Dynamic real-time online measurement method and system for internal temperature of lithium ion battery

Abstract

The invention discloses a dynamic real-time online measurement method and system for the internal temperature of a lithium ion battery, and relates to the technical field of temperature measurement of the lithium ion battery, and the main scheme is as follows: obtaining the battery working data of the current lithium ion battery and calculating the actual working environment temperature; obtaining relaxation time; in the relaxation time, continuously measuring a dynamic impedance phase angle; acquiring historical use data of the battery, and calculating an influence factor and a battery aging coefficient; calculating a static impedance phase angle through the influence factor, the battery aging coefficient and the dynamic impedance phase angle; calculating the static temperature according to the static impedance phase angle and the actual working environment temperature; calculating a dynamic temperature according to the static temperature and the battery working data; setting a dynamic temperature threshold set, comparing the dynamic temperature with the threshold, judging whether the battery works in the optimal performance range, and if the dynamic temperature does not meet the threshold, triggering abnormal early warning; according to the scheme, the use safety of the battery is improved, and the performance of the battery is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature measurement of lithium ion batteries, and in particular to a method and system for dynamic real-time online measurement of the internal temperature of a lithium ion battery. Background Art

[0002] With the rapid development of new energy vehicles and energy storage technology, lithium-ion batteries, as important energy storage devices, are widely used in electric vehicles, portable electronic devices and other fields due to their high energy density, long life and no memory effect. Especially under complex and changeable driving conditions, the internal temperature of lithium-ion batteries is easily affected by various factors and changes, which puts higher requirements on battery management and control.

[0003] In combination with the above invention, the prior art still has the following deficiencies:

[0004] Traditional temperature monitoring methods mainly rely on surface temperature sensors, which cannot accurately reflect the temperature distribution inside the battery, especially during high-power charging and discharging. Sensor temperature measurement requires physical modification of the battery, which may damage the battery structure and sealing, and is costly. Especially when there are a large number of batteries, installing a sensor on each battery will significantly increase the cost. It will also be affected by the internal environment of the battery, interfering with the measurement accuracy and damaging the sensor life, making it impossible to monitor the safe working status of the battery in real time. Summary of the invention

[0005] 1. Technical issues to be solved

[0006] In view of the shortcomings of the prior art, the present invention provides a method and system for dynamic real-time online measurement of the internal temperature of a lithium-ion battery. By combining the battery working data, the current working state of the battery can be fully understood and the actual working environment temperature T of the battery can be accurately calculated. s , avoiding the limitations of relying solely on surface temperature sensors, ensuring the reliability of data, and providing basic data for subsequent temperature calculations; using an impedance phase angle detection device for measurement, there is no need to physically modify the battery, avoiding damage to the battery structure and sealing, and saving costs; setting a dynamic temperature threshold set, real-time monitoring of the dynamic temperature Tmult, timely detecting temperature anomalies, and ensuring that timely measures can be taken in different situations.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented by the following technical solutions: A method for dynamic real-time online measurement of the internal temperature of a lithium-ion battery, comprising the following steps:

[0009] Step 1: Obtain the battery operating data of the current lithium-ion battery; calculate the actual working environment temperature T based on the battery operating datas ;

[0010] Step 2: At the actual working environment temperature T s Under the condition of , the relaxation time of the lithium-ion battery is obtained; during the relaxation time, the dynamic impedance phase angle θ of the lithium-ion battery is continuously measured by using the impedance phase angle detection device d ;

[0011] Step 3: Obtain the historical usage data of lithium-ion batteries, calculate the impact factor B based on the historical usage data, and calculate the battery aging coefficient A through the impact factor B and battery working data; calculate the battery aging coefficient A through the impact factor B, battery aging coefficient A and dynamic impedance phase angle θ d , calculate the static impedance phase angle θ of the lithium-ion battery s ;

[0012] Step 4: According to the obtained static impedance phase angle θ s The actual working environment temperature T s , calculate the static temperature Tstatic;

[0013] Step 5: Calculate the dynamic temperature Tmult of the lithium-ion battery based on the static temperature Tstatic and the battery operating data;

[0014] Step 6: Set a dynamic temperature threshold set, compare the dynamic temperature Tmult with the dynamic temperature threshold, and determine whether the lithium-ion battery is working within the optimal performance range. If it does not meet the set dynamic temperature threshold set, an abnormal warning is triggered.

[0015] In the preferred embodiment of the above-mentioned method for dynamically measuring the internal temperature of a lithium-ion battery in real time online, the method for obtaining the battery operating data of the current lithium-ion battery is:

[0016] Battery operating data includes battery charging current I c , battery discharge current I d and the battery surface temperature measurement value T b ; Use current sensor to obtain the charging current I of lithium-ion battery c and the discharge current I d , use the temperature sensor to obtain the lithium-ion battery surface temperature measurement value T b .

[0017] In the preferred embodiment of the above-mentioned method for dynamic real-time online measurement of the internal temperature of a lithium-ion battery: the actual working environment temperature T S The method to obtain is:

[0018] Calculate the actual working environment temperature T based on the battery working data S , the formula is as follows:

[0019]

[0020] Among them, R is the internal resistance of the battery, ranging from 0 to 1; M is the surface area of ​​the battery; h is the convection heat transfer coefficient;

[0021] In the preferred embodiment of the above-mentioned method for dynamic real-time online measurement of the internal temperature of a lithium-ion battery: the method for calculating the convection heat transfer coefficient h is:

[0022] The battery working data also includes the lithium-ion battery historical usage experience constant Y and the lithium-ion battery initial temperature Tc;

[0023] The convective heat transfer coefficient h is calculated based on the battery working data, and the formula is as follows:

[0024]

[0025] Among them, g is the acceleration of gravity; β is the volume expansion coefficient, which ranges from 0.1 to 1; q is the convective heat transfer.

[0026] In the preferred embodiment of the above-mentioned method for dynamic real-time online measurement of internal temperature of lithium-ion battery: the calculation method of the influence factor B is:

[0027] The historical usage data includes the number of charge and discharge times X, charge and discharge depth K, charge and discharge rate D and average operating temperature U. The impact factor B is calculated based on the historical usage data. The formula is as follows:

[0028]

[0029] In the preferred embodiment of the above-mentioned method for dynamic real-time online measurement of internal temperature of lithium-ion battery: the calculation method of battery aging coefficient A is as follows;

[0030] The battery working data also includes the current actual capacity Qc, the initial capacity Qn and the lithium-ion battery idle time TI;

[0031] The formula for calculating the battery capacity retention rate SH based on the current actual capacity Qct and initial capacity Qn is as follows:

[0032]

[0033] According to the lithium-ion battery capacity retention rate SH, battery idle time TI and influencing factor B, the battery aging coefficient A is calculated based on the following formula:

[0034]

[0035] In the preferred embodiment of the above-mentioned method for dynamic real-time online measurement of internal temperature of lithium-ion battery: calculating the static impedance phase angle θ of lithium-ion battery s, based on the following formula:

[0036] θ s =θ d ×A×B+C

[0037] Among them, C is a natural constant.

[0038] In the preferred embodiment of the above-mentioned method for dynamic real-time online measurement of internal temperature of lithium-ion battery: according to the static impedance phase angle θ s The actual working environment temperature T s , calculate the static temperature Tstatic, based on the following formula:

[0039]

[0040] Among them, T s With T s-1 Indicates two adjacent actual operating temperature values; θ s With θ s-1 Represents the phase angle of two adjacent static impedances.

[0041] In the preferred embodiment of the above-mentioned method for dynamic real-time online measurement of the internal temperature of a lithium-ion battery: the method for calculating the dynamic temperature Tmult of the lithium-ion battery is:

[0042] The battery working data also includes thermal characteristic parameters PM, charge-discharge state parameters Scharge-discharge and external environment parameters ET; according to the static temperature Tstatic and the battery working data, the dynamic temperature Tmult of the lithium-ion battery is calculated according to the following formula:

[0043]

[0044] Among them, α is the thermal diffusion coefficient inside the battery, and its value range is usually between 0.01 and 0.1; dT is the temperature change; dt is the time change; is the rate of temperature change.

[0045] On the other hand, the present invention also discloses a real-time online dynamic measurement system for the internal temperature of a lithium-ion battery, which is used to implement the above-mentioned intelligent management method, including:

[0046] The data acquisition module is used to obtain the current battery working data of the lithium-ion battery; calculate the actual working environment temperature T according to the battery working data s ;

[0047] Relaxation time and dynamic impedance measurement module, used to measure the actual working environment temperature T sUnder the condition of , the relaxation time of the lithium-ion battery is obtained; during the relaxation time, the dynamic impedance phase angle θ of the lithium-ion battery is continuously measured by using the impedance phase angle detection device d ;

[0048] The static impedance phase angle calculation module is used to obtain the historical usage data of lithium-ion batteries, calculate the impact factor B based on the historical usage data, and calculate the battery aging coefficient A through the impact factor B and battery working data; calculate the battery aging coefficient A through the impact factor B, battery aging coefficient A and dynamic impedance phase angle θ d , calculate the static impedance phase angle θ of the lithium-ion battery s ;

[0049] Static temperature acquisition module, used to obtain the static impedance phase angle θ s The actual working environment temperature T s , calculate the static temperature Tstatic;

[0050] A dynamic temperature calculation module is used to calculate the dynamic temperature Tmult of the lithium-ion battery according to the static temperature Tstatic and the battery working data;

[0051] The temperature abnormality warning module is used to set a dynamic temperature threshold set, compare the dynamic temperature Tmult with the dynamic temperature threshold, and determine whether the lithium-ion battery is working within the optimal performance range. If it does not meet the set dynamic temperature threshold set, an abnormality warning is triggered.

[0052] (III) Beneficial effects

[0053] The present invention provides a method and system for dynamic real-time online measurement of the internal temperature of a lithium-ion battery, which has the following beneficial effects:

[0054] (1) By obtaining the current working data of the lithium-ion battery, the current working status of the battery can be fully understood, so as to more accurately evaluate the impact of the external environment on the internal temperature of the battery and provide basic data for subsequent temperature calculations; combined with the battery working data, the actual working environment temperature of the battery can be accurately calculated, avoiding the limitations of relying solely on surface temperature sensors and ensuring the reliability of the data;

[0055] (2) By accurately obtaining the relaxation time, we can better understand the dynamic behavior of the battery and improve the accuracy of subsequent measurements; by continuously measuring the dynamic impedance phase angle during the relaxation time, we can capture the impedance changes of the battery under different states and provide key parameters for subsequent temperature calculations; by using the impedance phase angle detection device for measurement, there is no need to physically modify the battery, thus avoiding damage to the battery structure and improving the safety and reliability of the measurement;

[0056] (3) By obtaining the historical usage data of the battery, we can fully understand the battery usage and provide rich data support for subsequent calculations. By calculating the impact factor B based on the historical usage data, we can quantify the influencing factors during battery use and improve the accuracy of the calculation. By calculating the battery aging coefficient A based on the impact factor B and the battery working data, we can evaluate the aging degree of the battery and provide important parameters for subsequent temperature calculations. Combined with the static impedance phase angle θ s and the actual working environment temperature T s , improving the accuracy of temperature calculation;

[0057] (4) The dynamic temperature Tmult is calculated by combining the static temperature Tstatic and the battery working data, and the influence of factors such as battery charging and discharging rate, ambient temperature, and battery aging on the dynamic temperature Tmult is comprehensively considered to improve the comprehensiveness and accuracy of temperature calculation; a dynamic temperature threshold set is set to monitor the dynamic temperature Tmult in real time, and temperature anomalies are discovered in time to ensure that timely measures can be taken in different situations to improve the safety and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 The present invention is a schematic diagram of the working steps of a method for dynamic real-time online measurement of the internal temperature of a lithium-ion battery. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] See also Figure 1 The present invention provides a method for dynamic real-time online measurement of the internal temperature of a lithium-ion battery, comprising the following steps:

[0061] Step 1: Obtain the battery operating data of the current lithium-ion battery; calculate the actual working environment temperature T based on the battery operating data s ;

[0062] Step 1 includes the following:

[0063] Step 101: Install a sensor for detecting current lithium-ion battery operating data. When installing the sensor, it is necessary to confirm that its accuracy, range, and interface type are compatible with the vehicle system to obtain the battery operating data of the lithium-ion battery in real time;

[0064] Step 102: Actual working environment temperature T S The method to obtain is:

[0065] Battery operating data includes charging current I c , discharge current I d and the battery surface temperature T b ; Use current sensor to obtain the charging current I of lithium-ion battery c and the discharge current I d , use the temperature sensor to obtain the lithium-ion battery surface temperature measurement value T b ;

[0066] Calculate the actual working environment temperature T based on the battery working data S , the formula is as follows:

[0067]

[0068] Among them, R is the internal resistance of the battery, ranging from 0 to 1; M is the surface area of ​​the battery; h is the convection heat transfer coefficient.

[0069] It should be noted that this formula is calculated by adding the heat generated during charging and discharging in the battery working data to the proportion of the actual battery heat exchange area, and finally adding the battery surface temperature T b , get the actual working environment temperature T S ; The larger the battery internal resistance R, the higher the actual working environment temperature T S The bigger it is.

[0070] Step 103: The method for calculating the convective heat transfer coefficient h is:

[0071] The battery working data also includes the lithium-ion battery historical usage experience constant Y and the lithium-ion battery initial temperature Tc;

[0072] The convective heat transfer coefficient h is calculated based on the battery working data, and the formula is as follows:

[0073]

[0074] Among them, g is the acceleration of gravity; β is the volume expansion coefficient, which ranges from 0.1 to 1; q is the convective heat transfer.

[0075] It should be noted that this formula uses the measured value of the lithium-ion battery surface temperature T bThe difference between the initial temperature Tc of the lithium-ion battery and the ratio of the gravitational acceleration g and the volume expansion coefficient β to the convective heat transfer q is multiplied by the historical experience constant Y of the lithium-ion battery to obtain the convective heat transfer coefficient h; wherein, the initial temperature Tc of the lithium-ion battery is obtained by a sensor; the volume expansion coefficient β is an average value obtained by multiple experimental data and consulting existing databases and literature, and the value range is between 0.1 and 1; the convective heat transfer coefficient h represents the efficiency coefficient of heat transfer from one place to another through the flow of fluid. The higher the convective heat transfer coefficient, the stronger the convective heat transfer; the convective heat transfer q is measured by measuring the heat generated by the battery when it is working and transferred to the fluid through convective heat transfer. The calorimeter can measure the heat absorbed by the fluid, thereby obtaining the convective heat transfer q between the battery and the fluid. The convective heat transfer q represents the total amount of heat transferred by convection per unit time; the historical experience constant Y of the lithium-ion battery is gradually optimized and determined by collecting and analyzing the historical use data of the battery, combining statistical methods and machine learning technology, and is an important parameter for evaluating battery aging and performance changes;

[0076] When using, combine the contents of step 101 to step 103:

[0077] By acquiring data such as the battery's charging current, discharging current, and surface temperature, we can fully understand the battery's current working status, thereby more accurately evaluating the impact of the external environment on the battery's internal temperature and providing basic data for subsequent temperature calculations. Combined with the battery's working data, the actual working environment temperature of the battery can be accurately calculated, avoiding the limitations of relying solely on surface temperature sensors and ensuring data reliability.

[0078] Step 2: At the actual working environment temperature T s Under the condition of , the relaxation time of the lithium-ion battery is obtained; during the relaxation time, the dynamic impedance phase angle θ of the lithium-ion battery is continuously measured by using the impedance phase angle detection device d ;

[0079] Step 2 includes the following:

[0080] Step 201: The method for obtaining the relaxation time is:

[0081] Under the actual working environment temperature, humidity and air pressure, a pulse current is applied to the battery for charging and discharging to obtain a voltage relaxation curve; a voltage change rate threshold is preset, and after each charging and discharging, when the voltage change rate is equal to the voltage change rate threshold, the time value of the corresponding voltage relaxation curve is obtained, and the obtained time value is determined as the relaxation time of this charging and discharging.

[0082] It should be noted that the method for obtaining the voltage change rate threshold is: consult academic literature and industry standards in the field of lithium-ion batteries, and select an appropriate voltage change rate threshold. Generally, this threshold should be small enough to ensure that the voltage has basically returned to a stable state.

[0083] Step 202: Continuously measure the dynamic impedance phase angle θ of the lithium-ion battery d , and obtain the dynamic impedance phase angle θ d ;

[0084] It should be noted that a time window is determined based on the relaxation time τ provided by the automotive electronic control system. This time window should cover the stable stage after the relaxation time τ ends to ensure that the dynamic impedance phase angle θ of the battery in a stable state is measured. d The impedance phase angle detection device applies a small AC signal, usually a sine wave, to the battery; measures the battery's response to the signal, which contains the battery's impedance and phase angle information, and calculates the dynamic impedance phase angle θ through a built-in algorithm. d .

[0085] When used, combine the contents of step 201 to step 202:

[0086] During use, ensure the synchronization of communication between the vehicle electronic control system, the impedance phase angle detection device and the battery management system. By accurately obtaining the relaxation time, the dynamic behavior of the battery can be better understood and the accuracy of subsequent measurements can be improved. Continuously measuring the dynamic impedance phase angle during the relaxation time can capture the impedance changes of the battery in different states and provide key parameters for subsequent temperature calculations. Measurements using the impedance phase angle detection device do not require physical modifications to the battery, thus avoiding damage to the battery structure and improving the safety and reliability of the measurement. During the entire measurement process, strictly abide by the electrical safety operating procedures to ensure the safety of personnel and equipment. Consider the impact of environmental factors such as temperature and humidity on the measurement results, and take appropriate measures to compensate or correct them.

[0087] Step 3: Obtain the historical usage data of lithium-ion batteries, calculate the impact factor B based on the historical usage data, and calculate the battery aging coefficient A through the impact factor B and battery working data; calculate the battery aging coefficient A through the impact factor B, battery aging coefficient A and dynamic impedance phase angle θ d , calculate the static impedance phase angle θ of the lithium-ion battery s ;

[0088] Step three includes the following:

[0089] Step 301: The calculation method of the impact factor B is:

[0090] The historical usage data includes the number of charge and discharge times X, charge and discharge depth K, charge and discharge rate D and average operating temperature U. The impact factor B is calculated based on the historical usage data. The formula is as follows:

[0091]

[0092] It should be noted that the principle of this formula is: calculate the proportion of the number of charge and discharge times X, charge and discharge depth K, charge and discharge rate D and average operating temperature U in the entire historical usage data respectively, and then add the obtained data to obtain the influencing factor B; adding 1 is to prevent the denominator from being zero, which is a common processing method in mathematics, especially when dealing with a divisor that may be zero; the number of charge and discharge times X, charge and discharge depth O, charge and discharge rate D and average operating temperature U of the lithium-ion battery are obtained through real-time monitoring and recording by the battery management system.

[0093] Step 302: The calculation method of the battery aging coefficient A is as follows;

[0094] The battery working data also includes the current actual capacity Qc, the initial capacity Qn and the lithium-ion battery idle time TI;

[0095] The formula for calculating the battery capacity retention rate SH based on the current actual capacity Qc and initial capacity Qn is as follows:

[0096]

[0097] It should be noted that the principle of this formula is: by calculating the ratio of the current actual capacity Qc of the battery to the initial capacity Qn of the battery, and then multiplying the ratio by 100%, converting it into a percentage form, and then obtaining the battery capacity retention rate SH; the battery capacity retention rate SH is obtained by regularly performing capacity tests in multiple charge and discharge cycles, recording each test result, and calculating the ratio of the current capacity to the initial capacity. The battery capacity retention rate SH is an important indicator to measure the degree of battery aging.

[0098] According to the lithium-ion battery capacity retention rate SH, battery idle time TI and influencing factor B, the battery aging coefficient A is calculated based on the following formula:

[0099]

[0100] It should be noted that the principle of this formula is: calculate the ratio of the battery idle time TI to the influencing factor B. This ratio reflects the relative importance of idle aging in the entire battery aging process. If the ratio is large, it means that idle aging may be the main factor causing battery performance degradation. This ratio can highlight the importance of idle time to the battery aging coefficient A, and then multiply it by the battery capacity retention rate SH to get a value. Multiply this value by 100% to get the battery aging coefficient A. The larger the value of A, the worse the battery performance.

[0101] Step 303: Calculate the static impedance phase angle θ of the lithium-ion battery s , based on the following formula:

[0102] θ s =θ d ×A×B+C

[0103] Among them, C is a natural constant.

[0104] It should be noted that the principle of this formula is: through the dynamic impedance phase angle θ d The data value obtained by multiplying the battery aging coefficient A and the influence factor B plus a natural number C is obtained to obtain the static impedance phase angle θ s , usually C takes a positive integer, in order to better analyze the static impedance phase angle θ s ; Through this formula, the dynamic impedance phase angle θ d The phase angle θ of the static impedance s The static impedance phase angle θ can be calculated from the dynamic state information of the battery. The introduction of the battery aging coefficient A and the influencing factor B makes it possible to calculate the static impedance phase angle θ s In the process of aging, the static performance of the battery under different aging degrees and external conditions can be comprehensively evaluated. The natural number C plays the role of an offset in the formula. This offset will be directly added to the calculation result, so that the static impedance phase angle is adjusted based on the dynamic parameter calculation, so that the static impedance phase angle θ s More practical significance.

[0105] When used, combine the contents of step 301 to step 303:

[0106] By obtaining the historical usage data of the battery, we can fully understand the usage of the battery, including the number of charge and discharge times, charge and discharge depth, and usage time, etc., providing rich data support for subsequent calculations; by calculating the influencing factor B based on the historical usage data, we can quantify the influencing factors during the battery use process and improve the accuracy of the calculation; by calculating the battery aging coefficient A through the influencing factor B and the battery working data, we can evaluate the aging degree of the battery and provide important parameters for subsequent temperature calculations; by analyzing the static impedance phase angle θs , can evaluate the battery's health status, performance changes and fault conditions, and provide important reference data for battery management and research.

[0107] Step 4: According to the obtained static impedance phase angle θ s The actual working environment temperature T s , calculate the static temperature Tstatic;

[0108] The formula used is as follows:

[0109]

[0110] Among them, T s With T s-1 Indicates two adjacent actual operating temperature values; θ s With θ s-1 Represents the phase angle of two adjacent static impedances.

[0111] It should be noted that the principle of this formula is: compare the difference between two adjacent actual operating temperatures with two adjacent static impedance phase angles, add the obtained ratio to the numerical actual operating temperature value, and finally get the static temperature value Tstatic. When it increases, it means that the temperature difference T s -T s-1 Phase angle difference θ relative to static impedance s -θ s-1 The change is more significant. In physical terms, it will increase the static temperature value Tstatic, and the increase depends on the original temperature value T s and the degree of increase in the ratio; the static temperature value Tstatic can be used to calibrate the battery thermal management system and evaluate the temperature control effect of the battery under different working conditions.

[0112] Combined with the content of step 4: through the static impedance phase angle θ s The actual working environment temperature T s , calculates the static temperature Tstatic, improves the accuracy of temperature calculation, and can more reliably evaluate the health status of the battery.

[0113] Step 5: Calculate the dynamic temperature Tmult of the lithium-ion battery based on the static temperature Tstatic and the battery operating data;

[0114] Step five includes the following:

[0115] Step 501: The battery operating data also includes thermal characteristic parameters PM, charge-discharge state parameters Scharge-discharge and external environment parameters ET;

[0116] It should be noted that the thermal characteristic parameter PM describes the physical properties of lithium-ion batteries during the heat transfer process, and the thermal characteristic parameter PM is obtained by referring to the material manual; the charge and discharge state parameter Scharge-discharge is specifically a voltage parameter, and the voltage data is collected by the sensor, and the parameter average is taken to obtain the charge and discharge state parameter Scharge-discharge; the external environment parameter ET is specifically a humidity parameter, and the data under different humidity conditions is measured by the sensor, and the external environment parameter ET is obtained by taking the average value.

[0117] Step 502: Calculate the dynamic temperature Tmult of the lithium-ion battery according to the following formula:

[0118]

[0119] Among them, α is the thermal diffusion coefficient inside the battery, and its value range is usually between 0.01 and 0.1; dT is the temperature change; dt is the time change; is the rate of temperature change.

[0120] It should be noted that the principle of this formula is: temperature change rate The thermal conductivity value is obtained by multiplying the thermal diffusion effect coefficient α inside the battery. The thermal characteristic parameter PM is multiplied by the charge and discharge state parameters and the external environment parameters to obtain the battery working data value. The change of the battery working data value comprehensively reflects the influence of various factors on the dynamic temperature Tmult during the actual working process of the battery, and is an important factor in the change of the dynamic temperature Tmult. The thermal conductivity value plus the working data value plus the static temperature Tstatic obtains the dynamic temperature Tmult. The static temperature Tstatic is the basic component of the dynamic temperature Tmult. The thermal conductivity value reflects the ability of the battery material itself to conduct heat. Among them, the thermal diffusion effect coefficient α inside the battery is obtained through multiple experimental data and consulting existing databases and literature, and the value range is usually between 0.01 and 0.1; the temperature change rate It reflects how fast the temperature inside the battery changes over time. The sensor collects data and records the readings at certain time intervals. The initial temperature is set to T1, and the temperature after a time interval of Δt is set to T2. The temperature change dT is then obtained. The temperature change rate is obtained by obtaining the ratio of the temperature change dT to the time change dt.

[0121] When used, combine the contents of step 501 to step 502:

[0122] During the calculation process, the accuracy and reliability of all input data are ensured. The calculation formula of dynamic temperature contains multiple parameters, and these parameters interact with each other, which can accurately predict the temperature changes of the battery under different working conditions, improve the comprehensiveness and accuracy of temperature calculation, thereby optimizing the thermal management of the battery and extending the battery life.

[0123] Step 6: Set a dynamic temperature threshold set, compare the dynamic temperature Tmult with the dynamic temperature threshold, and determine whether the lithium-ion battery is working within the optimal performance range. If it does not meet the set dynamic temperature threshold set, an abnormal warning is triggered;

[0124] Step six includes the following:

[0125] Step 601: Determine a dynamic temperature threshold set:

[0126] By referring to the safe temperature range provided by the battery manufacturer, a dynamic temperature threshold set for the lithium-ion battery is set. The lower temperature threshold Tlower is set to 0°C to prevent the battery from being overcooled; the upper temperature threshold Tupper is set to 45°C to ensure that the battery operates within the optimal performance range.

[0127] Step 602: The method for determining whether an abnormal warning is triggered is:

[0128] The current dynamic temperature Tmult is obtained through the previous calculation steps. Upper limit comparison: when the dynamic temperature Tmult> the upper limit temperature threshold Tupper, the alarm signal is immediately triggered; lower limit comparison: when the dynamic temperature Tmult< the lower limit temperature threshold Tlower, the alarm signal is immediately triggered.

[0129] When used, combine the contents of step 601 to step 602:

[0130] Set a set of dynamic temperature thresholds, establish an intelligent early warning system, monitor the dynamic temperature Tmult in real time, detect temperature anomalies in time, ensure that timely measures can be taken in different situations, and improve the safety and reliability of the system; provide remote monitoring and management functions through the user interface and remote monitoring system, so that users can understand the battery status in time.

[0131] On the other hand, the present invention also discloses a real-time online dynamic measurement system for the internal temperature of a lithium-ion battery, which is used to implement the above-mentioned intelligent management method, comprising:

[0132] The data acquisition module is used to obtain the current battery working data of the lithium-ion battery; calculate the actual working environment temperature T according to the battery working data s ;

[0133] Relaxation time and dynamic impedance measurement module, used to measure the actual working environment temperature T sUnder the condition of , the relaxation time of the lithium-ion battery is obtained; during the relaxation time, the dynamic impedance phase angle θ of the lithium-ion battery is continuously measured by using the impedance phase angle detection device d ;

[0134] The static impedance phase angle calculation module is used to obtain the historical usage data of lithium-ion batteries, calculate the impact factor B based on the historical usage data, and calculate the battery aging coefficient A through the impact factor B and battery working data; calculate the battery aging coefficient A through the impact factor B, battery aging coefficient A and dynamic impedance phase angle θ d , calculate the static impedance phase angle θ of the lithium-ion battery s ;

[0135] Static temperature acquisition module, used to obtain the static impedance phase angle θ s The actual working environment temperature T s , calculate the static temperature Tstatic;

[0136] A dynamic temperature calculation module is used to calculate the dynamic temperature Tmult of the lithium-ion battery according to the static temperature Tstatic and the battery working data;

[0137] The temperature abnormality warning module is used to set a dynamic temperature threshold set, compare the dynamic temperature Tmult with the dynamic temperature threshold, and determine whether the lithium-ion battery is working within the optimal performance range. If it does not meet the set dynamic temperature threshold set, an abnormality warning is triggered.

[0138] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware or in combination with computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0139] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0140] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for dynamic real-time online measurement of internal temperature of a lithium-ion battery, characterized in that: The following steps are involved: Step 1: Obtain the battery operating data of the current lithium-ion battery; calculate the actual working environment temperature T based on the battery operating data s ; Step 2: At the actual working environment temperature T s Under the condition of , the relaxation time of the lithium-ion battery is obtained; during the relaxation time, the dynamic impedance phase angle θ of the lithium-ion battery is continuously measured by using the impedance phase angle detection device d ; Step 3: Obtain the historical usage data of lithium-ion batteries, calculate the impact factor B based on the historical usage data, and calculate the battery aging coefficient A through the impact factor B and battery working data; calculate the battery aging coefficient A through the impact factor B, battery aging coefficient A and dynamic impedance phase angle θ d , calculate the static impedance phase angle θ of the lithium-ion battery s ; Step 4: According to the obtained static impedance phase angle θ s The actual working environment temperature T s , calculate the static temperature Tstatic; Step 5: Calculate the dynamic temperature Tmult of the lithium-ion battery based on the static temperature Tstatic and the battery operating data; Step 6: Set a dynamic temperature threshold set, compare the dynamic temperature Tmult with the dynamic temperature threshold, and determine whether the lithium-ion battery is working within the optimal performance range. If it does not meet the set dynamic temperature threshold set, an abnormal warning is triggered.

2. The method for dynamic real-time online measurement of internal temperature of a lithium-ion battery according to claim 1, characterized in that: The method to obtain the current battery working data of the lithium-ion battery is: Battery operating data includes battery charging current I c , battery discharge current I d and the battery surface temperature measurement value T b ; Use current sensor to obtain the charging current I of lithium-ion battery c and the discharge current I d , use the temperature sensor to obtain the lithium-ion battery surface temperature measurement value T b .

3. A method for dynamic real-time online measurement of internal temperature of a lithium-ion battery according to claim 2, characterized in that: Actual working environment temperature T S The method to obtain is: Calculate the actual working environment temperature T based on the battery working data S , the formula is as follows: Among them, R is the internal resistance of the battery, ranging from 0 to 1; M is the surface area of ​​the battery; h is the convection heat transfer coefficient.

4. A method for dynamic real-time online measurement of internal temperature of a lithium-ion battery according to claim 3, characterized in that: The method for calculating the convective heat transfer coefficient h is: The battery working data also includes the lithium-ion battery historical usage experience constant Y and the lithium-ion battery initial temperature Tc; The convective heat transfer coefficient h is calculated based on the battery working data, and the formula is as follows: Among them, g is the acceleration of gravity; β is the volume expansion coefficient, which ranges from 0.1 to 1; q is the convective heat transfer.

5. A method for dynamic real-time online measurement of internal temperature of a lithium-ion battery according to claim 4, characterized in that: The calculation method for calculating the impact factor B is: The historical usage data includes the number of charge and discharge times X, charge and discharge depth K, charge and discharge rate D and average operating temperature U. The impact factor B is calculated based on the historical usage data. The formula is as follows:

6. A method for dynamic real-time online measurement of internal temperature of a lithium-ion battery according to claim 5, characterized in that: The calculation method of battery aging coefficient A is: The battery working data also includes the current actual capacity Qc, the initial capacity Qn and the lithium-ion battery idle time TI; The battery capacity retention rate SH is calculated based on the current actual capacity Qc and initial capacity Qn, and the formula is as follows: According to the lithium-ion battery capacity retention rate SH, battery idle time TI and influencing factor B, the battery aging coefficient A is calculated based on the following formula:

7. A method for dynamic real-time online measurement of internal temperature of a lithium-ion battery according to claim 6, characterized in that: Calculate the static impedance phase angle θ of a lithium-ion battery s , based on the following formula: i s =θ d ×A×B+C Among them, C is a natural constant.

8. A method for dynamic real-time online measurement of internal temperature of a lithium-ion battery according to claim 7, characterized in that: According to the static impedance phase angle θ s The actual working environment temperature T s , calculate the static temperature Tstatic, based on the following formula: Among them, T s With T s-1 Indicates two adjacent actual operating temperature values; θ s With θ s-1 Represents the phase angle of two adjacent static impedances.

9. A method for dynamic real-time online measurement of internal temperature of a lithium-ion battery according to claim 8, characterized in that: The method for calculating the dynamic temperature Tmult of a lithium-ion battery is: The battery working data also includes thermal characteristic parameters PM, charge-discharge state parameters Scharge-discharge and external environment parameters ET; According to the static temperature Tstatic and the battery working data, the dynamic temperature Tmult of the lithium-ion battery is calculated according to the following formula: Among them, α is the thermal diffusion coefficient inside the battery, and its value range is usually between 0.01 and 0.1; dT is the temperature change; dt is the time change; is the rate of temperature change.

10. A dynamic real-time online measurement system for the internal temperature of a lithium-ion battery, used to implement the intelligent management method of any one of claims 1 to 9, characterized in that: include: A data acquisition module is used to obtain the battery working data of the current lithium-ion battery; Calculate the actual working environment temperature T based on the battery working data s ; Relaxation time and dynamic impedance measurement module, used to measure the actual working environment temperature T s Under the conditions of , obtain the relaxation time of lithium-ion batteries; During the relaxation time, the dynamic impedance phase angle θ of the lithium-ion battery is continuously measured using the impedance phase angle detection device. d ; The static impedance phase angle calculation module is used to obtain the historical usage data of lithium-ion batteries, calculate the impact factor B based on the historical usage data, and calculate the battery aging coefficient A through the impact factor B and battery working data; calculate the battery aging coefficient A through the impact factor B, battery aging coefficient A and dynamic impedance phase angle θ d , calculate the static impedance phase angle θ of the lithium-ion battery s ; Static temperature acquisition module, used to obtain the static impedance phase angle θ s The actual working environment temperature T s , calculate the static temperature Tstatic; A dynamic temperature calculation module is used to calculate the dynamic temperature Tmult of the lithium-ion battery according to the static temperature Tstatic and the battery working data; The temperature abnormality warning module is used to set a dynamic temperature threshold set, compare the dynamic temperature Tmult with the dynamic temperature threshold, and determine whether the lithium-ion battery is working within the optimal performance range. If it does not meet the set dynamic temperature threshold set, an abnormality warning is triggered.

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