Power battery low-temperature heating strategy determination method, battery management system and vehicle

Abstract

The application provides a power battery low-temperature heating strategy determination method, a battery management system and a vehicle, and belongs to the field of power battery thermal management. The method comprises the following steps: determining typical working conditions; determining a driving heating lower limit value, assuming a driving heating upper limit value, a charging heating lower limit value and a charging heating upper limit value under each typical working condition; obtaining multiple sets of simulation data through simulation tests by changing the assumed driving heating upper limit value, the charging heating lower limit value and the charging heating upper limit value, wherein the simulation data comprises heating opening times and heating energy consumption; determining optimal driving heating upper limit values, charging heating lower limit values and charging heating upper limit values according to the heating opening times and the heating energy consumption, and obtaining optimal heating strategies under each typical working condition. The heating strategy determination method provided by the application can take into account battery performance and heating energy consumption, meet the demand of the vehicle for the performance refinement and rationalization of the battery management system, and the existing heating mode can also determine the heating strategy according to the application.

Description

TECHNICAL FIELD

[0001] The application relates to a power battery low-temperature heating strategy determination method, a battery management system and a vehicle and belongs to the field of power battery thermal management. BACKGROUND

[0002] A low-temperature heating strategy of a power battery is an important link in the design of a power battery thermal management system. Determination of a reasonable low-temperature heating thermal management control strategy can not only ensure that the battery system works in a suitable temperature range and meets the demand of the whole vehicle on the battery charge-discharge rate, but also can reduce the increase of system energy consumption caused by battery heating, prolong the cruising range of an electric vehicle and enhance the core competitiveness of the product. Taking liquid heating as an example, at present, liquid heating has become a relatively common heating method for major vehicle manufacturers. However, the power of liquid PTC heating is larger than that of traditional electric heating film, and the heat transfer path of PTC heating is longer than that of electric heating film. The PTC heating method needs to heat the cooling liquid first, then heat the pipeline and cold plate through the cooling liquid and finally heat the battery.

[0003] There are many factors involved in the process of real vehicle operation. How to develop a reasonable, effective and safe heating strategy that takes into account the performance of the battery and the heating energy consumption has gradually become the key and difficult point in the design of a thermal management system.

[0004] At present, the power battery heating strategy is generally designed as fixed heating opening and closing thresholds, and the determination method of the strategy is usually determined by a large number of tests on various boundary conditions and is only considered from a single factor. However, as the requirements of the whole vehicle on the battery system are higher and higher, the performance of thermal management tends to be more refined and reasonable. The strategy should not only meet the heating rate and the charge-discharge rate, but also take into account the influence of heating energy consumption on the whole vehicle. The heating strategy determined simply to achieve the design performance of battery thermal management cannot meet the demand of the whole vehicle. A more complete heating strategy determination method is needed to meet the increasingly refined thermal management target. SUMMARY

[0005] The application aims to provide a power battery low-temperature heating strategy determination method, a battery management system and a vehicle, which are used to solve the problem that the existing strategy considers only a single factor and cannot meet the demand of the whole vehicle.

[0006] In order to achieve the above-mentioned purpose, the application provides a power battery low-temperature heating strategy determination method, which comprises the following steps:

[0007] 1) determining typical working conditions, the typical working conditions including ambient temperature, charge-discharge rate and starting temperature of vehicle driving; 2) under each typical working condition, determining the lower limit value of driving heating according to the relationship between the battery charge rate, discharge rate, feedback rate and temperature, assuming the upper limit value of driving heating, the lower limit value of charging heating and the upper limit value of charging heating; 3) determining the heating power and target water temperature for simulation calculation; 4) performing simulation test, establishing the driving heating window with the lower limit value and the upper limit value of driving heating, obtaining multiple different driving heating windows by changing the upper limit value of driving heating, performing simulation calculation on each driving heating window to obtain multiple groups of driving simulation data, the driving simulation data including the number of driving heating start and driving heating energy consumption; establishing the charging heating window with the lower limit value and the upper limit value of charging heating, obtaining multiple different charging heating windows by changing the lower limit value and the upper limit value of charging heating, performing simulation calculation on each charging heating window to obtain multiple groups of charging simulation data, the charging simulation data including the number of charging heating start and charging heating energy consumption; 5) determining the optimal driving heating window and the optimal charging heating window according to the number of driving heating start, driving heating energy consumption, the number of charging heating start and charging heating energy consumption, combining the optimal driving heating window and the optimal charging heating window to obtain the optimal heating strategy under each typical working condition.

[0008] The application obtains suitable heating strategies under various typical working conditions through big data working condition classification and simulation test, and obtains the optimal heating strategy by analyzing the specific effects of the heating strategies such as the number of heating start and heating energy consumption. The heating strategy obtained by the application can take into account the number of heating start and heating energy consumption, and can obtain the most suitable heating strategy according to the specific requirements of battery performance and energy consumption in actual situation, so that the heating strategy meets the requirements of actual situation and meets the demand of vehicle for fine thermal management of the battery management system.

[0009] Further, in the above-mentioned power battery low-temperature heating strategy determination method, the parameter values of the typical working conditions in step 1) are determined by big data statistics of the percentage of various parameters.

[0010] Further, in the above-mentioned power battery low-temperature heating strategy determination method, step 5) further includes identifying the demand of different heating strategies for charging capacity, excluding the charging heating window that cannot meet the charging capacity of the battery cell, and ensuring that the charging delay difference under the set typical working condition is within an acceptable range.

[0011] The application selects the charging capacity of the suitable heating strategy, excludes the heating strategy that cannot meet the charging capacity of the battery cell, avoids the risk that the optimal heating strategy obtained finally prolongs the charging time, and improves the accuracy of the optimal heating strategy.

[0012] Furthermore, in the above-mentioned method for determining the low-temperature heating strategy of power batteries, the method also includes evaluating the temperature difference between the cell temperature sampling point and the lowest temperature point in the cell's internal region during the execution of the optimal heating strategy through three-dimensional CFD simulation. If the temperature difference is greater than a set temperature threshold, the optimal heating strategy is adjusted.

[0013] By measuring the temperature difference between the cell temperature sampling point and the lowest cell temperature point using the final optimal heating strategy, if the temperature difference exceeds the set threshold, it indicates that the sampled cell temperature cannot fully reflect the cell temperature. The optimal heating strategy needs to be adjusted to avoid the situation where the cell temperature is too low and lithium plating occurs without heating being activated, thus improving the accuracy of the optimal heating strategy.

[0014] Furthermore, in the above method for determining the low-temperature heating strategy for power batteries, the heating power P0 mentioned in step 3) is calculated using the following formula:

[0015] P0η=(m P C p +m c C c +m l C l In the formula ΔT / t, ΔT / t is the heating rate, m P C is the total mass of the battery casing and cold plate in the battery circuit. p m is the specific heat capacity of the battery casing and cold plate in the battery circuit. c C represents the total mass of the battery cell. c For the specific heat capacity of the battery cell, m l C is the total mass of the coolant in the battery circuit. l η is the specific heat capacity of the coolant in the battery circuit, and η is the heating performance coefficient of the heating device.

[0016] Furthermore, in the above-mentioned method for determining the low-temperature heating strategy of the power battery, the target water temperature in step 3) is determined by comparing the low-temperature heating rate and the battery pack temperature difference corresponding to different target water temperatures.

[0017] The present invention also provides a battery management system that employs the above-mentioned method for determining the low-temperature heating strategy of power batteries.

[0018] The present invention also provides a vehicle, including a power battery and a battery management system, wherein the battery management system adopts the above-described battery management system. Attached Figure Description

[0019] Figure 1 This is a flowchart of the present invention;

[0020] Figure 2 The circuit diagram for the battery liquid thermal management system is shown below.

[0021] Wherein 1 is a battery and a water cooling plate, 2 is a liquid PTC, 3 is a circulating water pump, 4 is a liquid cooling unit, 5 is an expansion tank, 6 is a pipeline loop, 7 is a return water temperature monitoring point, 8 is an outlet water temperature monitoring point. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application is further described in detail below in combination with the drawings and examples.

[0023] Power battery low-temperature heating strategy determination method embodiment:

[0024] The flowchart of the present application is shown as follows: Figure 1 Firstly, the basic state of the battery is determined, i.e. the working condition and boundary condition of the battery. The typical working conditions under different temperature environments are obtained through big data analysis. The lower limit value of the driving process heating under each typical working condition is determined, i.e. the driving heating start temperature; the boundary parameters such as heating power and target water temperature are determined; the possible upper limit value of the driving process heating, the lower limit value of the charging process heating and the upper limit value of the charging process heating are simulated in matrix. The target values for measuring the heating strategy, such as battery performance, feedback ability, heating rate, temperature difference and heating energy consumption, are determined, and the optimal heating strategy for each typical working condition is matched in the simulation results. For special working conditions not belonging to the typical working conditions, the optimal heating strategy is determined through simulation experiment and classification according to the working condition type. Finally, it is evaluated whether the optimal heating strategy needs to be corrected for temperature difference, and the heating strategy not meeting the evaluation result is corrected for temperature difference.

[0025] Specific working process:

[0026] 1) Determine the basic state of the battery. Under specific working conditions and boundary conditions, the temperature drop of the battery pack is determined, and the heating strategy determined on this basis is meaningful. If the basic state of the battery changes, the finally determined optimal heating strategy will also change. The basic state of the battery includes the specific working condition and boundary condition of the battery. Under specific working conditions and boundary conditions, the temperature drop of the battery pack is determined, and the thermal management strategy can be determined on this basis.

[0027] According to the area where the vehicle travels, different heating strategy intervals are divided according to the environmental temperature interval corresponding to the environmental temperature statistical analysis of the big data, for example, region one is a severe cold region, the environmental temperature interval is determined as Tenv≤A℃, and the corresponding region is Heilongjiang, Jilin and other provinces; region two is a cold region, the environmental temperature interval is determined as A℃≤Tenv<B℃, and the corresponding region is Liaoning, Inner Mongolia, Gansu and other provinces; region three is a hot summer and cold winter region, the environmental temperature interval is determined as Tenv≥B℃, and this region generally does not need battery heating.

[0028] Determine the low temperature typical working condition corresponding to different environmental temperature intervals. Through big data vehicle information analysis, the typical environmental temperature, starting temperature, average discharge rate, charging rate, feedback rate and time corresponding to the environmental temperature of region one, region two and region three are analyzed by big data statistical analysis, and the distribution information of the environmental temperature, starting temperature, average discharge rate, charging rate, feedback rate and time is determined. Some distribution information is shown in Table One. According to the distribution information, the key parameters are determined according to the specific requirements, and the key parameters represent the typical working conditions corresponding to different environmental temperature intervals. The typical working condition parameters obtained are shown in Table Two.

[0029] Table One Distribution table of temperature information in different regions

[0030] Start temperature ℃ Temperature proportion of region one Temperature proportion of region two ＞-20 90％ 100％ ＞-15 85％ 95％ ＞-10 80％ 90％ ＞-5 75％ 85％ ＞0 70％ 80％

[0031] Table Two Typical working condition parameter table of different regions

[0032]

[0033] In the above table, the determination of the typical parameter value of the working condition in region one and region two is mainly determined by the percentage of big data statistics. Taking the environmental temperature as an example, it is assumed that the big data analysis shows that the environmental temperature greater than-20℃ can cover 90% of the environmental temperature conditions in the region, then the temperature value can be considered as the typical environmental temperature of the region, and the determination of other typical parameter values is the same as the above.

[0034] 2) Obtain the battery MAP, which represents the relationship between battery temperature and battery driving discharge rate, driving feedback rate and DC external charging rate. Since the battery has the lowest demand for battery rate during driving and charging, the driving heating lower limit value is determined according to the requirements of battery driving discharge rate and feedback rate under typical working condition and set as p℃. The driving heating upper limit value is set as q℃, which needs to be combined with the subsequent heating energy consumption to determine. The charging heating lower limit value is set as m℃, and the charging heating upper limit value is set as n℃. Considering that the further increase of heating temperature c℃ during charging process is beneficial to the driving heating energy consumption, the charging process heating upper limit value is reset as (n+c)℃. The battery heating lower limit value is the heating start threshold in the driving process or the charging process, which is used to ensure that the battery has the basic feedback ability and external DC charging ability required by the whole vehicle; the battery heating upper limit value is the heating shutdown threshold in the driving process or the charging process, which is used to ensure that the battery has a certain feedback ability and external DC charging ability after heating to meet the specific requirements.

[0035] Considering that the battery pack can be heated by the waste heat of the cooling liquid after the liquid heating is completed, the temperature rise ΔT0 of the battery cells caused by the cooling liquid from the target water temperature to the normal temperature during the self-circulation process can be estimated by the following formula, the influence of ΔT0 should be considered when determining the upper limit value n ℃ of the charging heating, and the final PTC heating stop temperature n-ΔT0 ℃ is determined as the initial setting temperature when the liquid heating of the charging and driving PTC is completed. Wherein ΔT0 can be estimated by the following formula:

[0036] C 冷却液 m 冷却液 (t 加热结束水温 -t 自循环结束水温 )=KC 电芯比热 m 电芯总质量 ΔT0

[0037] Wherein K is an empirical coefficient, mainly affected by the pipeline, the cooling of the cooling plate and the outside, the heat capacity temperature rise of the cooling plate and the pipeline, in the specific calculation, the actual liquid heating system can be combined to estimate, also can be calibrated by experimental means; C 冷却液 is the specific heat capacity of the cooling liquid, the unit is J / (kg·℃); m 冷却液 is the total mass of the cooling liquid in the battery system circuit, the unit is kg, which can be obtained by calculating the mass of the cooling liquid in the pipeline and the cooling liquid in the liquid cooling plate; t 加热结束水温 is the outlet water temperature collected by the unit when the PTC heating stops, the unit is ℃; t 自循环结束水温 is the outlet water temperature collected by the unit when the water pump self-circulation stops, the unit is ℃; C 电芯比热 is the specific heat capacity of the battery cell, the unit is J / (kg·℃); m 电芯总质量 is the total mass of the battery cell in the battery system, the unit is kg; ΔT0 is the temperature rise of the battery cell through the self-circulation process after the PTC heating stops, the unit is ℃.

[0038] 3) Build a battery thermal management system circuit, the schematic diagram of the battery thermal management system circuit is shown in Figure 2 , including 1 battery and water cooling plate, 2 liquid PTC, 3 circulating water pump, 4 liquid cooling unit, 5 expansion tank, 6 pipeline circuit, 7 return water temperature monitoring point, 8 outlet water temperature monitoring point. Simulate the actual scene of the vehicle battery cabin, and carry out low temperature strategy experiment calibration for each typical working condition.

[0039] 4) Build a system simulation model, and correct the heat exchange between the battery system and the external environment in the simulation model through experimental calibration. Determine the PTC / electric heating film heating power and target water temperature boundary parameters under a certain typical working condition, carry out matrix simulation on different heating upper limit values or heating lower limit values that may meet the demand, and determine a set of optimal heating upper limit values and heating lower limit values for charging and driving as the optimal heating strategy through the way of exclusion one by one; or first determine the battery temperature, feedback capacity, heating rate, battery system temperature difference, and heating energy consumption as evaluation targets, and obtain the optimal heating strategy under a certain typical working condition through simulation calculation and comparison of the specific values of the evaluation targets.

[0040] Specifically, the PTC heating power is determined by the following formula:

[0041] P0η=(m P C p +m c C c +m l C l )·ΔT / t

[0042] Where ΔT / t is the heating rate, unit: ℃ / s; m P is the total mass of the battery shell and cold plate in the battery system loop, unit: kg; m c is the total mass of the battery cell, unit: kg; m l is the total mass of the battery loop cooling liquid, unit: kg; C p is the specific heat capacity of the battery shell and cold plate in the battery system loop, unit: J / (kg·℃); C c is the specific heat capacity of the battery cell, unit: J / (kg·℃); C l is the specific heat capacity of the battery loop cooling liquid, unit: J / (kg·℃), and η is the heating performance coefficient of the heater.

[0043] The target water temperature mainly affects the heating rate and temperature difference when the battery starting temperature is low. The target water temperature is determined by comparing the low-temperature heating rate and battery pack temperature difference targets corresponding to different target water temperatures; the battery pack temperature difference is determined by the temperature bearing capacity of the battery cell and the thermal conductive adhesive, and the temperature bearing capacity of the battery cell and the thermal conductive adhesive can be obtained by combining the three-dimensional CFD simulation evaluation safety risk process.

[0044] After determining the PTC power and the target water temperature, enter the strategy determination stage to enumerate the heating window that can meet the demand: the charging process strategy sets different charging heating windows according to the (m, n + c) ℃ temperature interval, that is, the corresponding charging heating window is set by changing the size of m, n and c, and the battery charging process is simulated according to the set charging heating window; the driving process strategy sets different driving heating windows according to the (p, q) ℃ temperature interval, that is, the corresponding driving heating window is set by changing the size of q, and the discharge process and feedback process in the driving of the battery are simulated according to the set charging heating window, wherein p is a determined value, and p can also be adjusted according to the situation, and when adjusting, the adjustment range of p is small to avoid affecting the power of the vehicle.

[0045] Generally, the higher the driving heating upper limit value is set, the larger the heating window is, the longer the single heating time is, the stronger the feedback ability of the battery in the heating interval is, but the single heating energy consumption is higher, and the time for cooling down to the starting threshold value again is prolonged; the higher the charging heating upper limit value is set, the larger the heating window is, the longer the single heating time is, and under the condition that the feedback demand of the whole vehicle is met, the single heating energy consumption is higher, but since the battery temperature is higher after charging is completed, it is helpful to improve the starting temperature of the battery in the driving stage. In addition, the driving heating window should not be too small, and the reasons are as follows: 1) to ensure that the heating strategy will not be mistakenly started due to the jump of the temperature sampling point within the error range; 2) to effectively avoid the frequent starting of the water pump, the heating relay and other components, and to ensure the service life thereof; 3) if the temperature difference correction is involved in the strategy, the window is too small, and the single heating time is too short to correct the mutual transition between the target temperature and the real temperature of the temperature sampling point. Correspondingly, the charging heating window should not be too large. For example, in the case of Tmin≥m ℃ on / Tmin≥(m+10) ℃ off, the battery will not be heated when the battery temperature is in the (m+1, m+9) ℃ temperature interval, which further affects the battery charging delay.

[0046] The simulation results identify the demand of different heating strategies on the charging capacity, and the strategy threshold that cannot meet the charging capacity of the battery is excluded to ensure that there is no charging delay difference between the heating strategies or the charging delay difference is within an acceptable range under typical working conditions.

[0047] The screened heating strategies are evaluated, and the optimal strategy can be determined according to the heating start-up times, the charging heating energy consumption, the driving heating energy consumption, and the comprehensive information of the charging and driving heating energy consumption. The simulation information example is shown in Table Three as follows:

[0048] Table Three Simulation Information Example Table

[0049]

[0050] The above information can indicate that the driving process needs to start heating twice for 5 open 10 switch and 5 open 12 switch, and the energy consumption of 5 open 10 switch is more optimal; the charging process improves the charging strategy, which has a weak effect on reducing the energy consumption of the next day driving, and based on the consideration of reducing the driving energy consumption, the 14 open 16 switch and 14 open 18 switch strategies are selected; considering that the 14 open 18 switch cannot trigger heating in the 15-17℃ interval, if the heating is started, the time required to reach the optimal charging temperature, i.e. the heating end temperature, is longer than that of the 14 open 16 switch strategy, there is a charging delay difference, and the total heating energy consumption of a single day is the lowest, and the 14 open 16 switch strategy is selected.

[0051] At this point, the optimal heating strategy for a certain area (typical working condition) can be determined, and similarly, the optimal strategy for other areas can be determined.

[0052] 5) Evaluate whether temperature difference correction is needed during the start-stop process of the optimal heating strategy. The temperature sampling point of the battery cell is usually set on the upper surface of the battery cell, so the temperature collected by the temperature sampling point cannot completely represent the temperature of various places inside the battery cell. Through three-dimensional CFD simulation means, the temperature difference between the temperature sampling point of the battery cell and the lowest temperature point and the highest temperature point inside the battery cell under the optimal strategy is evaluated, and if the temperature difference is greater than the set threshold, the optimal heating strategy is adjusted. Before heating starts, the temperature of the temperature sampling point is not lower than the lower limit of heating, but the lowest temperature point inside the battery cell may be lower than the lower limit of heating, or even lithium precipitation occurs due to too low temperature, so the lower limit of heating needs to be lowered, i.e. when the temperature difference between the temperature sampling point of the battery cell and the lowest temperature point inside the battery cell is greater than the set threshold, the lower limit of the heating window needs to be lowered; similarly, during the heating process, the temperature of the temperature sampling point does not reach the upper limit of heating, but the highest temperature point inside the battery cell may have exceeded the upper limit of heating, or even the temperature is too high to cause high-temperature safety risks, so the upper limit of heating needs to be lowered, i.e. when the temperature difference between the temperature sampling point of the battery cell and the highest temperature point inside the battery cell is greater than the set threshold, the upper limit of the heating window needs to be lowered.

[0053] 6) Determine some special working conditions of the low-temperature heating system, such as frequent power-on and power-off, parked heating, night-time small-multiple charging for a long time, day / night long-term storage, etc. Through simulation or experimental means, the heating energy consumption increase under special working conditions is optimized to determine the optimal heating strategy under special working conditions. For example, in the actual use of the liquid heating battery heating system, the water pump self-circulation method is used to effectively utilize the heat of the cooling liquid in the circuit after normal heating is completed. After the vehicle is parked for a certain period of time, the heating is interrupted to save energy. To avoid wasting the heat in the cooling water, an abnormal heating termination water pump self-circulation determination is added to further utilize the heat in the circulating water to continuously supply the battery pack. The self-circulation time is determined by the battery management system according to the battery temperature and the cooling liquid temperature. If Toutlet-Tbattery min≥u℃, the self-circulation instruction is sent. During the self-circulation process, Toutlet-Tbattery min≤v℃ or the self-circulation time reaches p min, the battery management system sends a shutdown instruction.

[0054] Battery management system embodiment:

[0055] The application also provides a battery management system which adopts the same power battery low-temperature heating strategy determination method as the above-mentioned power battery low-temperature heating strategy determination method embodiment, and thus will not be described here.

[0056] Vehicle embodiment:

[0057] The application also provides a vehicle which includes a power battery and a battery management system, and the battery management system adopts the same battery management system as the above-mentioned battery management system embodiment, and thus will not be described here.

[0058] Through experimental verification, the heating strategy determination method proposed by the application can take into account the influence of battery performance and heating energy consumption, meet the needs of the vehicle for the performance refinement and rationalization of the battery management system, and the existing heating method can also determine the optimal heating strategy according to the heating strategy determination method of the application.

Claims

1. A method for determining a low-temperature heating strategy for a power battery, characterized in that, Includes the following steps: 1) Determine typical operating conditions, including ambient temperature, charge / discharge rate, and start-up temperature; 2) Under various typical operating conditions, determine the lower limit of vehicle heating based on the relationship between battery charging rate, discharging rate, feedback rate and temperature, and assume the upper limit of vehicle heating, the lower limit of charging heating and the upper limit of charging heating. 3) Determine the heating power and target water temperature to be used for simulation calculations; 4) Conduct simulation experiments, establish a vehicle heating window with end values ​​of the lower limit and upper limit of vehicle heating, obtain multiple different vehicle heating windows by changing the upper limit of vehicle heating, and obtain multiple sets of vehicle simulation data for each vehicle heating window through simulation calculation. The vehicle simulation data includes the number of times vehicle heating is turned on and the energy consumption of vehicle heating. A charging heating window is established with the lower and upper limits of charging heating as the endpoints. By changing the lower and upper limits of charging heating, multiple different charging heating windows are obtained. Multiple sets of charging simulation data are obtained by simulating and calculating each charging heating window. The charging simulation data includes the number of times charging heating is turned on and the charging heating energy consumption. 5) Determine the optimal driving heating window and the optimal charging heating window based on the number of times the driving heating is activated, the energy consumption of driving heating, the number of times the charging heating is activated, and the energy consumption of charging heating. Combine the optimal driving heating window and the optimal charging heating window to obtain the optimal heating strategy under each typical working condition. The temperature difference between the cell temperature sampling point and the lowest temperature point in the cell's internal region during the execution of the optimal heating strategy is evaluated using three-dimensional CFD simulation. If the temperature difference is greater than the set temperature threshold, the optimal heating strategy is adjusted.

2. The method for determining the low-temperature heating strategy of a power battery according to claim 1, characterized in that, The parameter values ​​for the typical working conditions described in step 1) are determined by statistical analysis of the percentage of various parameters.

3. The method for determining the low-temperature heating strategy of a power battery according to claim 1, characterized in that, Step 5) also includes identifying the charging capacity requirements of different heating strategies, eliminating charging heating windows that cannot meet the charging capacity of the battery cells, and ensuring that the charging delay difference under typical operating conditions is within an acceptable range.

4. The method for determining the low-temperature heating strategy of a power battery according to claim 1, characterized in that, The lower limit for vehicle heating is determined based on the requirements for battery discharge rate and feedback rate under typical operating conditions.

5. The method for determining the low-temperature heating strategy of a power battery according to claim 1, characterized in that, The heating power mentioned in step 3) It is calculated using the following formula: In the formula For heating rate, This refers to the total mass of the battery casing and cold plate in the battery circuit. This refers to the specific heat capacity of the battery casing and cold plate in the battery circuit. This refers to the total mass of the battery cells. For the specific heat capacity of the battery cell, This refers to the total mass of the coolant in the battery circuit. This refers to the specific heat capacity of the coolant in the battery circuit. This is the coefficient of performance for heating devices.

6. The method for determining the low-temperature heating strategy of a power battery according to claim 1, characterized in that, The target water temperature mentioned in step 3) is determined by comparing the low-temperature heating rate and battery pack temperature difference corresponding to different target water temperatures.

7. A battery management system, characterized in that, The method for determining the low-temperature heating strategy of the power battery as described in any one of claims 1 to 6 is adopted.

8. A vehicle, comprising a power battery and a battery management system, characterized in that, The battery management system described in claim 7 is used.

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