Vehicle and vehicle energy management method

Abstract

The present application discloses a vehicle and a vehicle energy management method. The method comprises: if a navigation system of a vehicle is enabled, on the basis of navigation information, determining a target traveling distance of the vehicle; if the navigation system of the vehicle is not enabled, when startup spatiotemporal parameters of the vehicle meet preset spatiotemporal parameter conditions, determining the target traveling distance on the basis of a historical traveling distance probability distribution of the vehicle, wherein the preset spatiotemporal parameter conditions comprise: the startup spatiotemporal parameters fall within a target spatiotemporal parameter interval, and a probability value of the target spatiotemporal parameter interval in a historical spatiotemporal parameter probability distribution of the vehicle is greater than or equal to a probability threshold; and acquiring a predicted temperature change value of a power battery at the target traveling distance, on the basis of the predicted temperature change value, determining whether the vehicle meets a safe traveling condition, and if so, controlling the vehicle to enter an energy management working condition. The present application can improve vehicle energy management efficiency.

Description

Vehicles and Vehicle Energy Management Methods

[0001] Cross-references to related applications

[0002] This application claims priority to Chinese Patent Application No. 202411576940.5, filed on November 6, 2024, entitled "Vehicle and Vehicle Energy Management Method", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application belongs to the field of vehicle control technology, and in particular relates to a vehicle and a vehicle energy management method. Background Technology

[0004] Vehicle energy management refers to the effective utilization and optimized allocation of a vehicle's energy to improve its overall efficiency and sustainability, such as increasing its driving range. For new energy vehicles, energy management includes, but is not limited to, battery charging and discharging strategies, energy recovery, and power distribution. Clearly, effective energy management strategies play a crucial role in improving vehicle performance.

[0005] Currently, some technologies manage vehicle energy based on driving distance, but this method relies on vehicle navigation and is not very applicable when the vehicle navigation is not enabled. Summary of the Invention

[0006] The embodiments of this application provide a vehicle and a vehicle energy management method, which can at least to some extent help improve the vehicle's driving range while avoiding the impact of energy management on the vehicle's safe driving, thereby improving energy management efficiency.

[0007] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0008] A first aspect of this application provides a vehicle energy management method, wherein the vehicle includes a power battery, the method comprising:

[0009] If the vehicle's navigation is enabled, the target driving distance of the vehicle is determined based on the navigation information;

[0010] If the vehicle's navigation is not activated, then if the vehicle's startup spatiotemporal parameters meet the preset spatiotemporal parameter conditions, the target driving distance is determined according to the vehicle's historical driving distance probability distribution. The preset spatiotemporal parameter conditions include: the startup spatiotemporal parameters are located within the target spatiotemporal parameter interval, and the probability value of the target spatiotemporal parameter interval in the vehicle's historical spatiotemporal parameter probability distribution is greater than or equal to a probability threshold.

[0011] The predicted temperature change of the power battery under the target driving distance is obtained. Based on the predicted temperature change, it is determined whether the vehicle meets the safe driving conditions. If so, the vehicle is controlled to enter the energy management mode.

[0012] Optionally, the start-up spatiotemporal parameters include start-up location and start-up time, the preset spatiotemporal parameter conditions include preset location conditions and preset time conditions, and the vehicle's start-up spatiotemporal parameters satisfying the preset spatiotemporal parameter conditions include:

[0013] The starting position of the vehicle satisfies the preset position conditions, which include: the starting position is located in a target starting position interval, and the first probability value of the target starting position interval in the probability distribution of the vehicle's historical starting position is greater than or equal to a first probability threshold.

[0014] The vehicle's start time meets the preset time conditions, which include: the start position is located within a target start time interval, and the second probability value of the target time position interval in the vehicle's historical start time probability distribution is greater than or equal to a second probability threshold.

[0015] Optionally, determining the target driving distance based on the probability distribution of the vehicle's historical driving distance includes:

[0016] Obtain the probability distribution of each driving distance and each distance interval in the vehicle's history;

[0017] The expected value is determined based on the probability distribution of each driving distance and the distance intervals, and the expected value is used as the target driving distance.

[0018] Optionally, obtaining the predicted temperature change value of the power battery at the target driving distance, and determining whether the vehicle meets the safe driving conditions based on the predicted temperature change value, includes:

[0019] Obtain the historical temperature change value of the power battery under the target driving distance, and use the historical temperature change value as the temperature change prediction value;

[0020] Obtain the temperature difference between the current temperature value of the power battery and the safe temperature threshold.

[0021] If the predicted temperature change is less than or equal to the temperature difference, then the vehicle meets the safe driving conditions.

[0022] Optionally, obtaining the predicted temperature change value of the power battery at the target driving distance, and determining whether the vehicle meets the safe driving conditions based on the predicted temperature change value, includes:

[0023] The temperature difference between the current temperature value of the power battery and the safe temperature threshold is obtained, and the temperature difference is used as the predicted temperature change value.

[0024] The ambient temperature is obtained, and based on a preset correspondence, a safe distance threshold corresponding to the ambient temperature and the predicted temperature change is determined, wherein the safe distance threshold is the maximum driving distance of the vehicle when the battery temperature of the power battery is less than the safe temperature threshold.

[0025] If the target driving distance is less than or equal to the safe distance threshold, then the vehicle meets the safe driving conditions.

[0026] Optionally, after controlling the vehicle to enter the energy management mode, the method further includes:

[0027] During vehicle operation, the power battery is not cooled when its temperature is below a first temperature threshold, and / or the power battery is not heated when its temperature is above a second temperature threshold, wherein the first temperature threshold is above the second temperature threshold.

[0028] Optionally, the vehicle includes an air conditioning system, and after controlling the vehicle to enter energy management mode, the method further includes:

[0029] If, during vehicle operation, the remaining distance to the target travel distance is less than or equal to a preset distance, the air conditioning system will be adjusted as follows:

[0030] When the ambient temperature is greater than or equal to a third temperature threshold, the air conditioning system is adjusted to a first target temperature, wherein the first target temperature is greater than a user-preset temperature;

[0031] Alternatively, when the ambient temperature is less than or equal to a fourth temperature threshold, the air conditioning system is adjusted to a second target temperature, wherein the fourth temperature threshold is less than the third temperature threshold, and the second target temperature is less than the user-preset temperature.

[0032] Optionally, after controlling the vehicle to enter the energy management mode, the method further includes:

[0033] If a user's request to exit energy management is detected, and / or if an abnormality is detected in the energy management condition, the vehicle is controlled to exit the energy management condition.

[0034] The energy management exit requirements include: improved comfort requirements and / or improved power requirements.

[0035] Optionally, the method is applied to the commuting conditions of the vehicle.

[0036] A second aspect of this application provides a vehicle energy management device, the vehicle including a power battery, the device comprising:

[0037] The first determining unit is used to determine the target driving distance of the vehicle based on navigation information if the vehicle's navigation is turned on.

[0038] The second determining unit is configured to determine the target driving distance based on the historical driving distance probability distribution of the vehicle if the vehicle's navigation is not activated, provided that the vehicle's startup spatiotemporal parameters meet preset spatiotemporal parameter conditions. The preset spatiotemporal parameter conditions include: the startup spatiotemporal parameters are located within the target spatiotemporal parameter interval, and the probability value of the target spatiotemporal parameter interval in the historical spatiotemporal parameter probability distribution of the vehicle is greater than or equal to a probability threshold.

[0039] The third determining unit is used to obtain the predicted temperature change value of the power battery under the target driving distance, and determine whether the vehicle meets the safe driving conditions based on the predicted temperature change value. If so, the vehicle is controlled to enter the energy management mode.

[0040] A third aspect of this application provides a computer-readable storage medium storing at least one computer program instruction, which is loaded and executed by a processor to perform the operations described in any of the methods described in the first aspect.

[0041] According to a fourth aspect of the embodiments of this application, a vehicle is provided, including one or more processors and one or more memories, wherein at least one piece of program code is stored in the one or more memories, the at least one piece of program code being loaded and executed by the one or more processors to perform the operations performed as described in any of the methods of the first aspect.

[0042] The embodiments of the present invention provide one or more technical solutions that achieve at least the following technical effects or advantages:

[0043] The vehicle energy management method provided in this application embodiment determines the target driving distance of the vehicle based on navigation information if the vehicle's navigation is on. If the vehicle's navigation is not on, the target driving distance is determined based on the probability distribution of the vehicle's historical driving distance, provided that the vehicle's startup spatiotemporal parameters meet preset spatiotemporal parameter conditions. The preset spatiotemporal parameter conditions include: the startup spatiotemporal parameters being located within a target spatiotemporal parameter interval, and the probability value of the target spatiotemporal parameter interval in the probability distribution of the vehicle's historical spatiotemporal parameters being greater than or equal to a probability threshold. The method also obtains a predicted temperature change value of the power battery at the target driving distance and determines whether the vehicle meets safe driving conditions based on the predicted temperature change value. If so, the method controls the vehicle to enter energy management mode. Therefore, the target driving distance of the vehicle can be determined even when navigation is not on. Based on the target driving distance and the predicted temperature change value of the power battery, it is determined whether the vehicle meets safe driving conditions. When the vehicle meets safe driving conditions, the method controls the vehicle to enter energy management mode, thereby helping to improve the vehicle's driving range while avoiding the impact of energy management on safe driving, thus improving energy management efficiency.

[0044] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0045] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0046] Figure 1 shows a flowchart of a vehicle energy management method according to an embodiment of this application;

[0047] Figure 2 shows a probability distribution of historical vehicle usage locations according to an embodiment of this application.

[0048] Figure 3 shows the historical startup time probability distribution of an embodiment of this application;

[0049] Figure 4 shows the probability distribution of historical driving distances in an embodiment of this application;

[0050] Figure 5 shows a structural diagram of a vehicle energy management device according to an embodiment of this application;

[0051] Figure 6 shows a schematic diagram of the structure of a computer system suitable for implementing the embodiments of this application in a vehicle. Detailed Implementation

[0052] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0053] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0054] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0055] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0056] It should also be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such uses of these terms can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described.

[0057] Referring to Figure 1, a flowchart of an energy management method according to an embodiment of this application is shown.

[0058] As shown in Figure 1, a first aspect of this application provides a vehicle energy management method, wherein the vehicle includes a power battery, and the method includes:

[0059] Step S10. If the vehicle's navigation is enabled, determine the target driving distance of the vehicle based on the navigation information;

[0060] Understandably, when the vehicle's navigation is on, the navigation system can provide real-time information such as the total distance between the vehicle and the destination, the remaining distance, the current time, the remaining time, and the real-time vehicle speed. Based on this navigation information, it can effectively determine whether the trip is a short trip and the target driving distance for the trip.

[0061] Step S20. If the vehicle's navigation is not turned on, then if the vehicle's startup spatiotemporal parameters meet the preset spatiotemporal parameter conditions, the target driving distance is determined according to the vehicle's historical driving distance probability distribution. The preset spatiotemporal parameter conditions include: the startup spatiotemporal parameters are located in the target spatiotemporal parameter interval, and the probability value of the target spatiotemporal parameter interval in the vehicle's historical spatiotemporal parameter probability distribution is greater than or equal to a probability threshold.

[0062] It should be noted that, in cases where the vehicle's navigation is not activated, or where the vehicle does not follow navigation instructions after activation, this embodiment of the application can predict the most probable driving conditions based on the user's historical driving habits. Therefore, it is possible to pre-learn the user's historical driving habits.

[0063] Understandably, when learning from a user's historical driving habits, those habits need to exhibit certain regularity. For example, during commuting, a user's driving habits are usually quite regular. Therefore, the following explanation uses commuting as an example to illustrate the self-learning process of a user's historical driving habits.

[0064] Understandably, when conducting self-learning, irregular information features can be filtered out first. For example, the premise of self-learning a user's historical driving habits is that the driving time is a weekday. For instance, the vehicle's TBOX (remote communication terminal) sends time information (lunar or solar calendar date), and the vehicle controller determines whether the current date is a statutory holiday or a weekend. Thus, the driving information of non-filtered weekends or holidays is filtered out, leaving the driving information of weekdays, in order to improve the accuracy of subsequent self-learning.

[0065] Referring to Figure 2, a probability distribution map of historical vehicle location according to an embodiment of this application is shown.

[0066] As shown in Figure 2, the historical travel location of the user's vehicle is obtained. For example, the most probable location is home or office. For instance, the TBOX (remote communication terminal) sends the longitude and latitude information of the vehicle to the controller, such as 114°E and 30°N. The controller obtains several longitude and latitude information to obtain the start and end locations of the user's vehicle over a period of time, and then analyzes the probability distribution of historical vehicle usage locations.

[0067] Referring to Figure 3, a probability distribution diagram of historical startup time of an embodiment of this application is shown.

[0068] As shown in Figure 3, the user's vehicle start time is obtained within a certain period of time. For example, under commuting conditions, big data analysis determines that the user's work hours are from 6:30 to 9:00 and their get off work hours are from 17:00 to 21:00. There may also be two trips between 11:00 and 14:00 at noon, so the number of times the vehicle is used per day is 2 to 4.

[0069] Understandably, if a user makes 5 or more trips in a day, only the departure times of the first two trips need to be used. Additionally, if the vehicle's journey distance is short, such as less than or equal to 3km, it can be ignored. For example, the TBOX (remote communication terminal) sends the vehicle's starting time to the controller. The controller obtains the user's vehicle's start times over a period of time and can then analyze the historical start time probability distribution. For instance, in Figure 3, the start time probability is highest between 6.7 and 7.53, followed by 19.7 to 20.35, and then 18.4 to 19.05.

[0070] Referring to Figure 4, a probability distribution diagram of historical driving distances according to an embodiment of this application is shown.

[0071] As shown in Figure 4, the distribution of the user's vehicle's travel distance over a certain period is obtained. The distribution interval can be 5km, 3km, or 2km; no specific limitation is made here. The vehicle's travel distance refers to the actual distance traveled from power-on to power-off. For example, the navigation system sends the vehicle's travel distance to the controller. The controller obtains the user's vehicle's startup time over a period and can then analyze the historical travel distance probability distribution. For instance, in Figure 4, the 11.4-15.2 km distance interval has the highest probability, followed by the 0-3.8 km distance interval. Therefore, the travel distance distribution probability x... i and distance interval d i The expected value S can be determined, i.e., S = ∑x i *d i .

[0072] In some embodiments, when self-learning from a user's historical driving habits, the historical driving dynamic characteristics of the user's vehicle can also be analyzed, such as the maximum drive power and maximum regenerative braking power per trip. The maximum drive power reflects the user's maximum acceleration demand, and the maximum regenerative braking power reflects the user's maximum deceleration demand. Based on these maximum acceleration or deceleration demands, it can be determined whether the charging and discharging capacity of the power battery covers the user's power requirements. Thus, the historical probability distributions of maximum drive power and maximum regenerative braking power can be obtained, and based on these probability distributions, expected values ​​can be calculated. These expected values ​​reflect the user's maximum power and maximum braking demands.

[0073] In some embodiments, when self-learning from a user's historical driving habits, the historical temperature variation characteristics of the vehicle's power battery can also be analyzed. For example, during vehicle operation, under different ambient temperatures and without thermal management of the power battery, the temperature change of the power battery during a single trip, such as the change in cell temperature, can be obtained. For instance, a functional relationship z = f(x, y) can be established based on the ambient temperature, the single-trip distance, and the cell temperature change value during the single trip, where z represents the cell temperature change value, x represents the ambient temperature, and y represents the single-trip distance.

[0074] Furthermore, vehicle speed also affects cell temperature over the same distance traveled; for example, higher speeds result in greater cell temperature increases. For instance, during commuting, lower speeds lead to smaller cell temperature increases, such as 2°C, while at higher speeds, the increases are larger, such as 4°C. Therefore, when analyzing battery temperature change characteristics later, if the vehicle speed is higher, such as greater than 140 km / h, a correction factor for the effect of vehicle speed on cell temperature changes can be increased. For example, a correction factor of 2 means that the cell temperature change at high speeds is twice that under commuting conditions.

[0075] In some embodiments, when learning from users' historical driving habits, the probability distribution of historical passenger cabin temperature can also be analyzed.

[0076] It is understandable that the spatiotemporal parameters of vehicle startup can refer to the time and space parameters at the time of vehicle startup. The time parameter can be the startup time, and the space parameter can be the startup location. When analyzing the probability distribution of spatiotemporal parameters, multiple spatiotemporal parameter intervals are set, each with a corresponding probability value. Thus, the probability values ​​of multiple spatiotemporal parameter intervals constitute the spatiotemporal parameter probability distribution.

[0077] Because the probability distributions of vehicle location, start time, and travel distance under commuting conditions are learned in advance, when the probability value of the target spatiotemporal parameter where the start time spatiotemporal parameter falls is greater than or equal to a probability threshold, such as greater than or equal to 50%, 60%, or 70%, it indicates that this interval accounts for a large proportion of the entire probability distribution. For example, if the start time is in the period of 6.7-7.35 in Figure 3, this period accounts for a large proportion, indicating that this period is more likely to fall within the commuting condition's time frame. In this case, the most probable target travel distance under commuting conditions is further obtained based on the historical travel distance probability distribution.

[0078] In some embodiments, the start-up spatiotemporal parameters include start-up location and start-up time, and the preset spatiotemporal parameter conditions include preset location conditions and preset time conditions. The vehicle's start-up spatiotemporal parameters satisfying the preset spatiotemporal parameter conditions include:

[0079] Step S21. The starting position of the vehicle satisfies the preset position condition, the preset position condition including: the starting position is located in a target starting position interval, and the first probability value of the target starting position interval in the probability distribution of the vehicle's historical starting position is greater than or equal to a first probability threshold.

[0080] For example, the latitude and longitude information of the starting location is 114° East longitude and 30° North latitude, which is located in the target starting location range, and the first probability value of the range is greater than or equal to 70%.

[0081] Step S22. The vehicle's start time satisfies the preset time condition, which includes: the start position is located within a target start time interval, and the second probability value of the target time position interval in the vehicle's historical start time probability distribution is greater than or equal to a second probability threshold.

[0082] For example, the start time is 7 a.m., which is within the target start time interval, where the first probability value is greater than or equal to 60%.

[0083] In some embodiments, determining the target driving distance based on the probability distribution of the vehicle's historical driving distance includes:

[0084] Step S23. Obtain the probability distribution of each driving distance and each distance interval of the vehicle's history;

[0085] For example, the distance intervals include 0-3.8, 2.8-7.6, 11.4-15.2, 15.2-19, and 34.2-38. The driving distribution probabilities corresponding to these intervals are 0.35, 0.01, 0.6, 0.005, and 0.007, respectively.

[0086] Step S24. Determine the expected value based on the probability distribution of each driving distance and the distance intervals, and use the expected value as the target driving distance.

[0087] For example, under the above distance intervals and the above probability distributions for each travel distance, the expected value is: S = ∑x i *d i , where x i d represents the probability distribution of the travel distance. i Indicates a distance interval.

[0088] Step S30. Obtain the predicted temperature change value of the power battery under the target driving distance, determine whether the vehicle meets the safe driving conditions based on the predicted temperature change value, and if so, control the vehicle to enter the energy management mode.

[0089] In some embodiments, obtaining the predicted temperature change value of the power battery at the target driving distance, and determining whether the vehicle meets the safe driving conditions based on the predicted temperature change value, includes:

[0090] Step S31A. Obtain the historical temperature change value of the power battery under the target driving distance, and use the historical temperature change value as the predicted temperature change value;

[0091] Based on the above, the embodiments of this application can obtain the historical temperature change values ​​of the power battery under different driving distances through self-learning in advance.

[0092] Step S32A. Obtain the temperature difference between the current temperature value of the power battery and the safe temperature threshold;

[0093] Understandably, the safe temperature threshold is the minimum temperature value corresponding to when the performance of the power battery is unrestricted, such as the minimum temperature value corresponding to when the charging and discharging power is unrestricted. When the safe temperature threshold is exceeded, the discharge power of the power battery may decrease, thereby affecting the safe operation of the vehicle. For example, if the safe temperature threshold is 50℃, 51℃, 55℃, etc., and the current temperature value is T1, then the temperature difference is 50-T1, 51-T1, 55-T1, etc.

[0094] Step S33A. If the predicted temperature change is less than or equal to the temperature difference, then the vehicle meets the safe driving conditions.

[0095] In some embodiments, obtaining the predicted temperature change value of the power battery at the target driving distance, and determining whether the vehicle meets the safe driving conditions based on the predicted temperature change value, includes:

[0096] Step S31B. Obtain the temperature difference between the current temperature value of the power battery and the safe temperature threshold, and use the temperature difference as the predicted temperature change value;

[0097] Step S32B. Obtain the ambient temperature, and based on a preset correspondence, determine a safe distance threshold corresponding to the ambient temperature and the predicted temperature change value, wherein the safe distance threshold is the maximum driving distance of the vehicle when the battery temperature of the power battery is less than the safe temperature threshold;

[0098] Based on the above, the embodiments of this application can establish a functional relationship between battery temperature change, ambient temperature and driving distance in advance through self-learning. Thus, the maximum driving distance corresponding to the power battery temperature not exceeding the safe temperature threshold can be determined.

[0099] Step S33B. If the target driving distance is less than or equal to the safe distance threshold, then the vehicle meets the safe driving conditions.

[0100] In some embodiments, after controlling the vehicle to enter energy management mode, the method further includes:

[0101] During vehicle operation, the power battery is not cooled when its temperature is below a first temperature threshold, and / or the power battery is not heated when its temperature is above a second temperature threshold, wherein the first temperature threshold is above the second temperature threshold.

[0102] For example, the first temperature threshold is less than the safe temperature threshold, such as 45°C, 48°C, etc.

[0103] Understandably, when the ambient temperature is not very high (e.g., above 25°C but below 40°C), the temperature rise of the power battery is unlikely to exceed the safe temperature threshold. Therefore, minor cooling needs can be ignored, thus saving energy and increasing driving range. However, when the battery temperature exceeds the safe temperature threshold, cooling of the power battery is necessary to ensure safe vehicle operation.

[0104] Understandably, when the ambient temperature is not very low (e.g., above -10 degrees Celsius but below 10 degrees Celsius), the charging and discharging efficiency of the power battery is less affected by the ambient temperature, so heating the power battery is not necessary, thus saving energy. In this case, the waste heat from the engine and motor can be fully utilized to heat the battery, thereby improving waste heat utilization efficiency. However, when the ambient temperature is low, such as below -10 degrees Celsius, heating of the power battery is necessary, and the vehicle's coasting energy can also be fully utilized for heating.

[0105] In some embodiments, the vehicle includes an air conditioning system, and after controlling the vehicle to enter an energy management mode, the method further includes:

[0106] If, during vehicle operation, the remaining distance to the target travel distance is less than or equal to a preset distance, the air conditioning system will be adjusted as follows:

[0107] When the ambient temperature is greater than or equal to a third temperature threshold, the air conditioning system is adjusted to a first target temperature, wherein the first target temperature is greater than a user-preset temperature;

[0108] Alternatively, when the ambient temperature is less than or equal to a fourth temperature threshold, the air conditioning system is adjusted to a second target temperature, wherein the fourth temperature threshold is less than the third temperature threshold, and the second target temperature is less than the user-preset temperature.

[0109] It should be noted that when the vehicle's remaining driving distance is short, such as less than 3 kilometers, the air conditioning system can still meet the user's cooling or heating needs for a short time after being adjusted up or down. Therefore, when the ambient temperature is greater than or equal to the third temperature threshold, such as greater than 28 degrees Celsius, if the user's set temperature is 25 degrees Celsius, the air conditioning system temperature can be increased by 2-3 degrees Celsius, for example, adjusted to 28 degrees Celsius. Conversely, when the ambient temperature is less than or equal to the fourth temperature threshold, such as less than 10 degrees Celsius, if the user's set temperature is 25 degrees Celsius, the air conditioning system temperature can be decreased by 2-3 degrees Celsius. This saves energy.

[0110] In some embodiments, after controlling the vehicle to enter energy management mode, the method further includes:

[0111] If a user's request to exit energy management is detected, and / or if an abnormality is detected in the energy management condition, the vehicle is controlled to exit the energy management condition.

[0112] The energy management exit requirements include: improved comfort requirements and / or improved power requirements.

[0113] One example of the need to improve comfort is that if the user readjusts the air conditioning temperature after the system has been set to a temperature that is different from the user's preset temperature, it means that the user does not accept the weakening of the air conditioning system's performance and believes that comfort needs to be improved.

[0114] Among them, the demand for improved power performance can be: the user's expected value of the maximum driving power distribution is greater than the maximum long-term discharge power of the power battery. If the above situation occurs multiple times during vehicle operation, it is considered that the user needs to improve the power performance.

[0115] Among them, abnormal energy management conditions may be caused by the battery cell temperature exceeding the safe temperature threshold, the actual driving distance of the vehicle exceeding the target driving distance, or the user having the intention to charge (e.g., there is a charging station on the navigation route).

[0116] Therefore, in this embodiment, regardless of whether navigation is enabled or disabled, no cloud-based big data platform is required. The identification of commuting conditions and energy management strategies are implemented on the vehicle side, minimizing computational and data storage demands. Upon entering energy management mode, energy management of battery temperature and / or the air conditioning system saves vehicle energy and increases driving range. When user feedback indicates poor comfort, inadequate power, or abnormal energy management conditions, the system can promptly exit energy management mode, improving the user experience.

[0117] Referring to Figure 5, a structural diagram of a vehicle energy management device according to an embodiment of this application is shown.

[0118] As shown in Figure 5, a second aspect of this application provides a vehicle energy management device 200, wherein the vehicle includes a power battery, and the device 200 includes:

[0119] The first determining unit 201 is used to determine the target driving distance of the vehicle based on navigation information if the vehicle's navigation is turned on.

[0120] The second determining unit 202 is used to determine the target driving distance based on the historical driving distance probability distribution of the vehicle if the vehicle's navigation is not turned on, provided that the vehicle's startup spatiotemporal parameters meet preset spatiotemporal parameter conditions. The preset spatiotemporal parameter conditions include: the startup spatiotemporal parameters are located within the target spatiotemporal parameter interval, and the probability value of the target spatiotemporal parameter interval in the historical spatiotemporal parameter probability distribution of the vehicle is greater than or equal to a probability threshold.

[0121] The third determining unit 203 is used to obtain the predicted temperature change value of the power battery under the target driving distance, and determine whether the vehicle meets the safe driving conditions based on the predicted temperature change value. If so, the vehicle is controlled to enter the energy management mode.

[0122] According to a third aspect of the embodiments of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing at least one computer program instruction, the at least one computer program instruction being loaded and executed by a processor to perform the operation as described in any of the methods in the first aspect.

[0123] Computer-readable storage media may be portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the computer-readable storage medium of this application is not limited thereto. In this application, the readable storage medium may be any tangible medium that contains or stores a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0124] A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0125] Program code for performing the operations of this application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0126] Referring to Figure 6, it is a schematic diagram of the structure of a computer system suitable for implementing the embodiments of this application in a vehicle.

[0127] According to a fourth aspect of the embodiments of this application, a vehicle is provided, including one or more processors and one or more memories, wherein at least one piece of program code is stored in the one or more memories, and the at least one piece of program code is loaded and executed by the one or more processors to perform the operation as performed by any of the methods in the first aspect.

[0128] As shown in Figure 6, the vehicle 400 is presented in the form of a general-purpose computing device. The components of the vehicle 400 may include, but are not limited to: at least one processing unit 410, at least one storage unit 420, and a bus 430 connecting different system components (including storage unit 420 and processing unit 410).

[0129] The storage unit stores program code, which can be executed by the processing unit 410, causing the processing unit 410 to perform the steps described in the "Embodiment Method" section above according to various exemplary embodiments of this application.

[0130] Storage unit 420 may include readable media in the form of volatile storage units, such as random access memory (RAM) 421 and / or cache 422, and may further include read-only memory (ROM) 423.

[0131] Storage unit 420 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0132] Bus 430 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0133] Vehicle 400 can also communicate with one or more external devices 500 (e.g., keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable users to interact with vehicle 400, and / or any device that enables vehicle 400 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed through I / O (input / output) interface 450, which can also be connected to display unit 440 to display the communication content. Furthermore, vehicle 400 can communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 460. As shown, network adapter 460 communicates with other modules of vehicle 400 via bus 430. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with vehicle 400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0134] The functions described herein can be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions can be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and embodiments are within the scope and spirit of this invention and the appended claims. For example, due to the nature of software, the functions described above can be implemented using software executed by a processor, hardware, firmware, hardwired, or any combination thereof. Furthermore, the functional units can be integrated into a single processing unit, or each unit can exist physically separately, or two or more units can be integrated into a single unit.

[0135] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0136] The units described as separate components may or may not be physically separate. Similarly, the components of the control device may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0137] If the integrated unit is implemented as 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 technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0138] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A vehicle energy management method, characterized in that, The vehicle includes a power battery, and the method includes: If the vehicle's navigation is enabled, the target driving distance of the vehicle is determined based on the navigation information; If the vehicle's navigation is not activated, then if the vehicle's startup spatiotemporal parameters meet the preset spatiotemporal parameter conditions, the target driving distance is determined according to the vehicle's historical driving distance probability distribution. The preset spatiotemporal parameter conditions include: the startup spatiotemporal parameters are located within the target spatiotemporal parameter interval, and the probability value of the target spatiotemporal parameter interval in the vehicle's historical spatiotemporal parameter probability distribution is greater than or equal to a probability threshold. The predicted temperature change of the power battery under the target driving distance is obtained. Based on the predicted temperature change, it is determined whether the vehicle meets the safe driving conditions. If so, the vehicle is controlled to enter the energy management mode.

2. The method according to claim 1, characterized in that, The start-up spatiotemporal parameters include start-up location and start-up time; the preset spatiotemporal parameter conditions include preset location conditions and preset time conditions; the vehicle's start-up spatiotemporal parameters satisfying the preset spatiotemporal parameter conditions include: The starting position of the vehicle satisfies the preset position conditions, which include: the starting position is located in a target starting position interval, and the first probability value of the target starting position interval in the probability distribution of the vehicle's historical starting position is greater than or equal to a first probability threshold. The vehicle's start time meets the preset time conditions, which include: the start position is located within a target start time interval, and the second probability value of the target time position interval in the vehicle's historical start time probability distribution is greater than or equal to a second probability threshold.

3. The method according to claim 1, characterized in that, Determining the target driving distance based on the probability distribution of the vehicle's historical driving distance includes: Obtain the probability distribution of each driving distance and each distance interval in the vehicle's history; The expected value is determined based on the probability distribution of each driving distance and the distance intervals, and the expected value is used as the target driving distance.

4. The method according to claim 1, characterized in that, The step of obtaining the predicted temperature change value of the power battery at the target driving distance, and determining whether the vehicle meets the safe driving conditions based on the predicted temperature change value, includes: Obtain the historical temperature change value of the power battery under the target driving distance, and use the historical temperature change value as the temperature change prediction value; Obtain the temperature difference between the current temperature value of the power battery and the safe temperature threshold. If the predicted temperature change is less than or equal to the temperature difference, then the vehicle meets the safe driving conditions.

5. The method according to claim 1, characterized in that, The step of obtaining the predicted temperature change value of the power battery at the target driving distance, and determining whether the vehicle meets the safe driving conditions based on the predicted temperature change value, includes: The temperature difference between the current temperature value of the power battery and the safe temperature threshold is obtained, and the temperature difference is used as the predicted temperature change value. The ambient temperature is obtained, and based on a preset correspondence, a safe distance threshold corresponding to the ambient temperature and the predicted temperature change is determined, wherein the safe distance threshold is the maximum driving distance of the vehicle when the battery temperature of the power battery is less than the safe temperature threshold. If the target driving distance is less than or equal to the safe distance threshold, then the vehicle meets the safe driving conditions.

6. The method according to claim 1, characterized in that, After controlling the vehicle to enter energy management mode, the method further includes: During vehicle operation, the power battery is not cooled when its temperature is below a first temperature threshold, and / or the power battery is not heated when its temperature is above a second temperature threshold, wherein the first temperature threshold is above the second temperature threshold.

7. The method according to claim 1, characterized in that, The vehicle includes an air conditioning system, and after controlling the vehicle to enter energy management mode, the method further includes: If, during vehicle operation, the remaining distance to the target travel distance is less than or equal to a preset distance, the air conditioning system will be adjusted as follows: When the ambient temperature is greater than or equal to a third temperature threshold, the air conditioning system is adjusted to a first target temperature, wherein the first target temperature is greater than a user-preset temperature; Alternatively, when the ambient temperature is less than or equal to a fourth temperature threshold, the air conditioning system is adjusted to a second target temperature, wherein the fourth temperature threshold is less than the third temperature threshold, and the second target temperature is less than the user-preset temperature.

8. The method according to claim 1, characterized in that, After controlling the vehicle to enter energy management mode, the method further includes: If a user's request to exit energy management is detected, and / or if an abnormality is detected in the energy management condition, the vehicle is controlled to exit the energy management condition. The energy management exit requirements include: improved comfort requirements and / or improved power requirements.

9. The method according to any one of claims 1-8, characterized in that, The method is applied to the commuting conditions of the vehicle.

10. The method according to claim 1, characterized in that, The vehicle also includes a remote communication terminal. The starting position in the starting time-space parameters is determined by obtaining the longitude and latitude information of the vehicle through the remote communication terminal, and the starting time is determined by the time information sent by the remote communication terminal.

11. The method according to claim 1, characterized in that, The method further includes: If the vehicle's navigation is not activated, or if the vehicle does not follow the navigation instructions after activating navigation, the most probable driving conditions for this situation are predicted based on the user's historical driving habits.

12. The method according to claim 11, characterized in that, The prediction of the most probable driving conditions based on the user's historical driving habits includes: The system performs self-learning on the user's historical car usage habits; wherein, the self-learning includes filtering out unfiltered car usage information from weekends or holidays, and retaining car usage information from weekdays.

13. The method according to claim 12, characterized in that, When performing self-learning on the user's historical vehicle usage habits, the method also includes: analyzing the historical passenger compartment temperature probability distribution.

14. The method according to claim 1, further comprising: The vehicle's driving distance is obtained through the vehicle's navigation system, and the driving distance is the actual distance traveled by the vehicle from power-on to power-off. By obtaining the start time of a user's vehicle over a period of time and combining it with the vehicle's driving distance, a probability distribution map of the historical driving distance is obtained.

15. A vehicle, characterized in that, It includes one or more processors and one or more memories, wherein at least one piece of program code is stored in the one or more memories, and the at least one piece of program code is loaded and executed by the one or more processors to perform the operation performed by the method as described in any one of claims 1-14.

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