Control method and device of vehicle energy management system, vehicle and electronic device

Abstract

The application discloses a control method and device of a vehicle energy management system, a vehicle and an electronic device, and relates to the technical field of vehicles. The method comprises the following steps: acquiring a driving signal of the vehicle in a preset time segment; determining a first feature according to a dynamic signal and a second feature according to a control signal; classifying the first feature to obtain a first classification result, and classifying the second feature to obtain a second classification result; determining a target energy management mode based on the first classification result, the second classification result and a preset relationship table; and controlling the energy management system of the vehicle in a future preset time segment according to the target energy management mode. The application solves the technical problem that related technologies control the energy management system of the vehicle through fixed management rules, resulting in low comprehensiveness, low safety, low efficiency and low flexibility.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and more specifically, to a control method, apparatus, vehicle, and electronic device for a vehicle energy management system. Background Technology

[0002] With the rapid development of new energy vehicle technology, the demand for intelligent energy management in vehicles is gradually increasing. The energy management system in a vehicle is used to provide different energy sources to offer users different driving experiences. Therefore, the control methods for the vehicle energy management system are extremely important.

[0003] Currently, vehicle energy management systems are controlled through fixed management rules, but this method cannot balance drivability and comfort during driving, resulting in low comprehensiveness, low safety, low efficiency, and low flexibility.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a control method, apparatus, vehicle, and electronic device for a vehicle energy management system, to at least solve the technical problems of related technologies that control vehicle energy management systems through fixed management rules, resulting in low comprehensiveness, low security, low efficiency, and low flexibility.

[0006] According to one embodiment of the present invention, a control method for a vehicle energy management system is provided, comprising: acquiring driving signals of a vehicle within a preset time segment, wherein the driving signals are used to determine dynamic signals and control signals of the vehicle during driving; determining a first feature based on the dynamic signals and determining a second feature based on the control signals, wherein the first feature represents the driving style of the vehicle and the second feature represents the comfort style of the vehicle; classifying the first feature to obtain a first classification result and classifying the second feature to obtain a second classification result, wherein the first classification result represents the driving intensity requirement of the vehicle within the preset time segment and the second classification result represents the comfort intensity requirement of the vehicle within the preset time segment; determining a target energy management mode based on the first classification result, the second classification result, and a preset relationship table, wherein the preset relationship table represents the relationship between the driving intensity requirement, the comfort intensity requirement, and the target energy management mode, and the target energy management mode represents the energy supply intensity of the vehicle within the preset time segment; and controlling the vehicle's energy management system within a future preset time segment according to the target energy management mode.

[0007] Optionally, classifying the first feature to obtain a first classification result and classifying the second feature to obtain a second classification result includes: calculating the density function of the first feature to obtain a first density function value and calculating the density function of the second feature to obtain a second density function value; calculating the joint probability of the first density function value to obtain a first joint probability and calculating the joint probability of the second density function value to obtain a second joint probability; determining the first classification result based on the magnitude of the first joint probability and determining the second classification result based on the magnitude of the second joint probability.

[0008] Optionally, the dynamic signal includes at least one of the following: vehicle speed signal, acceleration signal, deceleration signal, accelerator pedal opening signal, and brake pedal opening signal. Determining the first feature based on the dynamic signal includes: determining a vehicle speed threshold based on the vehicle speed signal; determining an acceleration threshold based on the acceleration signal; determining a deceleration threshold based on the deceleration signal; determining an accelerator pedal opening threshold and an accelerator pedal opening change rate based on the accelerator pedal opening signal; determining a brake pedal opening threshold and a brake pedal opening change rate based on the brake pedal opening signal; and determining the first feature based on the vehicle speed threshold, acceleration threshold, deceleration threshold, accelerator pedal opening threshold, accelerator pedal opening change rate, brake pedal opening threshold, and brake pedal opening change rate.

[0009] Optionally, the control signal includes at least one of the following: an air conditioning start signal, an in-vehicle set temperature signal, an ambient temperature signal, an airflow level signal, a seat heating signal, and a seat ventilation signal. Determining the second feature based on the control signal includes: determining the air conditioning start duration based on the air conditioning start signal; determining the temperature difference based on the in-vehicle set temperature signal and the ambient temperature signal; determining the airflow threshold based on the airflow level signal; determining a heating level threshold and a first ratio based on the seat heating signal, wherein the first ratio is the ratio of the seat heating duration to a preset time segment; and determining a ventilation level threshold and a second ratio based on the seat ventilation signal, wherein the second ratio is the ratio of the seat ventilation duration to a preset time segment. The second feature is determined based on the air conditioning start duration, temperature difference, airflow threshold, heating level threshold, first ratio, ventilation level threshold, and second ratio.

[0010] Optionally, the target energy management mode includes at least one of the following: mode 1, mode 2, mode 3, mode 4, and mode 5, wherein the drivability of mode 1, mode 2, and mode 4 is higher than that of mode 3 and mode 5, the comfort of mode 1, mode 2, and mode 3 is higher than that of mode 4 and mode 5, and the drivability and comfort of mode 1 are both higher than those of mode 2.

[0011] Optionally, the method further includes: acquiring the battery status of the vehicle; and determining the target energy management mode as the fifth mode in response to the battery status being less than a preset threshold.

[0012] Optionally, the method further includes: acquiring the vehicle's driving mode within a preset time segment; and determining driving intensity requirements and comfort intensity requirements based on the driving mode.

[0013] Optionally, the method further includes: storing the dynamic signal and the control signal in a first data layer, and storing the first feature and the second feature in a second data layer, wherein the first data layer is used for data preprocessing of the dynamic signal and the control signal, and the second data layer is used for feature value calculation of the dynamic signal and the control signal.

[0014] According to one embodiment of the present invention, a control device for a vehicle energy management system is also provided, comprising: an acquisition module for acquiring driving signals of a vehicle within a preset time segment, wherein the driving signals are used to determine dynamic signals and control signals of the vehicle during driving; a first determination module for determining a first feature based on the dynamic signals and a second feature based on the control signals, wherein the first feature represents the driving style of the vehicle and the second feature represents the comfort style of the vehicle; a classification module for classifying the first feature to obtain a first classification result and classifying the second feature to obtain a second classification result, wherein the first classification result represents the driving intensity requirement of the vehicle within the preset time segment and the second classification result represents the comfort intensity requirement of the vehicle within the preset time segment; a second determination module for determining a target energy management mode based on the first classification result, the second classification result, and a preset relationship table, wherein the preset relationship table represents the relationship between the driving intensity requirement, the comfort intensity requirement, and the target energy management mode, and the target energy management mode represents the energy supply intensity of the vehicle within the preset time segment; and a control module for controlling the vehicle's energy management system within a future preset time segment according to the target energy management mode.

[0015] Optionally, the classification module is further configured to calculate the density function of the first feature to obtain a first density function value, and calculate the density function of the second feature to obtain a second density function value; calculate the joint probability of the first density function value to obtain a first joint probability, and calculate the joint probability of the second density function value to obtain a second joint probability; determine the first classification result based on the magnitude of the first joint probability, and determine the second classification result based on the magnitude of the second joint probability.

[0016] Optionally, the first determining module is further configured to determine a vehicle speed threshold based on a vehicle speed signal; and, determine an acceleration threshold based on an acceleration signal; and, determine a deceleration threshold based on a deceleration signal; and, determine an accelerator pedal opening threshold and an accelerator pedal opening change rate based on an accelerator pedal opening signal; and, determine a brake pedal opening threshold and a brake pedal opening change rate based on a brake pedal opening signal; and determine a first feature based on the vehicle speed threshold, acceleration threshold, deceleration threshold, accelerator pedal opening threshold, accelerator pedal opening change rate, brake pedal opening threshold, and brake pedal opening change rate.

[0017] Optionally, the first determining module is further configured to: determine the air conditioning operating duration based on the air conditioning activation signal; determine the temperature difference based on the in-vehicle set temperature signal and the ambient temperature signal; determine the airflow threshold based on the airflow level signal; determine the heating level threshold and a first ratio based on the seat heating signal, wherein the first ratio is the ratio of the seat heating duration to a preset time segment; determine the ventilation level threshold and a second ratio based on the seat ventilation signal, wherein the second ratio is the ratio of the seat ventilation duration to a preset time segment; and determine a second feature based on the air conditioning operating duration, temperature difference, airflow threshold, heating level threshold, first ratio, ventilation level threshold, and second ratio.

[0018] Optionally, the target energy management mode includes at least one of the following: mode 1, mode 2, mode 3, mode 4, and mode 5, wherein the drivability of mode 1, mode 2, and mode 4 is higher than that of mode 3 and mode 5, the comfort of mode 1, mode 2, and mode 3 is higher than that of mode 4 and mode 5, and the drivability and comfort of mode 1 are both higher than those of mode 2.

[0019] Optionally, the second determining module is also used to obtain the battery status of the vehicle; in response to the battery status being less than a preset threshold, the target energy management mode is determined to be the fifth mode.

[0020] Optionally, the classification module is used to obtain the vehicle's driving mode within a preset time segment; and to determine the driving intensity requirements and comfort intensity requirements based on the driving mode.

[0021] Optionally, the first determining module is further configured to store the dynamic signal and the control signal in the first data layer, and store the first feature and the second feature in the second data layer, wherein the first data layer is configured to perform data preprocessing on the dynamic signal and the control signal, and the second data layer is configured to perform feature value calculation on the dynamic signal and the control signal.

[0022] According to one embodiment of this application, a vehicle is also provided, which is used to execute the control method of the vehicle energy management system in any of the above claims.

[0023] According to one embodiment of the present invention, a computer-readable storage medium is also provided, wherein the storage medium stores a computer program, wherein the computer program is configured to execute the control method of the vehicle energy management system described above when run on a computer or processor.

[0024] According to one embodiment of the present invention, an electronic device is also provided, including 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 control method of the vehicle energy management system described in any of the preceding claims.

[0025] In this embodiment of the invention, driving signals of a vehicle within a preset time segment are acquired. These driving signals are used to determine the vehicle's dynamic signals and control signals during operation. A first feature is determined based on the dynamic signals, and a second feature is determined based on the control signals. The first feature represents the vehicle's driving style, and the second feature represents the vehicle's comfort style. The first feature is then classified to obtain a first classification result, and the second feature is classified to obtain a second classification result. The first classification result represents the vehicle's driving intensity requirement within the preset time segment, and the second classification result represents the vehicle's comfort intensity requirement within the preset time segment. A target energy management mode is determined based on the first classification result, the second classification result, and a preset relationship table. The table represents the relationship between driving intensity requirements, comfort intensity requirements, and the target energy management mode. The target energy management mode represents the energy supply intensity of the vehicle within a preset time segment. Finally, based on the target energy management mode, the vehicle's energy management system is controlled within a future preset time segment. This allows the energy management system to balance drivability and comfort during actual vehicle operation. It can flexibly provide different energy management modes best suited to the current driver based on different actual situations, ensuring a balance between power and comfort. This approach offers high comprehensiveness, high safety, high efficiency, and high flexibility, thereby solving the technical problem of related technologies controlling the vehicle's energy management system through fixed management rules, which leads to lower comprehensiveness, lower safety, lower efficiency, and lower flexibility. Attached Figure Description

[0026] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0027] Figure 1 This is a flowchart of a control method for a vehicle energy management system according to one embodiment of the present invention;

[0028] Figure 2This is a structural block diagram of the control device for a vehicle energy management system according to one embodiment of the present invention. Detailed Implementation

[0029] For ease of understanding, some concepts related to the embodiments of the present invention are explained by way of example for reference.

[0030] As shown below:

[0031] Naive Bayes classification algorithm: A classification algorithm based on Bayes' theorem and the assumption of conditional independence of features. It assumes that all features are mutually independent, that is, given a class, features are conditionally independent. Based on this assumption, the Naive Bayes algorithm can classify by calculating posterior probabilities. The advantages of the Naive Bayes algorithm are its simplicity and speed, good performance on small datasets, and ability to handle multi-class classification problems.

[0032] The main storage layer (Data Warehouse Layer, DW) is used to store cleaned, integrated, and organized structured data. The DW typically employs a star or snowflake schema, offering highly optimized query performance. It is a core component of the data warehouse, supporting various analytical and reporting needs, and providing decision support and business intelligence.

[0033] Operational Data Store Layer (ODS): This layer stores raw data extracted from various source systems. It typically employs the third normal form model to preserve historical changes in the data, facilitating data cleaning, transformation, and integration. The ODS can serve as an intermediary layer for data extraction and loading within a data warehouse, enabling real-time or periodic data extraction, loading, and transformation.

[0034] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0035] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0036] According to one embodiment of the present invention, an embodiment of a control method for a vehicle energy management system is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0037] This method embodiment can be executed in an electronic device, similar control device, or system that includes a memory and a processor. Taking an electronic device as an example, the electronic device may include one or more processors and a memory for storing data. Optionally, the electronic device may also include a communication device for communication functions and a display device. Those skilled in the art will understand that the above structural description is merely illustrative and does not limit the structure of the electronic device. For example, the electronic device may include more or fewer components than described above, or have a different configuration than described above.

[0038] A processor may include one or more processing units. For example, a processor may include a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a microcontroller unit (MCU), a field-programmable gate array (FPGA), a neural network processing unit (NPU), a tensor processing unit (TPU), or an artificial intelligence (AI) processor. Different processing units may be independent components or integrated into one or more processors. In some instances, electronic devices may also include one or more processors.

[0039] The memory can be used to store computer programs, such as the computer program corresponding to the control method of the vehicle energy management system in this embodiment of the invention. The processor implements the control method of the vehicle energy management system by running the computer program stored in the memory. The memory may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to electronic devices via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0040] Communication devices are used to receive or send data via a network. Specific examples of such networks may include wireless networks provided by the mobile terminal's communication provider. In one example, the communication device includes a network interface controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the communication device may be a radio frequency (RF) module used for wireless communication with the Internet.

[0041] The display device can be, for example, a touchscreen liquid crystal display (LCD) and a touch display (also referred to as a "touchscreen" or "touch screen"). This LCD allows the user to interact with the user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), which allows the user to interact with the GUI by touching and / or gesturing on a touch-sensitive surface. Optional human-computer interaction functions include: creating web pages, drawing, word processing, creating electronic documents, playing games, video conferencing, instant messaging, sending and receiving emails, a call interface, playing digital video, playing digital music, and / or web browsing, etc. Executable instructions for performing the above human-computer interaction functions are configured / stored in one or more processor-executable computer program products or readable storage media.

[0042] This embodiment provides a control method for a vehicle energy management system operating on an electronic device. Figure 1 This is a flowchart of a control method for a vehicle energy management system according to one embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0043] Step S10: Obtain the vehicle's driving signals within a preset time segment;

[0044] Among them, driving signals are used to determine the dynamic signals and control signals of the vehicle during driving.

[0045] It is understood that during vehicle operation, there are multiple consecutive time segments, and the vehicle's driving status may change over time. By pre-setting time segments to obtain the vehicle's driving signals, the vehicle's driving status can be obtained accurately and conveniently in real time. This embodiment of the invention does not limit this.

[0046] This step can be understood as acquiring the vehicle's driving signals within a preset time segment, and determining the vehicle's dynamic signals and control signals during the driving process based on the driving signals. Optionally, this step can be implemented through vehicle network equipment in the vehicle, which is not limited in this embodiment of the invention.

[0047] For example, vehicle bus signals can be obtained through vehicle network equipment in the vehicle, and dynamic signals and control signals of the vehicle during driving can be extracted from the vehicle bus signals. This embodiment of the invention is not limited to this.

[0048] Step S11: Determine the first feature based on the dynamic signal and the second feature based on the control signal;

[0049] The first feature is used to represent the vehicle's driving style, and the second feature is used to represent the vehicle's comfort style.

[0050] This step can be understood as determining the vehicle's driving style based on dynamic signals and determining the vehicle's comfort style based on control signals. It can be understood that during the driving process, the vehicle's driving mode will also be different due to the different driving habits of the driver.

[0051] Optionally, a first feature representing the driving style of a vehicle can be obtained by calculating the eigenvalues ​​of the dynamic signal, and a second feature representing the comfort style of the vehicle can be obtained by calculating the eigenvalues ​​of the control signal. This embodiment of the invention is not limited to this.

[0052] Step S12: Classify the first feature to obtain the first classification result, and classify the second feature to obtain the second classification result;

[0053] The first classification result represents the driving intensity requirement of the vehicle within a preset time segment, and the second classification result represents the comfort intensity requirement of the vehicle within a preset time segment.

[0054] This step can be understood as classifying the first feature representing the vehicle's driving style to obtain the vehicle's driving intensity requirements within a preset time segment, and classifying the second feature representing the vehicle's comfort style to obtain the vehicle's comfort intensity requirements within a preset time segment.

[0055] Optionally, this step can be implemented using a classification algorithm, and this embodiment of the invention is not limited thereto. For example, a Bayesian classification algorithm can be used to classify the first feature representing the vehicle's driving style to obtain the vehicle's driving intensity requirement within a preset time segment, i.e., the first classification result; and a Bayesian classification algorithm can be used to classify the second feature representing the vehicle's comfort style to obtain the vehicle's comfort intensity requirement within the preset time segment, i.e., the second classification result; this embodiment of the invention is not limited thereto.

[0056] Step S13: Determine the target energy management mode based on the first classification result, the second classification result, and the preset relationship table;

[0057] The preset relationship table is used to represent the relationship between driving intensity requirements, comfort intensity requirements, and target energy management mode. The target energy management mode is used to represent the energy supply intensity of the vehicle within a preset time segment.

[0058] This step can be understood as determining the target energy management mode to represent the energy supply intensity of the vehicle within a preset time segment, based on the relationship between the vehicle's driving intensity requirements, comfort intensity requirements, driving intensity requirements, comfort intensity requirements, and the target energy management mode.

[0059] Optionally, the preset relationship table can be determined based on the vehicle's historical driving intensity requirements, comfort intensity requirements, and historical target energy management modes, and this embodiment of the invention does not impose any limitations on this.

[0060] Step S14: Control the vehicle's energy management system within a future preset time segment according to the target energy management mode.

[0061] It is understandable that the vehicle's energy management system is used to control the vehicle's drive system and comfort system to provide energy to the vehicle. This step can be understood as controlling the vehicle's energy management system in a future preset time segment based on the energy supply intensity of the vehicle in a preset time segment.

[0062] For example, when the preset time segment duration is N, after the target energy management mode for the first N-cycle is determined, the system operates according to the target energy management mode between time N and 2*N. When the signal recording reaches 2*N, that is, the second evaluation cycle is entered, the target energy management mode is determined between N and 2*N. If the target energy management mode changes, it is switched according to the above-mentioned preset relationship table. If it does not change, the current energy management mode remains unchanged. This embodiment of the invention does not limit the scope of the invention.

[0063] Through the above steps, driving signals of the vehicle within a preset time segment are acquired. These driving signals are used to determine the vehicle's dynamic signals and control signals during operation. A first feature is determined based on the dynamic signals, and a second feature is determined based on the control signals. The first feature represents the vehicle's driving style, and the second feature represents the vehicle's comfort style. The first feature is then classified to obtain a first classification result, and the second feature is classified to obtain a second classification result. The first classification result represents the vehicle's driving intensity requirement within the preset time segment, and the second classification result represents the vehicle's comfort intensity requirement within the preset time segment. Based on the first classification result, the second classification result, and a preset relationship table, a target energy management mode is determined. The table represents the relationship between driving intensity requirements, comfort intensity requirements, and the target energy management mode. The target energy management mode represents the energy supply intensity of the vehicle within a preset time segment. Finally, based on the target energy management mode, the vehicle's energy management system is controlled within a future preset time segment. This allows the energy management system to balance drivability and comfort during actual vehicle operation. It can flexibly provide different energy management modes best suited to the current driver based on different actual situations, ensuring a balance between power and comfort. This approach is highly comprehensive, safe, efficient, and flexible, thus solving the technical problem of related technologies controlling the vehicle's energy management system through fixed management rules, which leads to lower comprehensiveness, lower safety, lower efficiency, and lower flexibility.

[0064] Optionally, in step S11, the dynamic signal includes at least one of the following: vehicle speed signal, acceleration signal, deceleration signal, accelerator pedal opening signal, and brake pedal opening signal. Determining the first feature based on the dynamic signal may include the following execution steps:

[0065] Step S11a: Determine the vehicle speed threshold based on the vehicle speed signal; and,

[0066] The vehicle speed threshold can be understood as the maximum driving speed of a vehicle within a preset time period. This step can be understood as determining the maximum driving speed based on the vehicle speed signal within the preset time period. Optionally, this step can be achieved by continuously detecting the vehicle speed change within the preset time period after obtaining the vehicle speed signal, and determining the maximum driving speed of the vehicle within the preset time period, i.e., the vehicle speed threshold. This embodiment of the present invention does not limit this.

[0067] Step S11b: Determine the acceleration threshold based on the acceleration signal; and,

[0068] The acceleration threshold can be understood as the highest acceleration of a vehicle within a preset time period. This step can be understood as determining the highest acceleration based on the acceleration signal within the preset time period. Optionally, this step can be achieved by continuously detecting the acceleration change of the vehicle within the preset time period after acquiring the acceleration signal, and determining the highest acceleration of the vehicle within the preset time period, i.e., the acceleration threshold. This embodiment of the invention does not limit this.

[0069] Step S11c: Determine the deceleration threshold based on the deceleration signal; and,

[0070] The deceleration threshold can be understood as the highest deceleration of a vehicle within a preset time period. This step can be understood as determining the highest deceleration based on the acceleration signal within the preset time period. Optionally, this step can be achieved by continuously detecting the deceleration change of the vehicle within the preset time period after obtaining the deceleration signal, and determining the highest deceleration of the vehicle within the preset time period, i.e., the deceleration threshold. This embodiment of the invention does not limit this.

[0071] Step S11d: Determine the accelerator pedal opening threshold and the accelerator pedal opening change rate based on the accelerator pedal opening signal; and,

[0072] The accelerator pedal opening threshold can be understood as the maximum accelerator pedal opening of the vehicle within a preset time period, and the accelerator pedal opening change rate can be understood as the rate at which the accelerator pedal opening of the vehicle changes within a preset time period. This step can be understood as determining the maximum accelerator pedal opening and the rate at which the accelerator pedal opening changes based on the accelerator pedal opening signal within a preset time period.

[0073] Optionally, this step can be achieved by acquiring the accelerator pedal opening signal, continuously detecting the change in the accelerator pedal opening within a preset time period, recording the opening value, and then calculating the rate of change of the accelerator pedal opening, i.e., the accelerator pedal opening change rate, based on the opening value and the preset time. This embodiment of the invention does not limit this step.

[0074] Step S11e: Determine the brake pedal opening threshold and brake pedal opening change rate based on the brake pedal opening signal;

[0075] The brake pedal opening threshold can be understood as the maximum brake pedal opening of the vehicle within a preset time period, and the brake pedal opening change rate can be understood as the rate at which the brake pedal opening of the vehicle changes within a preset time period. This step can be understood as determining the maximum brake pedal opening and the rate at which the brake pedal opening changes based on the brake pedal opening signal within a preset time period.

[0076] Optionally, this step can be achieved by acquiring the brake pedal opening signal, continuously detecting the change in the brake pedal opening of the vehicle within a preset time period, recording the opening value, and then calculating the rate of change of the brake pedal opening, i.e., the brake pedal opening change rate, based on the opening value and the preset time. This embodiment of the invention does not limit this step.

[0077] Step S11f: Determine the first feature based on the vehicle speed threshold, acceleration threshold, deceleration threshold, accelerator pedal opening threshold, accelerator pedal opening change rate, brake pedal opening threshold, and brake pedal opening change rate.

[0078] This step can be understood as determining the vehicle's driving style based on the vehicle's maximum speed, maximum acceleration, maximum deceleration, maximum accelerator pedal opening, rate of change of accelerator pedal opening, maximum brake pedal opening, and rate of change of brake pedal opening within a preset time period.

[0079] Optionally, in step S11, the control signal includes at least one of the following: air conditioning on signal, in-vehicle temperature setting signal, ambient temperature signal, airflow level signal, seat heating signal, and seat ventilation signal. Determining the second feature based on the control signal may include the following execution steps:

[0080] Step S11g: Determine the air conditioner's operating duration based on the air conditioner activation signal; and,

[0081] The air conditioning operating time can be understood as the duration of the vehicle's air conditioning operation within a preset time period. This step can be understood as determining the air conditioning operating time based on the air conditioning operating signal within the preset time period. Optionally, this step can be achieved by continuously detecting the air conditioning operating signal within the preset time period after obtaining the air conditioning operating signal, and determining the air conditioning operating time within the preset time period. This embodiment of the invention does not impose any limitations on this.

[0082] Step S11h: Determine the temperature difference based on the in-vehicle temperature signal and the ambient temperature signal; and,

[0083] The temperature difference can be understood as the temperature difference between the vehicle's interior and the external environment within a preset time period. This step can be understood as determining the temperature difference between the vehicle's interior and the external environment based on the vehicle's internal temperature signal and the ambient temperature signal within a preset time period.

[0084] Optionally, this step can be achieved by acquiring the in-vehicle temperature setting signal and the ambient temperature signal, measuring the in-vehicle temperature and the external ambient temperature, and determining the temperature difference through difference calculation. This embodiment of the invention does not limit this step.

[0085] It is understood that when the air conditioning is not turned on to adjust the temperature inside the vehicle, the temperature inside the vehicle is the same as the outside ambient temperature, and the temperature difference is zero. This embodiment of the invention does not impose any restrictions on this.

[0086] Step S11i: Determine the airflow threshold based on the airflow level signal; and,

[0087] The airflow threshold can be understood as the maximum airflow value of the vehicle's air conditioning within a preset time period. This step can be understood as determining the maximum airflow value of the air conditioning based on the airflow level signal within the preset time period. Optionally, this step can be achieved by continuously detecting the airflow level signal of the vehicle within the preset time period after obtaining the airflow level signal, and then determining the maximum airflow value of the vehicle within the preset time period, i.e., the airflow threshold. This embodiment of the invention does not impose any limitations on this.

[0088] It is understood that when a user selects automatic air conditioning and does not make manual settings, the maximum air volume value is calculated according to the actual wind speed of the automatic air conditioning, and this embodiment of the invention does not limit it.

[0089] Step S11j: Determine the heating level threshold and a first ratio based on the seat heating signal, wherein the first ratio is the ratio of the seat heating duration to a preset time segment; and,

[0090] The heating level threshold can be understood as the maximum heating level value of the vehicle's air conditioning within a preset time period. The first ratio can be understood as the ratio of the seat heating duration to the preset time segment. This step can be understood as determining the maximum heating level value of the air conditioning and the ratio of the seat heating duration to the preset time segment based on the seat heating signal within the preset time period.

[0091] Optionally, this step can be achieved by continuously detecting the seat heating signal of the vehicle within a preset time period after obtaining the seat heating signal, determining the maximum heating level value of the vehicle within the preset time period, and calculating the quotient between the seat heating duration and the preset time segment duration to obtain a first ratio. This embodiment of the invention does not limit this step.

[0092] Step S11k: Determine the ventilation level threshold and the second ratio based on the seat ventilation signal, wherein the second ratio is the ratio of the seat ventilation duration to the preset time segment;

[0093] The seat ventilation threshold can be understood as the maximum seat ventilation value of the vehicle's air conditioning within a preset time period. The second ratio can be understood as the ratio of the seat heating duration to the preset time segment. This step can be understood as determining the maximum seat ventilation value of the air conditioning and the ratio of the seat ventilation duration to the preset time segment based on the seat ventilation signal within the preset time period.

[0094] Optionally, this step can be achieved by continuously detecting the seat ventilation signal of the vehicle within a preset time period after obtaining the seat ventilation signal, determining the maximum seat ventilation value of the vehicle within the preset time period, and calculating the quotient between the seat ventilation duration and the preset time segment duration to obtain a second ratio. This embodiment of the invention does not limit this.

[0095] Step S11l: Determine the second feature based on the air conditioner operating time, temperature difference, air volume threshold, heating level threshold, first ratio, ventilation level threshold, and second ratio.

[0096] This step can be understood as determining the vehicle's comfort style based on the following factors within a preset time period: the duration of the vehicle's air conditioning operation, the maximum airflow value of the temperature difference between the vehicle's interior and exterior environments, the maximum heating level value, the ratio of seat heating duration to the preset time segment, the maximum seat ventilation value, and the ratio of seat heating duration to the preset time segment.

[0097] Optionally, in step S12, classifying the first feature to obtain a first classification result and classifying the second feature to obtain a second classification result may include the following steps:

[0098] Step S120: Calculate the density function for the first feature to obtain the first density function value, and calculate the density function for the second feature to obtain the second density function value;

[0099] This step can be understood as performing a density function calculation on the first feature representing the vehicle's driving style to obtain a first density function value, and performing a density function calculation on the second feature representing the vehicle's comfort style to obtain a second density function value.

[0100] Optionally, the density function of the normal distribution can be obtained by first calculating the mean and variance of each feature value in the first and second features mentioned above. This embodiment of the invention does not limit this. Specifically, when calculating the mean and variance of each feature value in the first and second features mentioned above, assuming that they follow a normal distribution, the first density function value and the second density function value of the normal distribution are calculated respectively. Then, the first density function value and the second density function value can be calculated by the Bayesian classification algorithm. The specific calculation process can be shown in the following formula (1):

[0101]

[0102] In the above formula (1), μ is the mean and σ is the standard deviation. The density function value of each feature value in the above driving style and comfort style is calculated and determined, that is, the first density function value and the second density function value are determined. This embodiment of the present invention is not limited.

[0103] For example, the above vehicle speed threshold can be denoted as Vmax, the acceleration threshold as amax, the deceleration threshold as dmax, the accelerator pedal opening threshold as accpmax, the accelerator pedal opening change rate as accpmax_v, the brake pedal opening threshold as brkpmax, and the brake pedal opening change rate as brkpmax_v. Then, the density function values ​​calculated according to the above formula (1) can be denoted as A1, A2, A3, A4, A5, A6, and A7, which are the first density function values. This embodiment of the invention does not limit the specific density function values.

[0104] For example, the air conditioner operating time can be denoted as ac_per, the temperature difference as T, the air volume threshold as blowmax, the heating level threshold as hotmax, the first ratio as hot_per, the ventilation level threshold as windmax, and the second ratio as wind_per. Then, the density function values ​​calculated according to the above formula (1) can be denoted as B1, B2, B3, B4, B5, B6, and B7, which are the second density function values. This embodiment of the invention does not limit the specific density function values.

[0105] Step S121: Calculate the joint probability of the first density function value to obtain the first joint probability, and calculate the joint probability of the second density function value to obtain the second joint probability;

[0106] This step can be understood as performing joint probability calculation on the density function values ​​in the first density function value to obtain the first joint probability, and performing joint probability calculation on the density function values ​​in the second density function value to obtain the second joint probability.

[0107] Optionally, driving intensity requirements can be divided into three levels: strong, medium, and weak, denoted by C1, C2, and C3 respectively, and comfort intensity requirements can be divided into three levels: strong, medium, and weak, denoted by D1, D2, and D3 respectively. The first joint probability can then be calculated using mathematical formulas, and the specific calculation process can be shown in the following formulas (2)-(4):

[0108] P(A1A2A3A4A5A6A7|C1)=

[0109] P(A1|C1)P(A2|C1)P(A3|C1)P(A4|C1)P(A5|C1)P(A6|C1)P(A7|C1)(2)

[0110] P(A1A2A3A4A5A6A7|C2)=

[0111] P(A1|C2)P(A2|C2)P(A3|C2)P(A4|C2)P(A5|C2)P(A6|C2)P(A7|C2)(3)

[0112] P(A1A2A3A4A5A6A7|C3)=

[0113] P(A1|C3)P(A2|C3)P(A3|C3)P(A4|C3)P(A5|C3)P(A6|C3)P(A7|C3)(4)

[0114] Therefore, the joint probability of different driving intensity requirements is calculated separately, and the embodiments of the present invention are not limited thereto.

[0115] The second joint probability can be calculated using mathematical formulas, and the specific calculation process can be shown in the following formulas (5)-(7):

[0116] P(B1B2B3B4B5B6B7|D1)=

[0117] P(B1|D1)P(B2|D1)P(B3|D1)P(B4|D1)P(B5|D1)P(B6|D1)P(B7|D1)(5)

[0118] P(B1B2B3B4B5B6B7|D2)=

[0119] P(B1|D2)P(B2|D2)P(B3|D2)P(B4|D2)P(B5|D2)P(B6|D2)P(B7|D2)(6)

[0120] P(B1B2B3B4B5B6B7|D3)=

[0121] P(B1|D3)P(B2|D3)P(B3|D3)P(B4|D3)P(B5|D3)P(B6|D3)P(B7|D3)(7)

[0122] The combined probability of different comfort intensity requirements is calculated accordingly, and the embodiments of the present invention are not limited thereto.

[0123] Step S122: Determine the first classification result based on the magnitude of the first joint probability, and determine the second classification result based on the magnitude of the second joint probability.

[0124] This step can be understood as determining the driving intensity requirement of the vehicle within a preset time segment based on the magnitude of the first joint probability, and determining the comfort intensity requirement of the vehicle within a preset time segment based on the magnitude of the second joint probability.

[0125] In an optional embodiment, the probability values ​​of P(A1A2A3A4A5A6A7|C1), P(A1A2A3A4A5A6A7|C2), and P(A1A2A3A4A5A6A7|C3) calculated in step S121 can be compared. If P(A1A2A3A4A5A6A7|C1) is the largest, the driving intensity requirement of the vehicle within the preset time segment is C1, i.e., the driving intensity requirement is strong. If P(A1A2A3A4A5A6A7|C2) is the largest, the driving intensity requirement of the vehicle within the preset time segment is C2, i.e., the driving intensity requirement is medium. If P(A1A2A3A4A5A6A7|C3) is the largest, the driving intensity requirement of the vehicle within the preset time segment is C3, i.e., the driving intensity requirement is weak. This embodiment of the invention does not impose any limitations.

[0126] In an optional embodiment, the probability values ​​of P(B1B2B3B4B5B6B7|D1), P(B1B2B3B4B5B6B7|D2), and P(B1B2B3B4B5B6B7|D3) calculated in step S121 can be compared. If P(B1B2B3B4B5B6B7|D1) is the largest, the comfort intensity requirement of the vehicle within the preset time segment is D1, i.e., the comfort intensity requirement is strong. If P(B1B2B3B4B5B6B7|D2) is the largest, the comfort intensity requirement of the vehicle within the preset time segment is D2, i.e., the comfort intensity requirement is medium. If P(B1B2B3B4B5B6B7|D3) is the largest, the comfort intensity requirement of the vehicle within the preset time segment is D3, i.e., the comfort intensity requirement is weak. This embodiment of the invention does not impose any limitations.

[0127] Optionally, step S12 may also include the following execution steps:

[0128] Step S123: Store the dynamic signal and control signal in the first data layer, and store the first feature and the second feature in the second data layer;

[0129] The first data layer is used for data preprocessing of dynamic signals and control signals, and the second data layer is used for eigenvalue calculation of dynamic signals and control signals.

[0130] It is understandable that after acquiring the dynamic signals and control signals, due to environmental influences during vehicle operation, some signals may be distorted during transmission, or data may be missing when the vehicle is in a location with poor signal. Therefore, it is necessary to perform data preprocessing on the dynamic signals and control signals to filter out data that does not conform to reality, and supplement some missing data through interpolation and other methods. This embodiment of the invention does not limit this.

[0131] Optionally, the dynamics signals and control signals are stored in a first data layer for signal data preprocessing, such as a DW data layer; this embodiment of the invention is not limited thereto. Specifically, the dynamics signals can be stored in a driving signal library, and the control signals can be stored in a comfort signal library; this embodiment of the invention is not limited thereto.

[0132] Optionally, after calculating the eigenvalues ​​of the dynamic signal and the control signal to obtain the first feature and the second feature, the first feature and the second feature can be stored in the second data layer, such as the ODS data layer. This embodiment of the invention is not limited to this.

[0133] Optionally, step S12 may also include the following execution steps:

[0134] Step S123: Obtain the vehicle's driving mode within a preset time segment;

[0135] It is understandable that in real-world scenarios, drivers may manually select a driving mode based on their own driving habits. Driving modes may include sport mode, energy-saving mode, and comfort mode, etc., and this embodiment of the invention does not limit such selection.

[0136] Understandably, Sport mode offers better performance and allows for more aggressive driving, Comfort mode provides better comfort but is less aggressive, and Eco mode has lower performance in both the comfort and drive systems.

[0137] Step S124: Determine the driving intensity requirements and comfort intensity requirements based on the driving mode.

[0138] Optionally, driving intensity requirements and comfort intensity requirements can be determined based on the relationship between driving mode, driving intensity requirements, and comfort intensity requirements. For example, the relationship between driving mode, driving intensity requirements, and comfort intensity requirements can be shown in Table 1 below:

[0139] Table 1. Relationship between Driving Mode, Driving Intensity Requirements, and Comfort Intensity Requirements

[0140] Driving intensity requirements powerful middle weak Comfort and strength requirements middle powerful weak

[0141] For example, when the driving mode is Sport mode, it means that the driving intensity requirement is high and the comfort intensity requirement is medium. When the driving mode is Comfort mode, it means that the driving intensity requirement is medium and the comfort intensity requirement is high. When the driving mode is Eco mode, it means that the driving intensity requirement is low and the comfort intensity requirement is low. The driving intensity requirement and comfort intensity requirement are determined in this way. This embodiment of the invention is not limited.

[0142] Optionally, the target energy management mode includes at least one of the following: mode one, mode two, mode three, mode four, and mode five.

[0143] Among them, the driving performance of the first, second and fourth modes is better than that of the third and fifth modes, the comfort of the first, second and third modes is better than that of the fourth and fifth modes, and the driving performance and comfort of the first mode are both better than those of the second mode.

[0144] The first mode can be understood as an energy management mode where both driving intensity and comfort requirements are at a high level. The second mode can be understood as an energy management mode where driving intensity is high and comfort requirements are medium, or both driving intensity and comfort requirements are medium. The third mode can be understood as an energy management mode where driving intensity is low and comfort requirements are high, or both driving intensity and comfort requirements are low and medium. The fourth mode can be understood as an energy management mode where driving intensity is high and comfort requirements are low. The fifth mode can be understood as an energy management mode where both driving intensity and comfort requirements are low.

[0145] Optionally, the relationship between driving intensity requirements, comfort intensity requirements, and the target energy management mode can be shown in Table 2 below:

[0146] Table 2 Relationship between Driving Intensity Requirements, Comfort Intensity Requirements, and Target Energy Management Mode

[0147]

[0148] The first mode described above can be understood as the energy management system appropriately limiting both driving and comfort capabilities. The second mode can be understood as the energy management system not limiting the capabilities of the driving and comfort systems, providing energy according to driving needs. The third mode can be understood as the energy management system appropriately limiting the capabilities of the comfort system, while the driving system provides energy according to driving needs. The fourth mode can be understood as the energy management system providing energy to the comfort system according to the driver's needs, while appropriately limiting the torque and power increase rate of the driving system. The fifth mode can be understood as the energy management system not limiting the capabilities of the driving and comfort systems, providing energy according to driving needs; however, this embodiment of the invention does not impose any limitations on this.

[0149] Understandably, for drivers with high comfort requirements, comfort should be satisfied as much as possible. For drivers with extremely high comfort requirements and moderate driving performance requirements, the rate of power output from the drive system should be appropriately limited, meaning the vehicle's acceleration capabilities should be slightly reduced, while the comfort system's capabilities should be kept at their maximum. For drivers with high driving performance requirements and moderate comfort requirements, the comfort system's capabilities can be appropriately limited, reserving energy for the drive system to ensure the driver has sufficient reserve power for rapid acceleration. For drivers with low requirements for both comfort and driving performance, each system can provide energy according to driving needs without special treatment. For drivers with high requirements for both comfort and driving performance, since the capabilities of the vehicle's comfort and drive systems are fixed, energy can only be provided to each system according to driving needs.

[0150] Optionally, step S13 may also include the following execution steps:

[0151] Step S130: Obtain the vehicle's battery status;

[0152] This step can be understood as the status of the vehicle's power battery. Optionally, this step can obtain the vehicle's battery status through the vehicle's battery management system, which is not limited in this embodiment of the invention.

[0153] Step S131: In response to the battery state being less than a preset threshold, the target energy management mode is determined to be the fifth mode.

[0154] The preset threshold can be understood as the minimum threshold indicating that the vehicle battery is in poor condition. If the value is less than the minimum threshold, it means that the vehicle battery is in poor condition and may affect the normal driving of the vehicle. In this case, the target energy management mode is set to the fifth mode, that is, the energy management system can provide energy according to driving needs. This embodiment of the invention does not impose any restrictions.

[0155] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0156] This embodiment also provides a control device for a vehicle energy management system, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0157] Figure 2 This is a structural block diagram of a control device for a vehicle energy management system according to one embodiment of the present invention, such as... Figure 2 As shown, taking a vehicle energy management system control device 200 as an example, the device includes: an acquisition module 201, used to acquire driving signals of the vehicle within a preset time segment, wherein the driving signals are used to determine the dynamic signals and control signals of the vehicle during driving; a first determination module 202, used to determine a first feature based on the dynamic signals and a second feature based on the control signals, wherein the first feature represents the driving style of the vehicle and the second feature represents the comfort style of the vehicle; and a classification module 203, used to classify the first feature to obtain a first classification result and to classify the second feature to obtain a second classification result. As a result, the first classification result is used to represent the driving intensity requirement of the vehicle within a preset time segment, and the second classification result is used to represent the comfort intensity requirement of the vehicle within the preset time segment; the second determination module 204 is used to determine the target energy management mode based on the first classification result, the second classification result, and a preset relationship table, wherein the preset relationship table is used to represent the relationship between driving intensity requirement, comfort intensity requirement, and target energy management mode, and the target energy management mode is used to represent the energy supply intensity of the vehicle within the preset time segment; the control module 205 is used to control the vehicle's energy management system within a future preset time segment according to the target energy management mode.

[0158] Optionally, the classification module 203 is further configured to calculate the density function of the first feature to obtain a first density function value, and calculate the density function of the second feature to obtain a second density function value; calculate the joint probability of the first density function value to obtain a first joint probability, and calculate the joint probability of the second density function value to obtain a second joint probability; determine the first classification result based on the magnitude of the first joint probability, and determine the second classification result based on the magnitude of the second joint probability.

[0159] Optionally, the first determining module 202 is further configured to determine a vehicle speed threshold based on a vehicle speed signal; and, determine an acceleration threshold based on an acceleration signal; and, determine a deceleration threshold based on a deceleration signal; and, determine an accelerator pedal opening threshold and an accelerator pedal opening change rate based on an accelerator pedal opening signal; and, determine a brake pedal opening threshold and a brake pedal opening change rate based on a brake pedal opening signal; and determine a first feature based on the vehicle speed threshold, acceleration threshold, deceleration threshold, accelerator pedal opening threshold, accelerator pedal opening change rate, brake pedal opening threshold, and brake pedal opening change rate.

[0160] Optionally, the first determining module 202 is further configured to: determine the air conditioning operating duration based on the air conditioning activation signal; determine the temperature difference based on the in-vehicle set temperature signal and the ambient temperature signal; determine the airflow threshold based on the airflow level signal; determine the heating level threshold and a first ratio based on the seat heating signal, wherein the first ratio is the ratio of the seat heating duration to a preset time segment; determine the ventilation level threshold and a second ratio based on the seat ventilation signal, wherein the second ratio is the ratio of the seat ventilation duration to a preset time segment; and determine a second feature based on the air conditioning operating duration, temperature difference, airflow threshold, heating level threshold, first ratio, ventilation level threshold, and second ratio.

[0161] Optionally, the target energy management mode includes at least one of the following: mode 1, mode 2, mode 3, mode 4, and mode 5, wherein the drivability of mode 1, mode 2, and mode 4 is higher than that of mode 3 and mode 5, the comfort of mode 1, mode 2, and mode 3 is higher than that of mode 4 and mode 5, and the drivability and comfort of mode 1 are both higher than those of mode 2.

[0162] Optionally, the second determining module 204 is further configured to acquire the battery status of the vehicle; in response to the battery status being less than a preset threshold, the target energy management mode is determined to be the fifth mode.

[0163] Optionally, the classification module is used to obtain the vehicle's driving mode within a preset time segment; and to determine the driving intensity requirements and comfort intensity requirements based on the driving mode.

[0164] Optionally, the first determining module 202 is further configured to store the dynamic signal and the control signal in the first data layer, and store the first feature and the second feature in the second data layer, wherein the first data layer is configured to perform data preprocessing on the dynamic signal and the control signal, and the second data layer is configured to perform feature value calculation on the dynamic signal and the control signal.

[0165] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0166] Embodiments of this application also provide a vehicle for performing the steps in any of the above method embodiments.

[0167] Optionally, in this embodiment, the vehicle may be configured to store a computer program for performing the following steps:

[0168] Step S1: Obtain the vehicle's driving signals within a preset time segment;

[0169] Step S2: Determine the first feature based on the dynamic signal and the second feature based on the control signal;

[0170] Step S3: Classify the first feature to obtain the first classification result, and classify the second feature to obtain the second classification result;

[0171] Step S4: Determine the target energy management mode based on the first classification result, the second classification result, and the preset relationship table;

[0172] Step S5: Control the vehicle's energy management system within a future preset time segment according to the target energy management mode.

[0173] Embodiments of the present invention also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to perform the steps in any of the above method embodiments when run on a computer or processor.

[0174] Optionally, in this embodiment, the computer-readable storage medium may be configured to store a computer program for performing the following steps:

[0175] Step S1: Obtain the vehicle's driving signals within a preset time segment;

[0176] Step S2: Determine the first feature based on the dynamic signal and the second feature based on the control signal;

[0177] Step S3: Classify the first feature to obtain the first classification result, and classify the second feature to obtain the second classification result;

[0178] Step S4: Determine the target energy management mode based on the first classification result, the second classification result, and the preset relationship table;

[0179] Step S5: Control the vehicle's energy management system within a future preset time segment according to the target energy management mode.

[0180] Optionally, in this embodiment, the computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0181] Embodiments of the present invention also provide an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0182] Optionally, in this embodiment, the processor in the above-described electronic device may be configured to run a computer program to perform the following steps:

[0183] Step S1: Obtain the vehicle's driving signals within a preset time segment;

[0184] Step S2: Determine the first feature based on the dynamic signal and the second feature based on the control signal;

[0185] Step S3: Classify the first feature to obtain the first classification result, and classify the second feature to obtain the second classification result;

[0186] Step S4: Determine the target energy management mode based on the first classification result, the second classification result, and the preset relationship table;

[0187] Step S5: Control the vehicle's energy management system within a future preset time segment according to the target energy management mode.

[0188] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0189] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0190] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0191] 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 instance, 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 coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0192] The units described as separate components may or may not be physically separate. The components shown as units 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 according to actual needs.

[0193] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0194] 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 the present 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 described in the various embodiments of the present 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.

[0195] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A control method for a vehicle energy management system, characterized in that, include: Acquire driving signals of the vehicle within a preset time segment, wherein the driving signals are used to determine the dynamic signals and control signals of the vehicle during driving; A first feature is determined based on the dynamic signal, and a second feature is determined based on the control signal, wherein the first feature is used to represent the driving style of the vehicle, and the second feature is used to represent the comfort style of the vehicle; The first feature is classified to obtain a first classification result, and the second feature is classified to obtain a second classification result, wherein the first classification result is used to represent the driving intensity requirement of the vehicle in the preset time segment, and the second classification result is used to represent the comfort intensity requirement of the vehicle in the preset time segment. The target energy management mode is determined based on the first classification result, the second classification result, and the preset relationship table. The preset relationship table is used to represent the relationship between the driving intensity requirement, the comfort intensity requirement, and the target energy management mode. The target energy management mode is used to represent the energy supply intensity of the vehicle within the preset time segment. The vehicle's energy management system is controlled within the preset time segment in the future according to the target energy management mode; The classification of the first feature to obtain a first classification result and the classification of the second feature to obtain a second classification result include: calculating a density function on the first feature to obtain a first density function value and calculating a density function on the second feature to obtain a second density function value; calculating a joint probability on the first density function value to obtain a first joint probability and calculating a joint probability on the second density function value to obtain a second joint probability; determining the first classification result based on the magnitude of the first joint probability and determining the second classification result based on the magnitude of the second joint probability.

2. The method according to claim 1, characterized in that, The dynamic signal includes at least one of the following: vehicle speed signal, acceleration signal, deceleration signal, accelerator pedal opening signal, and brake pedal opening signal. Determining the first feature based on the dynamic signal includes: Determine the vehicle speed threshold based on the vehicle speed signal; and, Determine the acceleration threshold based on the acceleration signal; and, Determine the deceleration threshold based on the deceleration signal; and, The accelerator pedal opening threshold and the accelerator pedal opening change rate are determined based on the accelerator pedal opening signal; and... The brake pedal opening threshold and the brake pedal opening change rate are determined based on the brake pedal opening signal; The first feature is determined based on the vehicle speed threshold, the acceleration threshold, the deceleration threshold, the accelerator pedal opening threshold, the accelerator pedal opening change rate, the brake pedal opening threshold, and the brake pedal opening change rate.

3. The method according to claim 1, characterized in that, The control signal includes at least one of the following: air conditioning on signal, in-vehicle temperature setting signal, ambient temperature signal, airflow level signal, seat heating signal, and seat ventilation signal. The second feature determined based on the control signal includes: The duration of air conditioner operation is determined based on the air conditioner activation signal; and... The temperature difference is determined based on the in-vehicle temperature signal and the ambient temperature signal; and... Determine the airflow threshold based on the airflow level signal; and A heating level threshold and a first ratio are determined based on the seat heating signal, wherein the first ratio is the ratio of the seat heating duration to the preset time segment; and, The ventilation level threshold and the second ratio are determined based on the seat ventilation signal, wherein the second ratio is the ratio of the seat ventilation duration to the preset time segment; The second feature is determined based on the air conditioner operating time, the temperature difference, the air volume threshold, the heating level threshold, the first ratio, the ventilation level threshold, and the second ratio.

4. The method according to claim 1, characterized in that, The target energy management mode includes at least one of the following: a first mode, a second mode, a third mode, a fourth mode, and a fifth mode, wherein the drivability of the first mode, the second mode, and the fourth mode is higher than that of the third mode and the fifth mode, the comfort of the first mode, the second mode, and the third mode is higher than that of the fourth mode and the fifth mode, and both the drivability and comfort of the first mode are higher than those of the second mode.

5. The method according to claim 4, characterized in that, Also includes: Obtain the battery status of the vehicle; In response to the battery state being less than a preset threshold, the target energy management mode is determined to be the fifth mode.

6. The method according to claim 1, characterized in that, Also includes: Obtain the driving mode of the vehicle within the preset time segment; The driving intensity requirement and the comfort intensity requirement are determined based on the driving mode.

7. The method according to claim 1, characterized in that, Also includes: The dynamic signal and the control signal are stored in the first data layer, and the first feature and the second feature are stored in the second data layer. The first data layer is used to perform data preprocessing on the dynamic signal and the control signal, and the second data layer is used to calculate the feature values ​​of the dynamic signal and the control signal.

8. A vehicle, characterized in that, The vehicle is used to execute the control method of the vehicle energy management system as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program is configured to execute the control method of the vehicle energy management system as described in any one of claims 1 to 7 when run on a computer or processor.

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