Electric vehicle power battery system preheating control method applied to low-temperature environment

Abstract

According to the electric vehicle power battery system preheating control method applied to the low-temperature environment, a targeted preheating optimization strategy can be provided based on the real-time working condition and the energy condition of a vehicle in combination with travel requirements, and meanwhile the influence of the temperature on battery capacity fading is considered; and establishing an optimization problem by taking the minimum total energy consumption as a target, and solving to obtain a relatively accurate heating target temperature under different environment temperatures and different battery pack SOCs, so that the battery pack can reach the optimal temperature state through the optimal heating duration before each travel plan. In addition, the optimized battery system preheating strategy can avoid the redundant heating process in the single discharge period, and the vehicle endurance level in the low-temperature environment can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of heating of electric vehicle power battery systems, and particularly relates to a preheating strategy for an electric vehicle power battery system in a low-temperature environment. Background Art

[0002] The discharge capacity of a power battery significantly decreases in a low-temperature environment. Therefore, it is necessary to heat the battery through the electric vehicle thermal management system. However, since the heating process also consumes a part of the battery system energy, the reduction of the cruising range of an electric vehicle in low temperature cannot be avoided. Existing technologies usually heat the battery pack to a relatively high temperature at low temperature to improve the low-temperature discharge performance of the battery system and reduce the influence of temperature on the discharge capacity of the battery pack. However, some existing battery heating strategies mainly judge whether heating is required based on a temperature threshold, that is, when the battery temperature is lower than a certain value, such as 10°C, the heating of the battery pack is triggered, and the battery pack is heated every time the vehicle travels. Therefore, it will cause unnecessary waste of system energy consumption, thereby further reducing the cruising range of the electric vehicle. Compared with the heating strategy based on the temperature threshold, some existing technologies provide a customized preheating strategy for the battery pack according to the state of charge of the battery and the specific energy demand of a single vehicle trip, which can avoid the ineffective heating of the battery pack in a single discharge cycle and save heating energy consumption. However, when the vehicle needs to be heated, it still takes a certain amount of time to heat the battery from a relatively low temperature to a relatively high temperature, and there is still much room for improvement in terms of efficiency. Summary of the Invention

[0003] In view of this, aiming at the technical problems existing in the field, the present invention provides a preheating control method for an electric vehicle power battery system applied in a low-temperature environment, which specifically includes the following steps:

[0004] Step 1: Calculate the total available discharge energy Q of the current power battery pack at normal temperature according to the ambient temperature and SOC all ;

[0005] Step 2: Calculate the total required energy Q of the high- and low-voltage systems of the vehicle according to the intended driving mileage and the current operating conditions req ;

[0006] Step 3: Calculate the available discharge energy Q of the power battery pack at the current ambient temperature according to the total available discharge energy Q obtained in step, the current ambient temperature T all , the current ambient temperature T a and the initial temperature T of the battery 0 ; cut ;

[0007] Step 4: Compare the available discharge energy Q at the current ambient temperature cut with the total required energy Qreq , determine whether to perform heating:

[0008] a. When Q cut > Q req , do not perform heating;

[0009] b. When Q cut < Q req < Q all , heating is required;

[0010] c. When Q cut < Q req , appropriate heating should be performed on the premise of ensuring the vehicle's cruising range.

[0011] In several cycles before implementing the preheating control method for the electric vehicle power battery system of the present invention, based on the SOC, the intended driving mileage, and the environmental temperature information obtained when performing each step, establish a relationship table among the heating temperature range - intended driving mileage - SOC corresponding to different environmental temperatures; and in subsequent cycles, based on the real-time collected environmental temperature, SOC, and planned intended driving mileage, look up the table online to obtain the judgment result of whether to perform heating, so as to completely replace the judgment process of the original step 4.

[0012] Furthermore, the total dischargeable energy Q of the battery pack at normal temperature all is specifically calculated using the following formula:

[0013]

[0014] where SOC(t) is the SOC of the current battery pack; SOC(0) is the lower boundary of the SOC interval for calculating the net energy; U ocv is the open-circuit voltage of the battery pack; C ap is the rated capacity of the battery pack;

[0015] The dischargeable energy Q at the current environmental temperature and the current SOC state of the battery pack cut is calculated using the following formula:

[0016] Q cut = Q all * E tem (T a , SOC(t))

[0017] where T a is the current environmental temperature; E tem is the energy retention rate of the battery pack at different environmental temperatures and SOCs, and it is specifically obtained by fitting the experimental data of the fully discharged battery using the following formula:

[0018]

[0019] Among them, T a is the current ambient temperature; p 1 ~p 5 are the parameters to be fitted.

[0020] Furthermore, after performing step 4 and determining that the battery pack needs to be heated, the influence of temperature on the battery life can also be considered, and the heating target temperature of the battery pack can be optimized to reduce heat energy waste and alleviate battery life attenuation. The specific optimization process includes:

[0021] Taking the target temperature T t of battery heating as the control variable, an optimization problem is established with the minimum total energy consumption during the heating process as the optimization objective:

[0022]

[0023] Among them, min represents minimization; s.t. represents constraints; E dis (T t ) represents the discharge efficiency of the battery at the target temperature T t , which is obtained by fitting using the least squares method for different experimental temperatures; Q(T 0 ) represents the dischargeable energy of the battery at the temperature of T 0 , Q(T t ) represents the dischargeable energy of the battery at the target temperature T t , and they are calculated respectively based on the discharge efficiency at different temperatures and using the following formula:

[0024]

[0025] For the optimization algorithm adopted in the above calculation process ⑤, specifically choose any one of the active-set method, the Sequential Quadratic Programming (SQP) method, and the trust-region-reflective method.

[0026] Furthermore, after determining that the battery pack needs to be heated and optimizing the heating target temperature, according to the average temperature drop rate of the battery pack at the current ambient temperature and the average temperature rise rate of the battery pack heating by the in-vehicle heating module, the required heating time is calculated and preheating is started; the specific process includes:

[0027] The average temperature drop rate r 1 of the battery pack at the current ambient temperature is obtained in advance through battery system simulation and bench experiments:

[0028] Assume that the time when the vehicle starts to stand still in a low-temperature environment is t 1, the initial temperature of the battery pack at the start of static storage is T 0 , the ambient temperature is T a , the next vehicle usage time planned by the vehicle owner is recorded as t 2 , the real-time temperature of the battery pack during static storage is T, then the relationship between T and T 0 , r 1 and t 1 is as follows:

[0029] T = f(T 0 , r 1 , t 1 , t)

[0030] After obtaining the average temperature drop rate r 1 , use the following formula to calculate the time when the battery temperature drops below 0°C during the vehicle static storage stage:

[0031] t p = T 0 / r 1

[0032] Based on this time t p make another judgment: when t 2 - t 1 ≤ t p , it means that the battery pack temperature does not drop below 0°C before the next vehicle usage, and there is no need to turn on the heating function; when t 2 - t 1 > t p , it indicates that before the next vehicle usage, the battery pack temperature has dropped below 0°C during the vehicle static storage process, and self-heating is required before vehicle usage.

[0033] The average temperature rise rate r of the battery pack heating 2 is also obtained in advance through battery system simulation and bench tests;

[0034] The target temperature for the optimized battery pack heating is T 2 , then the heating time to make the battery pack reach this target temperature is:

[0035]

[0036] Based on the next vehicle usage time t planned by the vehicle owner 2 , finally determine the recommended heating time t h as:

[0037]

[0038] The preheating control method for an electric vehicle power battery system provided by the present invention and applied to a low-temperature environment can provide a targeted preheating optimization strategy based on the real-time vehicle conditions, energy status, and travel requirements. At the same time, considering the influence of the battery pack operating temperature on battery capacity loss, it optimizes the heating target temperature of the battery pack, enabling the battery pack to reach the best temperature state through the most appropriate heating duration before each travel plan. Meanwhile, it avoids redundant heating processes within a single discharge cycle, reduces waste of heating energy consumption, and thus helps to improve the vehicle's endurance level in a low-temperature environment. In addition, the optimized battery system preheating strategy can also avoid redundant heating processes within a single discharge cycle, contributing to improving the vehicle's endurance level in a low-temperature environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is a schematic flow chart of the method provided by the present invention;

[0040] Figure 2 is a schematic diagram of an optional division of the battery pack heating range in an example of the present invention;

[0041] Figure 3 is a schematic diagram of the relationship curve between battery energy loss and temperature in an example of the present invention;

[0042] Figure 4 is a graph showing the relationship between discharge voltage and capacity of the battery at different temperatures in an example of the present invention;

[0043] Figure 5 is a schematic diagram of the fitting curve of battery discharge efficiency and temperature in an example of the present invention;

[0044] Figure 6 is a surface diagram of the optimized battery heating target temperature in an example of the present invention.

[0045] Figure 7 is a control flow chart for determining the heating time and performing preheating in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] The technical solutions of the present invention will be described clearly and completely below with reference to the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention fall within the protection scope of the present invention.

[0047] The preheating control method for an electric vehicle power battery system provided by the present invention and applied to a low-temperature environment, as Figure 1 shown, specifically includes the following steps:

[0048] Step 1: Calculate the total available discharge energy Q of the current power battery pack at normal temperature based on the ambient temperature and SOC all ;

[0049] Step 2: Calculate the total required energy Q of the vehicle's high and low voltage systems according to the desired driving mileage and the current operating conditions req ;

[0050] Step 3: Calculate the available discharge energy Q of the power battery pack at the current ambient temperature based on the total available discharge energy Q at normal temperature obtained in the previous step all , the current ambient temperature T a and the initial temperature T of the battery 0 ; cut ;

[0051] Step 4: Compare the available discharge energy Q at the current ambient temperature cut with the total required energy Q req , and determine whether to perform heating:

[0052] a. When Q cut >Q req , it indicates that the discharge energy of the battery without heating also meets the driving requirements, so heating is not required;

[0053] b. When Q cut <Q req <Q all , it indicates that the total available discharge energy of the battery at normal temperature meets the driving requirements, while the discharge energy at the current temperature does not meet the driving requirements, and heating is required;

[0054] c. When Q cut <Q req , it indicates that the energy of the battery does not meet the driving requirements even when it is fully discharged. However, in this case, the battery can still be heated to make it discharge as much electricity as possible and extend its driving range.

[0055] Before implementing the preheating control method of the electric vehicle power battery system of the present invention, based on the SOC, desired driving mileage, and ambient temperature information obtained when performing each step, establish a relationship table among the heating temperature range - desired driving mileage - SOC corresponding to different ambient temperatures as Figure 2 shown. In Figure 2Among them, when the coordinates determined according to the predicted mileage and the SOC state of the battery pack are within interval II, it indicates that the dischargeable energy of the battery pack at the current temperature and SOC is greater than the required energy corresponding to the predicted driving mileage, and the battery pack can meet the requirements of the predicted driving mileage without heating; when it is within interval I, it indicates that the driving demand energy corresponding to the predicted driving mileage is greater than the dischargeable energy of the battery pack at the current temperature and SOC but less than the total energy of the battery pack. At this time, the battery pack needs to be heated to the target temperature to meet the requirements of the predicted driving mileage; within interval III, it indicates that the required energy corresponding to the predicted driving mileage is greater than the total energy of the battery pack at the current SOC state of the battery pack. In this case, even heating the battery cannot meet the corresponding predicted driving mileage requirements. In this case, if the requirements of the predicted driving mileage are to be met, the battery pack needs to be charged.

[0056] In the later stage, only based on the real-time collected ambient temperature, SOC and the planned driving mileage, look up the table online to obtain the judgment result of whether heating is required, so as to completely replace the judgment process of the original step 4.

[0057] In a preferred embodiment of the present invention, the total dischargeable energy Q of the battery pack at normal temperature all is specifically calculated by the following formula:

[0058]

[0059] wherein, SOC(t) is the SOC of the current battery pack; SOC(0) is the lower boundary of the SOC interval for calculating the net energy; U ocv is the open-circuit voltage of the battery pack; C ap is the rated capacity of the battery pack;

[0060] The dischargeable energy Q at the current ambient temperature cut is calculated by the following formula:

[0061] Q cut = Q all * E tem (T a , SOC(t))

[0062] wherein, T a is the current ambient temperature; E tem is the energy retention rate of the battery pack at different ambient temperatures and SOCs, and it is specifically obtained by fitting the experimental data of fully discharging the battery by the following formula:

[0063]

[0064] wherein, T a is the current ambient temperature; p 1 ~p 5 are the parameters to be fitted.

[0065] After performing step 4 and determining that the battery pack needs to be heated, the heating target temperature is further optimized. The specific process includes: ① Establishing an energy consumption model of the vehicle's high- and low-voltage systems corresponding to different temperature conditions, and using this energy consumption model to calculate the energy required for vehicle driving during a specific duration; ② Conducting cyclic discharge experiments on the battery at different temperatures, and establishing a battery life degradation model related to temperature based on the experimental results; ③ Establishing a heating energy consumption model based on the battery's heat balance equation to calculate the heating energy consumption required to heat the battery from the starting temperature T 0 to the target temperature T t ; ④ Taking the target temperature T t of battery heating as the control variable, establishing an optimization problem with the minimum total energy consumption during the heating process as the optimization goal, and setting constraint conditions based on the dischargeable capacity and energy consumption of the battery; ⑤ Selecting a suitable optimization algorithm to solve the optimization problem established in calculation process ④, and finally obtaining the optimal heating target temperature corresponding to different starting temperatures.

[0066] In a preferred embodiment of the present invention, in the above calculation process ① when establishing the energy consumption model of the vehicle's high- and low-voltage systems, first calculate the output power data of the vehicle drive system based on the vehicle dynamics equation:

[0067] P drv =mgfucosθ + 0.5AC D ρu 3 +mgusinθ + δma c u

[0068] where m is the curb weight of the vehicle, g is the acceleration due to gravity, θ is the road slope, A is the frontal area of the vehicle, C D is the air resistance coefficient, ρ is the air density, u and a c are the vehicle driving speed and driving acceleration respectively, and f and δ represent the rotating mass conversion coefficient and rolling resistance coefficient respectively;

[0069] Then, calibrate the power energy consumption model of the high- and low-voltage systems corresponding to different temperatures through simulation; calculate the energy Q required for vehicle driving during a specific duration based on this model and the following formula req :

[0070]

[0071] where t 0 is the starting time of driving; t 1 is the ending time of driving; P drv is the output power of the drive system during driving; P h is and P lThey are the high and low voltage system powers of the vehicle, including the compressor power, PTC heater power, and power of in-vehicle low-voltage electronic instrument devices in the thermal management system, etc.

[0072] In the above calculation process ②, specifically establish the following battery life degradation model regarding temperature:

[0073]

[0074] Among them, Q loss represents the battery energy loss caused by temperature; Q all is the maximum dischargeable energy of the battery; A is the fitting coefficient. Specifically, the discharge capacity at room temperature is used as the maximum dischargeable energy of the battery, and the battery life degradation equation is fitted using the cyclic discharge experimental data of the battery at different temperatures. Taking the fitting result of the battery cycle life data in an example experiment as an illustration, the total energy Q all value is 210, and the value of the fitting coefficient A in the equation is obtained as 0.32 to determine the relationship between temperature and battery energy loss, as shown in Figure 3 . It can be seen from the figure that the lower the temperature, the greater the energy loss of the battery, and as the temperature increases, the change rate of the battery energy loss decreases; Ea is the activation energy of the battery, and its value in this embodiment is 15162, R is the gas constant, with a value of 8.314, and T is the temperature of the battery.

[0075] The specific form of the heating energy consumption model established in the above calculation process ③ is as follows:

[0076] Q ph = m bat × C bat × (T t - T 0 ) / η ph

[0077] Among them, m bat is the total mass of the battery; C bat is the specific heat capacity of the battery; η ph is the heating efficiency.

[0078] In the above calculation process ④, specifically establish the following form of optimization problem:

[0079]

[0080] Among them, min represents minimization; s.t. represents constraints; E dis (T t ) represents the discharge efficiency of the battery at the target temperature T t ; Q(T 0 ) represents the dischargeable energy of the battery at the temperature T 0 ; Q(T t)Indicates the dischargeable energy of the battery at the target temperature T t when.

[0081] The discharge efficiency corresponding to different temperatures can be obtained through a fitting process based on the least squares method: calculate the discharge efficiency of the battery at the experimental test temperature points based on the discharge capacity data of the battery; use the least squares method to fit the discharge efficiency at the limited experimental temperature test points to obtain the discharge efficiency expression E dis (T) of the battery with respect to temperature.

[0082] In a preferred embodiment of the present invention, the discharge capacity curves of the battery at different temperatures are as Figure 4 shown. Assuming the discharge capacity of the battery is C dis , taking the maximum discharge capacity of the battery at 25 °C as C dis,25 as a reference, the discharge efficiency E dis (T) of the battery at different temperatures can be calculated by the following formula:

[0083]

[0084] Through the above calculations, a two-dimensional table of the battery discharge efficiency and temperature at each test temperature point in this embodiment can be obtained, as shown in Table 1 below:

[0085] Table 1 Two-dimensional table of the relationship between battery discharge efficiency E dis and temperature

[0086] Temperature (°C) -20 -10 0 10 25 <![CDATA[E dis > 0.847 0.899 0.924 0.957 1

[0087] Assume that the functional relationship between the battery discharge efficiency and temperature is:

[0088] E dis (T) = f(T) = a × exp(b × T) + c × exp(d × T)

[0089] where a, b, c, and d are fitting parameters; exp(*) represents the exponential function. Based on the experimental calculation data in Table 1, use the least squares method to fit the expression of E dis (T) to obtain the functional relationship between E dis (T) and temperature, as Figure 5 shown. In this embodiment, the values of the fitting parameters a, b, c, and d are: 20.44, -0.007487, -19.51, and -0.008046, respectively.

[0090] Based on the functional expression of the battery discharge efficiency E dis (T) obtained by fitting, calculate the discharge capacity of the battery at temperature T 0 and temperature T t when:

[0091]

[0092] Based on the maximum dischargeable energy Q of the battery all , the battery discharge efficiency E dis (T), the heating energy consumption Q of the battery ph , the energy consumption Q required for vehicle driving req , the battery at temperature T 0 and temperature T t when the dischargeable energy Q(T 0 ) and Q(T t ), that is, the optimization problem is established. When solving the established optimization problem, specifically select any one of the active-set method, the Sequential Quadratic Programming (SQP) method, and the trust-region-reflective method. Taking the SQP algorithm as an example, solve the objective equation to obtain the optimal heating target temperature of the battery at different SOCs and different initial temperatures, as Figure 6 shown. It can be seen that the optimized heating target temperature gradually increases with the increase of the initial temperature and SOC, rather than heating the battery to a relatively high temperature in any case like the traditional threshold-based heating strategy. The actual energy state of the battery is considered during the optimization process of the heating target temperature, and the influence of temperature on battery energy loss is also considered. Heating the battery to the optimized target temperature can reduce the influence of temperature on battery life and effectively reduce the heating energy consumption of the battery.

[0093] In a preferred embodiment of the present invention, as Figure 7 shown, after determining that the battery pack needs to be heated and optimizing the heating target temperature, calculate the required heating time and start preheating according to the average temperature drop rate of the battery pack at the current ambient temperature and the average temperature rise rate of the battery pack heating by the on-vehicle heating module; the specific process includes:

[0094] The average temperature drop rate r of the battery pack at the current ambient temperature 1 is obtained in advance through battery system simulation and bench test:

[0095] Assume that the vehicle starts to stand still in a low-temperature environment at time t 1 , the initial temperature of the battery pack at the start of standing still is T 0 , the ambient temperature is T a , the next vehicle usage time planned by the owner is recorded as t 2 , the real-time temperature of the battery pack during standing still is T, then T and T 0 , r 1 and t1 The relationship between them is as follows:

[0096] T = f(T 0 , r 1 , t 1 , t)

[0097] After obtaining the average temperature drop rate r 1 , use the following formula to calculate the time when the battery temperature drops below 0°C during the vehicle's static phase:

[0098] t p = T 0 / r 1

[0099] Based on this time t p , make another judgment: when t 2 - t 1 ≤ t p , it indicates that the battery pack temperature has not dropped below 0°C before the next vehicle use, and the heating function does not need to be turned on; when t 2 - t 1 > t p , it means that before the next vehicle use, the battery pack temperature has dropped below 0°C during the vehicle's static process, and self-heating is required before vehicle use.

[0100] The average temperature rise rate r of the battery pack heating 2 is also obtained in advance through battery system simulation and bench tests;

[0101] The target temperature for the optimized battery pack heating is T 2 , then the heating time to make the battery pack reach this target temperature is:

[0102]

[0103] Based on the next vehicle use time t 2 planned by the vehicle owner, finally determine the recommended heating time t h as:

[0104]

[0105] It should be understood that the magnitudes of the sequence numbers of the steps in the embodiments of the present invention do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0106] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A preheating control method for an electric vehicle power battery system in a low temperature environment, characterized in that: The specific steps include: Step 1: Calculate the total dischargeable energy Q of the current power battery pack at room temperature based on the ambient temperature and SOC all ; Step 2: Calculate the total energy required by the vehicle's high and low voltage systems Q based on the desired mileage and current operating conditions req ; Step 3: The total dischargeable energy Q at room temperature obtained according to the steps all 、Current ambient temperature T a And the initial temperature T0 of the battery to calculate the dischargeable energy Q of the power battery pack at the current ambient temperature cut ; Step 4: Compare the dischargeable energy Q at the current ambient temperature cut and total energy demand Q req , determine whether to heat: a. When Q cut >Q req When, no heating is performed; b. When Q cut req all When heating is required;​​ c. When Q cut req When the vehicle is in use, it is necessary to heat it appropriately while ensuring the vehicle's mileage.​ In the actual execution of the method in the early several cycles, based on the SOC, expected mileage and ambient temperature information obtained when executing each step, a relationship table between the heating temperature range-to-be-driven mileage-SOC corresponding to different ambient temperatures is established; and in the subsequent cycles, based on the real-time collected ambient temperature T a , SOC and planned mileage are looked up online to obtain the judgment result of whether to heat up, so as to completely replace the judgment process of the original step 4.

2. The method according to claim 1, characterized in that: The total dischargeable energy Q of the battery pack at room temperature all The specific calculation is based on the following formula: Among them, SOC(t) is the current SOC of the battery pack; SOC(0) is the lower boundary of the SOC interval for calculating net energy; U ocv is the open circuit voltage of the battery pack; C ap is the rated capacity of the battery pack; Dischargeable energy Q at current ambient temperature cut Calculated using the following formula: Q cut =Q all *E tem (T a ,SOC(t)) Among them, T a is the current ambient temperature; E tem is the energy retention rate of the battery pack at different ambient temperatures and SOCs, which is obtained by fitting the experimental data of full discharge of the battery using the following formula: Among them, T a is the current ambient temperature; p1~p5 are the parameters to be fitted.

3. The method according to claim 1, characterized in that: After determining that the battery pack needs to be heated, the effect of temperature on life is also considered. By optimizing the heating target temperature of the battery pack, the heating energy consumption of the battery pack is reduced, and the battery degradation is delayed; The optimization process includes: The target temperature T for battery heating t As the control variable, the total energy consumption in the heating process is minimized as the optimization target to establish an optimization problem, and constraints are set based on the dischargeable capacity and energy consumption of the battery; the specific form of the established optimization problem is as follows: Among them, min means minimization; st means constraint; Q loss Indicates that temperature causes battery energy loss; Q ph is the heating energy consumption of the battery pack; E dis (T t ) indicates that the battery is at the target temperature T t The discharge efficiency under different experimental temperatures is obtained by fitting using the least square method; Q(T0) represents the dischargeable energy of the battery at temperature T0, Q(T t ) indicates that the battery is at the target temperature T t The dischargeable energy at different temperatures is calculated based on the energy retention rate at different temperatures using the following formula:

4. The method according to claim 3, characterized in that: After determining in step 4 that the battery pack needs to be heated and the optimized heating target temperature is obtained, the heating time required for heating the battery pack to the optimized target temperature is calculated according to the average temperature drop rate of the battery pack under the current ambient temperature and the average temperature rise rate of the battery pack heated by the vehicle heating module, and preheating is started; the specific process includes: The average temperature drop rate r1 of the battery pack at the current ambient temperature is obtained in advance through battery system simulation and bench experiments: Assume that the time when the vehicle starts to rest in a low temperature environment is t1, the initial temperature of the battery pack at the beginning of rest is T0, and the ambient temperature is T a , the next time the owner plans to use the car is recorded as t2, and the real-time temperature of the battery pack during the static process is T. The relationship between T and T0, r1 and t1 is as follows: T=f(T0,r1,t1,t) After obtaining the average temperature drop rate r1, use the following formula to calculate the time it takes for the battery temperature to drop below 0°C during the vehicle's stationary phase: t p =T0 / r1 Based on the time t p Judge again: when t2-t1≤t p When t2-t1>t p When the temperature of the battery pack drops below 0°C during the vehicle's resting state before the next use, it indicates that the battery pack needs to be self-heated before the vehicle is used. The average temperature rise rate r2 of the battery pack heating is also obtained in advance through battery system simulation and bench experiments; Based on the above optimized battery pack heating target temperature T2, the heating time required for the battery pack to reach the target temperature is calculated as: Based on the next time the owner plans to use the car, t2, the recommended heating time t is finally determined. h for:

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