Multi-mode power battery service temperature dynamic evaluation method based on fusion of ultrasonic features and state parameters

Abstract

The invention discloses a multi-mode power battery service temperature dynamic evaluation method based on ultrasonic feature and state parameter fusion, which comprises the following steps: 1, controlling a state variable, and calculating a compensation coefficient of an environment temperature; 2, controlling a temperature variable, and constructing a state compensation matrix; 3, environment temperature compensation and state compensation are carried out on the sound amplitude and the flight time in the actual measurement environment, and normalization processing is carried out; and 4, determining each weight coefficient of the temperature estimation model. According to the invention, high-precision, real-time and non-destructive monitoring of the internal temperature of the battery can be realized under the conditions of not implanting an internal sensor and not damaging the structure of the battery, so that key safety problems of thermal runaway early warning, quick charge thermal management, life prediction and the like of the power battery are effectively solved.

Description

TECHNICAL FIELD

[0001] The application relates to the field of battery detection, in particular to a multi-modal power battery service temperature dynamic evaluation method based on ultrasonic feature and state parameter fusion. BACKGROUND

[0002] As the core power source of electric vehicles and energy storage systems, the safety and performance of lithium ion batteries are highly dependent on precise temperature management. The internal temperature of the battery is the most direct and sensitive indicator of the electrochemical state, health degree and safety risk. Over-temperature can lead to capacity attenuation, shortened life, and even cause thermal runaway accidents. However, traditional temperature measurement techniques have significant limitations: contact temperature measurement (such as thermocouples) has low spatial resolution and cannot sense the real temperature field distribution inside the cell. In addition, implantable measurement damages the battery structure and increases the risk of short circuit. Non-contact infrared temperature measurement is limited by the interference of the shell thermal resistance and is difficult to penetrate the packaging to obtain the internal temperature. These techniques cannot meet the core needs of accurate, real-time, non-invasive and non-destructive sensing of the internal temperature of power batteries. SUMMARY

[0003] The present application overcomes the deficiencies of the prior art and provides a multi-modal power battery service temperature dynamic evaluation method based on ultrasonic feature and state parameter fusion. This method can obtain the internal temperature of the battery using ultrasonic signals combined with the electrochemical state of the battery without damaging the battery structure, thereby ensuring the safety of the battery throughout its life cycle, improving its fast charging performance and energy efficiency, and optimizing the thermal management control strategy. This method solves the industry problem of real-time and non-destructive sensing of the internal temperature of the battery.

[0004] To achieve the above-mentioned application purposes, the technical solutions adopted by the present application are as follows: The multi-modal power battery service temperature dynamic evaluation method based on ultrasonic feature and state parameter fusion comprises the following steps: Step 1: Calibrate the environmental temperature compensation coefficient corresponding to the sound amplitude value of a certain type of battery and the environmental temperature compensation coefficient corresponding to the time of flight ; Step 2: Construct a compensation matrix of the state of charge and the state of health of the lithium ion battery and input it into the battery management system (BMS); wherein, represents the compensation amount of the sound amplitude value of the lithium ion battery under the th state of health value , th state of charge value , represents the compensation amount of the sound amplitude value of the lithium ion battery under the th state of health value , Each state of charge value The amount of compensation for the flight time of lithium-ion batteries. This represents the total number of lithium-ion batteries at each health state value. This represents the total number of health status values; Step 3, based on , as well as Determine the set of Y lithium-ion batteries at ambient temperatures. Set of state of charge values and the A set of health status values The actual internal temperature below And the sound amplitude value after environmental temperature compensation, state compensation and normalization. With flight time ; in, Indicates the first The normalized acoustic amplitude value of a lithium-ion battery. Indicates the first Normalized flight time for each lithium-ion battery; Indicates the first The ambient temperature corresponding to each lithium-ion battery. Indicates the first The state of charge (SOC) of each lithium-ion battery. Indicates the first The health status of each lithium-ion battery. Indicates the first The actual internal temperature of a lithium-ion battery; Step 4: Construct a temperature estimation model for the same type of lithium-ion battery as in Step 1 using equation (20), and solve it using the constrained least squares method to obtain the result. Optimal weighting coefficients and Optimal weighting coefficients and the set of state of charge values Optimal weighting coefficients With health status value set Optimal weighting coefficients Nonlinear coupling terms Optimal weighting coefficients ; (20) In equation (20), express The weighting coefficients, for The weighting coefficients, The set of state-of-charge values The optimal weighting coefficients, A set of health status values The weighting coefficients, Nonlinear coupling term Weighting coefficients; Step 5: Use the temperature estimation model with optimal weighting coefficients to estimate the internal temperature of the lithium-ion battery at the current moment, and trigger an alarm when the estimated internal temperature is greater than the temperature threshold.

[0005] The real-time temperature monitoring method for lithium-ion batteries based on the fusion of ultrasonic features and electrochemical parameters described in this invention is characterized in that step 1 includes the following steps: Step 1.1: Set the ambient temperature Set the reference ambient temperature and set the state of charge. Set as the reference state of charge, and set the health state Set as the baseline health status; After a battery of a certain model was left to stand for a period of time at a reference ambient temperature, reference state of charge, and reference health condition, the amplitude of the ultrasonic signal of the same model battery was measured. and flight time and will Set as the reference sound amplitude value, and Set as the baseline flight time; Step 1.2, the same battery under the reference state of charge and reference health state. Aperture temperature with equal variation , … … After being left to stand for a period of time, the sound amplitude of the same battery at each ambient temperature was measured. , … … With flight time , … … ; in, Indicates the first A series of aperture temperature gradients, Indicates the first Aperture temperature with equal variation The amplitude value below, Indicates the first Aperture temperature with equal variation Flight time below; Step 1.3: Calculate the first step using equations (1) and (2) respectively. Aperture temperature with equal variation The amplitude value below the rate of change of and the rate of change of (1) (2) Step 1.4, the average rate of change of the sound amplitude at the equal difference ambient temperatures is calculated by using formula (3) and formula (4) respectively and the average rate of change of the time of flight at the equal difference ambient temperatures is calculated by using formula (3) and formula (4) respectively (3) (4) Step 1.5, the change amount of the ambient temperature relative to is calculated by using formula (5) and the average change amount of the equal difference ambient temperatures is calculated by using formula (6) (5) (6) Step 1.6, the covariance of the sound amplitude and the covariance of the time of flight are calculated by using formula (7) and formula (8) respectively (7) (8) Step 1.7, the ambient temperature variance is calculated by using formula (9) (9) Step 1.8, the ambient temperature compensation coefficient of the sound amplitude and the ambient temperature compensation coefficient of the time of flight are calculated by using formula (9) and (10) respectively (10) (11).

[0006] Further, the step 2 comprises the following steps: Step 2.1, 80%~100% of the health state is evenly divided into ​​​​​Health status value , … … And prepare separately for each health status value. Block lithium-ion batteries, thus obtaining The block contains lithium-ion batteries of the same model as those used in step 1, wherein... For the first A health status value; Step 2.2: Divide the 0~100% state of charge evenly into The first state of charge value, thus making the first Health status value Below The state of charge (SOC) values ​​of the block lithium-ion batteries are set as follows: , … … ,in, For the first Health status value The next The state of charge (SOC) value of a block lithium-ion battery; Step 2.3, at the reference ambient temperature Next, and After each lithium-ion battery was left to stand for a period of time, the acoustic amplitude and flight time of each lithium-ion battery were measured under different health and state of charge values. Health status value The next Each state of charge value The acoustic amplitude value of the lithium-ion battery is denoted as Flight time is recorded as ; Step 2.4, Record The maximum value of the sound amplitude measured from a lithium-ion battery. and minimum value and the maximum value in flight time and minimum value ; Step 2.5: Calculate the first step according to equations (12) and (13). Health status value The next Each state of charge value The compensation amount of the sound amplitude of the lithium-ion battery The compensation amount for flight time is : (12) (13).

[0007] Furthermore, step 3 includes the following steps: Step 3.1: Obtain the same model as in Step 1. The first lithium-ion battery, and in the first Ambient temperature , No. Each state of charge value and the Health status value Next to the The lithium-ion battery was subjected to ultrasonic testing to obtain the first... The sound amplitude of a lithium-ion battery Flight time and actual internal temperature Thus obtain Each lithium-ion battery is located at an ambient temperature range. Set of state of charge values and the A set of health status values The amplitude value below , … … Flight time , … … and actual internal temperature , … … ; Step 3.2: Using equations (14) and (15), obtain the first... The ambient temperature compensated sound amplitude of a lithium-ion battery And flight time after ambient temperature compensation : (14) (15) Step 3.3, in the compensation matrix In the middle, the result is obtained through table lookup and bilinear interpolation algorithms. and Corresponding compensation amount ,in, For the first The amount of sound amplitude compensation for each lithium-ion battery. For the first Flight time compensation for each lithium-ion battery; Step 3.4: According to equations (16) and (17), the first... sound amplitude value of the lithium-ion battery after state compensation and time of flight after state compensation (16) (17) Step 3.5, the normalized sound amplitude value of the lithium-ion battery is obtained according to formula (18) and (19) and time of flight after normalization (18) (19).

[0008] The electronic device comprises a memory and a processor, and is characterized in that the memory is used for storing a program supporting the processor to execute the multi-modal power battery service temperature dynamic evaluation method, and the processor is configured to execute the program stored in the memory.

[0009] The computer readable storage medium stores a computer program, and the computer program is characterized in that when the computer program is executed by a processor, the steps of the multi-modal power battery service temperature dynamic evaluation method are executed.

[0010] Compared with the prior art, the present application has the following advantages: 1) The present application utilizes the significant difference in acoustic propagation characteristics (sound attenuation coefficient SA, time of flight TOF) of lithium-ion batteries at different temperatures and aging states, establishes a multi-parameter physical fusion model, and dynamically decouples and compensates ultrasonic feature parameters and electrochemical state parameters (SOC, SOH), thereby achieving accurate, real-time, and non-invasive measurement of the internal temperature of the battery, solving the problem of existing battery temperature monitoring technology requiring implanted sensors or relying on inaccurate external measurements, significantly improving safety monitoring reliability and avoiding battery structure damage.

[0011] 2) The present application adopts time of flight extraction technology based on cross-correlation algorithm and frequency domain sound attenuation analysis technology, combined with dynamic compensation matrix and normalization processing method, effectively eliminates the coupling interference of SOC and SOH changes on acoustic parameters, improves the large error problem of traditional single parameter temperature sensing method in the whole life cycle of the battery, and realizes the temperature estimation accuracy of ±1.5℃ under all working conditions from new battery to end of life (SOH≥80%).

[0012] ​​​3) The ultrasonic detection technology of the present application has unique advantages in the field of battery state monitoring: based on the propagation theory of Biot fluid saturated porous medium, the differences in acoustic impedance and sound velocity caused by the changes in physical parameters such as Young's modulus and density of the material can be used to realize the in-situ characterization of the internal state of the battery. This method has high sensitivity, fast response speed, and low equipment cost, and has made progress in the state of charge (SOC) estimation of ternary lithium and lithium cobalt oxide batteries. By extending the ultrasonic technology to the field of temperature monitoring, through the construction of a multi-modal evaluation model that integrates ultrasonic features and electrical / thermal parameters, it is expected to break through the limitations of traditional temperature measurement techniques. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 Flowchart of the temperature monitoring method of the present application. DETAILED DESCRIPTION

[0014] In this embodiment, the multi-modal dynamic evaluation method for the service temperature of the power battery based on the fusion of ultrasonic features and state parameters is to realize the electrochemical state decoupling and temperature inversion of acoustic features through the establishment of a multi-parameter dynamic compensation model and a physically guided fusion estimation algorithm, so as to accurately calculate the internal temperature of the battery through easily obtained ultrasonic signals and battery state parameters. Specifically, as shown in Figure 1 The method includes the following steps: Step 1, calibrate the ambient temperature compensation coefficient corresponding to the sound amplitude of a certain type of battery and the ambient temperature compensation coefficient corresponding to the time of flight to strip the influence of ambient temperature itself on acoustic parameters.

[0015] Step 1.1, set the ambient temperature as the reference ambient temperature, generally select 25℃ as the reference ambient temperature, set the state of charge as the reference state of charge, generally select 50% of the state of charge value as the reference state of charge, set the health state as the reference health state, generally select 100% of the health state value as the reference state of charge; Control the state of charge and the health state unchanged to exclude the interference of the battery state, after a certain type of battery is placed at the reference ambient temperature, the reference state of charge and the reference health state for a period of time, the sound amplitude and the time of flight of the ultrasonic signal of the same type of battery are measured, and is set as the reference sound amplitude, and is set as the reference time of flight.

[0016] Step 1.2, under the same battery at the reference state of charge and the reference health state, at an equal difference ambient temperature , … … Below, temperature points can be selected as -20℃, ..., 15℃, 20℃, 25℃, 30℃, ..., 60℃. After being left to stand for a period of time, each temperature point needs to be kept at a constant temperature for at least 2 hours. The sound amplitude value of the same battery at each ambient temperature can be measured. , … … With flight time , … … ; in, Indicates the first A series of aperture temperature gradients, Indicates the first Aperture temperature with equal variation The amplitude value below, Indicates the first Aperture temperature with equal variation Flight time.

[0017] Step 1.3: Within a limited temperature range (-20℃~60℃), the changes in acoustic parameters are approximately linearly related to temperature. A linear model is sufficient to guarantee accuracy and is computationally simple, making it ideal for real-time implementation in embedded systems. The equations (1) and (2) are used to calculate the... Aperture temperature with equal variation The amplitude value below Compared to rate of change as well as Compared to rate of change : (1) (2) Step 1.4: Calculate the sound amplitude value using equations (3) and (4) respectively. Average rate of change under uniform ambient temperatures With flight time Average rate of change under uniform ambient temperatures : (3) (4).

[0018] Step 1.5: Calculate the first step using equation (5). Ambient temperature Compared to Change Therefore, equation (6) is used to calculate The average change in ambient temperature at different arithmetic progressions : (5) (6) Step 1.6: Calculate the covariance of the sound amplitude using equations (7) and (8) respectively. Covariance with flight time : (7) (8) Step 1.7: Calculate the ambient temperature variance using equation (9). : (9) Step 1.8: Calculate the ambient temperature compensation coefficient for the sound amplitude using equations (9) and (10) respectively. Ambient temperature compensation coefficient with flight time ; (10) (11).

[0019] Step 2: Construct the state compensation matrix of the lithium-ion battery And enter it into the Battery Management System (BMS); Step 2.1: Divide the 80%~100% health status evenly into... Health status value , … … For lithium-ion batteries, when the state of health (SOH) value is below 80%, their safety and reliability are extremely low, requiring disposal. Therefore, the calibration mainly focuses on lithium-ion batteries with a SOH value above 80%. Commonly used preparation methods include SOH values ​​of 100%, 95%, 90%, 85%, and 80%, with separate preparations made for each SOH value. Block lithium-ion batteries, thus obtaining The block contains lithium-ion batteries of the same model as those used in step 1, wherein... For the first A health status value; Step 2.2: Divide the 0~100% state of charge evenly into The state of charge value can be divided every 10%, thus dividing the first value into 10% values. Health status value Below The state of charge values of the blocks of lithium-ion batteries are respectively set as 、 、…、 、…、 wherein, is the state of charge value of the jth lithium-ion battery under the ith state of health value . Step 2.3, under the reference ambient temperature , the experimental ambient temperature is generally strictly controlled at 25℃ to eliminate the influence of ambient temperature variables, and after the lithium-ion batteries are left for a period of time, at least 2 hours, the sound amplitude and the time of flight of each lithium-ion battery under different state of health values and different state of charge values are measured, wherein the sound amplitude of the jth lithium-ion battery under the ith state of health value

[0020] and the ith state of charge value is recorded as , and the time of flight is recorded as . Step 2.4, the maximum value and the minimum value of the sound amplitude and the maximum value and the minimum value of the time of flight measured by the lithium-ion batteries are recorded. Step 2.5, the compensation amount of the sound amplitude and the compensation amount of the time of flight of the jth lithium-ion battery under the ith state of health value and the ith state of charge value are respectively calculated according to formula (12) and (13) as follows:

[0021] (12) (13). The above calculation results are stored as a multi-dimensional data structure (a two-dimensional array in actual programming), and the logical structure is shown in the following table: In actual application scenarios, according to the real-time state of charge value and state of health value provided by the BMS, the corresponding compensation value is determined by combining the look-up table and the interpolation method.

[0022]

[0023] In actual application scenarios, according to the real-time state of charge value and state of health value provided by the BMS, the corresponding compensation value is determined by combining the look-up table and the interpolation method.

[0024] ​​​​​​​Taking a state of charge (SBC) of 15% and a health state of 83% as an example, the SBC range is first defined as [10%, 20%], and the health state range is defined as [80%, 85%]. The compensation values ​​for the four adjacent corner points are then extracted from the matrix. , ), ( , ), ( , ), ( , Next, interpolation calculations are performed on the compensation values. Taking the calculation of sound amplitude as an example, the compensation value for sound amplitude when the state of charge is 15% and the health state is 83% is: .

[0025] Similarly, the compensation value for flight time can be calculated when the state of charge is 15% and the health status is 83%.

[0026] Step 3, based on , as well as For sound amplitude and flight time, environmental temperature compensation and state compensation must be performed first, followed by state compensation. This is because environmental temperature compensation uses pre-calibrated coefficients under fixed charged / healthy states. Only by eliminating the influence of environmental temperature can the current measured value and the compensation matrix (calibrated at 25°C) be under the same environmental temperature reference, thus enabling correct table lookup. Step 3.1: Obtain the same model as in Step 1. The first lithium-ion battery, and in the first Ambient temperature , No. Each state of charge value and the Health status value Next to the The lithium-ion battery was subjected to ultrasonic testing to obtain the first... The sound amplitude of a lithium-ion battery Flight time and actual internal temperature Thus obtain Each lithium-ion battery is located at an ambient temperature range. Set of state of charge values and the A set of health status values The amplitude value below , … … Flight time , … … and actual internal temperature , … … .

[0027] Step 3.2: Convert the sound amplitude and flight time to the reference ambient temperature. Generally, 25℃ is selected as the reference ambient temperature. Use equations (14) and (15) to obtain the values ​​of the first and second stages respectively. The ambient temperature compensated sound amplitude of a lithium-ion battery And flight time after ambient temperature compensation ,: (14) (15) Step 3.3, in the compensation matrix In the middle, the result is obtained through table lookup and bilinear interpolation algorithms. and Corresponding compensation amount ,in, For the first The amount of sound amplitude compensation for each lithium-ion battery. For the first Flight time compensation for each lithium-ion battery.

[0028] Step 3.4: According to equations (16) and (17), the first... The amplitude value of the state-compensated lithium-ion battery and flight time after state compensation : (16) (17) Step 3.5: According to equations (18) and (19), we obtain the first... Normalized sound amplitude value of a lithium-ion battery and normalized flight time : (18) (19).

[0029] Step 4: Construct a temperature estimation model for the same type of lithium-ion battery as in Step 1 using equation (20), and solve it using the constrained least squares method to obtain the result. Optimal weighting coefficients and Optimal weighting coefficients optimal weight coefficients of the set of state of charge values optimal weight coefficients of the set of state of health values optimal weight coefficients of the set of state of charge values optimal weight coefficients of the set of state of health values optimal weight coefficients of the nonlinear coupling term optimal weight coefficients of the nonlinear coupling term (20) In formula (20), denotes the weight coefficient of denotes the weight coefficient of denotes the weight coefficient of denotes the weight coefficient of optimal weight coefficients of the set of state of charge values optimal weight coefficients of the set of state of health values optimal weight coefficients of the set of state of health values optimal weight coefficients of the set of state of health values optimal weight coefficients of the nonlinear coupling term optimal weight coefficients of the nonlinear coupling term

[0030] The data set is divided into a training set and a test set to prevent overfitting. If the effect is not good, a regression with regularization or an intelligent optimization algorithm can be used to solve more optimal weights.

[0031] Step 5, using the temperature estimation model under the optimal weight coefficient to estimate the internal temperature of the lithium ion battery at the current time, and triggering a warning when the estimated internal temperature is greater than the temperature threshold.

[0032] In this embodiment, an electronic device includes a memory for storing a program supporting a processor to execute the above method, and the processor is configured to execute the program stored in the memory.

[0033] In this embodiment, a computer readable storage medium has a computer program stored thereon, and the computer program is executed by a processor to perform the steps of the above method.​

Claims

1. A method for dynamic evaluation of service temperature of a multi-modal power battery based on fusion of ultrasonic features and state parameters, characterized in that, The method comprises the following steps: Step 1, calibrate the ambient temperature compensation coefficient corresponding to the sound amplitude value of a certain type of battery and the ambient temperature compensation coefficient corresponding to the time of flight ; Step 2: Construct a compensation matrix for the state of charge and state of health of lithium-ion batteries. And enter it into the Battery Management System (BMS); among which, Indicates the first Health status value The next Each state of charge value The amount of compensation for the acoustic amplitude of the lithium-ion battery. Indicates the first Health status value The next Each state of charge value The amount of compensation for the flight time of lithium-ion batteries. This represents the total number of lithium-ion batteries at each health state value. This represents the total number of health status values; Step 3, based on , as well as Determine the set of Y lithium-ion batteries at ambient temperatures. Set of state of charge values and the A set of health status values The actual internal temperature below And the sound amplitude value after environmental temperature compensation, state compensation and normalization. With flight time ; in, Indicates the first The normalized acoustic amplitude value of a lithium-ion battery. Indicates the first Normalized flight time for each lithium-ion battery; Indicates the first The ambient temperature corresponding to each lithium-ion battery. Indicates the first The state of charge (SOC) of each lithium-ion battery. Indicates the first The health status of each lithium-ion battery. Indicates the first The actual internal temperature of a lithium-ion battery; Step 4, construct the temperature estimation model of the same type of lithium-ion battery as step 1 using formula (20), and solve it using the constrained least squares method, so as to obtain the optimal weight coefficient of the temperature estimation model The optimal weight coefficient of the temperature estimation model , and the optimal weight coefficient of the state of charge value set The optimal weight coefficient of the state of health value set The optimal weight coefficient of the nonlinear coupling term ;​​​​​ (20) in formula (20), denotes a weight coefficient of is a weight coefficient of is a set of state of charge values is an optimal weight coefficient of is a set of health state values is a weight coefficient of is a weight coefficient of a non-linear coupling term is a weight coefficient of a non-linear coupling term Step 5, estimating the internal temperature of the lithium ion battery at the current time by using the temperature estimation model under the optimal weight coefficient, and triggering a warning when the estimated internal temperature is greater than a temperature threshold. 2.The lithium-ion battery temperature real-time monitoring method based on fusion of ultrasonic characteristics and electrochemical parameters according to claim 1, characterized in that, The step 1 comprises the following steps: Step 1.1, Set the ambient temperature the state of charge the state of health the state of health; measuring an acoustic amplitude of an ultrasonic signal of a battery of the same model after the battery of the same model is left for a period of time at a reference ambient temperature, a reference state of charge, and a reference state of health and a time of flight and setting the acoustic amplitude as a reference acoustic amplitude and the time of flight as a reference time of flight; Step 1.2, the same battery under the reference state of charge and reference health state. Aperture temperature with equal variation , … … After being left to stand for a period of time, the sound amplitude of the same battery at each ambient temperature was measured. , … … With flight time , … … ; in, Indicates the first A series of aperture temperature gradients, Indicates the first Aperture temperature with equal variation The amplitude value below, Indicates the first Aperture temperature with equal variation Flight time below; Step 1.3: Calculate the first step using equations (1) and (2) respectively. Aperture temperature with equal variation The amplitude value below Compared to rate of change as well as Compared to rate of change : (1) (2) Step 1.

4. Calculate the average rate of change of the sound amplitude with respect to the temperature in :​​​ (3) (4) Step 1.5, calculate the first ambient temperature relative to the change amount , thus calculate the average change amount of the first arithmetic ambient temperature using formula (6) (5) (6) Step 1.

6. Calculate the covariance of the sound amplitude values with time of flight using formula (7) and formula (8) respectively Covariance with time of flight : (7) (8) Step 1.

7. Calculate ambient temperature variance using formula (9) : (9) Step 1.8, Calculate the ambient temperature compensation factor for the sound amplitude values using equations (9) and (10) respectively Ambient temperature compensation factor for time of flight ; (10) (11)。 3.The lithium-ion battery temperature real-time monitoring method based on fusion of ultrasonic features and electrochemical parameters according to claim 2, characterized in that, The step 2 comprises the following steps: Step 2.1, evenly divide the 80%~100% health status into health status values , , , , and prepare blocks of lithium ion batteries respectively at each health status value, thereby obtaining blocks of lithium ion batteries of the same model as Step 1, wherein is the health status value; Step 2.2, dividing the 0~100% state of charge evenly into state of charge values, thereby setting the state of charge value of the state of health value block lithium ion battery to , , , ,wherein is the state of charge value of the state of health value block lithium ion battery;​ Step 2.3, at the reference ambient temperature The amplitude and time of flight of each lithium-ion battery is measured at different state of health values and different state of charge values, wherein the first ;​​​​​​ Step 2.4, record Maximum value in the amplitude of the sound measured by the lithium-ion battery With minimum value And maximum value in the time of flight And minimum value ; Step 2.

5. Calculate the compensation amount of the sound amplitude value of the lithium ion battery under the first state of health value and the compensation amount of the time of flight for the first state of charge value of the lithium ion battery under the first :​​​​ (12) (13)。 4.The lithium-ion battery temperature real-time monitoring method based on fusion of ultrasonic features and electrochemical parameters according to claim 3, characterized in that, The step 3 comprises the following steps: Step 3.1: Obtain the same model as in Step 1. The first lithium-ion battery, and in the first Ambient temperature , No. Each state of charge value and the Health status value Next to the The lithium-ion battery was subjected to ultrasonic testing to obtain the first... The sound amplitude of a lithium-ion battery Flight time and actual internal temperature Thus obtain Each lithium-ion battery is located at an ambient temperature range. Set of state of charge values and the A set of health status values The amplitude value below , … … Flight time , … … and actual internal temperature , … … ; Step 3.2, the first sound amplitude value of the second lithium-ion battery is obtained by using formula (14) and formula (15) respectively after environmental temperature compensation and the time of flight after environmental temperature compensation : (14) (15) Step 3.3, in the compensation matrix , the corresponding compensation amount is obtained by table lookup and bilinear interpolation algorithm and , wherein, is the amplitude value compensation amount of the first lithium ion battery, is the time of flight compensation amount of the first lithium ion battery;​ Step 3.4, obtaining the compensated acoustic amplitude of the first lithium-ion cell from the formula (16) and the formula (17), respectively and the compensated time of flight ​ (16) (17) Step 3.5, obtaining the first normalized acoustic amplitude and normalized time of flight from the second lithium-ion battery of formula (18) and (19) : (18) (19)。 5. An electronic device comprising a memory and a processor, characterized in that The memory is configured to store a program supporting the processor to execute the multi-modal power battery service temperature dynamic evaluation method according to any one of claims 1-4, and the processor is configured to execute the program stored in the memory.

6. A computer-readable storage medium having stored thereon a computer program, characterized in that The computer program is executed by the processor to perform the steps of the multi-modal power battery service temperature dynamic evaluation method according to any one of claims 1-4.

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