0055] d(P_meas(t)) / dt=-P_meas(t) / τ (5)

[0056] Equation (5) is a classic first-order linear homogeneous differential equation with constant coefficients. It is solved using the method of separation of variables:

[0057] 1) Separate the variables, moving the terms containing P_meas(t) to one side of the equation and the terms containing time t to the other side:

[0058] (1 / P_meas(t))*d(P_meas(t))=-(1 / τ)*dt (6)

[0059] 2) Integrate both sides: Integrate both sides of equation (6) separately:

[0060] ∫(1 / P_meas(t))dP_meas(t)=∫-(1 / τ)dt (7)

[0061] The integration result is:

[0062] ln|P_meas(t)|=-t / τ+C (8)

[0063] Where C is an arbitrary integration constant. Note that the battery may generate or absorb heat during the measurement process, so P_meas(t) may be positive or negative.

[0064] 3) Convert to exponential form by taking the natural exponent e on both sides of equation (8) to eliminate the logarithm:

[0065] |P_meas(t)|=exp(-t / τ+C)=exp(C)*exp(-t / τ) (9)

[0066] 4) Determine the constant and the general solution. Let A = ±exp(C), and we obtain the general solution:

[0067] P_meas(t)=A*exp(-t / τ) (10)

[0068] The constant A here is determined by the initial conditions, and the value of A can be positive or negative to absorb the absolute value sign.

[0069] 5. Apply initial conditions to determine particular solutions.

[0070] For equation (10), the "initial time" is the time t_end when the charging and discharging ends. Let the thermal power measured by the instrument at this time be P0, that is, the initial condition is: when t=t_end, P_meas(t_end)=P0.

[0071] Substituting the initial condition into the general solution (10):

[0072] P0=A*exp(-t_end / τ) (11)

[0073] Therefore, the constant A can be solved:

[0074] A=P0*exp(t_end / τ) (12)

[0075] Substituting equation (12) into equation (10), we finally obtain the original thermal power attenuation model for the data segment t≥t_end adopted in this invention:

[0076] P_meas(t)=P0*exp(t_end / τ)*exp(-t / τ)=P0*exp[-(t-t_end) / τ] (13)

[0077] The core innovation of this invention lies in recognizing that the "tailing" phenomenon in isothermal calorimetry measurements is not simply noise or error, but a direct reflection of the battery's thermal characteristics. By establishing a reasonable physical model (RC thermal circuit model), the battery's thermal inertia information (thermal time constant τ) contained in the tailing data is extracted, and this parameter is used to perform deconvolution processing on the original measurement signal, thereby eliminating the temporal distortion introduced by the heat transfer process and reconstructing the true power output curve of the battery's internal chemical heat source.

[0078] Compared with traditional methods, the advantages of this invention are:

[0079] 1. Solid physical foundation: Based on the heat transfer principle of batteries, the correction process has clear physical significance;

[0080] 2. Significantly improved accuracy: Effectively eliminates power curve distortion caused by thermal hysteresis, especially significantly improving the measurement accuracy of peak power;

[0081] 3. Dual information acquisition: Not only does it correct the measurement data, but it can also simultaneously obtain the battery's thermal time constant τ, providing additional parameters for battery thermal characteristic analysis;

[0082] 4. High versatility: Applicable to various types and specifications of batteries, as long as their thermal response can be approximated by a first-order RC model.

[0083] In particular, this method can achieve high-precision correction, and its reliability stems from the following three aspects:

[0084] First, the rationality of the physical model: Although the lumped parameter model is a simplification of the actual battery (with a certain spatial size), its description of thermal relaxation processes (such as cooling after discharge) has been widely verified to be effective. Especially in isothermal calorimetry, the instrument's powerful temperature control capability forces the battery surface temperature to remain constant, which greatly simplifies the boundary conditions and allows the first-order RC model to fit the tailing data very accurately.

[0085] Second, the rigor of mathematical processing and the conservation of energy: The correction method of this invention is mathematically a deconvolution operation, which aims to recover the original clear signal P_int(t) from the measurement signal P_meas(t) which has been blurred by the system response (thermal inertia). This process is strictly based on the derivation of physical laws, and the final result meets the fundamental test criterion of energy conservation.

[0086] Third, robust handling of measurement noise: Directly differentiating experimental data amplifies high-frequency noise. In this invention, a smoothing filter is used to preprocess P_meas(t), which effectively suppresses random noise while preserving the true trend of signal variation, thus ensuring the calculation accuracy of dP_meas(t) / dt and guaranteeing the stability of the final correction result.

[0087] In summary, the correction method of this invention is not a simple empirical formula fitting, but a physical model correction method based on solid heat transfer principles, rigorous mathematical derivation, and robust data processing techniques. Its accuracy is guaranteed by a model with high goodness of fit, strictly satisfied energy conservation laws, and robust noise handling, significantly improving the accuracy of isothermal calorimetry measurement results in terms of time distribution and accurately reproducing the true transient heat generation behavior inside the battery. Attached Figure Description

[0088] Figure 1 This is a flowchart of the thermal hysteresis correction method for measuring the heat generation power of a battery isothermal calorimeter in an embodiment of the present invention.

[0089] Figure 2 This is a schematic diagram of the thermal hysteresis correction system for measuring the heat generation power of a battery using isothermal calorimetry in an embodiment of the present invention.

[0090] Figure 3The curves showing the changes in heat generation power and voltage over time, obtained by applying the battery isothermal calorimetry method in this embodiment of the invention.

[0091] Figure 4 This is a curve showing the change of the original thermal power and its fitted value over time in the data segment t≥t_end in this embodiment of the invention.

[0092] Figure 5 These are curves showing the changes in the original thermal power and the corrected internal actual thermal power of the battery over time in embodiments of the present invention. Detailed Implementation

[0093] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0094] like Figure 1 As shown, the present invention provides a method for correcting thermal hysteresis in the measurement of heat generation power using battery isothermal calorimetry, comprising the following steps:

[0095] S1. Data Acquisition: Acquire data on the change of the original thermal power P_meas of the battery with time t, as measured in the isothermal calorimetric test, and determine the end time t_end of charging and discharging.

[0096] S2. Thermal time constant fitting: Based on the data segment of the original thermal power t≥t_end, the thermal time constant τ of the battery is obtained by fitting.

[0097] S3. Power Correction Calculation: Based on the thermal time constant τ and the original thermal power-time data P_meas(t), calculate the corrected internal true heat generation power P_int(t).

[0098] S4. Data Output: Output the corrected internal true heat generation power-time data P_int(t).

[0099] Preferably, the thermal time constant τ of the battery obtained by fitting in step S2 is based on the physical principle that the internal heat generation of the battery is zero after charging and discharging. The tail signal measured by the instrument is the relaxation process of the internal heat storage through the thermal resistance, which follows an exponential decay law, specifically including:

[0100] Assuming the actual internal heat generation power of the battery is zero after charging and discharging, establish the original heat power decay expression for the data segment t≥t_end:

[0101] P_meas(t)=P0*exp[-(t-t_end) / τ];

[0102] Based on the above expression, a nonlinear least squares fit is performed on the data segment t≥t_end to obtain the thermal time constant τ and the initial value of the original thermal power decay P0.

[0103] Preferably, the calculation of the corrected internal true heat generation power P_int(t) in step S3 adopts the following formula:

[0104] P_int(t)=P_meas(t)+τ*dP_meas(t) / dt, t∈[0, t_end];

[0105] Where dP_meas(t) / dt is the first derivative of the original thermal power-time data P_meas(t) with respect to time, and t=0 and t=t_end are the start and end times of battery charging and discharging, respectively.

[0106] This formula shows that the power measured by the instrument, P_meas(t), is equal to the actual internal heat generation power, P_int(t), minus the power used to change the thermal state of the battery itself (heating / cooling).

[0107] Preferably, before calculating the first derivative dP_meas(t) / dt, the original thermal power-time data P_meas(t) is smoothed and filtered to suppress the influence of measurement noise on the numerical derivative. In one embodiment, Savitzky-Golay filtering is used for smoothing, with a window length of 51 and a polynomial order of 3.

[0108] Preferably, the thermal hysteresis correction method for measuring the heat generation power of a battery using isothermal calorimetry further includes a verification step:

[0109] Calculate the original total heat measurement Q_meas=∫P_meas(t)dt and the corrected total heat measurement Q_int=∫P_int(t)dt, where the start and end times of the integration of Q_meas are the start time of charging and discharging and the end time of the entire measurement, respectively, and the start and end times of the integration of Q_int are the start time of charging and discharging and the end time of charging and discharging, respectively.

[0110] Verify that |Q_int-Q_meas| / Q_meas≤ε, where ε is a preset error threshold.

[0111] This verification step is to ensure that the correction process complies with the law of conservation of energy. In one embodiment, the preset error threshold ε is 2%.

[0112] like Figure 2 As shown, the present invention also provides a thermal hysteresis correction system for measuring the heat generation power of a battery isothermal calorimeter, comprising:

[0113] The data acquisition module is used to acquire the raw thermal power-time data P_meas(t) of the battery measured in the isothermal calorimetry test, and to determine the end time t_end of charging and discharging.

[0114] The parameter fitting module is used to fit the battery's thermal time constant τ from the data segment t≥t_end in the original thermal power-time data;

[0115] The power correction module is used to calculate the corrected internal true heat generation power P_int(t) based on the thermal time constant τ and the original thermal power-time data P_meas(t);

[0116] The data output module is used to output the corrected internal true heat generation power-time data P_int(t).

[0117] Preferably, the parameter fitting module performs the following operations:

[0118] Based on the expression P_meas(t)=P0*exp[-(t-t_end) / τ], a nonlinear least squares fit is performed on the data segment t≥t_end to obtain the thermal time constant τ and the initial value of the original thermal power decay P0.

[0119] Preferably, the power correction module calculates the corrected internal true heat generation power using the following formula:

[0120] P_int(t)=P_meas(t)+τ*dP_meas(t) / dt, t∈[0, t_end];

[0121] Where dP_meas(t) / dt is the first derivative of the original thermal power-time data P_meas(t) with respect to time, and t=0 and t=t_end are the start and end times of battery charging and discharging, respectively.

[0122] Preferably, the thermal hysteresis correction system for measuring the heat generation power of the battery isothermal calorimetry further includes a data preprocessing module for smoothing and filtering the original heat power-time data P_meas(t) to suppress the influence of measurement noise on the numerical derivative.

[0123] In one embodiment, the implementation of the above system includes the following modules:

[0124] 1. Data interface module: Communicates with the isothermal calorimeter to acquire raw measurement data;

[0125] 2. Data Processing Module: Performs operations such as data smoothing, numerical differentiation, and integral calculation;

[0126] 3. Model Fitting Module: Implements a nonlinear least squares fitting algorithm;

[0127] 4. Correction Calculation Module: Performs power correction calculations based on the fitted parameters;

[0128] 5. Visualization module: Generates comparison charts between the original data and the corrected results;

[0129] 6. Data Output Module: Exports the correction results as a standard format file.

[0130] This invention also provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the steps of the thermal hysteresis correction method for measuring the heat generation power of a battery isothermal calorimeter as described above. Specifically, the computer program of this invention can be stored on any non-transient computer-readable storage medium, including but not limited to: hard disks, solid-state drives, USB flash drives, SD cards, optical discs, cloud storage, etc. When the program is executed by a processor, all the steps of the aforementioned method are implemented.

[0131] This invention can be widely applied to:

[0132] 1. Battery R&D: Providing more accurate testing methods for evaluating the thermal properties of new battery materials;

[0133] 2. Battery Management System: Provides precise heat generation power input for thermal management algorithms, improving temperature control accuracy and safety;

[0134] 3. Battery State Assessment: Based on accurate heat generation characteristics, develop new methods for estimating battery state of health (SOH) and internal state;

[0135] 4. Standard testing institutions: As a standard post-processing method for isothermal calorimetry testing, they improve the reliability and comparability of test results.

[0136] 5. This invention solves the long-standing problem of thermal hysteresis measurement error in isothermal calorimetry, providing a more accurate tool for studying battery thermal characteristics, and is of great significance for promoting battery technology progress and improving battery safety.

[0137] Example

[0138] First, please refer to... Figure 1 and Figure 2 Understand the correction method and system in this embodiment.

[0139] A 48Ah ternary soft-pack lithium-ion battery was used as the test object. After being discharged to 0% SOC, it was placed in a BIC-400A battery isothermal calorimeter for 2C constant current charging. The battery isothermal calorimeter adopted a power-compensated isothermal mode to ensure that the battery surface temperature was 25℃. The curves of the original thermal power and voltage change with time t are shown in the figure. Figure 3 When t=1428s, the battery is fully charged, that is, t_end=1428s; the original thermal power-time data still contains original thermal power data in the t≥t_end data segment.

[0140] Based on the expression P_meas(t)=P0*exp[-(t-t_end) / τ], a nonlinear least squares fit is performed on the data segment t≥t_end, yielding: thermal time constant τ=78.124s, initial value of original thermal power decay P0=16.9285W, and goodness of fit R2=0.9981. Please note that the fitting process must be constrained by setting the constraint τ>0 according to physical meaning.

[0141] The curves showing the changes in the original measured and fitted values ​​of thermal power over time for the data segment t≥t_end are shown below. Figure 4 .

[0142] Based on the fitting results, the formula P_int(t)=P_meas(t)+τ*dP_meas(t) / dt was applied for correction. The curves showing the changes of the original measured thermal power (measured value) and the corrected internal true thermal power (corrected value) over time are shown below. Figure 5 Please note that the time t in the correction calculation process is in the range of 0 to t_end.

[0143] Finally, the original total heat measurement was calculated to be Q_meas = ∫P_meas(t)dt = 19155 J, with the integration start and end times being t = 0 and t = 1905 s, respectively; the corrected total heat measurement was Q_int = ∫P_int(t)dt = 19011 J, with the integration start and end times being t = 0 and t = 1428 s, respectively; |Q_int - Q_meas| / Q_meas = 0.75%, while the preset error threshold ε is 2%, so the verification is successful.

[0144] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. The technical solution of the present invention can have many different specific embodiments and can be appropriately improved according to different application scenarios. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for correcting thermal hysteresis in the measurement of heat generation power using battery isothermal calorimetry, characterized in that, Includes the following steps: S1. Obtain data on the change of the original thermal power P_meas of the battery with time t as measured in the isothermal calorimetry test, and determine the end time t_end of charging and discharging; S2. Based on the data segment with original thermal power t≥t_end, the thermal time constant τ of the battery is obtained by fitting; S3. Based on the thermal time constant τ and the original thermal power-time data P_meas(t), calculate the corrected internal true heat generation power P_int(t); S4. Output the corrected internal true heat generation power-time data P_int(t).

2. The method according to claim 1, characterized in that, The fitting of the battery's thermal time constant τ in step S2 specifically includes: Assuming the actual internal heat generation power of the battery is zero after charging and discharging, establish the original heat power decay expression for the data segment t≥t_end: P_meas(t)=P0*exp[-(t-t_end) / τ]; Based on the above expression, a nonlinear least squares fit is performed on the data segment t≥t_end to obtain the thermal time constant τ and the initial value of the original thermal power decay P0.

3. The method according to claim 1, characterized in that, The calculation of the corrected internal true heat production power P_int(t) in step S3 uses the following formula: P_int(t)=P_meas(t)+τ*dP_meas(t) / dt, t∈[0, t_end]; Where dP_meas(t) / dt is the first derivative of the original thermal power-time data P_meas(t) with respect to time, and t=0 and t=t_end are the start and end times of battery charging and discharging, respectively.

4. The method according to claim 3, characterized in that, Before calculating the first derivative dP_meas(t) / dt, the original thermal power-time data P_meas(t) is smoothed and filtered to suppress the influence of measurement noise on the numerical derivative.

5. The method according to claim 1, characterized in that, It also includes a verification step: Calculate the original total heat measurement Q_meas=∫P_meas(t)dt and the corrected total heat measurement Q_int=∫P_int(t)dt, where the start and end times of the integration of Q_meas are the start time of charging and discharging and the end time of the entire measurement, respectively, and the start and end times of the integration of Q_int are the start time of charging and discharging and the end time of charging and discharging, respectively. Verify that |Q_int-Q_meas| / Q_meas≤ε, where ε is a preset error threshold.

6. A thermal hysteresis correction system for measuring the heat generation power of a battery using isothermal calorimetry, characterized in that, include: The data acquisition module is used to acquire the raw thermal power-time data P_meas(t) of the battery measured in the isothermal calorimetry test, and to determine the end time t_end of charging and discharging. The parameter fitting module is used to fit the battery's thermal time constant τ from the data segment t≥t_end in the original thermal power-time data; The power correction module is used to calculate the corrected internal true heat generation power P_int(t) based on the thermal time constant τ and the original thermal power-time data P_meas(t); The data output module is used to output the corrected internal true heat generation power-time data P_int(t).

7. The system according to claim 6, characterized in that, The parameter fitting module performs the following operations: Based on the expression P_meas(t)=P0*exp[-(t-t_end) / τ], a nonlinear least squares fit is performed on the data segment t≥t_end to obtain the thermal time constant τ and the initial value of the original thermal power decay P0.

8. The system according to claim 6, characterized in that, The power correction module calculates the corrected internal true heat generation power using the following formula: P_int(t)=P_meas(t)+τ*dP_meas(t) / dt, t∈[0, t_end]; Where dP_meas(t) / dt is the first derivative of the original thermal power-time data P_meas(t) with respect to time, and t=0 and t=t_end are the start and end times of battery charging and discharging, respectively.

9. The system according to claim 6, characterized in that, It also includes a data preprocessing module for smoothing and filtering the raw thermal power-time data P_meas(t) to suppress the influence of measurement noise on the numerical derivative.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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