Heat preservation control method, device and equipment for power battery of electric vehicle and medium

Abstract

The invention provides a heat preservation control method, device and equipment for a power battery of an electric vehicle and a medium, and the method comprises the steps: responding to a user to start an intelligent heat preservation function of a vehicle end, and judging whether the next vehicle using time is set or not; if the next vehicle using time is set, entering a heat preservation mode of the vehicle using time, determining a first heat preservation strategy based on the battery state information, the next vehicle using time and the environment temperature information, and carrying out heat preservation and heating treatment on the battery based on the first heat preservation strategy; and if the next car using time is not set, entering an active heat preservation mode, determining a second heat preservation strategy based on the battery state information, the environment temperature information and the historical car using habit information of the user, and carrying out heat preservation and heating treatment on the battery based on the second heat preservation strategy. Through a grading mode (based on vehicle using time / active heat preservation) and an automatic triggering mechanism, heat preservation on demand is achieved, premature heat preservation or invalid energy consumption when no demand exists is avoided, and energy is effectively saved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric vehicles, in particular to a heat preservation control method, device and equipment for power batteries of electric vehicles and a medium. BACKGROUND

[0002] With the rapid development of the new energy vehicle industry, the performance of power batteries as core components is significantly affected by temperature. In particular in low temperature environments, the internal chemical reaction rate of the battery slows down, the viscosity of the electrolyte increases, resulting in an increase in the internal resistance of the battery, capacity attenuation, and even the inability to start the vehicle in severe cases. Therefore, battery heat preservation measures are taken to maintain the appropriate working temperature of the battery. However, due to the crude control strategy, the battery temperature change trend cannot be accurately predicted, which easily causes excessive heating or insufficient heating, resulting in high energy consumption and poor heat preservation effect. At the same time, in the face of complex and variable environmental temperatures and vehicle use scenarios, there is a lack of adaptability and flexibility, making it difficult to meet the growing performance needs of new energy vehicles. Moreover, the current power battery heat preservation control technology is still in the "responsive" or "semi-automatic" stage, and it is difficult to balance the dual goals of heat preservation effect and energy consumption optimization. In particular in hybrid vehicle models, how to reasonably coordinate the comprehensive utilization of electric energy and engine heat to further improve the system energy efficiency and user experience in low temperature environments is still a technical problem to be solved. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a heat preservation control method, device and equipment for power batteries of electric vehicles, and a medium, which realizes "on-demand heat preservation" through a hierarchical mode (based on vehicle use time / active heat preservation) and an automatic triggering mechanism, avoids unnecessary energy consumption when heat preservation is performed too early or not required, and effectively saves energy.

[0004] The present application provides a heat preservation control method for power batteries of electric vehicles, which comprises: In response to the user starting the intelligent heat preservation function of the vehicle end, it is determined whether the next vehicle use time is set; If the next vehicle use time is set, the heat preservation mode of the vehicle use time is entered, a first heat preservation strategy is determined based on the battery state information, the next vehicle use time and the environmental temperature information, and the battery is heat preserved and heated based on the first heat preservation strategy; If the next vehicle use time is not set, the active heat preservation mode is entered, a second heat preservation strategy is determined based on the battery state information, the environmental temperature information and the user historical vehicle use habit information, and the battery is heat preserved and heated based on the second heat preservation strategy.

[0005] In one possible implementation, the first heat preservation strategy is determined based on the battery state information, the next vehicle use time and the environmental temperature information, which comprises: The battery temperature prediction model is used to perform battery temperature prediction processing on the current battery temperature, the battery state of charge information, the fuel tank oil quantity, the next vehicle use time and the ambient temperature information in the battery state information, to generate the first temperature maintenance strategy including a heating start temperature, a heating cutoff temperature and a heating number.

[0006] In one possible implementation, the battery temperature prediction model is used to perform battery temperature prediction processing on the current battery temperature, the battery state of charge information, the fuel tank oil quantity, the next vehicle use time and the ambient temperature information in the battery state information, to generate the first temperature maintenance strategy including a heating start temperature, a heating cutoff temperature and a heating number. The battery temperature prediction model is used to perform heating feasibility coefficient calculation on the battery state of charge information and the fuel tank oil quantity, to determine a heating feasibility coefficient. If the heating feasibility coefficient is greater than or equal to a preset threshold, the battery temperature prediction model is used to perform battery simulation prediction processing on the current battery temperature and the ambient temperature information, to predict a battery cooling rate. The heating start temperature, the heating cutoff temperature and the heating number are determined reversely based on the next vehicle use time and the battery cooling rate.

[0007] In one possible implementation, the temperature maintenance and heating processing on the battery based on the first temperature maintenance strategy includes: Before the vehicle is powered off and hibernates, a battery collector is configured based on the first temperature maintenance strategy to periodically monitor a minimum battery temperature. When the minimum battery temperature is monitored to be lower than a preset reverse wake-up temperature threshold, the battery management system is reversely woken up by the battery collector, the vehicle control system is woken up, and the battery is started to perform heating operation. It is determined whether the current battery temperature reaches the heating cutoff temperature in the first temperature maintenance strategy, and if not, the heating is continued, and if so, the heating is completed to enter a temperature maintenance cycle.

[0008] In one possible implementation, after the minimum battery temperature is monitored to be lower than the preset reverse wake-up temperature threshold, the temperature maintenance control method further includes: The first temperature maintenance strategy is dynamically verified based on new battery state information and new ambient temperature information, a new temperature maintenance strategy is generated if the first temperature maintenance strategy fails to pass the dynamic verification, and the battery is subjected to temperature maintenance and heating processing based on the new temperature maintenance strategy.

[0009] In one possible implementation, the second temperature maintenance strategy is determined based on the battery state information, the ambient temperature information and user historical vehicle use habit information. The battery state information, the ambient temperature information, and the user historical driving habit information are subjected to heating feasibility coefficient calculation and battery simulation prediction based on a battery temperature prediction model to generate the second heat preservation strategy.

[0010] The application further provides a heat preservation control device for a power battery of an electric vehicle, which comprises: The judgment module is configured to, in response to the user starting the intelligent heat preservation function of the vehicle end, judge whether the next driving time is set. The first heat preservation heating module is configured to, if the next driving time is set, enter a heat preservation mode for the driving time, determine a first heat preservation strategy based on the battery state information, the next driving time, and the ambient temperature information, and perform heat preservation and heating treatment on the battery based on the first heat preservation strategy. The second heat preservation heating module is configured to, if the next driving time is not set, enter an active heat preservation mode, determine a second heat preservation strategy based on the battery state information, the ambient temperature information, and the user historical driving habit information, and perform heat preservation and heating treatment on the battery based on the second heat preservation strategy.

[0011] In a possible implementation, the first heat preservation heating module is configured to determine the first heat preservation strategy based on the battery state information, the next driving time, and the ambient temperature information as follows: The current battery temperature, the battery state of charge information, the oil tank oil amount, the next driving time, and the ambient temperature information in the battery state information are subjected to battery temperature prediction treatment based on a battery temperature prediction model to generate the first heat preservation strategy including a heating starting temperature, a heating cutoff temperature, and a heating number.

[0012] The application further provides an electronic device, which comprises a processor, a memory, and a bus, the memory stores machine readable instructions executable by the processor, when the electronic device is running, the processor and the memory communicate through the bus, and the machine readable instructions are executed by the processor to perform the steps of the heat preservation control method for a power battery of an electric vehicle as described above.

[0013] The application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by the processor to perform the steps of the heat preservation control method for a power battery of an electric vehicle as described above.

[0014] The application provides a heat preservation control method, device and equipment of a power battery of an electric vehicle and a medium.

[0015] In order to make the above objectives, characteristics and advantages of the present application more apparent, clear and easy to understand, the following preferred embodiments are specifically described below with reference to the attached drawings. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some of the embodiments of the present application, and therefore should not be considered as a limitation to the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0017] Figure 1 A flow chart of a heat preservation control method of a power battery of an electric vehicle provided by the embodiments of the present application; Figure 2 A structure schematic diagram of a heat preservation control device of a power battery of an electric vehicle provided by the embodiments of the present application; Figure 3 A structure schematic diagram of a heat preservation control device of a power battery of an electric vehicle provided by the embodiments of the present application; Figure 4 A structure schematic diagram of an electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0018] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the following will be combined with the accompanying drawings in the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application and not all the embodiments. The components of the embodiments of the present application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, every other embodiment obtained by a person skilled in the art without creative work belongs to the scope of protection of the present application.

[0019] Firstly, the application scenarios applicable to the present application are introduced. The present application can be applied to the technical field of electric vehicles.

[0020] It is found through research that, with the rapid development of the new energy vehicle industry, the performance of the power battery as a core component is significantly affected by temperature. In particular, in a low-temperature environment, the internal chemical reaction rate of the battery slows down, the viscosity of the electrolyte increases, the internal resistance of the battery increases, the capacity decays, and in severe cases, the vehicle cannot even be started. Therefore, the battery insulation measures are taken to maintain the appropriate working temperature of the battery, but due to the crude control strategy, the trend of the battery temperature change cannot be accurately predicted, which easily causes excessive heating or insufficient heating, thereby resulting in high energy consumption and poor effect of the insulation. At the same time, in the face of complex and variable environmental temperature and vehicle use scenarios, there is a lack of adaptability and flexibility, making it difficult to meet the growing performance needs of new energy vehicles. Moreover, the current power battery insulation control technology still remains in the "responsive" or "semi-automatic" stage, and it is difficult to balance the dual goals of insulation effect and energy consumption optimization. In particular, in hybrid vehicle models, how to reasonably coordinate the comprehensive utilization of electric energy and engine heat energy to further improve the system energy efficiency and user experience in a low-temperature environment is still a technical problem to be solved.

[0021] Based on this, the embodiments of the present application provide an insulation control method for a power battery of an electric vehicle, which realizes "on-demand insulation" through a hierarchical mode (based on vehicle use time / active insulation) and an automatic triggering mechanism, avoids premature insulation or invalid energy consumption when there is no demand, and effectively saves energy.

[0022] Please refer to Figure 1 , Figure 1 The flowchart of the insulation control method for a power battery of an electric vehicle provided by the embodiments of the present application is shown in FIG. 1. As shown in FIG. 1, the insulation control method provided by the embodiments of the present application includes the following steps. Figure 1 S101: In response to the user starting the intelligent insulation function of the vehicle end, it is judged whether the next vehicle use time is set. ​

[0023] It should be noted that the user sets the use time, i.e. the next use time, and the use time can be set once or each time.

[0024] S102: If the next use time is set, enter the temperature maintenance mode of the use time, determine the first temperature maintenance strategy based on the battery state information, the next use time and the environmental temperature information, and perform temperature maintenance and heating treatment on the battery based on the first temperature maintenance strategy.

[0025] In this step, if the next use time is set, enter the temperature maintenance mode of the use time, determine the first temperature maintenance strategy according to the battery state information, the next use time and the environmental temperature information, and perform temperature maintenance and heating treatment on the battery according to the first temperature maintenance strategy.

[0026] Here, the battery state information includes the current battery temperature, the battery state of charge information and the oil tank oil amount.

[0027] Among them, after the vehicle is powered off, the vehicle end sends the user's next use time, the current battery temperature at the power-off time, the battery remaining capacity (SOC) and the oil tank oil amount to the temperature maintenance algorithm module of the cloud end. The temperature maintenance algorithm module of the cloud end obtains the vehicle position information through the GPS positioning system, queries the future 24 / 48 hour weather forecast of the environment where the vehicle is located. At the same time, the information uploaded by the vehicle end is input into the battery temperature prediction model, and the cloud end will formulate a temperature maintenance strategy based on the use time within 2s, and send the strategy to the vehicle end.

[0028] In one possible implementation, the first temperature maintenance strategy is determined based on the battery state information, the next use time and the environmental temperature information, including: The battery temperature prediction model is used to perform battery temperature prediction processing on the current battery temperature, the battery state of charge information, the oil tank oil amount, the next use time and the environmental temperature information in the battery state information, to generate the first temperature maintenance strategy including the heating start temperature, the heating cutoff temperature and the heating number.

[0029] Here, the battery temperature prediction model is used to perform battery temperature prediction processing on the current battery temperature, the battery state of charge information, the oil tank oil amount, the next use time and the environmental temperature information, to generate the first temperature maintenance strategy including the heating start temperature, the heating cutoff temperature and the heating number.

[0030] It should be noted that the battery temperature prediction model is a mathematical calculation model.

[0031] In one possible implementation, the battery temperature prediction model predicts the current battery temperature, battery state of charge information, tank fuel quantity, the next vehicle use time, and the ambient temperature information in the battery state information, generates the first temperature holding strategy including a heating start temperature, a heating cutoff temperature, and a heating number, and includes the following steps: A: The battery temperature prediction model calculates a heating feasibility coefficient based on the battery state of charge information and the tank fuel quantity, and determines the heating feasibility coefficient.

[0032] Here, the battery temperature prediction model calculates the heating feasibility coefficient based on the battery state of charge information and the tank fuel quantity, and determines the heating feasibility coefficient.

[0033] The heating feasibility coefficient is determined by the following formula: K = 0.6 * S / 50 + 0.4 * F / 20, K is the heating feasibility coefficient (≥ 0.5 allows heating, < 0.5 prohibits heating, and priority is given to power saving / quantity), S is the battery state of charge information (50 is taken as the benchmark, and SOC ≥ 50 is taken as 0.6), and F is the tank fuel quantity (20 is taken as the benchmark, and the fuel quantity ≥ 20 is taken as 0.4).

[0034] B: If the heating feasibility coefficient is greater than or equal to a preset threshold, the battery temperature prediction model performs battery simulation prediction processing on the current battery temperature and the ambient temperature information, and predicts a battery cooling rate.

[0035] Here, if the heating feasibility coefficient is greater than or equal to a preset threshold, the battery temperature prediction model performs battery simulation prediction processing on the current battery temperature and the ambient temperature information, and predicts a battery cooling rate.

[0036] The battery temperature change thermal simulation model is used to calculate a battery temperature change curve during vehicle hibernation in combination with an ambient temperature prediction curve. V = a + b * (T0-T1), V is the battery temperature drop rate (℃ / h, that is, the temperature drop per hour, a is the basic drop rate, b is the ambient temperature difference correction coefficient, the greater the temperature difference, the faster the drop rate. T0 is the current battery temperature, and T1 is the lowest ambient temperature during hibernation.

[0037] C: The heating start temperature, the heating cutoff temperature, and the heating number are determined in reverse based on the next vehicle use time and the battery cooling rate.

[0038] Here, the heating start temperature, the heating cutoff temperature, and the heating number are determined in reverse based on the next vehicle use time and the battery cooling rate.

[0039] Wherein, N=( (T0-Tend) - (T0-Tstart) ) / (Tstop-Tstart), T0: temperature before battery hibernation; Tstart: heating start temperature; Tend: hibernation end temperature without heating; Tstop: heating stop temperature; N is the predicted number of heating times.

[0040] In one possible implementation, the heat preservation and heating treatment of the battery based on the first heat preservation strategy includes: (1) Before the vehicle is powered off for hibernation, a battery collector is configured based on the first heat preservation strategy to periodically monitor the minimum battery temperature.

[0041] Here, before the vehicle is powered off for hibernation, the battery collector is configured based on the first heat preservation strategy to periodically monitor the minimum battery temperature.

[0042] (2) When the monitored minimum battery temperature is lower than a preset reverse wake-up temperature threshold, the battery management system is reverse-woken up by the battery collector to wake up the vehicle control system and start the battery for heating operation.

[0043] Here, according to the first heat preservation strategy, it is determined whether the heat preservation and heating needs to be started before the vehicle is used. If not, the vehicle directly enters hibernation. If yes, the battery collector is configured based on the first heat preservation strategy to reverse wake up the battery temperature. The collector can periodically collect the temperature and voltage of the battery during the vehicle hibernation, and when the minimum battery temperature is lower than the reverse wake-up battery temperature configured before hibernation, the collector will wake up the battery management system.

[0044] (3) It is determined whether the current battery temperature reaches the heating stop temperature in the first heat preservation strategy. If not, the heating continues. If yes, the heating is completed and enters the heat preservation cycle.

[0045] Here, it is determined whether the current battery temperature reaches the heating stop temperature in the first heat preservation strategy. If not, the heating continues. If yes, the heating is completed and enters the heat preservation cycle.

[0046] In one possible implementation, after the minimum battery temperature is monitored to be lower than the preset reverse wake-up temperature threshold, the heat preservation control method further includes: Based on the new battery state information and the new environment temperature information, the first heat preservation strategy is dynamically verified. If the first heat preservation strategy fails the dynamic verification, a new heat preservation strategy is generated, and the battery is subjected to heat preservation and heating treatment based on the new heat preservation strategy.

[0047] Here, according to the received use time, the current battery temperature, the ambient temperature, the SOC, and the fuel information, etc., a battery thermal management prediction model constructed in advance is called to evaluate whether the current vehicle performs a heat preservation strategy to ensure that the battery temperature is in a startable working interval when the use time arrives; if the evaluation result is no, or the evaluation energy consumption exceeds the preset energy saving threshold, an updated heat preservation strategy is generated. The updated heat preservation strategy at least includes a new heat preservation start time and a target heating temperature, and is sent to the vehicle terminal through a wireless communication network. After receiving the updated heat preservation strategy, the vehicle terminal replaces the original strategy and performs battery heat preservation operation according to the new strategy.

[0048] S103: If the next use time is not set, enter the active heat preservation mode, determine a second heat preservation strategy based on the battery state information, the ambient temperature information, and the user historical use habit information, and perform heat preservation and heating treatment on the battery based on the second heat preservation strategy.

[0049] In this step, if the next use time is not set, enter the active heat preservation mode, determine a second heat preservation strategy based on the battery state information, the ambient temperature information, and the user historical use habit information, and perform heat preservation and heating treatment on the battery based on the first heat preservation strategy.

[0050] It should be noted that the active heat preservation mode refers to a battery management system (BMS) or a vehicle control system (VCU) that automatically judges and triggers a battery heating (or cooling) control strategy based on real-time monitoring data when the vehicle is in a parked / sleeping state. The purpose is to prevent the battery temperature from exceeding the safe working range, avoid performance degradation, life attenuation, and even safety hazards.

[0051] Here, the process of performing heat preservation and heating treatment on the battery based on the second heat preservation strategy is consistent with the process of performing heat preservation and heating treatment on the battery based on the first heat preservation strategy described above, and this part will not be traced back.

[0052] In one possible implementation, the second heat preservation strategy is determined based on the battery state information, the ambient temperature information, and the user historical use habit information: The battery state information, the ambient temperature information, and the user historical use habit information are calculated for heating feasibility and battery simulation prediction based on a battery temperature prediction model to generate the second heat preservation strategy.

[0053] Here, the battery state information, the ambient temperature information, and the user historical use habit information are calculated for heating feasibility and battery simulation prediction based on a battery temperature prediction model to generate the second heat preservation strategy.

[0054] Among them, the battery management system periodically collects battery temperature, SOC and environmental temperature information in the vehicle parking state. The cloud obtains vehicle location information through the GPS positioning system, queries 24 / 48 hour weather forecast, combines user vehicle habits, calendar information (can identify weekdays or holidays) and battery temperature, environmental temperature, SOC, oil information sent by the vehicle end, and formulates the second heat preservation strategy based on the above information through the battery temperature prediction model and sends it to the vehicle end.

[0055] The active heat preservation strategy generation mechanism in the application and the heat preservation strategy generation mechanism based on the vehicle time constitute a double-track cooperative architecture: the heat preservation strategy based on the vehicle time is used as the main control strategy to realize on-demand preheating and improve user experience; and the active heat preservation strategy is used as a safety bottom strategy to intervene immediately when the battery temperature deviates from the safety range and forcibly start the heating or cooling operation. Further, the system is also configured with a strategy fusion unit for arbitration according to the preset priority rules when the two strategies are concurrent, and supports feeding the occurrence frequency and amplitude of the active heat preservation to the cloud model to dynamically optimize the starting time of the subsequent vehicle time heat preservation strategy, thereby forming a closed-loop optimization mechanism of 'experience learning-strategy evolution'.

[0056] In specific embodiments, for the use time of the vehicle, the S1: after the vehicle is powered off, the vehicle end sends the user's use time, the power battery temperature at the time of power off, the vehicle temperature, the battery remaining capacity (SOC), and the oil tank oil to the cloud end heat preservation algorithm module. S2: The cloud end heat preservation algorithm module obtains the vehicle position information through the GPS positioning system, queries the future 24 / 48 hour weather forecast of the environment where the vehicle is located. At the same time, the user's use time, the vehicle temperature, the power battery temperature, the battery remaining capacity (SOC), and the oil tank oil uploaded by the vehicle end are brought into the battery temperature prediction model, and the cloud end will formulate the first heat preservation strategy within 2s and send the strategy to the vehicle end. S3: According to the first heat preservation strategy, it is judged whether the heat preservation heating needs to be started before use. If not, the vehicle directly enters sleep. S4: If needed, the battery collector is configured according to the first heat preservation strategy to reverse wake up the battery temperature. The collector can periodically collect the temperature and voltage of the battery during the sleep of the vehicle end, and when the minimum battery temperature is lower than the reverse wake-up battery temperature configured before sleep, the collector will wake up the battery management system. S5: After the configuration is completed, the vehicle enters sleep, and the collector periodically monitors the battery temperature during sleep. S6: When the minimum battery temperature is lower than the reverse wake-up battery temperature configured before sleep, the collector wakes up the battery management system. S7: The battery management system wakes up the vehicle control system. S8: The vehicle end judges whether the heat preservation heating condition is met according to the current heat preservation strategy. If not, it enters the next heat preservation cycle. S9: If heating is needed, start heating. S10: Judge whether the heating cutoff temperature is reached. If not, continue heating. S11: If the heating cutoff temperature is reached, heating is completed, and the next heat preservation cycle is entered.

[0057] In the present application, the problems of low-temperature battery performance degradation and range anxiety are solved: traditional vehicles have no precise heat preservation mechanism, and the battery activity decreases sharply in low-temperature environment, which easily causes range shrinkage and starting difficulty, especially when the user needs to use the vehicle urgently or travel long distances, the uncertainty of the range causes anxiety, and the present application alleviates this problem from the root by dynamic heat preservation and precise temperature control. The problem of heat preservation energy consumption redundancy: the existing heat preservation function is mostly "always on", which does not adjust dynamically according to user needs and environment, resulting in energy waste (such as early heat preservation, energy consumption without demand), the present application realizes on-demand heat preservation and reduces invalid energy consumption through hierarchical mode and automatic triggering. The problem of single heat preservation strategy and insufficient scene adaptation: the traditional scheme does not integrate environmental prediction, user habits and other data, the heat preservation strategy is fixed, and it cannot adapt to different climates (such as severe cold in the north and cold and wet in the south) and different use scenarios (such as scheduled use and temporary use), the scheme relies on cloud multi-source data and prediction model to realize "one vehicle one strategy" and improve scene adaptability. The problem of function continuity and reliability: traditional and lack of battery monitoring during sleep period, which easily causes battery damage due to low-temperature leakage, the scheme guarantees uninterrupted function and no missing monitoring through local cache strategy and reverse wake-up mechanism during sleep period.

[0058] The application provides a heat preservation control method of a power battery of an electric vehicle, which comprises the following steps: in response to a user starting an intelligent heat preservation function of a vehicle end, determining whether a next vehicle use time is set; if the next vehicle use time is set, entering a heat preservation mode of the vehicle use time, determining a first heat preservation strategy based on battery state information, the next vehicle use time and environment temperature information, and performing heat preservation and heating treatment on the battery based on the first heat preservation strategy; if the next vehicle use time is not set, entering an active heat preservation mode, determining a second heat preservation strategy based on the battery state information, the environment temperature information and user historical vehicle use habit information, and performing heat preservation and heating treatment on the battery based on the second heat preservation strategy. Through hierarchical modes (based on vehicle use time / active heat preservation) and an automatic triggering mechanism, the method realizes "on-demand heat preservation", avoids early heat preservation or invalid energy consumption when there is no demand, and effectively saves energy.

[0059] Please refer to Figure 2 、 Figure 3 , Figure 2 Fig. 1 is a structural schematic diagram of a heat preservation control device of a power battery of an electric vehicle provided by the application; Figure 3 Fig. 2 is another structural schematic diagram of the heat preservation control device of the power battery of the electric vehicle provided by the application. As shown in Fig. 2, the heat preservation control device 200 comprises the following parts: Figure 2 a judgment module 210, configured to determine whether a next vehicle use time is set in response to a user starting an intelligent heat preservation function of a vehicle end; a first heat preservation and heating module 220, configured to enter a heat preservation mode of the vehicle use time if the next vehicle use time is set, determine a first heat preservation strategy based on battery state information, the next vehicle use time and environment temperature information, and perform heat preservation and heating treatment on the battery based on the first heat preservation strategy; a second heat preservation and heating module 230, configured to enter an active heat preservation mode if the next vehicle use time is not set, determine a second heat preservation strategy based on the battery state information, the environment temperature information and user historical vehicle use habit information, and perform heat preservation and heating treatment on the battery based on the second heat preservation strategy.

[0060] Further, the first heat preservation and heating module 220 is configured to determine the first heat preservation strategy based on the battery state information, the next vehicle use time and the environment temperature information as follows: performing battery temperature prediction treatment on the current battery temperature, battery charge state information, oil tank oil quantity, the next vehicle use time and the environment temperature information in the battery state information based on a battery temperature prediction model, to generate the first heat preservation strategy containing a heating starting temperature, a heating cutoff temperature and a heating number.

[0061] ​Furthermore, the first heat preservation and heating module 220 is used to perform battery temperature prediction processing on the current battery temperature, battery state of charge information, fuel tank level, next vehicle usage time, and ambient temperature information in the battery state information based on the battery temperature prediction model, and generate the first heat preservation strategy including heating start temperature, heating stop temperature, and heating number of times: Based on the battery temperature prediction model, the heating feasibility coefficient is calculated using the battery state of charge information and the amount of oil in the tank, and the heating feasibility coefficient is determined. If the heating feasibility coefficient is greater than or equal to a preset threshold, then based on the battery temperature prediction model, battery simulation prediction processing is performed on the current battery temperature and the ambient temperature information to predict the battery cooling rate. The heating start temperature, heating stop temperature, and heating number are determined by inversely based on the next vehicle usage time and the battery cooling rate.

[0062] Furthermore, the first heat preservation and heating module 220 is used to perform heat preservation and heating treatment on the battery based on the first heat preservation strategy: Before the vehicle is powered off and enters hibernation, a battery data acquisition device is configured based on the first heat preservation strategy to periodically monitor the lowest battery temperature. When the battery's lowest temperature is detected to be lower than the preset reverse wake-up temperature threshold, the battery collector reverse wakes up the battery management system, which in turn wakes up the vehicle control system and starts the battery heating operation. Determine whether the current battery temperature has reached the heating cutoff temperature in the first heat preservation strategy. If it has not reached the cutoff temperature, continue heating. If it has reached the cutoff temperature, heating is complete and the heat preservation cycle begins.

[0063] Furthermore, such as Figure 3 As shown, the heat preservation control device 200 also includes a dynamic verification module 240, which is used for: The first heat preservation strategy is dynamically verified based on the new battery status information and the new ambient temperature information. If the first heat preservation strategy fails the dynamic verification, a new heat preservation strategy is generated, and the battery is subjected to heat preservation and heating treatment based on the new heat preservation strategy.

[0064] Furthermore, the second heat preservation and heating module 230 is used to determine the second heat preservation strategy based on the battery status information, the ambient temperature information, and the user's historical vehicle usage habits information. Based on the battery temperature prediction model, the heating feasibility coefficient is calculated and battery simulation prediction is performed on the battery status information, the ambient temperature information, and the user's historical vehicle usage information to generate the second heat preservation strategy.

[0065] The application provides a heat preservation control device of a power battery of an electric vehicle, the heat preservation control device comprises: a judgment module, configured to judge whether a next vehicle use time is set in response to a user starting an intelligent heat preservation function of a vehicle end; a first heat preservation heating module, configured to enter a heat preservation mode of a vehicle use time if the next vehicle use time is set, determine a first heat preservation strategy based on battery state information, the next vehicle use time and environment temperature information, and perform heat preservation heating treatment on the battery based on the first heat preservation strategy; and a second heat preservation heating module, configured to enter an active heat preservation mode if the next vehicle use time is not set, determine a second heat preservation strategy based on the battery state information, the environment temperature information and user historical vehicle use habit information, and perform heat preservation heating treatment on the battery based on the second heat preservation strategy. Through hierarchical modes (based on vehicle use time / active heat preservation) and an automatic triggering mechanism, the heat preservation is performed on demand, the early heat preservation or invalid energy consumption when there is no demand is avoided, and the energy is effectively saved.

[0066] Please refer to Figure 4 , Figure 4 A structural schematic diagram of an electronic device provided by the application is shown in the figure. Figure 4 As shown in the figure, the electronic device 400 comprises a processor 410, a memory 420 and a bus 430.

[0067] The memory 420 stores machine readable instructions executable by the processor 410, when the electronic device 400 is running, the processor 410 and the memory 420 communicate through the bus 430, and the machine readable instructions are executed by the processor 410, which can execute the steps of the heat preservation control method of the power battery of the electric vehicle in the method embodiment shown in the above. Figure 1 The specific implementation can be referred to the method embodiment, and will not be repeated here.

[0068] The application further provides a computer readable storage medium, the computer readable storage medium stores a computer program, and the computer program is executed by the processor, which can execute the steps of the heat preservation control method of the power battery of the electric vehicle in the method embodiment shown in the above. Figure 1 The specific implementation can be referred to the method embodiment, and will not be repeated here.

[0069] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiment, and will not be repeated here.

[0070] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other manners. The described device embodiments are merely schematic, for example, the division of the units is only a logical function division, and there can be another division manner in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, or the among different units, can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0071] The units described as separated components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. In actual implementation, some or all of the units can be selected according to actual needs to achieve the purposes of the embodiments of the present application.

[0072] In addition, each functional unit in the embodiments of the present application can be integrated in one processing unit, or each unit can exist physically as a separate unit, or two or more units can be integrated in one unit.

[0073] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0074] Finally, it should be noted that the above-described embodiments are merely specific embodiments of the present application, which are used to illustrate the technical solutions of the present application, but not to limit the same. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that any skilled person in the art can still modify or easily think of changes to the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some of the technical features, within the technical scope disclosed by the present application. The modifications, changes or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for heat preservation control of a power battery for an electric vehicle, characterized in that, Applied to the cloud, the heat preservation control method includes: In response to the user activating the vehicle's intelligent insulation function, determine whether to set the next usage time; If the next usage time is set, the vehicle will enter the heat preservation mode for the usage time. Based on the battery status information, the next usage time, and the ambient temperature information, a first heat preservation strategy will be determined, and the battery will be heat-preserved and heated based on the first heat preservation strategy. If no next usage time is set, the system enters active heat preservation mode. Based on the battery status information, the ambient temperature information, and the user's historical usage habits, a second heat preservation strategy is determined, and the battery is heat-preserved based on the second heat preservation strategy.

2. The heat preservation control method according to claim 1, characterized in that, The first insulation strategy determined based on battery status information, the next vehicle usage time, and ambient temperature information includes: Based on the battery temperature prediction model, the current battery temperature, battery state of charge information, fuel tank level, next vehicle usage time, and ambient temperature information in the battery status information are processed to predict the battery temperature, and a first heat preservation strategy including heating start temperature, heating end temperature, and heating number of times is generated.

3. The heat preservation control method according to claim 2, characterized in that, The battery temperature prediction model performs battery temperature prediction processing on the current battery temperature, battery state of charge information, fuel tank level, next vehicle usage time, and ambient temperature information in the battery state information to generate a first heat preservation strategy that includes a heating start temperature, a heating stop temperature, and the number of heating cycles, including: Based on the battery temperature prediction model, the heating feasibility coefficient is calculated using the battery state of charge information and the amount of oil in the tank, and the heating feasibility coefficient is determined. If the heating feasibility coefficient is greater than or equal to a preset threshold, then based on the battery temperature prediction model, battery simulation prediction processing is performed on the current battery temperature and the ambient temperature information to predict the battery cooling rate. The heating start temperature, heating stop temperature, and heating number are determined by inversely based on the next vehicle usage time and the battery cooling rate.

4. The heat preservation control method according to claim 1, characterized in that, The heat preservation and heating treatment of the battery based on the first heat preservation strategy includes: Before the vehicle is powered off and enters hibernation, a battery data acquisition device is configured based on the first heat preservation strategy to periodically monitor the lowest battery temperature. When the battery's lowest temperature is detected to be lower than the preset reverse wake-up temperature threshold, the battery collector reverse wakes up the battery management system, which in turn wakes up the vehicle control system and starts the battery heating operation. Determine whether the current battery temperature has reached the heating cutoff temperature in the first heat preservation strategy. If it has not reached the cutoff temperature, continue heating. If it has reached the cutoff temperature, heating is complete and the heat preservation cycle begins.

5. The heat preservation control method according to claim 4, characterized in that, After the minimum battery temperature is detected to be lower than a preset reverse wake-up temperature threshold, the heat preservation control method further includes: The first heat preservation strategy is dynamically verified based on the new battery status information and the new ambient temperature information. If the first heat preservation strategy fails the dynamic verification, a new heat preservation strategy is generated, and the battery is subjected to heat preservation and heating treatment based on the new heat preservation strategy.

6. The heat preservation control method according to claim 1, characterized in that, The second insulation strategy determined based on the battery status information, the ambient temperature information, and the user's historical driving habits includes: Based on the battery temperature prediction model, the heating feasibility coefficient is calculated and battery simulation prediction is performed on the battery status information, the ambient temperature information, and the user's historical vehicle usage information to generate the second heat preservation strategy.

7. A heat preservation control device for a power battery of an electric vehicle, characterized in that, The heat preservation control device includes: The judgment module is used to respond to the user activating the vehicle's intelligent insulation function and determine whether to set the next usage time. The first heat preservation and heating module is used to enter the heat preservation mode for the next vehicle use time if the next vehicle use time is set. It determines the first heat preservation strategy based on the battery status information, the next vehicle use time and the ambient temperature information, and performs heat preservation and heating treatment on the battery based on the first heat preservation strategy. The second heat preservation and heating module is used to enter the active heat preservation mode if no next vehicle use time is set. It determines the second heat preservation strategy based on the battery status information, the ambient temperature information, and the user's historical vehicle use habits information, and performs heat preservation and heating treatment on the battery based on the second heat preservation strategy.

8. The heat preservation control device according to claim 7, characterized in that, The first heat preservation and heating module is used to determine the first heat preservation strategy based on battery status information, the next vehicle usage time, and ambient temperature information. Based on the battery temperature prediction model, the current battery temperature, battery state of charge information, fuel tank level, next vehicle usage time, and ambient temperature information in the battery status information are processed to predict the battery temperature, and a first heat preservation strategy including heating start temperature, heating end temperature, and heating number of times is generated.

9. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. The machine-readable instructions are executed by the processor to perform the steps of the thermal insulation control method for the electric vehicle power battery as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the heat preservation control method for the electric vehicle power battery as described in any one of claims 1 to 6.

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