CN114859256A - Method and device for predicting remaining available energy of battery pack - Google Patents

Abstract

The invention relates to the technical field of power batteries, in particular to a method and a device for predicting the residual available energy of a battery pack, wherein the method comprises the following steps: determining a future charge state sequence according to the current charge state, the cut-off charge state and the set charge sequence difference of the battery pack; determining a corresponding future maximum current sequence according to the battery pack temperature and the future state of charge sequence; determining a future terminal voltage sequence of the battery pack according to the future maximum current sequence, the future state of charge sequence and the battery pack temperature; and determining the available battery energy of the battery pack according to the future terminal voltage sequence, the battery pack capacity and the set charge sequence difference of the battery pack. The scheme can solve the problems that the prediction precision of the residual available energy of the battery pack is difficult to guarantee or the process is complicated and the workload is large in the prior art.

Description

Method and device for predicting remaining available energy of battery pack

technical field

The invention relates to the technical field of power batteries, in particular to a method and device for predicting the remaining available energy of a battery pack.

Background technique

At present, the main methods for estimating the remaining available energy of lithium-ion batteries are as follows: 1) According to the standard temperature, standard discharge current and battery internal resistance, the nominal capacity of the battery is obtained by testing, and the temperature-current-SOC three-dimensional surface is drawn. The current temperature of the battery, the current SOC, the nominal capacity of the battery, the internal resistance of the battery and the future current of the battery are used to estimate the remaining available energy, and the remaining available energy of the battery is further calculated by combining the current terminal voltage, the internal resistance of the battery and the future current of the battery; 2) The current state of charge (SOC) is determined as a measure of the current capacity of the battery, based on at least one of battery-related parameters (current, internal resistance, maximum state of charge and minimum state of charge), and the power consumption mode is collected to calculate the energy state; The energy state estimation model of electric energy and thermal energy, measures the external power consumption, internal ohmic heat energy, polarization heat energy and entropy heat production under different discharge rates, obtains the maximum available energy under different discharge rates, and simulates the maximum theoretical total energy and each 4) Detect the temperature of the battery; according to the temperature and the first correspondence between the pre-stored temperature and the capacity of the battery, determine the battery's capacity at this temperature capacity; determine the SOC of the battery according to the battery capacity; determine the open circuit voltage of the battery under the SOC of the battery according to the second correspondence between the SOC of the battery and the pre-stored SOC and the open circuit voltage of the battery; and according to the capacity of the battery, the open circuit voltage and the battery current to estimate the energy state of the battery.

Some of the above methods need to predict the future current to determine the future terminal voltage of the battery, but without GPS, the current prediction accuracy is difficult to guarantee; some need to calibrate the external power consumption and internal ohmic heat energy under different discharge rates , polarization heat energy and entropy heat generation, the method is cumbersome and has a large workload; some only estimate the energy state of the battery based on the battery capacity, open circuit voltage and battery current, and the accuracy is difficult to guarantee.

SUMMARY OF THE INVENTION

In view of the defects existing in the prior art, the purpose of the present invention is to provide a method and device for predicting the remaining available energy of a battery pack, which can solve the problem that in the prior art, the prediction accuracy of the remaining available energy of the battery pack is difficult to guarantee or the process is cumbersome and the workload is heavy The problem.

In order to achieve the above purpose, the technical scheme adopted in the present invention is:

In one aspect, the present invention provides a method for predicting the remaining available energy of a battery pack, comprising the following steps:

Determine the future state of charge sequence according to the current state of charge of the battery pack, the cut-off state of charge and the difference between the set charge sequence;

Determine the corresponding future maximum current sequence according to the battery pack temperature and the future state of charge sequence;

Determine the future terminal voltage sequence of the battery pack according to the future maximum current sequence, the future state of charge sequence and the battery pack temperature;

The available battery energy of the battery pack is determined according to the future terminal voltage sequence of the battery pack, the capacity of the battery pack and the set charge sequence difference.

In some optional solutions, the current state of charge is determined according to the current total current of the battery pack, including:

确定电池组的当前荷电状态，其中，SOC_init为上电时刻的初始SOC，C_batt,sys为电池组的容量，I(t)为t时刻电池组总电流，t₀为上电时刻。according to

Determine the current state of charge of the battery pack, where SOC _init is the initial SOC at the time of power-on, C _batt,sys is the capacity of the battery pack, I(t) is the total current of the battery pack at time t, and t ₀ is the power-on time.

In some optional solutions, the determination of the future state of charge sequence according to the current state of charge of the battery pack, the cut-off state of charge and the difference between the set charge sequence includes:

According to SOC _pre,j =SOC(t)-j·ΔSOC, determine the future state of charge sequence, where j=1,2,...nn, SOC(t) is the current state of charge, and n is the future state of charge sequence The total number, SOC _pre,n >SOC _lim , SOC _lim is the cut-off state of charge, and ΔSOC is the set charge sequence difference.

In some optional solutions, the corresponding future maximum current sequence is determined according to the battery pack temperature and the future state of charge sequence, including:

Based on the battery pack temperature, state of charge and the maximum current calibration table, according to the battery pack temperature and the future state of charge sequence, determine the future maximum current sequence corresponding to the future state of charge sequence.

In some optional solutions, the determination of the future terminal voltage sequence of the battery pack according to the future maximum current sequence, the future state of charge sequence and the battery pack temperature includes:

Determine the open circuit voltage value and ohmic internal resistance according to the future state of charge sequence and battery pack temperature;

According to the open circuit voltage value, ohmic internal resistance and the future maximum current sequence, determine the future terminal voltage sequence of the battery pack.

In some optional solutions, according to the open circuit voltage value, the ohmic internal resistance and the future maximum current sequence, the future terminal voltage sequence of the battery pack is determined, including:

确定电池组未来端电压序列；according to

Determine the future terminal voltage sequence of the battery pack;

Among them, U _oc is the open-circuit voltage value, R ₀ is the ohmic internal resistance, I _pre,j is the jth maximum current, tau ₁ is the product of R ₁ and C ₁ , which represents the time constant of the R ₁ C ₁ network, tau ₂ is the product of R ₂ and C ₂ , representing the time constant of the R ₂ C ₂ network, U ₁ (0) is the voltage of the R ₁ C ₁ network at time t-ΔT, and U ₂ (0) is the R ₂ C ₂ network The voltage at time t-△T, △T is a scheduling period, R ₁ is the concentration polarization internal resistance, R ₂ is the electrochemical polarization internal resistance, C ₁ is the concentration polarization capacitance, and C ₂ is the electrochemical electrode capacitor, t is the current moment.

In some optional solutions, determining the available battery energy of the battery pack according to the future terminal voltage sequence of the battery pack, the capacity of the battery pack and the set charge sequence difference, includes:

确定当前时刻电池组的可用电池能量RDE(t)，其中，n＝max{j|U_pre,j>U_lim∩SOC_pre,j>SOC_lim,j＝1,2,…}，U_lim为截止端电压，SOC_lim为截止荷电状态，U_pre,j为第j个电池组未来端电压，ΔSOC为设定荷电序列差，C_batt,sys为电池组的容量。according to

Determine the available battery energy RDE(t) of the battery pack at the current moment, where n=max{j|U _pre,j >U _lim ∩SOC _pre,j >SOC _lim ,j=1,2,…}, U _lim is Cut-off terminal voltage, SOC _lim is the cut-off state of charge, U _pre,j is the future terminal voltage of the jth battery pack, ΔSOC is the set charge sequence difference, and C _batt,sys is the capacity of the battery pack.

In some optional solutions, after the available battery energy of the battery pack is determined, the RDE(t) is also smoothed according to RDE(t) _smooth =RDE(t)-E _ΔSOC , where E _ΔSOC =∫I( t) · U(t)dt, I(t) is the total current of the battery pack at the current moment, and U(t) is the total voltage of the battery pack at the current moment.

In some optional solutions, the battery pack temperature is the real-time battery pack temperature at the current moment, or the predicted battery pack temperature after a set time period at the current moment according to the rate of change of the historical battery pack temperature.

On the other hand, the present invention also provides a device for predicting the remaining available energy of a battery pack, comprising:

a state-of-charge determination module, configured to determine a future state-of-charge sequence according to the current state of charge of the battery pack, the cut-off state of charge and the difference between the set charge sequence;

a maximum current prediction module, which is used to determine the corresponding future maximum current sequence according to the battery pack temperature and the future state of charge sequence;

The terminal voltage prediction module is used to determine the future terminal voltage sequence of the battery pack according to the future maximum current sequence, the future state of charge sequence and the battery pack temperature;

The available battery energy prediction module is used to determine the available battery energy of the battery pack according to the future terminal voltage sequence of the battery pack, the battery pack capacity and the set charge sequence difference. Compared with the prior art, the present invention has the advantages that the scheme determines the corresponding future maximum current sequence based on the battery pack temperature and the future state of charge sequence, and uses the future maximum current as the future working condition, which is a conservative prediction of the remaining available energy. The foundation is laid; according to the future maximum current sequence, the future state of charge sequence and the temperature of the battery pack, the future terminal voltage sequence of the battery pack is determined, which improves the calculation accuracy of the future terminal voltage of the battery pack; according to the real-time updated battery pack future terminal voltage sequence, Determine the available battery energy of the battery pack, effectively improve the estimation accuracy of the remaining available energy, and reduce the risk of the vehicle lying down.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present application more clearly, the following briefly introduces the drawings that are used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative effort.

1 is a flowchart of a method for predicting the remaining available energy of a battery pack in an embodiment of the present invention;

Detailed ways

In order to make the purposes, 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 described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

FIG. 1 is a flowchart of a method for predicting the remaining available energy of a battery pack in an embodiment of the present invention. As shown in FIG. 1 , the present invention provides a method for predicting the remaining available energy of a battery pack, including the following steps:

S1: Determine the future state of charge sequence according to the current state of charge of the battery pack, the cut-off state of charge and the difference between the set charge sequence.

确定电池组的当前荷电状态，其中，SOC_init为上电时刻的初始SOC，C_batt,sys为电池组的容量，t₀为上电时刻，I(t)为t时刻电池组总电流，当前电池组总电流通过传感器采集获得。In some optional embodiments, the current state of charge is determined according to the current total current of the battery pack, specifically including, according to

Determine the current state of charge of the battery pack, where SOC _init is the initial SOC at the time of power-on, C _batt,sys is the capacity of the battery pack, t ₀ is the power-on time, and I(t) is the total current of the battery pack at time t, The current total current of the battery pack is obtained through sensor acquisition.

In this example, step S1 specifically includes: determining a future state of charge sequence according to SOC _pre,j =SOC(t)-j·ΔSOC, where j=1,2,...n, and SOC(t) is the current state of charge state, n is the total number of future state-of-charge sequences, SOC _pre,n >SOC _lim , SOC _lim is the cut-off state of charge, and ΔSOC is the set charge sequence difference. The off state of charge is the state of charge of the off discharge.

S2: Determine the corresponding future maximum current sequence according to the battery pack temperature and the future state of charge sequence.

In some optional embodiments, the future maximum current sequence corresponding to the future state of charge sequence is determined according to the battery pack temperature and the future state of charge sequence based on the battery pack temperature, the state of charge and the maximum current calibration table.

In this embodiment, the SOP (StatenofnPower, battery energy state) table of the battery pack is calibrated by the battery stand, that is, the battery pack temperature, state of charge and maximum current calibration table, and different battery pack temperatures and different states of charge can be calibrated. The corresponding maximum current calibration table below. By bringing the battery pack temperature and future state of charge sequence into the battery pack temperature, state of charge and maximum current calibration table, the future maximum current sequence corresponding to the future state of charge sequence at the battery pack temperature can be obtained.

S3: Determine the future terminal voltage sequence of the battery pack according to the future maximum current sequence, the future state of charge sequence and the battery pack temperature.

In some optional embodiments, step S3 includes:

S31: Determine the open circuit voltage value and the ohmic internal resistance according to the future state of charge sequence and the temperature of the battery pack.

By performing HPPC (HybridnPulsenPowernCharacteristic, hybrid power pulse characteristic) tests on the battery packs at different battery pack temperatures and different states of charge, the ohmic internal resistance R ₀ value at each battery pack temperature is calculated, and the temperature of each battery pack is fitted. The concentration polarization internal resistance R ₁ , the electrochemical polarization internal resistance R ₂ , the concentration polarization capacitance C ₁ and the electrochemical polarization capacitance C ₂ values under the following conditions.

The different states of charge in this example are, for example: within 0% to 10% SOC, a charge and discharge HPPC test is performed every 1% SOC, and within 10% to 100% SOC, a charge and discharge HPPC test is performed every 5%.

In some optional embodiments, the battery pack temperature is the real-time battery pack temperature at the current moment, or the predicted battery pack temperature after a set period of time at the current moment according to the rate of change of the historical battery pack temperature.

In this example, the current battery pack temperature collected in real time by the temperature sensor is used to predict the battery pack temperature. According to the historical battery pack temperature, the change trend of the battery temperature is fitted, and the predicted battery pack temperature at a certain time in the future can be predicted. The set time period in this example is 5-10 minutes. When the predictable working time of the battery pack is less than the set time period, the set time period can be halved, or the current temperature can be directly used as the battery pack temperature. Predicting the temperature of the battery pack based on the future can better reflect the future working state of the battery, which is to lay the foundation for the subsequent more accurate prediction of the available battery energy.

S32: Determine the future terminal voltage sequence of the battery pack according to the open circuit voltage value, the ohmic internal resistance and the future maximum current sequence.

确定电池组未来端电压序列。Step S32 specifically includes: establishing a second-order RC model of the future terminal voltage of the battery pack, and according to the second-order RC model of the future terminal voltage of the battery pack

Determine the future terminal voltage sequence of the battery pack.

Among them, U _oc is the open-circuit voltage value, R ₀ is the ohmic internal resistance, I _pre,j is the jth maximum current, tau ₁ is the product of R ₁ and C ₁ , which represents the time constant of the R ₁ C ₁ network, tau ₂ is the product of R ₂ and C ₂ , representing the time constant of the R ₂ C ₂ network, U ₁ (0) is the voltage of the R ₁ C ₁ network at time t-ΔT, and U ₂ (0) is the R ₂ C ₂ network The voltage at time t-△T, △T is a scheduling period of the RC model, R ₁ is the concentration polarization internal resistance, R ₂ is the electrochemical polarization internal resistance, C ₁ is the concentration polarization capacitance, and C ₂ is the electrochemical polarization capacitance, and t is the current moment.

S4: Determine the available battery energy of the battery pack according to the battery pack future terminal voltage sequence, the battery pack capacity and the set charge sequence difference.

In some optional embodiments, an RDE (Remainingn Dischargingn Energy, remaining available energy) calculation model is established based on the battery pack future terminal voltage sequence, battery pack capacity C _batt,sys and ΔSOC, and the battery pack future terminal voltage sequence, battery pack The capacity and the set charge sequence difference are brought into the RDE calculation model, namely:

确定当前时刻电池组的可用电池能量RDE(t)，其中，n＝max{j|U_pre,j>U_lim∩SOC_pre,j>SOC_lim,j＝1,2,…}，U_lim为截止端电压，SOC_lim为截止荷电状态，U_pre,j为第j个电池组未来端电压，ΔSOC为设定荷电序列差，C_batt,sys为电池组的容量。according to

Determine the available battery energy RDE(t) of the battery pack at the current moment, where n=max{j|U _pre,j >U _lim ∩SOC _pre,j >SOC _lim ,j=1,2,…}, U _lim is Cut-off terminal voltage, SOC _lim is the cut-off state of charge, U _pre,j is the future terminal voltage of the jth battery pack, ΔSOC is the set charge sequence difference, and C _batt,sys is the capacity of the battery pack.

In this example, the cut-off state of charge is the state of charge at the end of discharge, the cut-off terminal voltage is the terminal voltage of the battery pack at the end of discharge, and the cut-off state of charge and cut-off terminal voltage are both updated in real time according to the battery pack temperature, and the battery pack temperature is the current The real-time battery pack temperature at the time, or the predicted battery pack temperature after a set time period based on the historical battery pack temperature from the power-on time to the current moment, can make the estimation mechanism more accurate when the predicted battery pack temperature is used.

In this example, ΔSOC is the SOC interval. If ΔSOC is 1% and the current state of charge SOC is 80%, the SOC sequence SOC _pre,j is: 80%, 79%, 78%...2%, 1% , 0%, wherein the minimum SOC is determined by SOC _lim , not necessarily 0%, SOC _pre,n >SOC _lim .

In some optional embodiments, after the available battery energy of the battery pack is determined, the RDE(t) is also smoothed according to RDE(t) _smooth =RDE(t)-E _ΔSOC , where E _ΔSOC =∫I (t)·U(t)dt, I(t) is the total current of the battery pack at the current moment, and U(t) is the total voltage of the battery pack at the current moment.

In this embodiment, the upper and lower limits of the integration of E _ΔSOC =∫I(t)·U(t)dt are the start time and end time of the currently set charge sequence difference, for example, when ΔSOC is set to 1%, 80% In the -79% segment, the start time is the time when the SOC is 80%, and the end time is the time when the SOC is 79%. The ΔSOC in this algorithm is set to 1%. The calculated RDE(t) at this SOC interval has a jump problem. In order to reduce the jump, the watt-hour integration method is used to smooth the estimated value of RDE(t). Time integration method, the accumulated charge and discharge energy is updated every 1% SOC interval, and the available battery energy is smoothed, which can improve the operation speed.

On the other hand, the present invention also provides an apparatus for predicting the remaining available energy of a battery pack, comprising: a state of charge determination module, a state of charge determination module, a terminal voltage prediction module and an available battery energy prediction module.

The state of charge determination module is used to determine the future state of charge sequence according to the current state of charge of the battery pack, the cut-off state of charge and the set charge sequence difference; the maximum current prediction module is used to determine the future state of charge sequence according to the battery pack temperature and future state of charge The sequence determines the corresponding future maximum current sequence; the terminal voltage prediction module is used to determine the future terminal voltage sequence of the battery pack according to the future maximum current sequence, the future state of charge sequence and the temperature of the battery pack; the available battery energy prediction module is used to determine the future terminal voltage sequence of the battery pack according to the future The terminal voltage sequence, the battery pack capacity and the set charge sequence difference determine the available battery energy of the battery pack.

To sum up, this scheme determines the corresponding future maximum current sequence based on the battery pack temperature and the future state of charge sequence, and takes the future maximum current as the future working condition, which lays the foundation for the conservative prediction of the remaining available energy; according to the future maximum current Sequence, future state of charge sequence and battery pack temperature, determine the future terminal voltage sequence of the battery pack, improve the calculation accuracy of the battery pack future terminal voltage; update the battery pack future terminal voltage sequence, discharge cut-off SOC and discharge cut-off voltage in real time, effectively improving the The estimation accuracy of the remaining available energy reduces the risk of the vehicle lying down. Combined with the watt-hour integration, the estimation result of the remaining available energy is smoothed, and the range of the driving range is reduced, and the driving experience of the vehicle is effectively improved.

It should be noted that, in this application, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply Any such actual relationship or sequence exists between these entities or operations. Moreover, the terms "comprising", "comprising" or any other variation thereof are intended to encompass a non-exclusive inclusion such that a process, method, article or device that includes a list of elements includes not only those elements, but also includes not explicitly listed or other elements inherent to such a process, method, article or apparatus. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in a process, method, article or apparatus that includes the element.

The above descriptions are only specific embodiments of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, this application is not intended to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims (10)

1. A method for predicting the remaining available energy of a battery pack, comprising the following steps: Determine the future state of charge sequence according to the current state of charge of the battery pack, the cut-off state of charge and the difference between the set charge sequence; Determine the corresponding future maximum current sequence according to the battery pack temperature and the future state of charge sequence; Determine the future terminal voltage sequence of the battery pack according to the future maximum current sequence, the future state of charge sequence and the battery pack temperature; The available battery energy of the battery pack is determined according to the future terminal voltage sequence of the battery pack, the capacity of the battery pack and the set charge sequence difference. 2. The method for predicting the remaining available energy of a battery pack according to claim 1, wherein the current state of charge is determined according to the current total current of the battery pack, comprising: according to

Determine the current state of charge of the battery pack, where SOC _init is the initial SOC at the time of power-on, C _batt,sys is the capacity of the battery pack, I(t) is the total current of the battery pack at time t, and t ₀ is the power-on time. 3 . The method for predicting the remaining available energy of a battery pack according to claim 1 , wherein the future state of charge is determined according to the current state of charge of the battery pack, the cut-off state of charge and the difference of the set charge sequence. 4 . sequence, including: According to SOC _pre,j =SOC(t)-j·ΔSOC, determine the future state of charge sequence, where j=1,2,...n, SOC(t) is the current state of charge, and n is the future state of charge sequence The total number, SOC _pre,n >SOC _lim , SOC _lim is the cut-off state of charge, and ΔSOC is the set charge sequence difference. 4. The method for predicting the remaining available energy of a battery pack according to claim 1, wherein the determining the corresponding future maximum current sequence according to the battery pack temperature and the future state-of-charge sequence, comprising: Based on the battery pack temperature, state of charge and the maximum current calibration table, according to the battery pack temperature and the future state of charge sequence, determine the future maximum current sequence corresponding to the future state of charge sequence. 5. The method for predicting the remaining available energy of a battery pack according to claim 1, wherein the determining the future terminal voltage sequence of the battery pack according to the future maximum current sequence, the future state of charge sequence and the battery pack temperature, comprises: Determine the open circuit voltage value and ohmic internal resistance according to the future state of charge sequence and battery pack temperature; According to the open circuit voltage value, ohmic internal resistance and the future maximum current sequence, determine the future terminal voltage sequence of the battery pack. 6. The method for predicting the remaining available energy of a battery pack according to claim 1, wherein the determining the future terminal voltage sequence of the battery pack according to the open circuit voltage value, the ohmic internal resistance and the future maximum current sequence, comprises: according to

Determine the future terminal voltage sequence of the battery pack; Among them, U _oc is the open-circuit voltage value, R ₀ is the ohmic internal resistance, I _pre,j is the jth maximum current, tau ₁ is the product of R ₁ and C ₁ , which represents the time constant of the R ₁ C ₁ network, tau ₂ is the product of R ₂ and C ₂ , representing the time constant of the R ₂ C ₂ network, U ₁ (0) is the voltage of the R ₁ C ₁ network at time t-ΔT, and U ₂ (0) is the R ₂ C ₂ network The voltage at the time of t-△T, △T is a scheduling period, R ₁ is the concentration polarization internal resistance, R ₂ is the electrochemical polarization internal resistance, C ₁ is the concentration polarization capacitance, and C ₂ is the electrochemical polarization Polarization capacitance, t is the current moment. 7 . The method for predicting the remaining available energy of a battery pack according to claim 1 , wherein the available battery energy of the battery pack is determined according to the future terminal voltage sequence of the battery pack, the battery pack capacity and the difference between the set charge sequence. 8 . ,include: according to

Determine the available battery energy RDE(t) of the battery pack at the current moment, where n=max{j|U _pre,j >U _lim ∩SOC _pre,j >SOC _lim ,j=1,2,…}, U _lim is Cut-off terminal voltage, SOC _lim is the cut-off state of charge, U _pre,j is the future terminal voltage of the jth battery pack, ΔSOC is the set charge sequence difference, and C _batt,sys is the capacity of the battery pack. 8 . The method for predicting the remaining available energy of a battery pack according to claim 7 , wherein after determining the available battery energy of the battery pack, it is further based on RDE(t) _smooth =RDE(t)-E _ΔSOC versus RDE(t 8 . ) for smoothing, where E _ΔSOC =∫I(t)·U(t)dt, I(t) is the total current of the battery pack at the current moment, and U(t) is the total voltage of the battery pack at the current moment. 9. The method for predicting the remaining available energy of a battery pack according to claim 1, wherein the temperature of the battery pack is the real-time battery pack temperature at the current moment, or the predicted current moment is set according to the rate of change of the historical battery pack temperature. Predicted battery pack temperature after a certain period of time. 10. A device for predicting the remaining available energy of a battery pack, comprising: a state-of-charge determination module, configured to determine a future state-of-charge sequence according to the current state of charge of the battery pack, the cut-off state of charge and the difference between the set charge sequence; The maximum current prediction module, which is used to determine the corresponding future maximum current sequence according to the battery pack temperature and the future state of charge sequence, The terminal voltage prediction module is used to determine the future terminal voltage sequence of the battery pack according to the future maximum current sequence, the future state of charge sequence and the battery pack temperature; The available battery energy prediction module is used to determine the available battery energy of the battery pack according to the future terminal voltage sequence of the battery pack, the battery pack capacity and the set charge sequence difference.

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