Battery pack energy health degree calculation method and device, computer equipment and medium

Abstract

The invention relates to the technical field of battery management, and discloses a battery pack energy health degree calculation method and device, computer equipment and a medium. In the initial life stage and the subsequent life stage of a battery pack, the energy health degree of the battery pack is calculated according to the charge state use interval corresponding to the corresponding stage and the charge state deviation of a battery cell; and considering the consistency deviation of the state of charge of the battery cell, and determining a discharge depth interval of energy iterative calculation. Carrying out iterative calculation by utilizing the discharge depth interval, determining discharge energy corresponding to each discharge depth of the battery pack, and calculating first discharge total energy and second discharge total energy corresponding to a service life starting stage and a service life subsequent stage of the battery pack, and determining the energy health degree of the battery pack in the subsequent stage of the service life according to the first discharge total energy and the second discharge total energy. The influence of the poor consistency of the cells after aging on the total discharge energy is considered, the total discharge energy of the battery pack in different life stages is iteratively calculated, the energy health degree of the battery pack is further calculated, and the accuracy is higher.

Description

Technical Field

[0001] The present application relates to the field of battery management technology, and specifically to a method, device, computer equipment, and medium for calculating the energy health of a battery pack. Background Art

[0002] Currently, battery packs are widely used as propulsion components in vehicles, such as electric vehicles. The energy health of a battery pack is a key metric required to assess its performance at each stage of its lifecycle. Accurately determining the energy health of a battery pack has become a pressing issue. Summary of the Invention

[0003] In view of this, the present application provides a method, apparatus, computer equipment and medium for calculating the energy health of a battery pack to obtain the energy health of a battery pack with high accuracy.

[0004] In a first aspect, the present application provides a method for calculating the energy health of a battery pack, the method comprising:

[0005] At the beginning of the life of the battery pack, a first depth of discharge interval is determined based on the first state of charge usage interval and the first state of charge deviation, where the first state of charge deviation indicates a difference between the states of charge of the battery cells of the battery pack under a target charging condition at the beginning of the life; a first discharge energy corresponding to each first depth of discharge in the first depth of discharge interval is determined; and a first total discharge energy is determined based on each first discharge energy;

[0006] In a subsequent life stage after the initial life stage of the battery pack, determining a second depth of discharge interval based on the second state of charge usage interval and the second state of charge deviation, the second state of charge deviation indicating a difference between the states of charge of the battery cells of the battery pack under a target charging condition in the subsequent life stage; determining a second discharge energy corresponding to each second depth of discharge in the second depth of discharge interval; and determining a second total discharge energy based on each second discharge energy.

[0007] An energy health of the battery pack in a subsequent lifespan stage is determined based on the first discharge total energy and the second discharge total energy.

[0008] Beneficial effects: This application takes into account the consistency deviation of the state of charge of the battery cells at the beginning and subsequent stages of the life of the battery pack, and accurately determines the discharge depth interval for iterative energy calculation according to the state of charge usage interval corresponding to the corresponding stage and the state of charge deviation of the battery cells. Then, iterative calculation is performed using the discharge depth interval to accurately calculate the discharge energy of the battery pack at each discharge depth, so as to determine the first discharge total energy and the second discharge total energy corresponding to the beginning and subsequent stages of the life of the battery pack, respectively, and thus determine the energy health of the battery pack in the subsequent stages of the life based on the first discharge total energy and the second discharge total energy. This application takes into account the effects of the outliers of aging cells, the deterioration of cell consistency, and the changes in the state of charge usage interval of aging cells on the total discharge energy after aging of the battery pack, accurately calculates the total discharge energy of the battery pack at different stages of its life, and then calculates the energy health of the battery pack with higher accuracy.

[0009] In an optional embodiment, the discharge energy corresponding to the target discharge depth is determined by an iterative operation corresponding to the target discharge depth, where the target discharge depth is the first discharge depth or the second discharge depth. The iterative operation includes:

[0010] Determine the starting cell internal resistance corresponding to the target depth of discharge based on the starting cell temperature corresponding to the target depth of discharge;

[0011] Determine the target cell temperature corresponding to the target depth of discharge based on the target depth of discharge, the starting cell temperature, the starting cell internal resistance, and the capacity attenuation coefficient corresponding to the target depth of discharge;

[0012] Determine the target cell internal resistance corresponding to the target discharge depth based on the target cell temperature;

[0013] The first discharge energy or the second discharge energy corresponding to the target discharge depth is determined according to the target cell internal resistance, the capacity attenuation coefficient, and the internal resistance growth rate corresponding to the target discharge depth.

[0014] Beneficial effect: The present application calculates the discharge energy corresponding to the target depth of discharge by performing an iterative operation, wherein the starting cell internal resistance is first determined by the starting cell temperature, and then the target cell internal resistance is determined by combining the capacity attenuation coefficient of the battery pack and taking into account the heat consumption of the cell internal resistance. The discharge energy corresponding to the target depth of discharge is then determined by using the capacity attenuation coefficient of the battery pack, the internal resistance growth rate, and the target cell internal resistance. In this way, the capacity attenuation after battery aging, the increase in internal resistance, and the influence of the electrothermal effect on power are comprehensively considered to obtain a more accurate discharge energy.

[0015] In an optional embodiment, determining the target cell temperature corresponding to the target depth of discharge according to the target depth of discharge, the starting cell temperature, the starting cell internal resistance, and the capacity attenuation coefficient corresponding to the target depth of discharge includes:

[0016] Determine the heat generation power of the battery pack from the previous depth of discharge to the target depth of discharge based on the starting cell internal resistance and the reference current of the battery pack;

[0017] Determine the discharge duration based on the previous discharge depth, target discharge depth, reference current, and capacity attenuation coefficient corresponding to the target discharge depth;

[0018] Determine the target cell temperature corresponding to the target depth of discharge based on the starting cell temperature, heat generation power, discharge time, heat generation coefficient of the battery pack, and heat dissipation time constant.

[0019] Beneficial effects: When performing iterative operations, the present application calculates the heating power of the battery pack at each iterative step and the required discharge time, and combines the initial cell temperature, heat generation coefficient and heat dissipation time constant of the battery pack to calculate the target cell temperature after discharge of the battery pack. The energy consumed by the heat generated by the internal resistance of the cell during the discharge process is taken into account to calculate the target cell temperature, thereby improving the accuracy of the discharge energy calculation.

[0020] In an optional embodiment, determining the first discharge energy or the second discharge energy corresponding to the target discharge depth according to the target cell internal resistance, the capacity attenuation coefficient, and the internal resistance growth rate corresponding to the target discharge depth includes:

[0021] Determine the target terminal voltage corresponding to the target depth of discharge based on the target cell internal resistance, the internal resistance growth rate corresponding to the target depth of discharge, the open circuit voltage of the battery pack, and the reference current;

[0022] The first discharge energy or the second discharge energy corresponding to the target discharge depth is determined according to the capacity attenuation coefficient, the target terminal voltage corresponding to the target discharge depth, the target terminal voltage of the previous discharge depth, and the nominal capacity of the battery pack.

[0023] Beneficial effect: This application calculates the target terminal voltage corresponding to the target discharge depth by the internal resistance growth rate of the battery after aging, thereby taking into account the influence of power attenuation and heat generation at the discharge end of the battery pack on the discharge energy, and further combines the capacity attenuation coefficient, nominal capacity and target terminal voltage of the battery pack to calculate the first discharge energy or the second discharge energy corresponding to the target discharge depth with higher accuracy.

[0024] In an optional embodiment, the method further includes:

[0025] Determine a first DC internal resistance of the battery pack at the beginning of its life and a second DC internal resistance at a later stage of its life, and calculate the internal resistance growth rate of the battery pack at the later stage of its life based on the ratio of the second DC internal resistance to the first DC internal resistance;

[0026] According to the internal resistance growth rate of the battery pack in the subsequent life stage, the internal resistance growth rate corresponding to the target discharge depth is determined.

[0027] Beneficial effect: The present application calculates the first DC internal resistance and the second DC internal resistance of the battery pack at the beginning stage and the subsequent stage of its life respectively, and then calculates the internal resistance growth rate of the battery pack in the subsequent stage of its life after aging based on the ratio between the second DC internal resistance and the first DC internal resistance, so that when iteratively calculating the total discharge energy of the battery pack, the influence of the internal resistance growth after battery aging on the calculation results can be considered to improve the calculation accuracy.

[0028] In an optional embodiment, the method further includes:

[0029] At the beginning of the battery pack's life, determine the nominal capacity of the battery pack;

[0030] During a subsequent lifespan of the battery pack, determining a first state of charge of the battery pack at a first time point, a second state of charge at a second time point, and an accumulated charge between the first time point and the second time point; and obtaining a remaining capacity based on the accumulated charge, the first state of charge, and the second state of charge;

[0031] Calculating a capacity attenuation coefficient of the battery pack in a subsequent lifespan based on a ratio of the remaining capacity to the nominal capacity, wherein the ratio of the remaining capacity to the nominal capacity is within a preset range;

[0032] According to the capacity attenuation coefficient of the battery pack in the subsequent stages of its life, the capacity attenuation coefficient corresponding to the target depth of discharge is determined.

[0033] Beneficial effects: This application calculates the nominal capacity and residual capacity of the battery pack at the beginning stage and subsequent stage of life respectively, and calculates the capacity attenuation coefficient of the battery pack in the subsequent stage of life according to the ratio between the residual capacity and the nominal capacity, so that it can be directly called in the subsequent iterative calculation of the total discharge energy of the battery pack in the subsequent stage of life, thereby considering the impact of capacity attenuation after battery aging on the calculation results and improving the accuracy of the calculation results.

[0034] In an optional embodiment, determining the energy health of the battery pack in a subsequent life stage according to the first total discharge energy and the second total discharge energy includes:

[0035] The energy health of the battery pack in the subsequent stage of its life is obtained based on the ratio between the second total discharge energy and the first total discharge energy; wherein, the lower the capacity attenuation coefficient of the battery pack in the subsequent stage of its life compared with the initial stage of its life or the higher the internal resistance growth rate, the smaller the second total discharge energy, and the lower the energy health of the battery pack in the subsequent stage of its life.

[0036] Beneficial Effects: This application accurately calculates the second total discharge energy that a battery pack can release in the later stages of its lifespan based on the capacity attenuation coefficient and internal resistance growth rate of the battery pack in the later stages of its lifespan. The lower the capacity attenuation coefficient or the higher the internal resistance growth rate, the smaller the second total discharge energy released. The second total discharge energy is then compared with the first total discharge energy released by the battery pack at the beginning of its lifespan to determine the change in the energy health of the battery pack in the later stages of its lifespan.

[0037] In a second aspect, the present application provides a device for calculating the energy health of a battery pack, the device comprising:

[0038] a first processing module, configured to determine, at a beginning stage of the life of the battery pack, a first depth of discharge interval based on a first state of charge usage interval and a first state of charge deviation, wherein the first state of charge deviation indicates a difference between states of charge of cells of the battery pack under a target charging condition at the beginning stage of the life; determine a first discharge energy corresponding to each first depth of discharge in the first depth of discharge interval; and determine a first total discharge energy based on each first discharge energy;

[0039] a second processing module, configured to determine, in a subsequent life stage after the initial life stage of the battery pack, a second depth of discharge interval based on the second state of charge usage interval and the second state of charge deviation, wherein the second state of charge deviation indicates a difference between the states of charge of the battery cells of the battery pack under a target charging condition in the subsequent life stage; determine a second discharge energy corresponding to each second depth of discharge in the second depth of discharge interval; and determine a second total discharge energy based on each second discharge energy;

[0040] The third processing module is used to determine the energy health of the battery pack in a subsequent life stage according to the first total discharge energy and the second total discharge energy.

[0041] In a third aspect, the present application provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, computer instructions being stored in the memory, and the processor executing the computer instructions to execute the method for calculating the energy health of a battery pack according to the first aspect or any corresponding embodiment thereof.

[0042] In a fourth aspect, the present application provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for calculating the energy health of a battery pack according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the specific implementation methods or the description of the prior art. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0044] Figure 1 is a flowchart of a method for calculating the energy health of a battery pack according to an embodiment of the present application;

[0045] Figure 2 is a flowchart of another method for calculating the energy health of a battery pack according to an embodiment of the present application;

[0046] Figure 3 is a schematic diagram of a flow chart for iteratively calculating discharge energy according to an embodiment of the present application;

[0047] Figure 4 is a flowchart of another method for calculating the energy health of a battery pack according to an embodiment of the present application;

[0048] Figure 5 is a schematic diagram of another process for iteratively calculating discharge energy according to an embodiment of the present application;

[0049] Figure 6 is a structural block diagram of a device for calculating the energy health of a battery pack according to an embodiment of the present application;

[0050] Figure 7 It is a schematic diagram of the hardware structure of the computer device of an embodiment of the present application. DETAILED DESCRIPTION

[0051] To make the purpose, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of this application.

[0052] According to an embodiment of the present application, an embodiment of a method for calculating the energy health of a battery pack is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0053] In this embodiment, a method for calculating the energy health of a battery pack is provided, which can be executed by a computer device on a vehicle on which the battery pack is installed, such as a battery management system (BMS), wherein the vehicle can be a land vehicle such as a vehicle or an electric vehicle, an aerial vehicle such as an aircraft or a flying car, or a water vehicle such as a ship. Figure 1 is a flow chart of a method for calculating the energy health of a battery pack according to an embodiment of the present application, such as Figure 1 As shown, the process includes the following steps:

[0054] Step S101, at the beginning of the life of the battery pack, determine a first discharge depth interval based on a first state of charge usage interval and a first state of charge deviation, where the first state of charge deviation indicates the difference between the states of charge of the battery cells of the battery pack under the target charging condition in the beginning of the life; determine a first discharge energy corresponding to each first discharge depth in the first discharge depth interval; and determine a first total discharge energy based on each first discharge energy.

[0055] Specifically, the first state of charge usage range may be a maximum allowable SOC usage range, and the first state of charge usage range may be pre-set in combination with the life stage of the battery pack.

[0056] Specifically, a battery pack is a complex system composed of multiple cells connected in series, parallel, or a combination of series and parallel. Even at the beginning of the battery pack's life (BOL), the state of charge (SOC) between the cells will have consistency deviations, which in turn affects the depth of discharge (DOD) of the entire battery pack. The depth of discharge refers to the percentage of the amount of electricity discharged by the battery pack during use as a percentage of its nominal capacity, and the value range is generally 1% to 100%. Therefore, when calculating the energy value that the battery pack can release in the BOL state based on the battery pack's depth of discharge range, it is necessary to consider the consistency deviation of the cell SOC in the BOL state.

[0057] In some optional embodiments, during the first N full charges of a new battery pack, the difference between the maximum and minimum cell SOCs of the battery cells after each full charge can be recorded. Furthermore, the difference between the maximum and minimum cell SOCs of the battery pack during the most recent full charge up to the start of step S101 can be used as the first state of charge deviation. Here, "new battery pack" is another name for a battery pack in the BOL state. For example, the formula for calculating the state of charge deviation DOD_diff can be as follows:

[0058] DOD_diff = (SOC_max - SOC_min)

[0059] Among them, SOC_max represents the maximum single-cell SOC, and SOC_min represents the minimum single-cell SOC.

[0060] Furthermore, the depth of discharge interval [DOD_start, DOD_end] is determined based on the state of charge interval [SOC_tail, SOC_head] and the state of charge deviation DOD_diff at the beginning of the battery pack's life, where the left endpoint of the depth of discharge interval DOD_start = 1-(SOC_head-DOD_diff), and the right endpoint of the depth of discharge interval DOD_end = 1-SOC_tail.

[0061] It should be noted that the depth of discharge is the percentage of the battery pack's discharged charge to its nominal capacity. The smaller the depth of discharge, the greater the battery pack's state of charge. Because the SOC of the battery cell has consistency deviation, the difference between the right endpoint of the state of charge usage range, SOC_head, and the consistency deviation DOD_diff of the battery cell when fully charged is combined to determine the maximum usable state of charge of the battery pack as a whole, thereby determining the left endpoint of the depth of discharge range, DOD_start.

[0062] In step S101, multiple first depths of discharge in a first depth of discharge interval are obtained. The difference between any two adjacent first depths of discharge can be the same. The multiple first depths of discharge are ordered from smallest to largest, with the smallest first depth of discharge being the first one among the multiple first depths of discharge, and the largest first depth of discharge being the last one among the multiple first depths of discharge. Iterative operations corresponding to the first depths of discharge are performed sequentially in ascending order of the multiple first depths of discharge.

[0063] In step S101, iterative operations corresponding to each first depth of discharge can be performed sequentially in ascending order of multiple first depths of discharge. For each first depth of discharge, the iterative operations corresponding to the first depth of discharge yield a first discharge energy corresponding to the first depth of discharge. The first discharge energy corresponding to the first depth of discharge indicates the discharge energy released by the battery pack from the previous depth of discharge to the first depth of discharge.

[0064] The iterative operation corresponding to the first depth of discharge may be any existing method for calculating the discharge energy released by the battery pack during a period from when the battery pack starts discharging at one depth of discharge to when the battery pack discharges to another depth of discharge.

[0065] It should be noted that the previous discharge depth of the first first discharge depth is the left endpoint of the first discharge depth interval. For other first discharge depths except the first first discharge depth, the previous discharge depth of the other first discharge depth is the previous first discharge depth of the other first discharge depth.

[0066] In a possible implementation, the sum of the first discharge energies corresponding to the first discharge depths obtained by executing step S101 once may be determined as the first total discharge energy.

[0067] In another possible implementation, step S101 is performed N1 times, each of the N1 times corresponding to a different full charge of the battery pack during the first N1 full charges at the beginning of the battery pack's life. When step S101 is performed for the M1th time, the first state of charge deviation may be: the difference between the maximum cell SOC and the minimum cell SOC during the full charge corresponding to the M1th time. The M1th time is any one of the N1 times. The sum of the first discharge energies corresponding to each first depth of discharge obtained by performing step S101 for the M1th time is determined as the total discharge capacity of the M1th time. Finally, the average value of the total discharge capacity of the N1 times may be determined as the first total discharge energy. Exemplarily, the value of N1 may be 5.

[0068] Step S102, in a subsequent life stage after the initial life stage of the battery pack, determining a second depth of discharge interval based on the second state of charge usage interval and the second state of charge deviation, the second state of charge deviation indicating the difference between the states of charge of the battery cells of the battery pack under the target charging condition in the subsequent life stage; determining a second discharge energy corresponding to each second depth of discharge in the second depth of discharge interval; and determining a second total discharge energy based on each second discharge energy.

[0069] It should be noted that the subsequent life stage can be any stage after the initial life stage of the battery pack. In the embodiment of the present application, the division of the life stages of the battery pack is not limited.

[0070] As an example, the subsequent life stage is the battery aging stage, which can be called the middle of life (MOL).

[0071] Specifically, the second state of charge usage range may be a maximum allowable SOC usage range. The second state of charge usage range may be pre-set in combination with the life stage of the battery pack.

[0072] Taking into account that the capacity and internal resistance of a battery pack will change after aging, the correspondence between different capacities and internal resistance states of the battery pack and the allowable SOC usage range can be pre-set. Based on this correspondence, the maximum allowable SOC usage range of the battery pack in the subsequent stage of its life can be selected to obtain the second state of charge usage range.

[0073] In one possible implementation, step S102 uses the difference between the maximum and minimum cell SOCs when the battery pack was last fully charged to measure the consistency deviation of the battery cell SOCs in the subsequent lifespan of the battery pack, thereby obtaining a second state-of-charge deviation. The second state-of-charge usage range and the second state-of-charge deviation are then combined to obtain a second depth-of-discharge range. For details, refer to step S101.

[0074] In step S102, multiple second depths of discharge in a second depth of discharge interval are obtained. The difference between any two adjacent second depths of discharge can be the same. The multiple second depths of discharge are ordered from smallest to largest, with the smallest second depth of discharge being the first and the largest second depth of discharge being the last. Iterative operations corresponding to the second depths of discharge are performed sequentially in ascending order.

[0075] In step S102, the iterative operation corresponding to each second depth of discharge can be performed sequentially in ascending order of the multiple second depths of discharge. For each second depth of discharge, the iterative operation corresponding to the second depth of discharge is performed to obtain a second discharge energy corresponding to the second depth of discharge. The second discharge energy corresponding to the second depth of discharge indicates the discharge energy released by the battery pack from the previous depth of discharge to the second depth of discharge.

[0076] The iterative operation corresponding to the second depth of discharge may be any existing method for calculating the discharge energy released by the battery pack during a period from when the battery pack starts discharging at one depth of discharge to when the battery pack discharges to another depth of discharge.

[0077] It should be noted that the previous discharge depth of the first second discharge depth is the left endpoint of the second discharge depth interval. For other second discharge depths other than the first second discharge depth, the previous discharge depth of the other second discharge depth is the previous second discharge depth of the other second discharge depth.

[0078] In a possible implementation, the sum of the second discharge energies corresponding to the second discharge depths obtained by executing step S102 once may be determined as the second total discharge energy.

[0079] In another possible implementation, step S102 is performed N2 times, each of the N2 times corresponding to a different full charge among the most recent N2 full charges of the battery pack in the subsequent life stage. When step S102 is performed for the M2th time, the second state of charge deviation may be: the difference between the maximum cell SOC and the minimum cell SOC during the full charge corresponding to the M2th time. The M2th time is any one of the N2 times. The sum of the second discharge energies corresponding to each second depth of discharge obtained by performing step S102 for the M2th time is determined as the total discharge capacity for the M2th time. Finally, the average value of the total discharge capacity of the N2 times can be determined as the second total discharge energy. Exemplarily, the value of N2 may be 5.

[0080] Step S103 : determining the energy health of the battery pack in a subsequent life stage according to the first total discharge energy and the second total discharge energy.

[0081] Specifically, according to the ratio between the second total discharge energy E_MOL and the first total discharge energy E_BOL, the energy health SOCE of the battery pack in the subsequent life stage is calculated, that is, energy health SOCE=E_MOL / E_BOL.

[0082] In some optional embodiments, taking the vehicle on which the battery pack is installed as an example, the operating conditions of the vehicle can be set, and the first discharge total energy E_BOL and the second discharge total energy E_MOL of the vehicle's battery pack under specific operating conditions, such as the Worldwide Harmonized Light Vehicles Test Cycle (WLTC), can be calculated, and then the energy health of the vehicle's battery pack under specific operating conditions in the subsequent stages of its life can be calculated.

[0083] The method for calculating the energy health of the battery pack provided in this embodiment takes into account the consistency deviation of the state of charge of the battery cells at the beginning stage of the life of the battery pack and the subsequent stage of the life, and accurately determines the discharge depth interval for the iterative energy calculation based on the state of charge usage interval corresponding to the corresponding stage and the state of charge deviation of the battery cells. Then, the discharge depth interval is used for iterative calculation to accurately calculate the discharge energy of the battery pack corresponding to each discharge depth, so as to determine the first discharge total energy and the second discharge total energy corresponding to the beginning stage of the life of the battery pack and the subsequent stage of the life, respectively, and thus determine the energy health of the battery pack in the subsequent stage of the life based on the first discharge total energy and the second discharge total energy. This application takes into account the influence of the outliers of the aged cells, the deterioration of the consistency of the cells, and the changes in the state of charge usage interval of the aged cells on the total discharge energy after the aging of the battery pack, accurately calculates the total discharge energy of the battery pack at different stages of the life, and then calculates the energy health of the battery pack with higher accuracy.

[0084] In this embodiment, a method for calculating the energy health of a battery pack is provided, which can be executed by a computer device on a vehicle. Figure 2 is a flow chart of a method for calculating the energy health of a battery pack according to an embodiment of the present application, such as Figure 2 As shown, the process includes the following steps:

[0085] Step S200, determining the capacity attenuation coefficient and internal resistance growth rate corresponding to the battery pack in the subsequent life stage, as well as determining the heat generation coefficient, heat dissipation time constant, and relationship parameters between the battery cell internal resistance and the battery cell temperature.

[0086] It's important to understand that the battery pack, as a critical component of a vehicle, has a performance and service life that directly impacts the vehicle's range, service life, and user experience. As a vehicle ages, aging of the battery pack cells is inevitable.

[0087] In this embodiment, in addition to considering the cell SOC consistency deviation caused by outliers and poor cell consistency after battery pack aging, the capacity decay and internal resistance increase after battery pack aging are also considered. Moreover, capacity decay reduces the battery pack's rechargeable energy, and increased internal resistance dissipates the battery pack's energy as heat as discharge proceeds, thereby affecting the battery pack's dischargeable energy. Therefore, before executing steps S201 and S202, the capacity decay coefficient, internal resistance growth rate, heat generation coefficient, and heat dissipation time constant corresponding to the battery pack at different life stages are evaluated. These are then directly referenced during the electrothermal coupling iterative calculation of discharge energy, improving iteration efficiency. Furthermore, the accuracy of the discharge energy calculation results is improved by considering the battery pack's capacity decay, internal resistance increase, and electrothermal effects.

[0088] It should be noted that electrothermal coupling iterative calculation refers to performing multiple iterative calculations during the simulation process by coupling the battery's electrical model (such as voltage, current, internal resistance, etc.) and thermal model (such as temperature distribution, heat conduction, etc.) to simulate the mutual influence of the electrical and thermal properties of the battery pack during the discharge process, thereby predicting the discharge energy of the battery pack.

[0089] Specifically, the battery pack's first DC internal resistance DCR_BOL at the beginning of its life and its second DC internal resistance DCR_MOL at the end of its life are determined. Then, based on the ratio of the second DC internal resistance to the first DC internal resistance, the internal resistance growth rate of the battery pack at the end of its life is calculated. Based on this internal resistance growth rate at the end of its life, the internal resistance growth rate corresponding to the target depth of discharge is determined.

[0090] In some optional embodiments, during the charging process, the internal resistance of the battery pack is calculated based on the voltage change ΔV and current change ΔI under specific operating conditions, so as to simulate the vehicle usage conditions using specific operating conditions. Taking the beginning of the life of the battery pack as an example (the same applies to the subsequent stages of the life), the battery pack is charged, and the voltage change and current change data of the battery pack under specific operating conditions are obtained during the charging process. The direct current resistance (DCR) of the battery cell at the beginning of the life is calculated based on the formula DCR = ΔV / ΔI. It should be noted that the above-mentioned specific operating conditions can be that the battery pack SOC range is 40% to 60%, the temperature is 20℃ to 45℃, and the battery pack is left to stand for 5 minutes during the charging process. The pulse charging current is given according to the maximum charging Map, and the voltage change and current change of the battery pack under the pulse charging current are obtained, and the DC internal resistance of the battery cell at the beginning of the life is calculated.

[0091] In some optional embodiments, taking the beginning of life as an example (and the same applies to subsequent life stages), the DC internal resistance of the battery cell at the beginning of life can be calculated multiple times according to the above process, and the results of the multiple calculations can be low-pass filtered to obtain the final first DC internal resistance DCR_BOL of the battery cell at the beginning of life. The low-pass filtering process can be performed by averaging the multiple calculated DC internal resistances to obtain the final first DC internal resistance DCR_BOL, but this application is not limited to this.

[0092] Furthermore, the internal resistance growth rate SOHR in the subsequent life stage is calculated based on the formula SOHR=DCR_MOL / DCR_BOL according to the second DC internal resistance DCR_MOL in the subsequent life stage obtained by testing and the first DC internal resistance DCR_BOL in the initial life stage stored.

[0093] In an embodiment of the present application, the first DC internal resistance and the second DC internal resistance corresponding to the battery pack at the beginning stage of its life and the subsequent stage of its life are respectively calculated, and then the internal resistance growth rate of the battery pack in the subsequent stage of its life after aging is calculated based on the ratio between the second DC internal resistance and the first DC internal resistance. This allows the influence of the internal resistance growth after battery aging on the calculation result of the discharge energy to be considered when iteratively calculating the total discharge energy of the battery pack, thereby improving the calculation accuracy.

[0094] Specifically, at the beginning of the battery pack's life, the nominal capacity of the battery pack is determined. Furthermore, at a later stage in the battery pack's life, a first state of charge (SOC) of the battery pack at a first time point, a second SOC of the battery pack at a second time point, and the cumulative charge between the first and second time points are determined. Then, based on the cumulative charge, the first SOC, and the second SOC, the remaining capacity is calculated. Based on the ratio of the remaining capacity to the nominal capacity, the capacity decay coefficient of the battery pack at the later stage of its life is calculated, where the ratio of the remaining capacity to the nominal capacity is within a preset range. Furthermore, based on the capacity decay coefficient of the battery pack at the later stage of its life, the capacity decay coefficient corresponding to the target depth of discharge is determined.

[0095] In some optional embodiments, the equivalent power Prms of the battery pack is calculated using a root mean square method, and the reference current Iref of the battery pack is obtained by dividing the equivalent power Prms by the nominal voltage of the battery pack.

[0096] In some embodiments, under specific operating conditions, such as WLTC, the equivalent power Prms of the battery pack under specific operating conditions may be calculated to determine the reference current Iref of the battery pack under the specific operating conditions.

[0097] Furthermore, the battery pack is tested for constant capacity using the reference current Iref at room temperature to obtain the nominal capacity Q of the battery pack at the beginning of its life. n .

[0098] In some optional embodiments, when calculating the capacity attenuation coefficient in the subsequent life stage, the calculation scheme may be an empirical formula calculation method or a two-point cumulative electricity capacity calculation method, but the present application is not limited thereto.

[0099] For example, taking the two-point cumulative capacity calculation method as an example, the open circuit voltage (OCV) of the battery pack at two time points can be used to look up the OCV-SOC comparison table to obtain the first state of charge SOC1 at the first time point, the second state of charge SOC2 at the second time point, and the accumulated cumulative capacity ΔQ during the period. Then, the remaining capacity Q in the subsequent life stage is calculated based on the following formula: Remain :

[0100]

[0101] Wherein, ΔQ is the capacity value obtained by Ampere-Hour Integration (AH).

[0102] It should be noted that the remaining capacity Q Remain It can be estimated online to calculate the remaining capacity Q of the battery pack in the subsequent life stage. Remain The following factors should be considered:

[0103] 1) For the first state of charge (SOC1) and second state of charge (SOC2) obtained by looking up the OCV-SOC relationship table, ensure that the battery cell is fully rested before reading the value to ensure that the change in dV / dt is sufficiently small. The resting time can refer to the resting time of the OCV test in the battery cell parameter table, and the voltage range where the dV / dSOC is too small should be avoided, such as the platform range of lithium iron phosphate (LFP) batteries.

[0104] 2) The estimation process should take into account the influence of the battery cell temperature, which can be between 10℃ and 40℃.

[0105] 3) The numerator ΔQ obtained by the AH integral should be as large as possible, at least greater than a first capacity threshold, where the first capacity threshold can be 37% of the nominal capacity. The error of the AH integral should not exceed an error threshold, which can be 1% of the nominal capacity.

[0106] 4) The remaining capacity Q can be estimated multiple times Remain , and filter the remaining capacity Q to obtain the final Remain For example, the two estimated capacity values ​​are processed by a filter coefficient Qfilter (default 0.85), and the change between the two estimated capacities should not be too large, with the maximum change not exceeding 5%.

[0107] 5) Remaining capacity Q for online update Remain The second capacity threshold should not be exceeded during the entire life cycle of the battery pack. The second capacity threshold may be 120% of the nominal capacity and may be set specifically according to the actual application scenario. This application is not limited thereto.

[0108] 6) Online estimated remaining capacity Q Remain Before updating, the nominal capacity should be output as the remaining capacity corresponding to this stage.

[0109] Furthermore, by calculating the remaining capacity Q in the subsequent life stage Remain , the nominal capacity Q at the beginning of reference life n , based on the formula SOHQ=Q Remain / Qn , calculate the capacity attenuation coefficient SOHQ of the battery pack in the subsequent life stage.

[0110] In this embodiment, the nominal capacity and remaining capacity corresponding to the battery pack at the beginning stage and the subsequent stage of its life are calculated respectively, and the capacity attenuation coefficient of the battery pack in the subsequent stage of its life is calculated based on the ratio between the remaining capacity and the nominal capacity. This is directly called for subsequent iterative calculations of the total discharge energy of the battery pack in the subsequent stage of its life, thereby taking into account the impact of capacity attenuation after battery aging on the calculation results of the discharge energy, thereby improving the accuracy of the calculation results.

[0111] Specifically, the battery pack is discharged at a constant current using a reference current Iref at different temperatures (e.g., room temperature 25°C, low temperature 0°C or -10°C, etc.), and the open circuit voltage change, terminal voltage change, and DOD change of the battery pack at different cell temperatures are obtained. The internal resistance change at different DODs is obtained using the formula Rt = (OCV-Vt) / Iref, where Rt represents the internal resistance of the battery pack, OCV represents the open circuit voltage of the battery pack, and Vt represents the terminal voltage of the battery pack. It should be noted that the battery pack voltage, current, and cell temperature data can be collected 5 minutes after the battery pack discharge begins to stabilize, and these data can be low-pass filtered before the internal resistance of the battery pack can be calculated.

[0112] Furthermore, based on the internal resistance values ​​Rt1[DOD,T1] and Rt2[DOD,T2] obtained from tests at different cell temperatures and different DODs, and based on the prototype formula Rt=R0*exp(-Rb / (T+273.15)), a nonlinear fitting method is used to calculate the relationship parameters R0[DOD] and Rb[DOD] between the cell internal resistance Rt and the cell temperature T at different DODs. Specifically, the calculation method can be to perform a linear regression calculation on the logarithm of the measured internal resistance value, and select the fitting parameters based on the goodness of fit value; or a nonlinear fitting method can be used to calculate R0 and Rb, such as the gradient descent method, the Gauss-Newton method, or the Newton-Raphson method. The specific calculation process can be referred to the detailed description of the relevant technology and will not be elaborated here. At the same time, the selection of DOD should refer to the change of internal resistance under different SOC. The internal resistance changes smoothly under high SOC, so the interval of DOD selection can be slightly larger, such as 10%. The internal resistance nonlinearity is large under low SOC, so the interval of DOD should be shortened, and an interval point can be selected at 3% SOC.

[0113] Specifically, the heat generation coefficient and heat dissipation time constant of the battery pack can be calculated based on the discharge condition data of the battery pack. The specific calculation method can be based on the thermal model To calculate, where T cell,k is the cell temperature at time k, Tcell,k-1 is the cell temperature at time k-1, R k-1 is the heating power between k-1 and k (this value is a periodically calculated value), Δt is the time interval between k-1 and k, Q c-1 is the heat generation coefficient from time k-1 to time k, τ is the heat dissipation time constant from time k-1 to time k, and Tamb is the ambient temperature.

[0114] The above embodiment uses the ambient temperature Tamb, the heating power R at the previous moment k-1 and the cell temperature T at the previous moment cell,k-1 As input, the current cell temperature T cell,k As output quantities, the heat generation coefficient Q and the heat dissipation time constant τ are to be solved. The time-varying heat generation coefficient Q and the heat dissipation time constant τ are calculated using the first-order identification method, recursive least squares method, or the forgetting factor recursive least squares method.

[0115] In some embodiments, a nonlinear fitting method may be used to perform parameter fitting to obtain a heat generation coefficient Q and a heat dissipation time constant τ with fixed values.

[0116] In some optional embodiments, the vehicle also features a water cooling system to cool the battery pack. The heat generation coefficient Q1 and heat dissipation time constant τ1 of the battery pack can be calculated separately when the water cooling system is on, and the heat generation coefficient Q2 and heat dissipation time constant τ2 of the battery pack when the water cooling system is off. This means that the heat generation coefficient and heat dissipation time constant can be selected based on the actual scenario, distinguishing between when the water cooling system is on and when it is off.

[0117] Step S201: At the beginning of the life of the battery pack, a first discharge depth interval is determined based on a first state of charge usage interval and a first state of charge deviation, where the first state of charge deviation indicates the difference between the states of charge of the battery cells of the battery pack under a target charging condition in the beginning of the life; for each first discharge depth in the first discharge depth interval, a first discharge energy corresponding to the first discharge depth is determined through an iterative operation corresponding to the first discharge depth; and a first total discharge energy is determined based on the first discharge energy corresponding to each first discharge depth.

[0118] Step S202: In a subsequent life stage after the initial life stage of the battery pack, a second depth of discharge interval is determined based on the second state of charge usage interval and the second state of charge deviation, where the second state of charge deviation indicates the difference between the states of charge of the battery cells of the battery pack under the target charging condition in the subsequent life stage; for each second depth of discharge in the second depth of discharge interval, a second discharge energy corresponding to the second depth of discharge is determined through an iterative operation corresponding to the second depth of discharge; and a second total discharge energy is determined based on the second discharge energy corresponding to each second depth of discharge.

[0119] In step S202, the capacity and internal resistance of the battery pack will change in the subsequent life stage after aging. Therefore, it is necessary to consider the capacity attenuation coefficient and internal resistance growth rate corresponding to the subsequent life stage to accurately calculate the total discharge energy of the battery pack in the subsequent life stage.

[0120] The iterative operation corresponding to the target discharge depth is taken as an example below to illustrate the iterative operation corresponding to the first discharge depth and the iterative operation corresponding to the second discharge depth.

[0121] The target discharge depth is the first discharge depth or the second discharge depth.

[0122] If the target depth of discharge is the first depth of discharge, the first discharge capacity corresponding to the target depth of discharge is obtained through an iterative operation corresponding to the target depth of discharge. If the target depth of discharge is the second depth of discharge, the second discharge capacity corresponding to the target depth of discharge is obtained through an iterative operation corresponding to the target depth of discharge.

[0123] like Figure 3 As shown, the iterative operation includes:

[0124] Step a1, determining the starting cell internal resistance corresponding to the target discharge depth according to the starting cell temperature corresponding to the target discharge depth, wherein the starting cell temperature corresponding to the target discharge depth is the initial value of the cell temperature or the target cell temperature of the previous discharge depth of the target discharge depth.

[0125] It should be noted that if the target depth of discharge is the first depth of discharge, the starting cell temperature corresponding to the target depth of discharge may be the current ambient temperature. If the target depth of discharge is the first second depth of discharge, the starting cell temperature corresponding to the target depth of discharge may be the current ambient temperature.

[0126] The plurality of first / second discharge depths are arranged in ascending order, wherein the smallest first / second discharge depth is the first first / second discharge depth among the plurality of first / second discharge depths, and the largest first / second discharge depth is the last first / second discharge depth among the plurality of first / second discharge depths.

[0127] It should be noted that the previous depth of discharge of the first / second depth of discharge is the left endpoint of the first / second depth of discharge interval. For other first / second depths of discharge except the first / second depth of discharge, the previous depth of discharge of the other first / second depth of discharge is the previous first / second depth of discharge of the other first / second depth of discharge.

[0128] Specifically, at the beginning of the iteration, DOD_Start of the discharge depth interval [DOD_start, DOD_end] is used as the iteration starting DOD point, the reference current Iref is used as the discharge current, ΔDOD is used as the iteration step size, and the ambient temperature Tamb at the beginning of the iteration is recorded as the current starting cell temperature. Based on the relationship parameters R0[DOD] and Rb[DOD] between the cell internal resistance and the cell temperature, the starting cell internal resistance Rt_k corresponding to the starting cell temperature T_k at the initial iteration is calculated.

[0129] Wherein, ΔDOD is a set iteration step, which is specifically the difference between two adjacent first / second depths of discharge, and can be a value such as 1%, and can be set according to actual iteration requirements.

[0130] Specifically, the target depth of discharge DOD_k after k iterations of ΔDOD can be calculated according to DOD_k=DOD_start+k*ΔDOD.

[0131] It should be noted that, when performing subsequent iterations, the starting cell temperature of the current iteration process may be the target cell temperature calculated for the last depth of discharge in the previous iteration. The calculation process of the target cell temperature is detailed in step a2.

[0132] Step a2: determining a target cell temperature corresponding to the target depth of discharge according to the target depth of discharge, the initial cell temperature, the initial cell internal resistance, and the capacity attenuation coefficient corresponding to the target depth of discharge.

[0133] Specifically, the heat generation power of the battery pack from the previous depth of discharge to the target depth of discharge is determined based on the starting cell internal resistance and the battery pack's reference current. Furthermore, the discharge duration is determined based on the previous depth of discharge, the target depth of discharge, the reference current, and the capacity decay coefficient corresponding to the target depth of discharge. Finally, the target cell temperature corresponding to the target depth of discharge is determined based on the starting cell temperature, heat generation power, discharge duration, the battery pack's heat generation coefficient, and the heat dissipation time constant.

[0134] In some optional implementations, when the number of iterations changes from k to k+1, let k=k+1, and calculate the heating power R_k within ΔDOD according to R_k=Iref^2*Rt_k.

[0135] In some optional implementations, the discharge time Δt required to discharge the capacity corresponding to ΔDOD is calculated according to Δt=ΔDOD*SOHQ / Iref.

[0136] It should be noted that since the internal resistance growth rate SOHR and the capacity attenuation coefficient SOHQ are based on the first DC internal resistance DCR_BOL at the beginning of life and the nominal capacity Q nAs a benchmark, the internal resistance growth rate SOHR and capacity decay coefficient SOHQ at the beginning of life are both 1. Therefore, when calculating the first total discharge energy of the battery pack at the beginning of its life, the impact of internal resistance growth and capacity decay on the discharge process can be ignored. However, in some embodiments, the internal resistance growth rate SOHR and capacity decay coefficient SOHQ at the beginning of life can be preset, for example, set to a value close to 1, to better represent the internal resistance state and capacity state of the battery pack at the BOL stage.

[0137] In some optional embodiments, the thermal model Calculate the target cell temperature T_k+1 of the battery pack after discharge ΔDOD, where T amb,k is the ambient temperature at the kth iteration.

[0138] In an embodiment of the present application, when performing an iterative operation, the heating power of the battery pack at each iterative step and the required discharge time are calculated, and the target cell temperature after discharge of the battery pack is calculated in combination with the initial cell temperature, heat generation coefficient and heat dissipation time constant of the battery pack. The target cell temperature is calculated by taking into account the energy consumed by the heat generated by the internal resistance of the cell during the discharge process, thereby improving the accuracy of the discharge energy calculation.

[0139] Step a3: determining the target cell internal resistance corresponding to the target depth of discharge according to the target cell temperature.

[0140] Specifically, after the battery pack is discharged by ΔDOD, the cell temperature rises to the target cell temperature. The target depth of discharge at this time is the target depth of discharge DOD_k+1 after iterating k+1 ΔDOD.

[0141] Specifically, based on the target cell temperature T_k+1, the relationship parameters R0[DOD] and Rb[DOD] between the cell internal resistance and the cell temperature, the target cell internal resistance Rt_k+1[DOD_k, T_k+1] corresponding to the target depth of discharge DOD_k+1 after k+1 iterations of ΔDOD is calculated.

[0142] Step a4: determining the first discharge energy or the second discharge energy corresponding to the target discharge depth according to the target cell internal resistance, the capacity attenuation coefficient, and the internal resistance growth rate corresponding to the target discharge depth.

[0143] Specifically, the target terminal voltage corresponding to the target discharge depth is determined based on the target cell internal resistance, the internal resistance growth rate corresponding to the target discharge depth, the open-circuit voltage of the battery pack, and the reference current. The first discharge energy or second discharge energy corresponding to the target discharge depth is determined based on the capacity attenuation coefficient, the target terminal voltage corresponding to the target discharge depth, the target terminal voltage at the previous discharge depth, and the nominal capacity of the battery pack.

[0144] In some optional embodiments, the target terminal voltage Vt_DOD(k+1) corresponding to the target depth of discharge DOD_k+1 can be calculated according to Vt_DOD(k+1)=OCV_DOD_(k+1)-Iref*R_k+1[DOD_k,T_k+1]*SOHR, where OCV_DOD_(k+1) is the open circuit voltage corresponding to the target depth of discharge DOD_k+1.

[0145] Furthermore, according to the formula ΔE=ΔDOD*Q n *SOHQ*(V_DOD(k)+V_DOD(k+1)) / 2, calculate the accumulated discharge energy ΔE within a single iteration step.

[0146] As the battery cells age, the power value that the battery pack can provide at the end of discharge will also decrease, that is, the terminal voltage will also change. This embodiment improves the calculation accuracy of the discharge energy by considering the power attenuation and heat generation at the end of discharge of the battery pack.

[0147] In an embodiment of the present application, the target terminal voltage corresponding to the target discharge depth is calculated by the internal resistance growth rate of the battery after aging, thereby considering the influence of power attenuation and heat generation at the discharge end of the battery pack on the discharge energy, and further combining the capacity attenuation coefficient, nominal capacity and target terminal voltage of the battery pack to calculate the first discharge energy or the second discharge energy corresponding to the target discharge depth with higher accuracy.

[0148] Step a5: Enter the iterative operation corresponding to the next discharge depth.

[0149] Specifically, if the target terminal voltage after the ΔDOD discharge is less than the set discharge cut-off voltage V terminal Or if DOD_k exceeds the maximum allowed iteration DOD, namely DOD_end, the iteration process is exited, and the total discharge energy E of the entire iteration process, namely the first total discharge energy E_BOL or the second total discharge energy E_MOL, is calculated based on the formula E=∑ΔE.

[0150] The above embodiment calculates the discharge energy corresponding to the target depth of discharge by performing an iterative operation, wherein the starting cell internal resistance is first determined by the starting cell temperature, and then the target cell internal resistance is determined by combining the capacity attenuation coefficient of the battery pack and taking into account the heat generation consumption of the cell internal resistance. The discharge energy corresponding to the target depth of discharge is then determined using the capacity attenuation coefficient of the battery pack, the internal resistance growth rate, and the target cell internal resistance. This comprehensively considers the capacity attenuation after battery aging, the increase in internal resistance, and the impact of the electrothermal effect on power, resulting in a more accurate discharge energy.

[0151] Step S203 : determining the energy health of the battery pack in a subsequent life stage according to the first total discharge energy and the second total discharge energy.

[0152] Specifically, at different life stages, an iterative calculation method based on electrothermal coupling is used to update the input for calculating the total discharge energy in real time using the SOHQ and SOHR at different life stages, and then calculate the energy value E_MOL released in the subsequent life stages, and calculate the energy health of the battery pack using the formula SOCE=E_MOL / E_BOL.

[0153] In step S203, the lower the capacity attenuation coefficient SOHQ of the battery pack in the subsequent stage of life compared to the initial stage of life or the higher the internal resistance growth rate SOHR, the smaller the second discharge total energy E_MOL, and the smaller the ratio between the second discharge total energy E_MOL and the first discharge total energy E_BOL, that is, the lower the energy health of the battery pack in the subsequent stage of life.

[0154] This embodiment accurately calculates the second total discharge energy that the battery pack can release in the later stages of its life based on the capacity decay coefficient and internal resistance growth rate of the battery pack in the later stages of its life. The lower the capacity decay coefficient or the higher the internal resistance growth rate, the smaller the second total discharge energy released. The second total discharge energy is then compared with the first total discharge energy released by the battery pack at the beginning of its life to determine the change in energy health of the battery pack in the later stages of its life.

[0155] This application is based on measured battery cell data, taking into account the aging of capacity and the increase in internal resistance at different life stages, the heat generation of the battery cells after aging, and the heat dissipation under different heat dissipation configurations, and then calculates the actual energy value that can be released. Based on the calculated energy values ​​at different life stages, the energy health is accurately calculated.

[0156] The method for calculating the energy health of the battery pack provided in this embodiment takes into account the consistency deviation of the state of charge of the battery cell at the beginning of the life of the battery pack and the subsequent life stage, and accurately determines the discharge depth interval for the iterative calculation of the energy according to the state of charge usage interval corresponding to the corresponding stage and the state of charge deviation of the battery cell. Then, the discharge depth interval is used for iterative calculation, and the capacity attenuation coefficient, internal resistance growth rate and electrothermal effect after aging of the battery pack are taken into account to determine the discharge energy corresponding to each discharge depth of the battery pack, so as to calculate the first total discharge energy and the second total discharge energy corresponding to the beginning of the life of the battery pack and the subsequent life stage respectively according to the sum of the discharge energies, and determine the energy health of the battery pack in the subsequent life stage according to the ratio of the second total discharge energy to the first total discharge energy. This application takes into account the influence of the deterioration of cell consistency, internal resistance growth, capacity attenuation and electrothermal effect on the total discharge energy after aging of the battery pack, iteratively calculates the total discharge energy of the battery pack at different life stages, and then calculates the energy health of the battery pack with higher accuracy and reliability.

[0157] The following takes the vehicle as an example and combines a specific application example to explain in detail the calculation method of the battery pack energy health of the present application. During the use of the battery pack of the entire vehicle, first calculate the reference current under specific working conditions, and discharge the capacity value and internal resistance value of the battery pack under the reference current to test; calculate the heat generation coefficient and heat dissipation time constant of the battery pack when the water cooling is turned on and off based on the discharge data; calculate the change of the internal resistance growth rate SOHR based on specific working conditions during the charging process; record the consistency deviation of the fully charged battery cell when fully charged; and update the capacity attenuation coefficient SOHQ of the battery pack based on the two-point cumulative charge method during use. Then, at the beginning of life stage BOL and the subsequent life stage MOL, the total discharge energy corresponding to the beginning of life stage BOL and the subsequent life stage MOL are iteratively calculated based on the electrothermal coupling method, and then the energy health SOCE of the battery pack is calculated.

[0158] like Figure 4 As shown, this application example includes the following steps:

[0159] Step 1: Calculate the equivalent power of the battery pack using the root mean square method, and divide the equivalent power by the nominal voltage of the battery pack to obtain the reference current of the battery pack.

[0160] Step 2: Perform a constant capacity test on the battery pack using a reference current at room temperature to obtain the nominal capacity of the battery pack at the beginning of its life.

[0161] Step 3: Determine the relationship parameters between the internal resistance of the battery cell and the temperature of the battery cell.

[0162] Step 4: Determine the heat generation coefficient and heat dissipation time constant of the battery pack, and distinguish between the operating conditions when the water cooling system is turned on and when the water cooling system is turned off.

[0163] Step 5: During the charging process, the internal resistance of the battery pack at different life stages is calculated based on the voltage change and current change under specific operating conditions, and the internal resistance growth rate of the battery pack in the subsequent life stages is calculated.

[0164] Step 6: Determine the remaining capacity of the battery pack at different life stages based on the state of charge obtained from the two OCV table lookups and the accumulated power during the period, and calculate the capacity attenuation coefficient of the battery pack in the subsequent life stages.

[0165] Step 7: Based on the above parameters and the iterative calculation method of electrothermal coupling, calculate the first discharge total energy and the second discharge total energy of the battery pack at the beginning of its life and the subsequent stage of its life, and then use the ratio of the second discharge total energy to the first discharge total energy to calculate the energy health of the battery pack.

[0166] Specifically, the iterative calculation method based on electrothermal coupling can be found in Figure 5 As shown, the following steps are included:

[0167] Step 71 : Determine a depth of discharge interval based on the state of charge usage intervals at different life stages and the state of charge deviations of the battery cells.

[0168] Step 72 , starting iteration with the starting value of the discharge depth interval as the iteration starting point, the reference current as the discharge current, and setting the iteration step size.

[0169] Step 73 , determining the starting cell temperature in the current iteration process, and then determining the starting cell internal resistance using the relationship parameter between the cell internal resistance and the cell temperature.

[0170] Step 74 , calculating the heating power based on the capacity attenuation coefficient and the starting cell internal resistance, and calculating the target cell temperature based on the starting cell temperature, heating power, heat generation coefficient, and heat dissipation time constant.

[0171] Step 75 : determining the target cell internal resistance according to the target cell temperature and the relationship parameter between the cell internal resistance and the cell temperature.

[0172] Step 76, calculate the terminal voltage of the battery pack according to the target cell internal resistance, internal resistance growth rate, open circuit voltage and reference current, and determine the discharge energy using the terminal voltage, capacity attenuation coefficient and nominal capacity.

[0173] Step 77, determine whether the iteration condition is met, if not, proceed to the next iteration step.

[0174] This application proposes a framework based on electrothermal coupling, which refers to specific working conditions and iteratively calculates the total discharge energy of the battery pack at different life stages, thereby deriving the health of the battery pack in the energy dimension.

[0175] This application takes into account the measured data of the battery cells and the relationship between temperature and internal resistance, and updates the internal resistance growth rate SOHR and capacity attenuation coefficient SOHQ in real time during the use of the battery pack in the entire vehicle. It takes into account the heat dissipation configuration of the pack, the heat generation and heat dissipation, and then iteratively calculates the energy values ​​at different life stages based on the electrothermal coupling calculation method, thereby determining the energy health of the battery pack.

[0176] This application can be used to calculate the energy health of vehicle battery packs, taking into account the capacity value, internal resistance value and SOC usage range at different life stages, and calculating the discharge energy in different SOC ranges at different life stages of the battery pack. The temperature rise during the discharge process is calculated through a thermal model predicted by temperature, and then the energy consumed by the heat generated by the internal resistance during the discharge process is calculated. At the same time, the change in internal resistance after the temperature rise of the battery pack is determined with reference to the relationship between temperature and internal resistance, and then the power performance of the battery pack after aging is evaluated. The depth of discharge at the end of the discharge of the battery pack is calculated through an iterative scheme, and the total discharge energy during the discharge process is calculated in combination with the voltage change during the iterative process. The total discharge energy of the battery pack at different life stages is then iteratively calculated to determine the energy health of the battery pack at different life stages.

[0177] Compared with the traditional method of calculating energy through table lookup, this application will refer to the unique operating conditions and battery pack aging conditions of each vehicle to calculate the total discharge energy at different life stages, and then calculate the energy health of each battery pack after aging; and consider the electrothermal coupling effect of each battery pack after aging, iteratively predict the temperature rise and heat consumption of battery packs with different aging degrees during the discharge process, and further calculate the total discharge energy at different battery cell temperatures, and then calculate the energy health at different life stages; it also considers the consistency deviation of the battery cells after aging and the power attenuation after aging, and then more accurately calculates the energy value of the battery pack under specific working conditions and the energy health at different life stages.

[0178] In this embodiment, a device for calculating the energy health of a battery pack is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be repeated here. As used below, the term "module" may be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

[0179] This embodiment provides a device for calculating the energy health of a battery pack. Figure 6 Shown, including:

[0180] A first processing module 601 is configured to determine, at the beginning of a battery pack's life, a first depth of discharge interval based on a first state of charge usage interval and a first state of charge deviation, where the first state of charge deviation indicates a difference between states of charge of cells of the battery pack under a target charging condition at the beginning of the life; determine a first discharge energy corresponding to each first depth of discharge in the first depth of discharge interval; and determine a first total discharge energy based on each first discharge energy.

[0181] A second processing module 602 is configured to determine, in a subsequent life stage after the initial life stage of the battery pack, a second depth of discharge interval based on the second state of charge usage interval and the second state of charge deviation, where the second state of charge deviation indicates a difference between the states of charge of the battery cells of the battery pack under a target charging condition in the subsequent life stage; determine a second discharge energy corresponding to each second depth of discharge in the second depth of discharge interval; and determine a second total discharge energy based on each second discharge energy.

[0182] The third processing module 603 is configured to determine the energy health of the battery pack in a subsequent life stage according to the first total discharge energy and the second total discharge energy.

[0183] In some optional embodiments, the device is further used to:

[0184] Determine a first DC internal resistance of the battery pack at the beginning of its life and a second DC internal resistance at a later stage of its life, and calculate the internal resistance growth rate of the battery pack at the later stage of its life based on the ratio of the second DC internal resistance to the first DC internal resistance;

[0185] According to the internal resistance growth rate of the battery pack in the subsequent life stage, the internal resistance growth rate corresponding to the target discharge depth is determined.

[0186] In some optional embodiments, the device is further used to:

[0187] At the beginning of the battery pack's life, determine the nominal capacity of the battery pack;

[0188] During a subsequent lifespan of the battery pack, determining a first state of charge of the battery pack at a first time point, a second state of charge at a second time point, and an accumulated charge between the first time point and the second time point; and obtaining a remaining capacity based on the accumulated charge, the first state of charge, and the second state of charge;

[0189] Calculating a capacity attenuation coefficient of the battery pack in a subsequent lifespan based on a ratio of the remaining capacity to the nominal capacity, wherein the ratio of the remaining capacity to the nominal capacity is within a preset range;

[0190] According to the capacity attenuation coefficient of the battery pack in the subsequent stages of its life, the capacity attenuation coefficient corresponding to the target depth of discharge is determined.

[0191] In some optional embodiments, the discharge energy corresponding to the target discharge depth is determined by an iterative operation corresponding to the target discharge depth, where the target discharge depth is the first discharge depth or the second discharge depth. The iterative operation performed by the first processing module 601 or the second processing module 602 includes:

[0192] Determine the starting cell internal resistance corresponding to the target depth of discharge based on the starting cell temperature corresponding to the target depth of discharge;

[0193] Determine the target cell temperature corresponding to the target depth of discharge based on the target depth of discharge, the starting cell temperature, the starting cell internal resistance, and the capacity attenuation coefficient corresponding to the target depth of discharge;

[0194] Determine the target cell internal resistance corresponding to the target discharge depth based on the target cell temperature;

[0195] The first discharge energy or the second discharge energy corresponding to the target discharge depth is determined according to the target cell internal resistance, the capacity attenuation coefficient, and the internal resistance growth rate corresponding to the target discharge depth.

[0196] In some optional implementations, the first processing module 601 or the second processing module 602 is further configured to:

[0197] Determine the heat generation power of the battery pack from the previous discharge depth to the target discharge depth based on the starting cell internal resistance and the battery pack's reference current;

[0198] Determine the discharge duration based on the previous discharge depth, target discharge depth, reference current, and capacity attenuation coefficient corresponding to the target discharge depth;

[0199] Determine the target cell temperature corresponding to the target depth of discharge based on the starting cell temperature, heat generation power, discharge time, heat generation coefficient of the battery pack, and heat dissipation time constant.

[0200] In some optional embodiments, the first processing module 601 or the second processing module 602 is further configured to: determine a target terminal voltage corresponding to the target depth of discharge based on the target cell internal resistance, the internal resistance growth rate corresponding to the target depth of discharge, the open circuit voltage of the battery pack, and the reference current;

[0201] The first discharge energy or the second discharge energy corresponding to the target discharge depth is determined according to the capacity attenuation coefficient, the target terminal voltage corresponding to the target discharge depth, the target terminal voltage of the previous discharge depth, and the nominal capacity of the battery pack.

[0202] In some optional implementations, the third processing module 603 is further configured to:

[0203] The energy health of the battery pack in the subsequent stage of its life is obtained based on the ratio between the second total discharge energy and the first total discharge energy; wherein, the lower the capacity attenuation coefficient of the battery pack in the subsequent stage of its life compared with the initial stage of its life or the higher the internal resistance growth rate, the smaller the second total discharge energy, and the lower the energy health of the battery pack in the subsequent stage of its life.

[0204] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0205] The battery pack energy health calculation device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0206] The embodiment of the present application also provides a computer device having the above Figure 6 The device for calculating the energy health of a battery pack is shown.

[0207] See also Figure 7 , Figure 7 This is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present application. Figure 7 As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 7 A processor 10 is taken as an example.

[0208] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0209] The memory 20 stores instructions that can be executed by at least one processor 10, so as to enable at least one processor 10 to execute the method shown in the above embodiment.

[0210] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0211] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0212] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 7 The bus connection is taken as an example.

[0213] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touch pad, an indicator stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor). The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display, and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0214] The embodiments of the present application also provide a computer-readable storage medium. The above-mentioned method according to the embodiment of the present application can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0215] Part of the present application may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present application through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes but is not limited to a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0216] Although the embodiments of the present application have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations shall fall within the scope defined by the appended claims.

Claims

1. A method for calculating the energy health of a battery pack, characterized in that: The method comprises: At the beginning of the life of the battery pack, a first depth of discharge interval is determined based on the first state of charge usage interval and the first state of charge deviation, where the first state of charge deviation indicates a difference between the states of charge of the battery cells of the battery pack under a target charging condition at the beginning of the life; a first discharge energy corresponding to each first depth of discharge in the first depth of discharge interval is determined; and a first total discharge energy is determined based on each first discharge energy; In a subsequent life stage after the initial life stage of the battery pack, determining a second depth of discharge interval based on the second state of charge usage interval and the second state of charge deviation, the second state of charge deviation indicating a difference between the states of charge of the battery cells of the battery pack under a target charging condition in the subsequent life stage; determining a second discharge energy corresponding to each second depth of discharge in the second depth of discharge interval; and determining a second total discharge energy based on each second discharge energy. An energy health of the battery pack in a subsequent lifespan stage is determined based on the first discharge total energy and the second discharge total energy.

2. The method according to claim 1, characterized in that The discharge energy corresponding to the target discharge depth is determined by an iterative operation corresponding to the target discharge depth, where the target discharge depth is the first discharge depth or the second discharge depth. The iterative operation includes: Determine the starting cell internal resistance corresponding to the target depth of discharge based on the starting cell temperature corresponding to the target depth of discharge; Determining a target cell temperature corresponding to the target depth of discharge according to the target depth of discharge, the starting cell temperature, the starting cell internal resistance, and a capacity attenuation coefficient corresponding to the target depth of discharge; Determining a target cell internal resistance corresponding to a target depth of discharge according to the target cell temperature; A first discharge energy or a second discharge energy corresponding to the target discharge depth is determined according to the target cell internal resistance, the capacity attenuation coefficient, and the internal resistance growth rate corresponding to the target discharge depth.

3. The method according to claim 2, characterized in that The determining the target cell temperature corresponding to the target depth of discharge according to the target depth of discharge, the starting cell temperature, the starting cell internal resistance, and the capacity attenuation coefficient corresponding to the target depth of discharge includes: Determining the heat generation power of the battery pack from the previous depth of discharge to the target depth of discharge based on the starting cell internal resistance and the reference current of the battery pack; Determining a discharge duration based on a previous depth of discharge, a target depth of discharge, the reference current, and a capacity decay coefficient corresponding to the target depth of discharge; A target cell temperature corresponding to a target depth of discharge is determined according to the starting cell temperature, the heating power, the discharge duration, the heat generation coefficient of the battery pack, and the heat dissipation time constant.

4. The method according to claim 2, characterized in that Determining a first discharge energy or a second discharge energy corresponding to the target discharge depth according to the target cell internal resistance, the capacity attenuation coefficient, and the internal resistance growth rate corresponding to the target discharge depth includes: Determine the target terminal voltage corresponding to the target depth of discharge based on the target cell internal resistance, the internal resistance growth rate corresponding to the target depth of discharge, the open circuit voltage of the battery pack, and the reference current; The first discharge energy or the second discharge energy corresponding to the target discharge depth is determined according to the capacity attenuation coefficient, the target terminal voltage corresponding to the target discharge depth, the target terminal voltage of the previous discharge depth, and the nominal capacity of the battery pack.

5. The method according to any one of claims 2 to 4, characterized in that The method further comprises: Determine a first DC internal resistance of the battery pack at the beginning of its life and a second DC internal resistance at a later stage of its life, and calculate the internal resistance growth rate of the battery pack at the later stage of its life based on the ratio of the second DC internal resistance to the first DC internal resistance; According to the internal resistance growth rate of the battery pack in the subsequent life stage, the internal resistance growth rate corresponding to the target discharge depth is determined.

6. The method according to any one of claims 2 to 4, characterized in that The method further comprises: At the beginning of the battery pack's life, determine the nominal capacity of the battery pack; In a subsequent lifespan of the battery pack, determining a first state of charge of the battery pack at a first time point, a second state of charge at a second time point, and an accumulated charge of the battery pack between the first time point and the second time point; and obtaining a remaining capacity based on the accumulated charge, the first state of charge, and the second state of charge; Calculating a capacity attenuation coefficient of the battery pack in a subsequent lifespan based on a ratio of the remaining capacity to the nominal capacity, wherein the ratio of the remaining capacity to the nominal capacity is within a preset range; According to the capacity attenuation coefficient of the battery pack in the subsequent stages of its life, the capacity attenuation coefficient corresponding to the target depth of discharge is determined.

7. The method according to any one of claims 2 to 4, characterized in that The determining of the energy health of the battery pack in a subsequent life stage according to the first discharge total energy and the second discharge total energy includes: The energy health of the battery pack in the subsequent stage of its life is obtained based on the ratio between the second total discharge energy and the first total discharge energy; wherein, the lower the capacity attenuation coefficient of the battery pack in the subsequent stage of its life compared with the initial stage of its life or the higher the internal resistance growth rate, the smaller the second total discharge energy, and the lower the energy health of the battery pack in the subsequent stage of its life.

8. A device for calculating the energy health of a battery pack, characterized in that: The device comprises: a first processing module, configured to determine, at a beginning stage of the life of the battery pack, a first depth of discharge interval based on a first state of charge usage interval and a first state of charge deviation, wherein the first state of charge deviation indicates a difference between states of charge of cells of the battery pack under a target charging condition at the beginning stage of the life; determine a first discharge energy corresponding to each first depth of discharge in the first depth of discharge interval; and determine a first total discharge energy based on each first discharge energy; a second processing module, configured to determine, in a subsequent life stage after the initial life stage of the battery pack, a second depth of discharge interval based on the second state of charge usage interval and the second state of charge deviation, wherein the second state of charge deviation indicates a difference between the states of charge of the battery cells of the battery pack under a target charging condition in the subsequent life stage; determine a second discharge energy corresponding to each second depth of discharge in the second depth of discharge interval; and determine a second total discharge energy based on each second discharge energy; The third processing module is used to determine the energy health of the battery pack in a subsequent life stage according to the first total discharge energy and the second total discharge energy.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for calculating the energy health of a battery pack according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for calculating the energy health of a battery pack according to any one of claims 1 to 7.

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