Method and device for reducing service power of lithium ion battery and battery pack

Abstract

According to the method and device for reducing the service power of the lithium ion battery and the battery pack, the to-be-detected battery does not need to be disassembled, the current thermal stability boundary is determined through the current thermal stability characteristic parameters of the to-be-detected lithium ion battery, and the target charging function and the maximum discharging rate are determined based on the current thermal stability boundary. The to-be-detected lithium ion battery is charged based on the target charging function and the current charging voltage, so that the risk of thermal runaway of the battery in the charging process is reduced; the to-be-detected lithium ion battery is discharged based on the target discharge rate not greater than the maximum discharge rate, the risk of thermal runaway of the battery in the discharge process is reduced, and the target charge function and the maximum discharge rate are updated through the thermal stability boundary, so that the purposes of dynamically and reasonably reducing the service power and improving the reliability of the battery are achieved. And the safety of the lithium ion battery is ensured.

Description

Technical Field

[0001] This application relates to the field of battery management technology, and in particular to a method, apparatus and battery pack for reducing the power consumption of lithium-ion batteries. Background Technology

[0002] Lithium-ion batteries are widely used as the primary energy source for many electrical devices, including electric vehicles, electric two-wheelers, unmanned aerial vehicles, and energy storage devices. However, during use, lithium-ion batteries often age due to factors such as damage to the positive and negative electrode structures and electrolyte decomposition, leading to lithium plating and internal short circuits, which further reduces the usable power of the lithium-ion battery. Thermal stability, as a battery characteristic related to thermal runaway failure, can also cause thermal runaway failures if batteries are used beyond their thermal stability limits.

[0003] To avoid the risk of thermal runaway in lithium-ion batteries, existing technologies reduce the power consumption of lithium-ion batteries. The common method is to stop charging and discharging the battery altogether, which can easily lead to over-protection.

[0004] Therefore, how to monitor the battery in real time, determine the thermal stability boundary, and dynamically adjust the battery's operating power has become an urgent problem to be solved. Summary of the Invention

[0005] The purpose of this application is to provide a method, apparatus, and battery pack for reducing the power consumption of lithium-ion batteries. The specific technical solution is as follows:

[0006] A first aspect of this application provides a method for reducing the power consumption of a lithium-ion battery, the method comprising:

[0007] The current thermal stability characteristic parameters of the lithium-ion battery to be tested are obtained. Based on the first relationship, the current thermal stability boundary corresponding to the current thermal stability characteristic parameters is determined. The first relationship is used to characterize the mapping relationship between the thermal stability characteristic parameters and the thermal stability boundary of the lithium-ion battery.

[0008] In the charging scenario: a target charging function is determined based on the current thermal stability boundary and the current charging voltage, wherein, when charging based on the current charging voltage and the target charging function, the maximum predicted charging temperature of the lithium-ion battery under test is not higher than the current thermal stability boundary; the lithium-ion battery under test is charged based on the target charging function and the current charging voltage. In the discharging scenario: a maximum discharge rate is determined based on the current thermal stability boundary, wherein, when discharging based on the current maximum discharge rate, the maximum predicted discharge temperature of the lithium-ion battery under test is not higher than the current thermal stability boundary; the lithium-ion battery under test is discharged based on the target discharge rate; the target discharge rate is not greater than the maximum discharge rate.

[0009] Charging the lithium-ion battery under test based on the target charging function and the current charging voltage reduces the risk of thermal runaway during charging. Discharging the lithium-ion battery under test based on a target discharge rate not exceeding the maximum discharge rate reduces the risk of thermal runaway during discharge. By updating the target charging function and maximum discharge rate through thermal stability boundaries, the power consumption can be dynamically and reasonably reduced to ensure the safety of lithium-ion batteries.

[0010] In one or more embodiments of this application, the maximum predicted charging temperature of the lithium-ion battery under test is determined when it is charged based on the current voltage and a first charging function. If the maximum predicted charging temperature is greater than the current thermal stability boundary, the first charging function is multiplied by a preset first coefficient to obtain an updated first charging function, and the process returns to the step of determining the maximum predicted charging temperature of the lithium-ion battery under test when it is charged based on the current voltage and the first charging function, and continues to execute. If the maximum predicted charging temperature is not higher than the current thermal stability boundary, the first charging function is used as the target charging function.

[0011] In one or more embodiments of this application, the temperature characteristic parameters of the lithium-ion battery under test are obtained when it is charged based on the current voltage and the first charging function, and a first temperature characteristic parameter is obtained. The first temperature characteristic parameter is input into a preset temperature rise prediction model for processing to obtain the law of temperature change of the lithium-ion battery over time during the charging process when the lithium-ion battery is charged based on the current voltage and the first charging function, and a first law is obtained. Based on the first law, the maximum predicted charging temperature of the lithium-ion battery under test when it is charged based on the current voltage and the first charging function is determined.

[0012] In one or more embodiments of this application, the maximum predicted discharge temperature of the lithium-ion battery under test is determined when it discharges based on the current maximum discharge rate. If the maximum predicted discharge temperature is greater than the current thermal stability boundary, the current maximum discharge rate is multiplied by a preset second coefficient to obtain an updated maximum discharge rate, and the process returns to the step of determining the maximum predicted discharge temperature of the lithium-ion battery under test when it discharges based on the current maximum discharge rate, and continues to execute. If the maximum predicted discharge temperature is not higher than the current thermal stability boundary, the current maximum discharge rate is used as the maximum discharge rate.

[0013] In one or more embodiments of this application, the temperature characteristic parameters of the lithium-ion battery under test are obtained when it is discharged based on the current maximum discharge rate, and a second temperature characteristic parameter is obtained. The second temperature characteristic parameter is input into a preset temperature rise prediction model for processing to obtain the law of temperature change of the lithium-ion battery over time during the discharge process based on the current maximum discharge rate, and a second law is obtained. Based on the second law, the maximum discharge prediction temperature of the lithium-ion battery under test is determined when it is discharged based on the current maximum discharge rate.

[0014] In one or more embodiments of this application, the maximum amplification factor is used as the target discharge factor.

[0015] In one or more embodiments of this application, before determining the current thermal stability boundary corresponding to the current thermal stability characteristic parameter based on a preset first relationship, multiple sample lithium-ion batteries are monitored to obtain the thermal stability characteristic parameters of the sample lithium-ion batteries. A hot box test is performed on each sample lithium-ion battery. For each sample lithium-ion battery, when a thermal runaway fault is detected, the temperature at this time is recorded and used as the thermal stability boundary of the sample lithium-ion battery. Based on the thermal stability characteristic parameters and thermal stability boundaries of each sample lithium-ion battery, the first relationship is determined.

[0016] A second aspect of this application provides an apparatus for reducing the power consumption of a lithium-ion battery, the apparatus being used in any of the methods for reducing the power consumption of a lithium-ion battery as described in the first aspect above.

[0017] A third aspect of this application provides a battery pack, including a determination device for reducing the power consumption of a lithium-ion battery as described above.

[0018] This application also provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0019] Memory, used to store computer programs;

[0020] A processor, when executing a program stored in a memory, implements the method steps for using power in any of the above-described lithium-ion batteries.

[0021] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for using power in any of the above-described lithium-ion batteries.

[0022] This application also provides a computer program product containing instructions that, when run on a computer, cause the computer to perform any of the above-described methods for using power in a lithium-ion battery.

[0023] Beneficial effects of the embodiments in this application:

[0024] The method, apparatus, and battery pack for reducing the power consumption of lithium-ion batteries provided in this application do not require disassembling the battery under test. They determine the current thermal stability boundary using the current thermal stability characteristic parameters of the lithium-ion battery under test, and then determine the target charging function and maximum discharge rate based on this boundary. Because the maximum predicted charging temperature of the lithium-ion battery under test is not higher than the current thermal stability boundary under the current charging voltage and charging function, charging the lithium-ion battery under test based on the target charging function and current charging voltage reduces the risk of thermal runaway during charging. Similarly, discharging the lithium-ion battery under test based on a target discharge rate not exceeding the maximum discharge rate reduces the risk of thermal runaway during discharge. By updating the target charging function and maximum discharge rate through the thermal stability boundary, the application achieves a dynamic and reasonable reduction in power consumption, ensuring the safety of the lithium-ion battery.

[0025] Of course, implementing any product or method of this application does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other embodiments can be obtained based on these drawings.

[0027] Figure 1 A schematic flowchart of a first method for reducing the power consumption of a lithium-ion battery according to some embodiments of this application;

[0028] Figure 2 A second flowchart illustrating a method for reducing the power consumption of a lithium-ion battery according to some embodiments of this application;

[0029] Figure 3 A schematic diagram of a third method for reducing the power consumption of a lithium-ion battery according to some embodiments of this application;

[0030] Figure 4 A schematic diagram of a device for reducing the power consumption of a lithium-ion battery according to some embodiments of this application;

[0031] Figure 5This is a schematic diagram of the structure of an electronic device provided in some embodiments of this application. Detailed Implementation

[0032] The technical solutions of this application will now be described clearly and in detail with reference to the accompanying drawings. Obviously, the embodiments described herein are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0033] In order to dynamically adjust the power consumption of the battery, this application provides a method, apparatus and battery pack for reducing the power consumption of a lithium-ion battery.

[0034] First, we will introduce methods for reducing the power consumption of lithium-ion batteries. These methods can be applied to electronic devices that provide services to reduce the power consumption of lithium-ion batteries, such as smart charging devices, computers, and servers, including both local and cloud servers.

[0035] To facilitate subsequent explanations, let's first introduce the terminology used in this application:

[0036] Lithium-ion batteries can be classified into several types based on their cathode materials, such as lithium cobalt oxide batteries, lithium manganese oxide batteries, lithium nickel oxide batteries, ternary lithium batteries, lithium iron phosphate batteries, lithium manganese iron phosphate batteries, or batteries that combine different types of materials (ternary hybrid lithium iron phosphate batteries, ternary hybrid lithium manganese iron phosphate batteries, etc.). Lithium-ion batteries can also be classified according to their shape or structure, such as cuboid (square-shell cells), prismatic, cylindrical (cylindrical cells), and pouch (soft-pack cells).

[0037] On the one hand, in the control strategies and methods of battery management systems or charging equipment, the core of the charging function is to execute charging operations according to a preset standard procedure based on the battery status of the device, such as current charge level, temperature, and voltage. This includes starting charging, stopping charging, switching charging modes, and handling abnormal situations (such as overcharge and over-temperature protection). For example, a charging function that adjusts charging parameters according to the battery's Standard Operating Procedure (SOP) is called an SOP charging function, thereby achieving a safe and efficient charging process. In other words, an SOP charging function generally refers to a function that implements device charging control according to a standardized procedure. The SOP charging function is used to standardize the logic in the charging process, ensuring safe and efficient charging. Charging parameters can be dynamically adjusted based on the SOP charging function. On the other hand, discharge parameters are adjusted according to the battery's power capability and maximum discharge rate to achieve a safe and efficient discharge process.

[0038] like Figure 1 As shown, Figure 1 A schematic flowchart illustrating the method for reducing the power consumption of a lithium-ion battery provided in this application. The method includes:

[0039] S110, Obtain the current thermal stability characteristic parameters of the lithium-ion battery to be tested;

[0040] S120, Based on the first relationship, determine the current thermal stability boundary corresponding to the current thermal stability characteristic parameter. The first relationship is used to characterize the mapping relationship between the thermal stability characteristic parameter and the thermal stability boundary of the lithium-ion battery.

[0041] S131, in the charging scenario: determine the target charging function based on the current thermal stability boundary and the current charging voltage, wherein, under the current charging voltage and the target charging function, the maximum predicted charging temperature of the lithium-ion battery to be tested is not higher than the current thermal stability boundary, and charge the lithium-ion battery to be tested based on the target charging function and the current charging voltage.

[0042] S132, In the discharge scenario: Determine the maximum discharge rate based on the current thermal stability boundary, wherein when discharging based on the current maximum discharge rate, the maximum predicted discharge temperature of the lithium-ion battery under test is not higher than the current thermal stability boundary, and discharge the lithium-ion battery under test based on the target discharge rate, wherein the target discharge rate is not greater than the maximum discharge rate.

[0043] The lithium-ion battery to be tested is installed in the product under test, which includes, but is not limited to, electric vehicles, unmanned aerial vehicles, home energy storage devices, industrial and commercial energy storage devices, uninterruptible power supplies, mobile energy storage devices, and other devices that use lithium-ion batteries.

[0044] Thermal stability characteristics include, but are not limited to, voltage, current, temperature, DC impedance, AC impedance, anode potential, cathode potential, dead lithium deposition, ultrasonic signals, and mechanical signals of lithium-ion batteries. These thermal stability characteristics can be obtained through measurement without disassembling the battery under test.

[0045] The first relationship is configured as a mapping between the thermal stability characteristic parameters of lithium-ion batteries and their thermal stability boundaries. Methods for determining the thermal stability boundaries of batteries include, but are not limited to, testing and calculation methods such as thermal chamber experiments and simulations.

[0046] In one example, the thermal stability boundary of the battery is determined based on a hot-box experiment. To more clearly describe the solution of this application, the following details how the thermal stability boundary of the battery is determined based on a hot-box experiment.

[0047] In the charging scenario, the temperature characteristic parameters of the lithium-ion battery during charging based on the current charging voltage and charging function are obtained. The temperature characteristic parameters of the lithium-ion battery are processed using a preset temperature rise prediction model. By utilizing the change law of battery temperature and time during the charging process, the maximum predicted charging temperature of the lithium-ion battery under the current charging voltage and charging function is determined.

[0048] Optional or additional temperature characteristic parameters of the lithium-ion battery may include: the initial voltage of the lithium-ion battery, the planned charging rate, the initial state of charge, the charging cut-off voltage, and the initial temperature of each individual cell. The preset temperature rise prediction model can be a 1D, 2D, or 3D temperature rise prediction model. The temperature rise prediction model may include: neural network models, recurrent neural network models, convolutional neural network models, etc., and this application does not limit this.

[0049] Before charging, a lithium-ion battery is in a resting state. The voltage of a lithium-ion battery in the first second of charging is the initial voltage of the lithium-ion battery, and the second before the initial voltage is the last second of the resting state.

[0050] The initial state of charge (SPC) of a lithium-ion battery refers to the state of charge corresponding to the last second of the resting time. To calculate the SPC of a lithium-ion battery, the open-circuit voltage corresponding to the last second of the resting time can be determined first. Then, based on a preset mapping relationship between open-circuit voltage and SPC, the initial SPC of the lithium-ion battery can be confirmed by looking up a table.

[0051] The temperature rise prediction model is developed based on the electrochemical mechanism model. The electrochemical mechanism model takes into account different dimensions of the battery cell during modeling, and then has corresponding models for different dimensions.

[0052] The 1D temperature rise prediction model mainly refers to the single-particle model, which does not take into account the influence of particle size inside the battery cell.

[0053] The quasi-two-dimensional temperature rise prediction model takes into account the electrochemical processes in both the electrode thickness direction and the electrode particle radius direction.

[0054] The three-dimensional temperature rise prediction model takes into account the heat generation and dissipation process in the length, width and height directions of the battery cell.

[0055] The preset temperature rise prediction model can be trained based on battery thermal parameters such as battery specific heat capacity, battery density, battery longitudinal and normal thermal conductivity, and battery heat dissipation coefficient.

[0056] The battery thermal parameters of the heat dissipation coefficient include solid-phase diffusion coefficient, solid-phase diffusion coefficient activation energy, solid-phase conductivity, reaction rate constant, reaction rate constant activation energy, transfer coefficient, material true density, open-circuit curve, entropy-thermal curve, liquid-phase diffusion coefficient, liquid-phase diffusion coefficient activation energy, liquid-phase conductivity, liquid-phase conductivity activation energy, and material property parameters related to liquid-phase activity.

[0057] Material property parameters related to liquid phase activity include the coating thickness of the active material on the electrode, the particle radius of the positive and negative electrodes, the coating surface density on the electrode, the compacted surface density on the electrode, the proportion of active material, the thickness of the current collector, the porosity, and the battery design parameters such as the length and width of the top and bottom coatings on the electrode.

[0058] The training method for the preset temperature rise prediction model can refer to the temperature rise prediction model training methods in related technologies, and is not limited here.

[0059] Because the maximum predicted charging temperature of the lithium-ion battery under test does not exceed the current thermal stability boundary under the current charging voltage and charging function, charging the lithium-ion battery under test based on the target charging function and the current charging voltage reduces the risk of thermal runaway during charging. The charging function is updated by using the thermal stability assessment boundary, thereby dynamically and reasonably reducing the power consumption and ensuring the safety of the lithium-ion battery.

[0060] In the discharge scenario: Obtain the temperature characteristic parameters of the lithium-ion battery at the current maximum discharge rate, process the temperature characteristic parameters of the lithium-ion battery using a preset temperature rise prediction model, observe the temperature change pattern of the lithium-ion battery over time during the discharge process, and determine the maximum predicted discharge temperature of the lithium-ion battery under test when it discharges at the current maximum discharge rate.

[0061] Because the predicted maximum discharge temperature of the lithium-ion battery under test does not exceed the current thermal stability boundary when discharged at the current maximum discharge rate, discharging the battery at a target discharge rate not exceeding the maximum discharge rate reduces the risk of thermal runaway during discharge. By updating the maximum discharge rate through thermal stability assessment boundaries, the goal of dynamically and rationally reducing power consumption and ensuring the safety of lithium-ion batteries can be achieved.

[0062] like Figure 2 As shown, in some optional examples of this application, step S131 is specifically implemented through the following steps:

[0063] S1311, In a charging scenario, determine the maximum predicted charging temperature of the lithium-ion battery under test when it is being charged based on the current charging voltage and the first charging function.

[0064] S1312, determine whether the maximum predicted charging temperature is higher than the current thermal stability boundary. If yes, proceed to step S1313; otherwise, proceed to step S1314.

[0065] S1313, multiply the first charging function by a preset first coefficient to obtain the updated first charging function, and return to step S1311 to continue execution;

[0066] S1314, the first charging function is used as the target charging function.

[0067] In a charging scenario, the first charging function can be a function that implements device charging control according to a standardized process. That is, the first charging function can be an SOP charging function. The first charging function can be preset in the electronic device. In one example, the electronic device is a battery management system, and the first charging function can be preset in the battery management system.

[0068] The temperature characteristic parameters of the lithium-ion battery under test are obtained when it is charged based on the current voltage and the first charging function, and are denoted as the first temperature characteristic parameters.

[0069] Optional or additional first temperature characteristic parameters may include: the initial voltage of the lithium-ion battery, the planned charge rate, the initial state of charge, the charge cutoff voltage, and the initial temperature of the individual cell.

[0070] The first temperature characteristic parameter is input into the preset temperature rise prediction model for processing to obtain the law of temperature change of lithium-ion battery with time during the charging process under the current voltage and the first charging function, which is denoted as the first law.

[0071] Based on the first principle, the maximum predicted charging temperature of the lithium-ion battery under test is determined as the maximum predicted charging temperature of the lithium-ion battery under the current charging voltage and charging function. It is then determined whether the current maximum predicted charging temperature is higher than the current thermal stability boundary. If the current maximum predicted charging temperature is higher than the current thermal stability boundary, it indicates that the first charging function does not meet the requirements, meaning that charging the lithium-ion battery based on this first charging function carries a risk of thermal runaway. In this case, the first charging function needs to be adjusted by multiplying it by a preset first coefficient to obtain an updated first charging function.

[0072] Optionally or additionally, the preset first coefficient can be set to any positive number less than 1, such as 0.99, 0.98, 0.97, 0.96, or 0.95. Preferably, the preset first coefficient is no greater than 1 and no less than 0.9.

[0073] After obtaining the updated first charging function, steps S1311 and S1312 are re-executed until the current maximum charging prediction temperature is not higher than the current thermal stability boundary.

[0074] If the current maximum predicted charging temperature is not higher than the current thermal stability boundary, it means that the first charging function meets the requirements. Using this first charging function as the target charging function, and charging the lithium-ion battery based on it, ensures that the maximum predicted charging temperature of the tested lithium-ion battery does not exceed the current thermal stability boundary, thus reducing the risk of thermal runaway during charging. Updating the charging function through thermal stability assessment boundaries allows for dynamic and reasonable reduction of power consumption, ensuring the safety of the lithium-ion battery.

[0075] like Figure 3 As shown, in some embodiments of this application, step S132 is specifically implemented through the following steps:

[0076] S1321, In a discharge scenario, determine the maximum predicted discharge temperature of the lithium-ion battery under test when it is discharged based on the current maximum discharge rate.

[0077] S1322, Determine whether the maximum predicted discharge temperature is higher than the current thermal stability boundary. If yes, proceed to step S1323; otherwise, proceed to step S1324.

[0078] S1323, Multiply the current maximum discharge rate by the preset second coefficient to obtain the updated maximum discharge rate, and return to step S1321 to continue execution;

[0079] S1324, use the current maximum discharge rate as the target maximum discharge rate.

[0080] In a discharge scenario, the maximum discharge rate can be preset in the electronic device. In one example, the electronic device is a battery management system, and the maximum discharge rate can be preset in the battery management system.

[0081] Optionally, the maximum discharge rate can be 15C, 10C, 8C, 5C, 3.0C, 2.0C, 1.0C, etc.

[0082] The temperature characteristic parameters of the lithium-ion battery under test are obtained based on the maximum discharge rate during discharge, and are denoted as the second temperature characteristic parameter.

[0083] Optional or additional second temperature characteristic parameters may include: the initial voltage of the lithium-ion battery, the planned discharge rate, the initial state of charge, the discharge cutoff voltage, and the initial temperature of the individual cell.

[0084] The second temperature characteristic parameter is input into a preset temperature rise prediction model for processing to obtain the law of temperature change of lithium-ion battery with time during discharge based on the maximum discharge rate, which is denoted as the second law.

[0085] Based on the second principle, the maximum predicted discharge temperature of the lithium-ion battery under test is determined as the maximum predicted discharge temperature when discharged at the maximum discharge rate. It is then determined whether the current maximum predicted discharge temperature is higher than the current thermal stability boundary. If the current maximum predicted discharge temperature is higher than the current thermal stability boundary, it indicates that the current maximum discharge rate does not meet the requirements, and discharging the lithium-ion battery at this maximum discharge rate may lead to thermal runaway risk. In this case, the maximum discharge rate needs to be adjusted by multiplying it by a preset second coefficient to obtain an updated maximum discharge rate.

[0086] In some embodiments of this application, the preset second coefficient includes, but is not limited to, any positive number less than 1, such as 0.99, 0.98, 0.97, 0.96, 0.95.

[0087] In some embodiments of this application, the preset second coefficient is less than the preset first coefficient. When using lithium-ion battery products, users generally mainly use the discharge mode of the lithium-ion battery. Setting the preset second coefficient used during the discharge process to be less than the preset first coefficient used during the charging process can reduce the user's perception of the discharge state.

[0088] Preferably, the second coefficient is preset to be no greater than 1 and no less than 0.95.

[0089] After obtaining the updated maximum discharge rate, repeat steps S1321 and S1322 until the current maximum discharge prediction temperature is not higher than the current thermal stability boundary.

[0090] If the current maximum predicted discharge temperature is not higher than the current thermal stability boundary, it means that the current maximum discharge rate meets the requirements. When discharging the lithium-ion battery based on this maximum discharge rate, the maximum predicted discharge temperature of the lithium-ion battery under test will not exceed the current thermal stability boundary. Discharging the lithium-ion battery under test based on a target discharge rate not exceeding the maximum discharge rate reduces the risk of thermal runaway during discharge. By updating the maximum discharge rate through thermal stability assessment boundaries, the goal of dynamically and reasonably reducing the power consumption and ensuring the safety of lithium-ion batteries can be achieved.

[0091] In some optional examples of this application, before the step of determining the current thermal stability boundary corresponding to the current thermal stability characteristic parameter based on a preset first relationship, the method further includes:

[0092] The method for determining the primary relation includes:

[0093] Multiple lithium-ion battery samples were monitored to obtain thermal stability characteristic parameters of the sample lithium-ion batteries.

[0094] As mentioned earlier, thermal stability characteristic parameters may include, but are not limited to, the voltage, current, temperature, DC impedance, AC impedance, anode potential, cathode potential, dead lithium deposition, ultrasonic signal, and mechanical signal of lithium-ion batteries.

[0095] The sample lithium-ion battery is a fully charged cell. After the sample lithium-ion battery is left to stand, it is placed in a hot box and heated at a preset temperature rise rate. After reaching a certain temperature, it is left to stand for a preset time.

[0096] For example, after allowing the sample lithium-ion battery to stand, it is placed in a hot chamber and heated at a rate of 5°C / min. After reaching different temperature points, it is left to stand for 1 hour. If no thermal runaway occurs, the temperature is continued to rise. The temperature point at which thermal runaway occurs is defined as the thermal stability boundary. The temperature points can be 90°C, 100°C, 110°C, and 120°C.

[0097] Thermal chamber tests were performed on each sample of lithium-ion batteries under different ambient temperatures and aging conditions. For each lithium-ion battery, the thermal chamber temperature was continuously adjusted, and the thermal stability boundary of the lithium-ion battery was observed. When a thermal runaway fault was detected in a sample of lithium-ion battery, the temperature at that moment was recorded, and this temperature was taken as the thermal stability boundary of that sample of lithium-ion battery. Based on the thermal stability characteristic parameters and thermal stability boundaries of each sample of lithium-ion battery, the mapping relationship between thermal stability-related characteristics and thermal stability boundaries was recorded. For example, the mapping relationship between thermal stability-related characteristics and thermal stability boundaries is recorded in a table.

[0098] This application provides an apparatus for reducing the power consumption of a lithium-ion battery, which is used to implement the method for reducing the power consumption of any of the above-mentioned lithium-ion batteries.

[0099] like Figure 4 In some embodiments of this application, the device includes:

[0100] The acquisition module 410 acquires the current thermal stability characteristic parameters of the lithium-ion battery to be tested.

[0101] The determination module 420 determines the current thermal stability boundary corresponding to the current thermal stability characteristic parameters based on the first relationship; the first relationship is used to characterize the mapping relationship between the thermal stability characteristic parameters and the thermal stability boundary of the lithium-ion battery.

[0102] The charging module 430, in the charging scenario, determines the target charging function based on the current thermal stability boundary and the current charging voltage. When charging based on the current charging voltage and the charging function, the maximum predicted charging temperature of the lithium-ion battery under test is not higher than the current thermal stability boundary. The lithium-ion battery under test is charged based on the target charging function and the current charging voltage.

[0103] The discharge module 440, in the discharge scenario: determines the maximum discharge rate based on the current thermal stability boundary, wherein when discharging based on the current maximum discharge rate, the maximum predicted discharge temperature of the lithium-ion battery under test is not higher than the current thermal stability boundary; discharges the lithium-ion battery under test based on the target discharge rate; the target discharge rate is not greater than the maximum discharge rate.

[0104] In some optional examples of this application, the charging module 430 is specifically used for:

[0105] Determine the maximum predicted charging temperature of the lithium-ion battery under test when it is charged based on the current voltage and the first charging function.

[0106] If the maximum predicted charging temperature is greater than the current thermal stability boundary, the first charging function is multiplied by a preset first coefficient to obtain an updated first charging function, and the process returns to the step of determining the maximum predicted charging temperature of the lithium-ion battery under test when it is charged based on the current voltage and the first charging function, and continues execution.

[0107] If the maximum predicted charging temperature is not higher than the current thermal stability boundary, the first charging function will be used as the target charging function.

[0108] In some optional examples of this application, the charging module 430 is specifically used for:

[0109] The temperature characteristic parameters of the lithium-ion battery under test are obtained based on the current voltage and the first charging function during charging, thus obtaining the first temperature characteristic parameters;

[0110] The first temperature characteristic parameter is input into a preset temperature rise prediction model for processing to obtain the law of temperature change of lithium-ion battery over time during charging based on the current voltage and the first charging function, thus obtaining the first law;

[0111] Based on the first law, the maximum predicted charging temperature of the lithium-ion battery under test is determined when it is charged based on the current voltage and the first charging function.

[0112] In some optional examples of this application, the discharge module 440 is specifically used for:

[0113] Determine the maximum predicted discharge temperature of the lithium-ion battery under test when it is discharged based on the current maximum discharge rate;

[0114] If the maximum predicted discharge temperature is greater than the current thermal stability boundary, multiply the current maximum discharge rate by the preset second coefficient to obtain the updated maximum discharge rate, and return to the step of determining the maximum predicted discharge temperature of the lithium-ion battery under test when it discharges based on the current maximum discharge rate, and continue execution.

[0115] If the maximum predicted discharge temperature is not higher than the current thermal stability boundary, the current maximum discharge rate will be used as the maximum discharge rate.

[0116] In some optional examples of this application, the discharge module 440 is specifically used for:

[0117] The temperature characteristic parameters of the lithium-ion battery under test are obtained when it is discharged based on the current maximum discharge rate, and the second temperature characteristic parameter is obtained.

[0118] The second temperature characteristic parameter is input into the preset temperature rise prediction model for processing to obtain the law of temperature change of lithium-ion battery with time during discharge based on the current maximum discharge rate, thus obtaining the second law.

[0119] Based on the second law, the maximum predicted discharge temperature of the lithium-ion battery under test is determined when it discharges at the current maximum discharge rate.

[0120] In some optional examples of this application, the maximum amplification factor is used as the target discharge factor.

[0121] In some optional examples of this application, the apparatus further includes: a relationship determination module, used to monitor multiple sample lithium-ion batteries and obtain the thermal stability characteristic parameters of the sample lithium-ion batteries before the step of determining the current thermal stability boundary corresponding to the current thermal stability characteristic parameter based on a preset first relationship;

[0122] A thermal chamber test was performed on each sample lithium-ion battery. For each sample lithium-ion battery, when a thermal runaway fault was detected, the temperature at that time was recorded and the temperature was used as the thermal stability boundary of the sample lithium-ion battery.

[0123] Based on the thermal stability characteristic parameters and thermal stability boundaries of each sample lithium-ion battery, the first relationship is determined.

[0124] This application also provides an electronic device, such as... Figure 5As shown, it includes a processor 601, a communication interface 602, a memory 603, and a communication bus 604, wherein the processor 601, the communication interface 602, and the memory 603 communicate with each other through the communication bus 604.

[0125] Memory 603 is used to store computer programs;

[0126] When processor 601 executes a program stored in memory 603, it performs the following steps:

[0127] Obtain the current thermal stability characteristic parameters of the lithium-ion battery under test;

[0128] Based on the first relation, the current thermal stability boundary corresponding to the current thermal stability characteristic parameter is determined. The first relation is used to characterize the mapping relationship between the thermal stability characteristic parameter and the thermal stability boundary of the lithium-ion battery.

[0129] In the charging scenario: the target charging function is determined based on the current thermal stability boundary and the current charging voltage. When charging based on the current charging voltage and charging function, the maximum predicted charging temperature of the lithium-ion battery under test is not higher than the current thermal stability boundary. The lithium-ion battery under test is charged based on the target charging function and the current charging voltage.

[0130] In the discharge scenario: the maximum discharge rate is determined based on the current thermal stability boundary. When discharging based on the current maximum discharge rate, the maximum predicted discharge temperature of the lithium-ion battery under test is not higher than the current thermal stability boundary. The lithium-ion battery under test is discharged based on the target discharge rate, which is not greater than the maximum discharge rate.

[0131] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0132] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0133] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0134] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0135] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps of any of the methods described above for reducing the power consumption of a lithium-ion battery.

[0136] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to perform any of the methods for reducing the power consumption of lithium-ion batteries described in the above embodiments.

[0137] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0138] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0139] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of devices, battery packs, electronic devices, computer-readable storage media, and computer programs containing instructions are basically similar to the method embodiments, and therefore the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0140] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A method for reducing the power consumption of a lithium-ion battery, characterized in that, The method includes: Obtain the current thermal stability characteristic parameters of the lithium-ion battery under test; Based on the first relationship, the current thermal stability boundary corresponding to the current thermal stability characteristic parameter is determined; the first relationship is used to characterize the mapping relationship between the thermal stability characteristic parameter and the thermal stability boundary of the lithium-ion battery. In the charging scenario: a target charging function is determined based on the current thermal stability boundary and the current charging voltage, wherein, when charging based on the current charging voltage and the target charging function, the maximum predicted charging temperature of the lithium-ion battery under test is not higher than the current thermal stability boundary; the lithium-ion battery under test is charged based on the target charging function and the current charging voltage; In the discharge scenario: the maximum discharge rate is determined based on the current thermal stability boundary, wherein when discharging based on the current maximum discharge rate, the maximum predicted discharge temperature of the lithium-ion battery under test is not higher than the current thermal stability boundary; the lithium-ion battery under test is discharged based on the target discharge rate; the target discharge rate is not greater than the maximum discharge rate.

2. The method according to claim 1, characterized in that, The step of determining the target charging function based on the current thermal stability boundary and the current charging voltage includes: Determine the maximum predicted charging temperature of the lithium-ion battery under test when it is being charged based on the current voltage and a first charging function. If the maximum predicted charging temperature is greater than the current thermal stability boundary, the first charging function is multiplied by a preset first coefficient to obtain an updated first charging function, and the process returns to the step of determining the maximum predicted charging temperature of the lithium-ion battery under test when it is charged based on the current voltage and the first charging function, and continues execution. If the maximum predicted charging temperature is not higher than the current thermal stability boundary, the first charging function is used as the target charging function.

3. The method according to claim 2, characterized in that, Determining the maximum predicted charging temperature of the lithium-ion battery under test when it is charged based on the current voltage and the first charging function includes: The temperature characteristic parameters of the lithium-ion battery under test are obtained based on the current voltage and the first charging function during charging, thus obtaining the first temperature characteristic parameters; The first temperature characteristic parameter is input into a preset temperature rise prediction model for processing to obtain the law of temperature change of lithium-ion battery over time during the charging process based on the current voltage and the first charging function, thus obtaining the first law; Based on the first rule, the maximum predicted charging temperature of the lithium-ion battery under test is determined when it is charged with the first charging function based on the current voltage.

4. The method according to claim 1, characterized in that, The determination of the maximum discharge rate based on the current thermal stability boundary includes: Determine the maximum predicted discharge temperature of the lithium-ion battery under test when it is discharged based on the current maximum discharge rate; If the maximum predicted discharge temperature is greater than the current thermal stability boundary, the current maximum discharge rate is multiplied by a preset second coefficient to obtain the updated maximum discharge rate, and the process returns to the step of determining the maximum predicted discharge temperature of the lithium-ion battery under test when it discharges based on the current maximum discharge rate, and continues to execute. If the predicted maximum discharge temperature is not higher than the current thermal stability boundary, the current maximum discharge rate is taken as the maximum discharge rate.

5. The method according to claim 4, characterized in that, Determining the maximum predicted discharge temperature of the lithium-ion battery under test when it is discharged based on the current maximum discharge rate includes: The temperature characteristic parameters of the lithium-ion battery under test are obtained when it is discharged based on the current maximum discharge rate, and the second temperature characteristic parameter is obtained. The second temperature characteristic parameter is input into the preset temperature rise prediction model for processing to obtain the law of temperature change of lithium-ion battery with time during discharge based on the current maximum discharge rate, thus obtaining the second law. Based on the second rule, the maximum predicted discharge temperature of the lithium-ion battery under test is determined when it discharges at the current maximum discharge rate.

6. The method according to claim 1, characterized in that, The maximum amplification factor is taken as the target discharge factor.

7. The method according to claim 1, characterized in that, Before the step of determining the current thermal stability boundary corresponding to the current thermal stability characteristic parameter based on a preset first relationship, the method further includes: The method for determining the primary relation includes: Multiple lithium-ion battery samples were monitored to obtain thermal stability characteristic parameters of the sample lithium-ion batteries; A thermal chamber test was performed on each sample lithium-ion battery. For each sample lithium-ion battery, when a thermal runaway fault was detected, the temperature at that time was recorded and the temperature was used as the thermal stability boundary of the sample lithium-ion battery. Based on the thermal stability characteristic parameters and thermal stability boundaries of each sample lithium-ion battery, the first relationship is determined.

8. A device for reducing the power consumption of a lithium-ion battery, characterized in that, The device is used to implement a method for reducing the power consumption of a lithium-ion battery as described in any one of claims 1-7.

9. A battery pack, characterized in that, Includes the device for reducing the power consumption of a lithium-ion battery as described in claim 8.

10. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the steps of the method described in any one of claims 1-7.

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