Vehicle thermal management method and electronic equipment

Abstract

The invention provides a vehicle thermal management method and electronic equipment, and the method comprises the steps: obtaining predicted travel information which comprises a predicted travel distance and a predicted travel duration; predicting power predicted energy consumption of the vehicle according to the predicted travel information and environment information, wherein the environment information comprises road condition information and climate temperature information associated with the predicted travel information; according to the power prediction energy consumption, the climate temperature information and the prediction travel information, a first controlled object is obtained through prediction, and the first controlled object comprises at least zero items of a first set including a variable-temperature running seat, a steering wheel, a battery and an air conditioning system capable of being started to run; and running or not running the first controlled object.

Description

Technical Field

[0001] The present application relates to the field of vehicles, in particular to a vehicle thermal management method 、 Electronic device and computer-readable storage medium. Background Art

[0002] Statistics show that short-distance vehicle travel consumes more energy than long-distance travel, with the vehicle's air conditioning system and battery consuming a large proportion of the energy. For example, during a short-distance trip, after the vehicle's thermal management system has completed the temperature increase or / and temperature decrease, there is still unused energy consumption due to the end of the trip, resulting in high energy consumption for short-distance trips.

[0003] Therefore, how to solve the extra energy consumption loss caused by vehicle travel has become an urgent problem to be solved. Summary of the invention

[0004] The present application provides a vehicle thermal management method and electronic equipment for reducing vehicle travel energy consumption.

[0005] In a first aspect, the present application provides a vehicle thermal management method, comprising: obtaining predicted trip information, the predicted trip information including a predicted trip distance and a predicted trip duration; predicting the predicted power energy consumption of the vehicle based on the predicted trip information and environmental information, the environmental information including road condition information and climate temperature information associated with the predicted trip information; obtaining a first controlled object based on the predicted power energy consumption and the climate temperature information, as well as the predicted trip information, the first controlled object including at least zero items of the following first set: seats, steering wheels and batteries that can operate at variable temperatures, and an air-conditioning system that can be started; and operating or not operating the first controlled object.

[0006] In some embodiments, the first controlled object is predicted based on the predicted power consumption, the climate temperature information, and the predicted travel information, and the first controlled object includes one or a combination of the following first set: a seat, a steering wheel, and a battery that can be operated at a variable temperature, and an air conditioning system that can be started and operated, including:

[0007] Determine a second controlled object from the following second set according to the predicted trip information, and then predict the predicted energy consumption of the cabin of the second controlled object, wherein the prediction method of the predicted energy consumption of the cabin includes the predicted trip information and the climate temperature information, and the second set includes: the seats and steering wheels with variable temperatures, and the startable air-conditioning system, and the second controlled object includes at least zero items of the second set; predict whether a third controlled object including the battery is obtained according to the predicted power energy consumption and the predicted cabin energy consumption, as well as the battery information of the battery; determine that the second controlled object and the third controlled object are the first controlled object.

[0008] In some implementations, the battery information includes the current power of the battery, the predicted remaining power of the battery, and the predicted temperature control energy consumption of the battery.

[0009] In some embodiments, the prediction of whether a third controlled object includes the battery is obtained based on the predicted power energy consumption and the predicted cabin energy consumption, as well as the battery information of the battery, including: in response to a first ratio being greater than a second ratio, predicting the third controlled object including the battery; in response to the first ratio being less than or equal to the second ratio, predicting the third controlled object not including the battery; wherein the first ratio is calculated based on the predicted power energy consumption, the predicted cabin energy consumption and the current power, and the second ratio is calculated based on the predicted power energy consumption, the predicted cabin energy consumption, the predicted temperature control energy consumption, and the predicted power margin.

[0010] In some embodiments, the specific calculation formula of the first ratio is:

[0011]

[0012] The specific calculation formula of the second ratio is:

[0013]

[0014] Among them, Q drive represents the predicted energy consumption of the power, Q hs represents the predicted energy consumption of the cabin, Q battery_heat represents the predicted temperature control energy consumption, represents the current charge of the battery, Indicates the predicted remaining power level of the battery.

[0015] In some embodiments, the calculation method of the predicted cabin energy consumption includes a first coefficient determined by the predicted travel distance and the predicted travel duration.

[0016] In some embodiments, the predicted temperature control energy consumption includes predicting the temperature change predicted energy consumption consumed by the battery to change the temperature from the current temperature to the target temperature, or predicting the temperature change predicted energy consumption consumed by the battery to change the temperature from the current temperature to the target temperature and the temperature maintenance predicted energy consumption consumed to maintain the target temperature.

[0017] In some embodiments, the temperature-dependent energy consumption calculation formula is: Q BH1 =α(T N -T0), the calculation formula of the temperature maintenance prediction energy consumption is: Q BH2 =h·(T N -T E )·t, where TN represents the target temperature predicted by the battery, and T0 represents the current temperature of the battery.

[0018] In some embodiments, the method also includes trip categories of short trips, medium trips, and long trips, and determining the second controlled object from the following second set based on the predicted trip information includes: in response to the predicted trip information being the short trip, determining the seat and / or the steering wheel as the second controlled object from the second set; in response to the predicted trip information being the medium trip, determining the seat, and / or the steering wheel, and the air-conditioning system as the second controlled object from the second set; in response to the predicted trip information being the long trip, determining the air-conditioning system as the second controlled object from the second set.

[0019] In some implementations, obtaining predicted travel information includes:

[0020] The predicted trip information is obtained by determining the usual trip data from the historical trip data; or, in response to input data input by a user, obtaining the predicted trip information.

[0021] In a second aspect of the present application, an electronic device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the vehicle thermal management method of the first aspect.

[0022] In a third aspect of the present application, a computer-readable storage medium is provided, which stores program instructions therein, and the program instructions are executed by a processor to perform the vehicle thermal management method of the first aspect.

[0023] Compared with the prior art, the technical solution of the present application generates the predicted power energy consumption of the vehicle based on the predicted travel information and environmental information including road condition information and climate temperature information, and then determines the first controlled object based on the predicted power energy consumption and climate temperature information, as well as the predicted travel information, and finally, runs or does not run the first controlled object. Based on the predicted travel information, the present application autonomously selects the first controlled object that matches the predicted travel information from the first set including seats, steering wheels, batteries, and air conditioning systems, thereby achieving effective management of possible travel energy consumption objects during vehicle travel and reducing the travel energy consumption of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0025] Figure 1 is a schematic diagram of a vehicle thermal management method according to an embodiment of the present application;

[0026] Figure 2 is a schematic diagram of a process for determining a first controlled object in a vehicle thermal management method according to an embodiment of the present application;

[0027] Figure 3 is a schematic flow chart of a vehicle thermal management method according to an embodiment of the present application for determining whether a third controlled object includes a battery;

[0028] Figure 4 is a schematic diagram of the first coefficient of the vehicle thermal management method according to an embodiment of the present application;

[0029] Figure 5 is a schematic diagram of a flow chart of determining a specific second controlled object in a vehicle thermal management method according to an embodiment of the present application;

[0030] Figure 6 is a schematic structural diagram of a vehicle thermal management device according to an embodiment of the present application;

[0031] Figure 7 It is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] The scheme of the embodiment of the present application is described in detail below in conjunction with the drawings of the specification.

[0033] In the following description, for the purpose of explanation rather than limitation, specific details such as specific system structures, interfaces, and technologies are provided to facilitate a thorough understanding of the present application.

[0034] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0035] The terms "first", "second", "third" in this application are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, the features defined as "first", "second", "third" can expressly or implicitly include at least one of the features. In the description of this application, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. In the embodiments of this application, all directional indications (such as up, down, left, right, front, back...) are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication also changes accordingly. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the steps or units listed, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices.

[0036] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0037] Please attend Figure 1 , Figure 1 A vehicle thermal management method is shown, which is used to effectively manage possible travel energy consumption objects during vehicle travel to reduce the vehicle's travel energy consumption.

[0038] 101: Obtaining predicted travel information, where the predicted travel information includes predicted travel distance and predicted travel duration;

[0039] The vehicle obtains the predicted travel information for this trip, including the predicted travel distance and predicted travel duration.

[0040] In some embodiments, a neural network model is trained by collecting the travel time, travel mileage, starting and destination locations, and historical traffic conditions information of the user's historical navigation information, so as to predict the user's predicted travel distance and predicted travel duration based on the neural network model.

[0041] In some embodiments, the vehicle obtains the user's historical travel data, and determines the habitual travel data therefrom to obtain the predicted trip information. That is, for a vehicle user who travels regularly, the vehicle obtains the starting point and destination of the habitual trip to obtain the predicted trip distance, and then obtains the predicted trip duration based on the predicted trip distance and road condition information.

[0042] Exemplarily, for regularly appearing vehicle users, they may be the residence and workplace of commuting users, and may be the starting point and destination of transportation users, such as bus scenarios and cargo transportation scenarios, which are not specifically limited here.

[0043] In some implementations, the vehicle responds to input data of the starting point and the destination input by the user, and then obtains a predicted travel distance based on the input data, and then obtains a predicted travel duration, for example, through navigation software.

[0044] 102: predicting the predicted power energy consumption of the vehicle according to the predicted travel information and environmental information, wherein the environmental information includes road condition information and climate temperature information associated with the predicted travel information;

[0045] The vehicle generates the predicted power energy consumption of the vehicle based on the predicted trip information and the environmental information, wherein the environmental information includes the road condition information and the climate temperature information. The predicted power energy consumption indicates the predicted power energy consumption of the vehicle during this trip.

[0046] In some embodiments, the predicted power consumption is calculated based on the predicted travel distance and the historical average power consumption, which can be recorded locally in the vehicle system or obtained through the cloud. Specifically, the calculation formula is:

[0047] Q drive =E ave ·S

[0048] In the formula, E ave is the historical average power consumption, and S is the predicted travel distance.

[0049] In some embodiments, in order to further improve the accuracy of power prediction energy consumption, the vehicle obtains a predicted travel distance including multiple predicted travel intervals, that is, the sum of the multiple predicted travel intervals is the predicted travel distance, and obtains road condition information of the corresponding predicted travel interval, and the road condition information includes the predicted vehicle speed and the predicted road slope. Among them, the road slope can be obtained based on the navigation software, or the road slope recorded in the history can be obtained. Similarly, the vehicle speed can also be obtained based on the navigation software combined with the current traffic information of the corresponding route of the predicted travel information.

[0050] The predicted power energy consumption of each segment corresponding to each predicted travel distance is calculated by predicting the travel distance and the road condition information, thereby obtaining the predicted power energy consumption of all segments, that is, the predicted power energy consumption.

[0051] Among them, the calculation method of segmented power prediction energy consumption is as follows:

[0052]

[0053] Where: m is the vehicle mass, g is the acceleration of gravity, f is the rolling resistance coefficient, C D is the drag coefficient, A is the frontal area, u is the vehicle speed, β is the road slope, δ is the rotation mass conversion coefficient, S i To predict the stroke interval, the rolling resistance coefficient, frontal area, drag coefficient and rotating mass conversion factor are preset values.

[0054] 103: predicting a first controlled object according to the predicted power consumption, the climate temperature information, and the predicted travel information, wherein the first controlled object includes at least zero items of the following first set: a seat, a steering wheel, and a battery capable of variable temperature operation, and an air conditioning system capable of starting and operating;

[0055] The vehicle determines a first controlled object based on the predicted power consumption, climate temperature information, and predicted travel information. The first controlled object is determined from a first set including a seat, a steering wheel, a battery, and an air conditioning system. The seat, the steering wheel, and the battery can be operated at variable temperatures, and the air conditioning system can be started.

[0056] It is understandable that the determined first controlled object may be the zero item of the first set, that is, the first controlled object does not include any object of the first set; the determined first controlled object may also be a combination of the first set.

[0057] 104: Run or not run the first controlled object.

[0058] After the vehicle determines the first controlled object, the vehicle operates or does not allow the first controlled object based on the specific object of the first controlled object.

[0059] It can be understood that when the first controlled object is zero, the vehicle does not operate the first controlled object. When the first controlled object is a combination of the first set, the vehicle operates the first controlled object, for example, when the first controlled object is a seat and an air conditioning system, the vehicle operates the seat set and starts the air conditioning system.

[0060] Based on the predicted trip information, the present application autonomously selects a first controlled object that matches the predicted trip information from a first set including seats, steering wheels, batteries, and air-conditioning systems, thereby achieving effective management of possible travel energy consumption objects during vehicle travel and reducing the vehicle's travel energy consumption.

[0061] See also Figure 2 , Figure 2 It shows how to determine the first controlled object, including:

[0062] 201: determining a second controlled object from the following second set according to the predicted travel information, and then predicting the predicted energy consumption of the cabin of the second controlled object, wherein the prediction method of the predicted energy consumption of the cabin includes the predicted travel information and the climate temperature information, the second set includes: the seats and steering wheels capable of variable temperature operation, and the air conditioning system capable of start-up operation, and the second controlled object includes at least zero items of the second set;

[0063] The vehicle determines a second controlled object based on the predicted trip information, and then obtains the predicted cabin energy consumption of the second controlled object. The second controlled object is determined from a second set including a seat, a steering wheel, and an air conditioning system. The predicted cabin energy consumption indicates the energy consumed by the second controlled object during the current trip of the vehicle.

[0064] It is understandable that the determined second controlled object may be the zero item of the second set, that is, the second controlled object does not include any object of the second set; the determined second controlled object may also be a combination of the second set.

[0065] 202: predicting whether a third controlled object includes the battery according to the predicted power energy consumption and the predicted cabin energy consumption, and the battery information of the battery;

[0066] The vehicle predicts whether to include a third controlled object including a battery based on the predicted power consumption and the predicted cabin energy consumption, as well as the battery information of the battery. The battery information includes battery prediction information and the current power of the battery, and the battery prediction information includes the predicted remaining power of the battery and the predicted temperature control energy consumption of the battery.

[0067] The current battery charge indicates the current battery charge of the vehicle during this trip.

[0068] The predicted temperature control energy consumption of the battery means the predicted temperature change energy consumption consumed by the battery to change the temperature from the current temperature to the target temperature, or the predicted temperature change energy consumption consumed by the battery to change the temperature from the current temperature to the target temperature and the predicted temperature maintenance energy consumption consumed to maintain the target temperature.

[0069] The predicted remaining charge level of the battery indicates the remaining charge level of the battery predicted based on the current charge level of the battery and the temperature change from the current temperature to the target temperature.

[0070] 203: Determine that the second controlled object and the third controlled object are the first controlled object.

[0071] After determining whether the third controlled object includes a battery, the vehicle determines the second controlled object and the third controlled object together as the first controlled object.

[0072] It can be understood that when the second controlled object is the zero item of the second set and the third controlled object does not include a battery, the first controlled object is an empty set, which does not have any controlled object, and thus the first controlled object is not operated in the aforementioned step 104; when the second controlled object is a combination of the second set and the third controlled object does not include a battery, the first controlled object includes the combination of the second set; when the second controlled object is a combination of the second set and the third controlled object includes a battery, the first controlled object includes the combination of the second set and the battery, and for the latter two, the first controlled object is operated in the aforementioned step 104.

[0073] See also Figure 3 , Figure 3 The process of determining whether the third controlled object includes a battery is shown, wherein the vehicle calculates a first ratio based on the power predicted energy consumption, the cabin predicted energy consumption and the current power, and the vehicle calculates a second ratio based on the power predicted energy consumption, the vehicle predicted energy consumption and the predicted temperature control energy consumption, and the predicted power reserve. Figure 3 include:

[0074] 301: In response to the first ratio being greater than the second ratio, predicting a third controlled object including the battery;

[0075] In response to the first ratio being greater than the second ratio, the vehicle predicts that a third controlled object including a battery is obtained.

[0076] 302: In response to the first ratio being less than or equal to the second ratio, predicting a third controlled object that does not include the battery.

[0077] In response to the first ratio being less than or equal to the second ratio, the vehicle predicts a third controlled object that does not include a battery.

[0078] In some embodiments, the specific calculation formula of the first ratio is:

[0079]

[0080] The specific calculation formula of the second ratio is:

[0081]

[0082] Among them, Q drive represents the predicted power consumption, Q hs represents the predicted energy consumption of the cabin, Q battery_heat represents the predicted temperature control energy consumption, Indicates the current battery charge. Indicates the estimated remaining battery power.

[0083] In some embodiments, after the second controlled object is determined, since the predicted energy consumption of each corresponding second controlled object is already in the prior art, this application will not repeat it in detail. The predicted energy consumption of each corresponding second controlled object can be obtained by the prior art, and then the predicted energy consumption of the cabin is obtained by summing them up. For example, the calculation formula for the predicted energy consumption of the cabin is Q HS =Q H1 +Q H2 +Q H3 , where Q H1 represents the predicted energy consumption of starting the air conditioning system, Q H2 represents the predicted energy consumption of the temperature-controlled steering wheel, Q H3 Represents the predicted energy consumption of a temperature-controlled seat.

[0084] In some implementations, to further optimize the energy consumption of the air conditioning system, a first coefficient k is set to adjust the energy consumption of the air conditioning system. Figure 4 , Figure 4 The specific first coefficients under different combinations of predicted travel distances and predicted travel times are shown, namely, Q H1 =kQ h1 , Q h1 Indicates the predicted energy consumption of the air-conditioning system before optimization, for example, calculated by calculating the load curve of the air-conditioning system and the predicted travel time through the ambient temperature and the air-conditioning target control temperature.

[0085] In some embodiments, the predicted energy consumption of the variable temperature steering wheel and the predicted energy consumption of the variable temperature seat can be determined by the temperature change strategy to determine the corresponding thermal power and working time, wherein the working time can be the predicted travel time, the user-set time, or the working time determined based on the temperature change strategy.

[0086] In some embodiments, the predicted temperature control energy consumption of the battery indicates the predicted temperature change energy consumption consumed by the battery from the current temperature to the target temperature, or the predicted temperature change energy consumption consumed by the battery from the current temperature to the target temperature and the predicted temperature maintenance energy consumption consumed by the battery to maintain the target temperature. Therefore, the calculation formula of the predicted temperature control energy consumption of the battery is Q BH1 =α(T N -T0), the calculation formula of the predicted temperature control energy consumption of the battery is Q BH2 =h·(T N -T E )·t, where T N represents the target temperature predicted by the battery, T0 represents the current temperature of the battery, T EThe climate temperature represents the climate temperature information, α is the battery heating coefficient, h is the battery heat exchange correlation coefficient, the battery heating coefficient and the battery heat exchange correlation coefficient are preset values, and t represents the predicted travel time.

[0087] In some embodiments, the predicted remaining battery charge may be based on T N Furthermore, in order to improve the accuracy of battery power prediction, the battery type and corresponding T N Look up the Soc table to obtain the predicted remaining power of the vehicle battery.

[0088] See also Figure 5 , Figure 5 Further, based on the association relationship between the preset second controlled object and the plurality of predicted trip information, a specific second controlled object under the corresponding predicted trip information is determined, wherein the association relationship includes pre-classifying the predicted trip information into trip categories of short-distance trip, medium-distance trip or long-distance trip, including:

[0089] 501: In response to the predicted trip information being the short trip, determining the seat and / or the steering wheel as the second controlled object from the second set;

[0090] In response to the predicted trip information being a short trip, the vehicle determines a seat and / or a steering wheel as a second controlled object from the second set.

[0091] 502: In response to the predicted trip information being the mid-trip, determining the seat, and / or the steering wheel, and the air conditioning system as the second controlled object from the second set;

[0092] In response to the predicted trip information being a mid-trip, the vehicle determines a seat, and / or a steering wheel, and an air conditioning system as a second controlled object from the second set;

[0093] Preferably, for mid-journey trips, the air conditioning system is operated at limited power during operation to reduce energy consumption.

[0094] 503: In response to the predicted trip information being the long-distance trip, determining the air-conditioning system as the second controlled object from the second set.

[0095] In response to the predicted trip information being a long-distance trip, the vehicle determines the air-conditioning system as the second controlled object from the second set.

[0096] It can be understood that the vehicle in the aforementioned embodiment includes a vehicle using a battery as a power source, such as an electric vehicle or a hybrid electric vehicle, which is not specifically limited here.

[0097] See also Figure 6, the present application also includes a vehicle thermal management device, comprising:

[0098] An acquisition unit 601 is used to acquire predicted travel information, where the predicted travel information includes a predicted travel distance and a predicted travel duration;

[0099] A first prediction unit 602, configured to predict the predicted power energy consumption of the vehicle according to the predicted travel information and environmental information, wherein the environmental information includes road condition information and climate temperature information associated with the predicted travel information;

[0100] The second prediction unit 603 is used to predict a first controlled object according to the power predicted energy consumption and the climate temperature information, as well as the predicted travel information, wherein the first controlled object includes at least zero items of the following first set: a seat, a steering wheel and a battery that can be operated at a variable temperature, and an air conditioning system that can be started and operated;

[0101] The execution unit 604 is configured to execute or not execute the first controlled object.

[0102] This application also includes an electronic device, see Figure 7 The method comprises: a memory 701 and a processor 702; wherein the memory is used to store programs; and the processor is used to execute the programs in the memory, including executing any method of the aforementioned embodiments;

[0103] Optionally, the electronic device further includes a bus system for connecting the memory and the processor so that the memory and the processor communicate with each other.

[0104] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0105] In some embodiments, the memory may be an internal storage unit of the cloud device, for example, a hard disk or memory of the cloud device. In other embodiments, the memory may also be an external storage device of the cloud device, for example, a plug-in hard disk equipped on the cloud device, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Further, the memory may also include both an internal storage unit of the cloud device and an external storage device. The memory is used to store an operating system, an application, a boot loader (BootLoader), data, and other programs, such as program code of a computer program, etc. The memory may also be used to temporarily store data that has been output or is to be output.

[0106] The present application also includes a computer-readable storage medium, which stores program instructions therein, and the program instructions are executed by a processor to implement any method in the aforementioned embodiments.

[0107] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of each of the above-mentioned method embodiments can be implemented.

[0108] The computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form. Computer readable media may include at least: any entity or device capable of carrying computer program code to a camera / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electric carrier signal, a telecommunication signal and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer readable media cannot be electric carrier signals and telecommunication signals.

[0109] The above are only implementation methods of the present application, and are not intended to limit the patent protection scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A vehicle thermal management method, characterized in that: include: Acquire predicted travel information, wherein the predicted travel information includes predicted travel distance and predicted travel duration; Predicting the predicted power energy consumption of the vehicle according to the predicted travel information and environmental information, wherein the environmental information includes road condition information and climate temperature information associated with the predicted travel information; A first controlled object is predicted based on the predicted power consumption, the climate temperature information, and the predicted travel information, wherein the first controlled object includes at least zero items of the following first set: a seat, a steering wheel, and a battery that can be operated at a variable temperature, and an air conditioning system that can be started and operated; The first controlled object is operated or not operated.

2. The vehicle thermal management method according to claim 1, characterized in that: The first controlled object is predicted based on the predicted power consumption, the climate temperature information, and the predicted travel information. The first controlled object includes one or a combination of the following first set: a seat, a steering wheel, and a battery that can be operated at a variable temperature, and an air conditioning system that can be started and operated, including: Determine a second controlled object from the following second set according to the predicted travel information, and then predict the predicted energy consumption of the cabin of the second controlled object, wherein the prediction method of the predicted energy consumption of the cabin includes the predicted travel information and the climate temperature information, the second set includes: the seats and steering wheels with variable temperature operation, and the air conditioning system that can be started and operated, and the second controlled object includes at least zero items of the second set; According to the predicted power energy consumption and the predicted cabin energy consumption, and the battery information of the battery, predict whether a third controlled object includes the battery, wherein the battery information includes the current power of the battery, the predicted remaining power of the battery, and the predicted temperature control energy consumption of the battery; The second controlled object and the third controlled object are determined to be the first controlled object.

3. The vehicle thermal management method according to claim 2, characterized in that: The predicting whether the third controlled object includes the battery according to the predicted power energy consumption and the predicted cabin energy consumption, and the battery information of the battery, comprises: In response to the first ratio being greater than the second ratio, predicting that a third controlled object including the battery is obtained; In response to the first ratio being less than or equal to the second ratio, predicting a third controlled object that does not include the battery; Among them, the first ratio is calculated based on the predicted power energy consumption, the predicted cabin energy consumption and the current power, and the second ratio is calculated based on the predicted power energy consumption, the predicted cabin energy consumption and the predicted temperature control energy consumption, as well as the predicted power margin.

4. The vehicle thermal management method according to claim 3, characterized in that: The specific calculation formula of the first ratio is: The specific calculation formula of the second ratio is: Among them, Q drive represents the predicted energy consumption of the power, Q hs represents the predicted energy consumption of the cabin, Q battery_heat represents the predicted temperature control energy consumption, represents the current charge of the battery, Indicates the predicted remaining power level of the battery.

5. The vehicle thermal management method according to claim 4, characterized in that: The calculation method of the predicted cabin energy consumption includes a first coefficient determined by the predicted travel distance and the predicted travel duration.

6. The vehicle thermal management method according to claim 3, characterized in that: The predicted temperature control energy consumption includes predicting the temperature change predicted energy consumption consumed by the battery when changing the temperature from the current temperature to the target temperature, or predicting the temperature change predicted energy consumption consumed by the battery when changing the temperature from the current temperature to the target temperature and the temperature maintenance predicted energy consumption consumed when maintaining the target temperature.

7. The vehicle thermal management method according to claim 6, characterized in that: The calculation formula of the temperature change prediction energy consumption is: Q BH1 =α(T N -T0), the calculation formula of the temperature maintenance prediction energy consumption is: Q BH2 =h·(T N -T E )·t, where T N represents the target temperature predicted by the battery, and T0 represents the current temperature of the battery.

8. The vehicle thermal management method according to any one of claims 2 to 7, characterized in that: The method further includes trip categories of short-distance trips, medium-distance trips, and long-distance trips, and the step of determining a second controlled object from the following second set according to the predicted trip information includes: In response to the predicted trip information being the short trip, determining the seat and / or the steering wheel as the second controlled object from the second set; In response to the predicted trip information being the mid-trip, determining the seat, and / or the steering wheel, and the air conditioning system as the second controlled object from the second set; In response to the predicted trip information being the long-distance trip, the air-conditioning system is determined as the second controlled object from the second set.

9. The vehicle thermal management method according to any one of claims 1 to 7, characterized in that: The obtaining of predicted travel information includes: Determining the usual travel data from the historical travel data to obtain the predicted trip information; or, In response to input data entered by the user, the predicted travel information is obtained.

10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the vehicle thermal management method according to any one of claims 1 to 9.

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