Control method and device of battery thermal management system, vehicle and storage medium

Abstract

This application discloses a control method, device, vehicle, and storage medium for a battery thermal management system, relating to the field of vehicle technology. The method includes: predicting battery temperature based on multi-source information such as navigation road conditions, battery status, and ambient temperature; and performing feedforward adjustment of the temperature control execution component based on the predicted battery temperature value. This enables the system to initiate moderate cooling in advance before a sudden load increase and actively reduce cooling intensity during low-load periods, thus stabilizing the battery operating temperature within a preset range. This significantly reduces the probability of battery thermal runaway and realizes a paradigm shift in power battery thermal management from passive response to active prediction. Furthermore, by avoiding ineffective thermal management energy consumption, it can improve the overall vehicle range, effectively resolving the contradiction between thermal management energy consumption and driving range.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a control method for a battery thermal management system, a control device for a battery thermal management system, a computer-readable storage medium, and a vehicle. Background Technology

[0002] With the popularization of new energy vehicles, driving range and economy have become key concerns for users and the industry, and the overall vehicle thermal management performance directly affects the vehicle's range and energy consumption. As the core energy source of new energy vehicles, the performance, lifespan, and safety of the power battery are highly dependent on the operating temperature, with the generally accepted suitable operating temperature range being 15℃–35℃. When the temperature is below 10℃, the battery capacity can decrease by 20%–30%, and the charging efficiency will decrease significantly; when the temperature is above 40℃, the battery internal resistance increases, side reactions intensify, and may even trigger the risk of thermal runaway; if the temperature fluctuation exceeds ±5℃, the battery consistency deteriorates, and the cycle life can be shortened by more than 15%.

[0003] Currently, power battery thermal management generally adopts a passive response control mode, which involves monitoring the battery temperature in real time and activating cooling or heating modules when the temperature exceeds a threshold. However, the battery has already deviated from its optimal operating conditions. If it encounters high-load scenarios such as rapid acceleration or continuous uphill climbing, the actual heat generation rate of the battery often exceeds the system's real-time heat dissipation capacity, leading to the risk of uncontrolled temperature rise. At the same time, since it is impossible to predict the temporal changes in driving conditions, it often operates with excessive cooling or heating during low-load phases, or passively compensates after a sudden increase in load, causing additional energy dissipation of the battery and directly affecting the vehicle's range performance. Summary of the Invention

[0004] This application aims to at least partially address one of the technical problems in the related art. To this end, the first objective of this application is to propose a control method for a battery thermal management system, comprising: acquiring road segment information of the vehicle's expected travel route, current battery state information, and the current ambient temperature of the battery, wherein the current battery state information includes the current battery temperature; determining the expected battery discharge current based on the road segment information, and determining the expected battery heat generation rate based on the expected battery discharge current and the current battery state information; determining the battery heat dissipation rate based on the current battery temperature and the current ambient temperature of the battery; determining a predicted battery temperature value based on the expected battery heat generation rate, the battery heat dissipation rate, and the current battery temperature; determining a target operating mode for a temperature control execution component based on the predicted battery temperature value, and controlling the temperature control execution component according to the target operating mode. This application predicts battery temperature based on multi-source information such as navigation road conditions, battery status, and ambient temperature, and performs feedforward adjustment of the temperature control execution components based on the predicted battery temperature. It can initiate moderate cooling in advance before a sudden increase in load and actively reduce the cooling intensity during low load stages, so that the battery operating temperature is stably maintained within a preset range, which significantly reduces the probability of battery thermal runaway and realizes a paradigm shift in power battery thermal management from passive response to active prediction. Furthermore, by avoiding ineffective thermal management energy consumption, it can improve the vehicle's driving range and effectively solve the contradiction between thermal management energy consumption and driving range.

[0005] The second objective of this application is to provide a control device for a battery thermal management system.

[0006] The third objective of this application is to provide a computer-readable storage medium.

[0007] The fourth objective of this application is to propose a vehicle.

[0008] To achieve the above objectives, a first aspect of this application proposes a control method for a battery thermal management system, comprising: acquiring road segment information of the vehicle's expected travel route, current battery status information, and the current ambient temperature of the battery, wherein the current battery status information includes the current battery temperature; determining the expected battery discharge current based on the road segment information, and determining the expected battery heat generation rate based on the expected battery discharge current and the current battery status information; determining the battery heat dissipation rate based on the current battery temperature and the current ambient temperature of the battery; determining a predicted battery temperature value based on the expected battery heat generation rate, the battery heat dissipation rate, and the current battery temperature; determining a target operating mode for a temperature control execution component based on the predicted battery temperature value, and controlling the temperature control execution component according to the target operating mode.

[0009] According to one embodiment of this application, a temperature control actuator includes a heating component and a heat dissipation component. A target operating mode for the temperature control actuator is determined based on a predicted battery temperature value, and the temperature control actuator is controlled according to the target operating mode. This includes: in response to a predicted battery temperature value being less than a first preset temperature threshold, determining the target operating mode of the heating component as a first heating mode, controlling the heating component according to the first heating mode, and shutting off the heat dissipation component; in response to a predicted battery temperature value being greater than or equal to the first preset temperature threshold and less than a second preset temperature threshold, determining the target operating mode of the heating component as a second heating mode, and controlling the heating component according to the second heating mode; in response to a predicted battery temperature value being greater than or equal to the second preset temperature threshold and less than or equal to a third preset temperature threshold, determining the target operating mode of the heat dissipation component as a first heat dissipation mode, and controlling the heat dissipation component according to the first heat dissipation mode. The heat dissipation component is controlled; in response to a predicted battery temperature value greater than a third preset temperature threshold and less than or equal to a fourth preset temperature threshold, the target operating mode of the heat dissipation component is determined to be a second heat dissipation mode, and the heat dissipation component is controlled according to the second heat dissipation mode; in response to a predicted battery temperature value greater than the fourth preset temperature threshold, the target operating mode of the heat dissipation component is determined to be a third heat dissipation mode, and the heat dissipation component is controlled according to the third heat dissipation mode, and when the current ambient temperature of the battery is greater than a fifth preset temperature threshold, the refrigerant valve is opened for heat dissipation; wherein, the heating power of the heating component in the first heating mode is higher than the heating power of the heating component in the second heating mode, the heat dissipation power of the heat dissipation component in the first heat dissipation mode is lower than the heat dissipation power of the heat dissipation component in the second heat dissipation mode, and the heat dissipation power of the heat dissipation component in the second heat dissipation mode is lower than the heat dissipation power of the heat dissipation component in the third heat dissipation mode.

[0010] According to one embodiment of this application, the road segment information includes road segment type, road segment slope, and road segment congestion coefficient. Determining the expected battery discharge current based on the road segment information includes: determining the basic battery discharge current and the battery discharge current calculation model based on the road segment type; inputting the basic battery discharge current, road segment slope, and road segment congestion coefficient into the battery discharge current calculation model to output the expected battery discharge current.

[0011] According to one embodiment of this application, the current state information of the battery includes the current internal resistance of the battery, the current voltage of the battery, and the current state of charge of the battery. Determining the expected heat generation rate of the battery based on the expected discharge current of the battery and the current state information of the battery includes: determining the current open-circuit voltage of the battery based on the current state of charge of the battery; calculating the current polarization voltage of the battery based on the difference between the current open-circuit voltage of the battery and the current voltage of the battery; calculating the expected polarization heat of the battery based on the product between the current polarization voltage of the battery and the expected discharge current of the battery; calculating the expected ohmic heat of the battery based on the product between the square of the expected discharge current of the battery and the current internal resistance of the battery; and calculating the expected heat generation rate of the battery based on the sum of the expected polarization heat and the expected ohmic heat.

[0012] According to one embodiment of this application, determining the battery heat dissipation rate based on the current battery temperature and the current ambient temperature of the battery includes: calculating the current convective heat transfer temperature difference of the battery based on the difference between the current battery temperature and the current ambient temperature of the battery; and calculating the battery heat dissipation rate based on the product of the current convective heat transfer temperature difference of the battery, the battery heat dissipation coefficient, and the battery heat dissipation area.

[0013] According to one embodiment of this application, determining a predicted battery temperature value based on the battery's expected heat generation rate, battery heat dissipation rate, and current battery temperature includes: calculating the battery's expected net heat flow rate based on the difference between the battery's expected heat generation rate and battery heat dissipation rate; calculating the battery's heat capacity based on the product of battery mass and battery specific pressure heat capacity; calculating the battery's expected temperature change rate based on the ratio of the battery's expected net heat flow rate to the battery's heat capacity; calculating the predicted battery temperature change value based on the product of the battery's expected temperature change rate and a preset temperature prediction step size; and calculating the predicted battery temperature value based on the sum of the current battery temperature and the predicted battery temperature change value.

[0014] According to one embodiment of this application, the method further includes: collecting actual battery temperature values ​​based on a preset time interval; determining temperature prediction error based on the absolute value of the difference between the actual battery temperature value and the corresponding predicted battery temperature value; and adjusting the model parameters of the battery discharge current calculation model based on the temperature prediction error.

[0015] To achieve the above objectives, a second aspect of this application provides a control device for a battery thermal management system. The device includes: an acquisition module for acquiring road segment information of the current road segment where the vehicle is located, current battery status information, current ambient temperature of the battery, and current battery temperature; a first determination module for determining the expected battery discharge current based on the road segment information; a second determination module for determining the expected battery heat generation rate based on the expected battery discharge current and current battery status information; a third determination module for determining the battery heat dissipation rate based on the current battery temperature and current ambient temperature of the battery; a fourth determination module for determining a predicted battery temperature value based on the expected battery heat generation rate, battery heat dissipation rate, and current battery temperature; a fifth determination module for determining a target operating mode of a temperature control execution component based on the predicted battery temperature value; and a control module for controlling the temperature control execution component according to the target operating mode.

[0016] To achieve the above objectives, a third aspect of this application provides a computer-readable storage medium storing a control program for a battery thermal management system, which, when executed by a processor, implements the aforementioned control method for the battery thermal management system.

[0017] To achieve the above objectives, a fourth aspect of this application provides a vehicle including a memory, a processor, and a control program for a battery thermal management system stored in the memory and capable of running on the processor. When the processor executes the control program for the battery thermal management system, it implements the aforementioned control method for the battery thermal management system.

[0018] According to the control method, apparatus, vehicle, and storage medium of the battery thermal management system of this application, the following steps are taken: First, road segment information of the vehicle's expected travel route, current battery status information, and current ambient temperature of the battery are acquired. The current battery status information includes the current battery temperature. Second, the expected battery discharge current is determined based on the road segment information, and the expected battery heat generation rate is determined based on the expected battery discharge current and the current battery status information. Third, the battery heat dissipation rate is determined based on the current battery temperature and the current ambient temperature. Fourth, a predicted battery temperature value is determined based on the expected battery heat generation rate, the battery heat dissipation rate, and the current battery temperature. Fifth, a target operating mode for the temperature control execution component is determined based on the predicted battery temperature value, and the temperature control execution component is controlled according to the target operating mode. This application predicts battery temperature based on multi-source information such as navigation road conditions, battery status, and ambient temperature, and performs feedforward adjustment of the temperature control execution components based on the predicted battery temperature. It can initiate moderate cooling in advance before a sudden increase in load and actively reduce the cooling intensity during low load stages, so that the battery operating temperature is stably maintained within a preset range, which significantly reduces the probability of battery thermal runaway and realizes a paradigm shift in power battery thermal management from passive response to active prediction. Furthermore, by avoiding ineffective thermal management energy consumption, it can improve the vehicle's driving range and effectively solve the contradiction between thermal management energy consumption and driving range. Attached Figure Description

[0019] Figure 1 This is a flowchart of a control method for a battery thermal management system according to some embodiments of this application; Figure 2 A flowchart of a control method for a battery thermal management system according to other embodiments of this application; Figure 3 This is a block diagram of a control device for a battery thermal management system according to some embodiments of this application; Figure 4 This is a block diagram of a vehicle according to some embodiments of this application. Detailed Implementation

[0020] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0021] The control method, apparatus, vehicle, and storage medium of the battery thermal management system according to embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0022] Figure 1 This is a flowchart of a control method for a battery thermal management system according to some embodiments of this application. (Refer to...) Figure 1 The control method of the battery thermal management system in this application embodiment may include the following steps: S110, obtain road segment information of the vehicle's expected travel route, current battery status information, and current ambient temperature of the battery, wherein the current battery status information includes the current battery temperature.

[0023] Specifically, road segment information for the vehicle's expected travel route can be collected through the navigation module. This information includes road segment type, road gradient, and road congestion coefficient. The road segment type can be urban roads, highways, or mountain roads. The road gradient is positive when going uphill and negative when going downhill. The road congestion coefficient can be 0 or 1, where 0 indicates smooth traffic and 1 indicates congestion. The current battery status information can be collected through the battery management system. This information can include the battery's current internal resistance, current voltage, and current state of charge. The current ambient temperature of the battery can be collected through an ambient temperature sensor located at the battery pack. The current battery temperature refers to the average temperature of all individual battery cells, and the temperature of each individual battery cell can be collected through a temperature sensor located at each individual battery cell.

[0024] S120 determines the expected battery discharge current based on road segment information, and determines the expected battery heat generation rate based on the expected battery discharge current and the current battery status information.

[0025] Specifically, after obtaining the road segment information, the expected battery discharge current can be determined by looking up a preset relationship mapping table between the road segment information and the expected battery discharge current. For example, the road segment information may include road segment type, road segment slope, and road segment congestion coefficient. Then, the preset relationship mapping table includes multiple road segment types-road segment slope-road segment congestion coefficients and the expected battery discharge current corresponding to each road segment type-road segment slope-road segment congestion coefficient.

[0026] After determining the expected battery discharge current, the expected battery discharge current and the current battery state information are input into a preset formula for calculating the expected battery heat generation rate to output the expected battery heat generation rate. For example, the current battery state information may include the current internal resistance, current voltage, and current open-circuit voltage. The expected ohmic heat can be calculated based on the expected battery heat generation rate and current internal resistance, and the expected polarization heat can be calculated based on the expected battery heat generation rate, current voltage, and current open-circuit voltage. The expected battery heat generation rate is then calculated based on the sum of the expected ohmic heat and the expected polarization heat.

[0027] S130 determines the battery heat dissipation rate based on the current battery temperature and the current ambient temperature of the battery.

[0028] Specifically, the battery heat generation rate defines the internal source of heat. In order to achieve temperature prediction, the battery heat dissipation rate also needs to be calculated in parallel. For example, the current battery temperature and the current ambient temperature of the battery can be input into a preset battery heat dissipation rate calculation formula to output the battery heat dissipation rate.

[0029] S140 determines the predicted battery temperature based on the battery's expected heat generation rate, battery heat dissipation rate, and current battery temperature.

[0030] Specifically, after determining the battery's expected heat generation rate and heat dissipation rate, the battery's expected net heat flow rate is calculated based on the difference between the two rates. This expected net heat flow rate is then input into the preset expected battery temperature change rate to output the predicted battery temperature change value. The predicted battery temperature value is obtained by summing the current battery temperature and the predicted battery temperature change value.

[0031] S150 determines the target operating mode of the temperature control actuator based on the predicted battery temperature value, and controls the temperature control actuator according to the target operating mode.

[0032] Specifically, after determining the predicted battery temperature, the target operating mode of the temperature control actuator can be determined by querying the preset battery temperature range in which the predicted battery temperature falls, and the temperature control actuator can be controlled according to the target operating mode. For example, if the predicted battery temperature is relatively high, the target operating mode of the temperature control actuator is determined to be the cooling mode; if the predicted battery temperature is relatively low, the target operating mode of the temperature control actuator is determined to be the heating mode.

[0033] This application predicts battery temperature based on multi-source information such as navigation road conditions, battery status, and ambient temperature, and performs feedforward adjustment of the temperature control execution components based on the predicted battery temperature. It can initiate moderate cooling in advance before a sudden increase in load and actively reduce the cooling intensity during low load stages, so that the battery operating temperature is stably maintained within a preset range, which significantly reduces the probability of battery thermal runaway and realizes a paradigm shift in power battery thermal management from passive response to active prediction. Furthermore, by avoiding ineffective thermal management energy consumption, it can improve the vehicle's driving range and effectively solve the contradiction between thermal management energy consumption and driving range.

[0034] In some embodiments, the temperature control actuator includes a heating component and a heat dissipation component. Determining a target operating mode for the temperature control actuator based on a predicted battery temperature value, and controlling the temperature control actuator according to the target operating mode, includes: determining a first heating mode as the target operating mode for the heating component in response to a predicted battery temperature value being less than a first preset temperature threshold, controlling the heating component according to the first heating mode, and shutting off the heat dissipation component; determining a second heating mode as the target operating mode for the heating component in response to a predicted battery temperature value being greater than or equal to the first preset temperature threshold and less than a second preset temperature threshold, and controlling the heating component according to the second heating mode; and determining a first heat dissipation mode as the target operating mode for the heat dissipation component in response to a predicted battery temperature value being greater than or equal to the second preset temperature threshold and less than or equal to a third preset temperature threshold, and controlling the heat dissipation component according to the first heat dissipation mode. The components are controlled; in response to a predicted battery temperature value greater than a third preset temperature threshold and less than or equal to a fourth preset temperature threshold, the target operating mode of the heat dissipation component is determined to be a second heat dissipation mode, and the heat dissipation component is controlled according to the second heat dissipation mode; in response to a predicted battery temperature value greater than a fourth preset temperature threshold, the target operating mode of the heat dissipation component is determined to be a third heat dissipation mode, and the heat dissipation component is controlled according to the third heat dissipation mode, and when the current ambient temperature of the battery is greater than a fifth preset temperature threshold, the refrigerant valve is opened for heat dissipation; wherein, the heating power of the heating component in the first heating mode is higher than the heating power of the heating component in the second heating mode, the heat dissipation power of the heat dissipation component in the first heat dissipation mode is lower than the heat dissipation power of the heat dissipation component in the second heat dissipation mode, and the heat dissipation power of the heat dissipation component in the second heat dissipation mode is lower than the heat dissipation power of the heat dissipation component in the third heat dissipation mode.

[0035] The first, second, third, fourth, and fifth preset temperature thresholds can all be pre-calibrated according to actual conditions. For example, the first preset temperature threshold could be 15℃, the second could be 18℃, the third could be 32℃, the fourth could be 35℃, and the fifth could be 28℃; no specific restrictions are imposed here. The heating element can be a PTC heater, and the heat dissipation element can be an electric fan, an electric water pump, etc.; no specific restrictions are imposed here.

[0036] For example, if the predicted battery temperature is less than the first preset temperature threshold, the target operating mode of the heating component is determined to be the first heating mode, and the heating component is controlled according to the first heating mode, and the heat dissipation component (e.g., an electric fan) is turned off to reduce heat loss. The heating power of the heating component in the first heating mode can be 700W.

[0037] If the predicted battery temperature is greater than or equal to the first preset temperature threshold and less than the second preset temperature threshold, then the target operating mode of the heating component is determined to be the second heating mode, and the heating component is controlled according to the second heating mode. The heating power of the heating component in the second heating mode can be 400W.

[0038] If the predicted battery temperature is greater than or equal to the second preset temperature threshold and less than or equal to the third preset temperature threshold, then the target working mode of the heat dissipation component is determined to be the first heat dissipation mode, and the heat dissipation component is controlled according to the first heat dissipation mode. For example, the speed of the electric water pump is n=1500r / min to achieve basic heat dissipation. The heat dissipation power consumption of the heat dissipation component in the first heat dissipation mode can be 150W.

[0039] If the predicted battery temperature is greater than the third preset temperature threshold and less than or equal to the fourth preset temperature threshold, the target working mode of the heat dissipation component is determined to be the second heat dissipation mode, and the heat dissipation component is controlled according to the second heat dissipation mode. For example, the electric water pump speed n=2500r / min, the electric fan is turned on with a 50% duty cycle, and the heat dissipation power consumption of the heat dissipation component in the second heat dissipation mode can be 350W.

[0040] If the predicted battery temperature exceeds the fourth preset temperature threshold, the target operating mode for the heat dissipation component is determined to be the third heat dissipation mode. The heat dissipation component is then controlled according to this mode. For example, the electric water pump speed is n=3500 r / min, the electric fan is on at 100% duty cycle, and the heat dissipation power consumption of the heat dissipation component in the third heat dissipation mode can be 600W. In this case, if the current ambient temperature of the battery exceeds the fifth preset temperature threshold, the refrigerant valve is activated for heat dissipation.

[0041] In some embodiments, the road segment information includes road segment type, road segment slope, and road segment congestion coefficient. Determining the expected battery discharge current based on the road segment information includes: determining the basic battery discharge current and the battery discharge current calculation model based on the road segment type; and inputting the basic battery discharge current, road segment slope, and road segment congestion coefficient into the battery discharge current calculation model to output the expected battery discharge current.

[0042] Specifically, the battery base discharge current can be determined by querying a preset relationship mapping table between the battery base discharge current and the road segment type. This preset relationship mapping table includes multiple road segment types and the corresponding battery base discharge current for each road segment type.

[0043] For example, in the case of a road segment type of urban road, the basic battery discharge current is 80A, and the expression for the battery discharge current calculation model is as follows: Ipred(t)= Ibase +k1×Ct×Ibase+k2×θt×Ibase; Where Ipred(t) represents the expected battery discharge current; Ibase represents the basic battery discharge current; Ct represents the road congestion coefficient; θt represents the road slope; k1 represents the first coefficient; and k2 represents the second coefficient. k1 and k2 can be determined based on actual conditions; for example, k1 can be 0.6 and k2 can be -0.02. No specific restrictions are imposed here.

[0044] When the road segment type is a highway, the basic battery discharge current is 120A, and the expression for the battery discharge current calculation model is as follows: Ipred(t)= Ibase +k3×Ct×Ibase+k4×θt×Ibase; Where k3 represents the third coefficient and k4 represents the fourth coefficient. k3 and k4 can be determined based on the actual situation; for example, k3 can be 0.2 and k4 can be 0.03. No specific restrictions are imposed here.

[0045] When the road type is mountain road, the basic battery discharge current is 100A, and the expression for the battery discharge current calculation model is as follows: Ipred(t)= Ibase +k5×Ct×Ibase+k6×|θt |×Ibase; Wherein, k5 represents the fifth coefficient; k6 represents the sixth coefficient. k5 and k6 can be determined according to the actual situation; for example, k5 can be 0.4 and k6 can be 0.05. No specific restrictions are imposed here.

[0046] After determining the battery base discharge current and the battery discharge current calculation model based on the road segment type, the battery base discharge current, road segment slope, and road segment congestion coefficient are input into the battery discharge current calculation model to output the expected battery discharge current.

[0047] In some embodiments, the current state information of the battery includes the current internal resistance of the battery, the current voltage of the battery, and the current state of charge of the battery. Determining the expected heat generation rate of the battery based on the expected discharge current of the battery and the current state information of the battery includes: determining the current open-circuit voltage of the battery based on the current state of charge of the battery; calculating the current polarization voltage of the battery based on the difference between the current open-circuit voltage of the battery and the current voltage of the battery; calculating the expected polarization heat of the battery based on the product between the current polarization voltage of the battery and the expected discharge current of the battery; calculating the expected ohmic heat of the battery based on the product between the square of the expected discharge current of the battery and the current internal resistance of the battery; and calculating the expected heat generation rate of the battery based on the sum of the expected polarization heat and the expected ohmic heat.

[0048] Specifically, the current battery status information includes the current internal resistance, current voltage, and current state of charge (SOC). After obtaining the current SOC, the current open-circuit voltage can be determined by querying a preset mapping table between the SOC and open-circuit voltage. The expected discharge current, current internal resistance, current voltage, and current open-circuit voltage are then input into the following formula to calculate the expected heat generation rate of the battery: ; Where Qpred(t) represents the battery's expected heat generation rate; Ipred(t) represents the battery's expected discharge current; Rbat represents the battery's current internal resistance; Uocv represents the battery's current open-circuit voltage; Ubat represents the battery's current voltage; and Uocv-Ubat represents the battery's current polarization voltage. This indicates the expected polarization heat of the battery; This indicates that the battery is expected to generate ohmic heat.

[0049] In some embodiments, determining the battery heat dissipation rate based on the current battery temperature and the current ambient temperature includes: calculating the current convective heat transfer temperature difference of the battery based on the difference between the current battery temperature and the current ambient temperature of the battery; and calculating the battery heat dissipation rate based on the product of the current convective heat transfer temperature difference of the battery, the battery heat dissipation coefficient, and the battery heat dissipation area.

[0050] Specifically, the current battery temperature and the ambient temperature of the battery can be input into the following formula to calculate the battery heat dissipation rate: ; Among them, Q diss (t) represents the battery heat dissipation rate; h represents the battery heat dissipation coefficient; A represents the battery heat dissipation area; T(t) represents the current battery temperature; Tenv represents the current ambient temperature of the battery; T(t)-Tenv represents the current convective heat transfer temperature difference of the battery.

[0051] In some embodiments, determining the predicted battery temperature based on the battery's expected heat generation rate, battery heat dissipation rate, and current battery temperature includes: calculating the battery's expected net heat flow rate based on the difference between the battery's expected heat generation rate and battery heat dissipation rate; calculating the battery's heat capacity based on the product of battery mass and battery specific pressure heat capacity; calculating the battery's expected temperature change rate based on the ratio of the battery's expected net heat flow rate to the battery's heat capacity; calculating the predicted battery temperature change based on the product of the battery's expected temperature change rate and a preset temperature prediction step size; and calculating the predicted battery temperature based on the sum of the current battery temperature and the predicted battery temperature change. The preset temperature prediction step size can be determined according to actual conditions; for example, a preset temperature prediction step size of 10 seconds is not specifically limited here.

[0052] Specifically, input the battery's expected heat generation rate, battery heat dissipation rate, and current battery temperature into the following formula to calculate the predicted battery temperature: ; Where Tpred(t) represents the predicted battery temperature; T(t) represents the current battery temperature; Qdiss(t) represents the battery heat dissipation rate; Qpred(t) represents the expected heat generation rate of the battery; m represents the battery mass; Cp represents the battery specific heat capacity at constant pressure; Qpred(t) - Qdiss(t) represents the expected net heat flow rate of the battery. Indicates the battery's heat capacity; Indicates the preset temperature prediction step size; This represents the predicted value of battery temperature change.

[0053] In some embodiments, the method further includes: acquiring actual battery temperature values ​​based on a preset time interval; determining a temperature prediction error based on the absolute value of the difference between the actual battery temperature value and the corresponding predicted battery temperature value; and adjusting the model parameters of the battery discharge current calculation model based on the temperature prediction error. The preset time interval can be determined according to actual conditions; for example, it can be 10 seconds, but no specific limitation is imposed here.

[0054] Specifically, the actual battery temperature value is collected at a preset time interval and compared with the corresponding predicted battery temperature value to calculate the temperature prediction error. If the temperature prediction error is less than or equal to the preset temperature prediction error threshold (e.g., 2℃), there is no need to adjust the model parameters of the battery discharge current calculation model based on the temperature prediction error. If the temperature prediction error is greater than the preset temperature prediction error threshold (e.g., 2℃), the model parameters of the battery discharge current calculation model are adjusted based on the temperature prediction error.

[0055] In the following explanation, we will take the adjustment of the battery discharge current calculation model for urban roads as an example. For instance, the adjustment amount of k1 can be determined by querying a preset relationship mapping table between the adjustment amount of k1 and the temperature prediction error. This preset relationship mapping table includes multiple temperature prediction errors and the corresponding adjustment amount of k1 for each temperature prediction error. After determining the adjustment amount of k1, k1 is adjusted based on the adjustment amount of k1. Similarly, the method for determining the adjustment amount of k2 is the same as the method for determining the adjustment amount of k1, and will not be repeated here.

[0056] In some embodiments, the predicted battery temperature for a future period of time can be determined based on road segment information of the vehicle's expected travel route, the current battery status information, the current ambient temperature of the battery, and the current battery temperature.

[0057] For example, suppose we need to predict the battery temperature 5 minutes later, and the preset temperature prediction step size is 10 seconds. That is, the current time is t0, and the battery temperature prediction times are t1, t2, ..., t36, where t1 is t0+10s, t2 is t1+10s, and so on. This will not be elaborated here.

[0058] The system acquires road segment information at time t1, battery status information at time t0, ambient temperature of the battery at time t0, and battery temperature at time t0. Based on the road segment information at time t1, it determines the expected battery discharge current at time t1, and based on the expected battery discharge current at time t1 and battery status information at time t0, it determines the expected battery heat generation rate at time t1. Based on the battery temperature at time t0 and ambient temperature of the battery at time t0, it determines the battery heat dissipation rate at time t1. Based on the expected battery heat generation rate, battery heat dissipation rate, and battery temperature at time t0, it determines the predicted battery temperature at time t1.

[0059] Furthermore, the system acquires road segment information at time t2, battery status information at time t0, ambient temperature of the battery at time t0, and predicted battery temperature at time t1. Based on the road segment information at time t2, the system determines the expected battery discharge current at time t2, and based on the expected battery discharge current at time t2 and the battery status information at time t0, it determines the expected battery heat generation rate at time t2. Based on the predicted battery temperature at time t1 and the ambient temperature of the battery at time t0, it determines the battery heat dissipation rate at time t2. Finally, based on the expected battery heat generation rate, the battery heat dissipation rate, and the predicted battery temperature at time t1, it determines the predicted battery temperature at time t2.

[0060] By analogy, the predicted battery temperature at time t36 can be calculated.

[0061] As a concrete example, refer to Figure 3 The control method of the battery thermal management system in this application embodiment may further include the following steps: S201, Begin.

[0062] S202, parameter initialization, and acquisition of navigation route information, battery status information, and ambient temperature of the battery.

[0063] (1) The navigation module establishes communication with the thermal management controller, reads the user-defined destination and planned route, parses the basic parameters of the route and stores them in the controller's memory. The parameters include: Road segment type set: L={L1,L2,L3} (L1=urban roads, L2=expressways, L3=mountain roads); Length of each road segment: S={S1,S2,…,Sn} (unit: km); Slope of each road section: θ={θ1, θ2,…, θn} (uphill is positive, downhill is negative, unit: °); Real-time traffic congestion coefficient: C={ C1,C2,…,Cn} (C=0 indicates smooth traffic, C=1 indicates congestion); Estimated travel time for each road segment: T = {T1, T2, ..., Tn} (unit: min); (2) The BMS (Battery Management System) performs initial detection of the battery status, collects the current temperature (Tb1, Tb2, ..., Tbn), current battery voltage Ubat, and current battery SOC of all individual cells in the battery pack, and calculates the average temperature of the battery pack (current battery temperature). ; Simultaneously calibrate the environmental sensors and read the current ambient temperature (Tenv) and wind speed (Vwind).

[0064] (3) Initial parameter thresholds for the thermal management controller, including: Target temperature range: Ttarget=[18℃,32℃] can be dynamically adjusted according to the battery type, such as [15℃,35℃] for ternary lithium batteries and [20℃,38℃] for lithium iron phosphate batteries; Cooling / heating start threshold: The first preset temperature threshold can be 15℃, the second preset temperature threshold can be 18℃, the third preset temperature threshold can be 32℃, the fourth preset temperature threshold can be 35℃, and the fifth preset temperature threshold can be 28℃. Maximum energy consumption limit of thermal management system: Pmax≤800W (to avoid excessive consumption of battery energy).

[0065] S203 performs filtering, calibration, and fusion on the collected data.

[0066] S204, determine the expected heat generation rate and heat dissipation rate of the battery, and determine the predicted battery temperature value based on the expected heat generation rate and heat dissipation rate of the battery.

[0067] (1) Extract the operating condition characteristic parameters Kt=(Lt, θt, Ct) of the vehicle's expected travel route. (2) Based on the operating condition characteristic parameters, the expected battery discharge current within the preset temperature prediction step is calculated using a pre-trained battery discharge current calculation model: When the road segment type is urban road, the basic battery discharge current is 80A, and the expression for the battery discharge current calculation model is as follows: Ipred(t)= Ibase +k1×Ct×Ibase-k2×θt×Ibase; Where Ipred(t) represents the expected battery discharge current; Ibase represents the basic battery discharge current; Ct represents the road congestion coefficient; θt represents the road slope; k1 represents the first coefficient; and k2 represents the second coefficient. k1 and k2 can be determined based on actual conditions; for example, k1 can be 0.6 and k2 can be -0.02. No specific restrictions are imposed here.

[0068] When the road segment type is a highway, the basic battery discharge current is 120A, and the expression for the battery discharge current calculation model is as follows: Ipred(t)= Ibase +0.2×Ct×Ibase+0.03×θt×Ibase; Where k3 represents the third coefficient and k4 represents the fourth coefficient. k3 and k4 can be determined based on the actual situation; for example, k3 can be 0.2 and k4 can be 0.03. No specific restrictions are imposed here.

[0069] When the road type is mountain road, the basic battery discharge current is 100A, and the expression for the battery discharge current calculation model is as follows: Ipred(t)= Ibase +0.4×Ct×Ibase+0.05×|θt |×Ibase; Wherein, k5 represents the fifth coefficient; k6 represents the sixth coefficient. k5 and k6 can be determined according to the actual situation; for example, k5 can be 0.4 and k6 can be 0.05. No specific restrictions are imposed here.

[0070] Input the battery's expected discharge current, current internal resistance, current voltage, and current open-circuit voltage into the following formula to calculate the battery's expected heat generation rate: ; Among them, Q pred (t) represents the expected rate of heat generation from the battery; I pred (t) represents the expected discharge current of the battery; R bat Indicates the current internal resistance of the battery; U ocv Indicates the current open-circuit voltage of the battery; U bat Indicates the current battery voltage; U ocv -U bat Indicates the current polarization voltage of the battery; This indicates the expected polarization heat of the battery; This indicates that the battery is expected to generate ohmic heat.

[0071] Input the current battery temperature and the current ambient temperature into the following formula to calculate the battery heat dissipation rate: ; Among them, Qdiss (t) represents the battery heat dissipation rate; h represents the battery heat dissipation coefficient; A represents the battery heat dissipation area; T(t) represents the current battery temperature; Tenv represents the current ambient temperature of the battery; T(t)-Tenv represents the current convective heat transfer temperature difference of the battery.

[0072] Input the battery's expected heat generation rate, battery heat dissipation rate, and current battery temperature into the following formula to calculate the predicted battery temperature: ; Among them, T pred Q(t) represents the predicted battery temperature; T(t) represents the current battery temperature; Q(t) represents the predicted battery temperature. diss (t) represents the battery heat dissipation rate; Q pred (t) represents the expected heat generation rate of the battery; m represents the battery mass; Cp represents the specific heat capacity at constant pressure of the battery; Q pred (t)-Q diss (t) represents the expected net heat flow rate of the battery; Indicates the battery's heat capacity; Indicates the preset temperature prediction step size; This represents the predicted value of battery temperature change.

[0073] S205, determine if the predicted battery temperature is >32℃. If so, proceed with S206 and S209.

[0074] S206, determine if 32℃ ≤ predicted battery temperature ≤ 35℃. If so, proceed with S207 and S208.

[0075] S207, triggers weak cooling strategy (second heat dissipation mode).

[0076] S208, electric water pump speed: 2500r / min, electric fan: 50%, power consumption: 350W.

[0077] S209: Determine if the predicted battery temperature is >35℃. If so, proceed with S210 and S211.

[0078] S210, triggers strong cooling strategy (third heat dissipation mode).

[0079] S211, electric water pump speed: 3500r / min, electric fan: 100%, power consumption: 600W.

[0080] S212, determine if the predicted battery temperature is < 18℃. If so, proceed with S213 and S216.

[0081] S213, determine if 15℃ ≤ predicted battery temperature ≤ 18℃. If so, execute S214 and S215.

[0082] S214, trigger the weak heating strategy (second heating mode).

[0083] S215, PTC: 400W.

[0084] S216, determine if the predicted battery temperature is < 15℃. If so, proceed with S217 and S218.

[0085] S217, trigger strong heating strategy (first heating mode).

[0086] S218, PTC: 700W, turn off the electric fan to reduce heat dissipation.

[0087] In summary, this application constructs a predictive thermal management system based on navigation information through a full-process control of "information collection - data fusion - operating condition prediction - heat demand calculation - strategy execution - closed-loop monitoring". The system architecture is shown in Table 1. Table 1

[0088] This application addresses the pain points of traditional passive response by deeply integrating navigation information with thermal management, providing an innovative approach to power battery management for new energy vehicles that combines safety and economy. It can be widely applied to various types of new energy vehicles, including pure electric and plug-in hybrid electric vehicles. This application boasts advantages such as high predictive accuracy, strong adaptability, and significant energy-saving effects, offering an innovative solution for the thermal management of power batteries in new energy vehicles.

[0089] Corresponding to the above embodiments, this application also proposes a control device for a battery thermal management system.

[0090] Reference Figure 3 The control device 300 of the battery thermal management system includes: an acquisition module 310, a first determination module 320, a second determination module 330, a third determination module 340, a fourth determination module 350, a fifth determination module 360, and a control module 370.

[0091] The acquisition module 310 is used to acquire road segment information of the current road segment where the vehicle is located, current battery status information, current ambient temperature of the battery, and current battery temperature; the first determination module 320 is used to determine the expected battery discharge current based on the road segment information; the second determination module 330 is used to determine the expected battery heat generation rate based on the expected battery discharge current and current battery status information; the third determination module 340 is used to determine the battery heat dissipation rate based on the current battery temperature and current ambient temperature of the battery; the fourth determination module 350 is used to determine the predicted battery temperature value based on the expected battery heat generation rate, battery heat dissipation rate, and current battery temperature; the fifth determination module 360 ​​is used to determine the target operating mode of the temperature control execution component based on the predicted battery temperature value; and the control module 370 is used to control the temperature control execution component according to the target operating mode.

[0092] According to one embodiment of this application, the temperature control execution component includes a heating component and a heat dissipation component. The fifth determining module 360 ​​is specifically configured to: determine the target operating mode of the heating component as a first heating mode in response to a predicted battery temperature value being less than a first preset temperature threshold, and control the heating component according to the first heating mode; and turn off the heat dissipation component in response to a predicted battery temperature value being greater than or equal to the first preset temperature threshold and less than a second preset temperature threshold, and control the heating component according to the second heating mode; determine the target operating mode of the heat dissipation component as a first heat dissipation mode in response to a predicted battery temperature value being greater than or equal to the second preset temperature threshold and less than or equal to a third preset temperature threshold, and control the heat dissipation component according to the first heat dissipation mode; and in response to a predicted battery temperature value... If the temperature value is greater than the third preset temperature threshold and less than or equal to the fourth preset temperature threshold, the target operating mode of the heat dissipation component is determined to be the second heat dissipation mode, and the heat dissipation component is controlled according to the second heat dissipation mode; if the predicted battery temperature value is greater than the fourth preset temperature threshold, the target operating mode of the heat dissipation component is determined to be the third heat dissipation mode, and the heat dissipation component is controlled according to the third heat dissipation mode, and when the current ambient temperature of the battery is greater than the fifth preset temperature threshold, the refrigerant valve is opened for heat dissipation; wherein, the heating power of the heating component in the first heating mode is higher than the heating power of the heating component in the second heating mode, the heat dissipation power of the heat dissipation component in the first heat dissipation mode is lower than the heat dissipation power of the heat dissipation component in the second heat dissipation mode, and the heat dissipation power of the heat dissipation component in the second heat dissipation mode is lower than the heat dissipation power of the heat dissipation component in the third heat dissipation mode.

[0093] According to one embodiment of this application, the road segment information includes road segment type, road segment slope and road segment congestion coefficient. The first determining module 320 is specifically used to determine the battery basic discharge current and the battery discharge current calculation model according to the road segment type; and input the battery basic discharge current, road segment slope and road segment congestion coefficient into the battery discharge current calculation model to output the battery expected discharge current.

[0094] According to one embodiment of this application, the current state information of the battery includes the current internal resistance of the battery, the current voltage of the battery, and the current state of charge of the battery. The second determining module 330 is specifically used to: determine the current open-circuit voltage of the battery based on the current state of charge of the battery; calculate the current polarization voltage of the battery based on the difference between the current open-circuit voltage and the current voltage of the battery; calculate the expected polarization heat of the battery based on the product between the current polarization voltage and the expected discharge current of the battery; calculate the expected ohmic heat of the battery based on the product between the square of the expected discharge current and the current internal resistance of the battery; and calculate the expected heat generation rate of the battery based on the sum of the expected polarization heat and the expected ohmic heat.

[0095] According to one embodiment of this application, the third determining module 340 is specifically used to calculate the current convective heat transfer temperature difference of the battery based on the difference between the current temperature of the battery and the current ambient temperature of the battery; and to calculate the battery heat dissipation rate based on the product of the current convective heat transfer temperature difference of the battery, the battery heat dissipation coefficient and the battery heat dissipation area.

[0096] According to one embodiment of this application, the fourth determining module 350 is specifically configured to: calculate the expected net heat flow rate of the battery based on the difference between the expected heat generation rate and the heat dissipation rate of the battery; calculate the battery heat capacity based on the product of the battery mass and the battery specific pressure heat capacity; calculate the expected temperature change rate of the battery based on the ratio of the expected net heat flow rate of the battery to the battery heat capacity; calculate the predicted value of the battery temperature change based on the product of the expected temperature change rate of the battery and the preset temperature prediction step size; and calculate the predicted value of the battery temperature based on the sum of the current battery temperature and the predicted value of the battery temperature change.

[0097] According to one embodiment of this application, the actual battery temperature is collected based on a preset time interval; the temperature prediction error is determined based on the absolute value of the difference between the actual battery temperature and the corresponding predicted battery temperature; and the model parameters of the battery discharge current calculation model are adjusted based on the temperature prediction error.

[0098] To achieve the above objectives, a second aspect of this application provides a control device for a battery thermal management system. The device includes: an acquisition module for acquiring road segment information of the current road segment where the vehicle is located, current battery status information, current ambient temperature of the battery, and current battery temperature; a first determination module for determining the expected battery discharge current based on the road segment information; a second determination module for determining the expected battery heat generation rate based on the expected battery discharge current and current battery status information; a third determination module for determining the battery heat dissipation rate based on the current battery temperature and current ambient temperature of the battery; a fourth determination module for determining a predicted battery temperature value based on the expected battery heat generation rate, battery heat dissipation rate, and current battery temperature; a fifth determination module for determining a target operating mode of a temperature control execution component based on the predicted battery temperature value; and a control module for controlling the temperature control execution component according to the target operating mode.

[0099] Corresponding to the above embodiments, this application also proposes a computer-readable storage medium.

[0100] The computer-readable storage medium of this application stores a control program for a battery thermal management system, which, when executed by a processor, implements the aforementioned control method for the battery thermal management system.

[0101] It should be noted that the above explanation of the embodiments and beneficial effects of the control method for the battery thermal management system also applies to the computer-readable storage medium of the embodiments of this application. To avoid redundancy, it will not be elaborated in detail here.

[0102] Corresponding to the above embodiments, this application also proposes a vehicle.

[0103] See Figure 4 As shown, the vehicle 400 of this application includes a memory 410, a processor 420, and a control program for a battery thermal management system stored in the memory 410 and executable on the processor 420. When the processor executes the control program for the battery thermal management system, it implements the aforementioned control method for the battery thermal management system.

[0104] It should be noted that the above-described embodiments and explanations of the beneficial effects of the control method for the battery thermal management system are also applicable to the vehicles described in this application. To avoid redundancy, they will not be elaborated in detail here.

[0105] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0106] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0107] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0108] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0109] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0110] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A control method for a battery thermal management system, characterized in that, include: The system obtains road segment information of the vehicle's expected travel route, current battery status information, and current ambient temperature of the battery, wherein the current battery status information includes the current battery temperature. The expected discharge current of the battery is determined based on the road segment information, and the expected heat generation rate of the battery is determined based on the expected discharge current of the battery and the current state information of the battery. The battery heat dissipation rate is determined based on the current temperature of the battery and the current ambient temperature of the battery. The predicted battery temperature is determined based on the battery's expected heat generation rate, the battery's heat dissipation rate, and the battery's current temperature; The target operating mode of the temperature control actuator is determined based on the predicted battery temperature, and the temperature control actuator is controlled according to the target operating mode. The road segment information includes road segment type, road segment slope, and road segment congestion coefficient. The step of determining the expected battery discharge current based on the road segment information includes: determining the basic battery discharge current and the battery discharge current calculation model based on the road segment type; inputting the basic battery discharge current, the road segment slope, and the road segment congestion coefficient into the battery discharge current calculation model to output the expected battery discharge current. The battery current state information includes the battery current internal resistance, battery current voltage, and battery current state of charge. Determining the battery's expected heat generation rate based on the battery's expected discharge current and the battery current state information includes: determining the battery's current open-circuit voltage based on the battery's current state of charge; calculating the battery's current polarization voltage based on the difference between the battery's current open-circuit voltage and the battery's current voltage; calculating the battery's expected polarization heat based on the product of the battery's current polarization voltage and the battery's expected discharge current; calculating the battery's expected ohmic heat based on the product of the square of the battery's expected discharge current and the battery's current internal resistance; and calculating the battery's expected heat generation rate based on the sum of the battery's expected polarization heat and the battery's expected ohmic heat. This also includes: collecting actual battery temperature values ​​based on a preset time interval; determining the temperature prediction error based on the absolute value of the difference between the actual battery temperature value and the corresponding predicted battery temperature value; and adjusting the model parameters of the battery discharge current calculation model based on the temperature prediction error.

2. The control method for the battery thermal management system according to claim 1, characterized in that, The temperature control actuator includes a heating component and a heat dissipation component. The step of determining the target operating mode of the temperature control actuator based on the predicted battery temperature value, and controlling the temperature control actuator according to the target operating mode, includes: In response to the predicted battery temperature being less than a first preset temperature threshold, the target operating mode of the heating component is determined to be a first heating mode, and the heating component is controlled according to the first heating mode, and the heat dissipation component is turned off. In response to the predicted battery temperature being greater than or equal to the first preset temperature threshold and less than the second preset temperature threshold, the target operating mode of the heating component is determined to be the second heating mode, and the heating component is controlled according to the second heating mode; In response to the predicted battery temperature being greater than or equal to the second preset temperature threshold and less than or equal to the third preset temperature threshold, the target operating mode of the heat dissipation component is determined to be the first heat dissipation mode, and the heat dissipation component is controlled according to the first heat dissipation mode. In response to the predicted battery temperature being greater than the third preset temperature threshold and less than or equal to the fourth preset temperature threshold, the target operating mode of the heat dissipation component is determined to be the second heat dissipation mode, and the heat dissipation component is controlled according to the second heat dissipation mode. In response to the predicted battery temperature being greater than the fourth preset temperature threshold, the target operating mode of the heat dissipation component is determined to be the third heat dissipation mode, and the heat dissipation component is controlled according to the third heat dissipation mode. When the ambient temperature of the battery is currently greater than the fifth preset temperature threshold, the refrigerant valve is opened for heat dissipation. Wherein, the heating power of the heating component in the first heating mode is higher than that of the heating component in the second heating mode, the heat dissipation power of the heat dissipation component in the first heat dissipation mode is lower than that of the heat dissipation power of the heat dissipation component in the second heat dissipation mode, and the heat dissipation power of the heat dissipation component in the second heat dissipation mode is lower than that of the heat dissipation power of the heat dissipation component in the third heat dissipation mode.

3. The control method for the battery thermal management system according to claim 1, characterized in that, Determining the battery heat dissipation rate based on the current battery temperature and the current ambient temperature includes: The current convective heat transfer temperature difference of the battery is calculated based on the difference between the current temperature of the battery and the current ambient temperature of the battery. The battery heat dissipation rate is calculated based on the product of the current convective heat transfer temperature difference of the battery, the battery heat dissipation coefficient, and the battery heat dissipation area.

4. The control method for the battery thermal management system according to claim 1, characterized in that, The process of determining the predicted battery temperature based on the battery's expected heat generation rate, the battery's heat dissipation rate, and the battery's current temperature includes: The expected net heat flow rate of the battery is calculated based on the difference between the expected heat generation rate and the expected heat dissipation rate of the battery. The battery heat capacity is calculated based on the product of battery mass and battery specific constant-pressure heat capacity. The expected rate of temperature change of the battery is calculated based on the ratio of the expected net heat flow rate of the battery to the heat capacity of the battery; The predicted value of battery temperature change is calculated based on the product of the expected rate of temperature change of the battery and the preset temperature prediction step size. The predicted battery temperature is calculated based on the sum of the current battery temperature and the predicted change in battery temperature.

5. A control device for a battery thermal management system, characterized in that, A control method for implementing the battery thermal management system according to any one of claims 1-4, wherein the apparatus comprises: The acquisition module is used to acquire road segment information where the vehicle is currently located, current battery status information, current ambient temperature of the battery, and current battery temperature. The first determining module is used to determine the expected discharge current of the battery based on the road segment information; The second determining module is used to determine the expected heat generation rate of the battery based on the expected discharge current of the battery and the current state information of the battery. The third determining module is used to determine the battery heat dissipation rate based on the current temperature of the battery and the current ambient temperature of the battery. The fourth determining module is used to determine a predicted battery temperature value based on the battery's expected heat generation rate, the battery's heat dissipation rate, and the battery's current temperature. The fifth determining module is used to determine the target operating mode of the temperature control execution component based on the predicted battery temperature value; The control module is used to control the temperature control actuator according to the target operating mode.

6. A computer-readable storage medium, characterized in that, It stores a control program for a battery thermal management system, which, when executed by a processor, implements the control method for the battery thermal management system according to any one of claims 1-4.

7. A vehicle, characterized in that, The system includes a memory, a processor, and a control program for a battery thermal management system stored in the memory and capable of running on the processor. When the processor executes the control program for the battery thermal management system, it implements the control method for the battery thermal management system according to any one of claims 1-4.

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