CN115596562A - Vehicle power control method, device, electronic device and storage medium - Google Patents

Abstract

The application provides a vehicle power control method, a vehicle power control device, an electronic device and a computer readable storage medium; the method comprises the following steps: obtaining sample dynamic characteristics of a vehicle when a sample user drives the vehicle; collecting the power characteristics to be tested of a vehicle when a user to be tested drives the vehicle; determining the relative characteristics to be measured of the dynamic characteristics to be measured relative to the dynamic characteristics of the sample according to the dynamic characteristics of the sample and the dynamic characteristics to be measured; and controlling the power of the vehicle according to the relative characteristics to be detected. Through the application, the vehicle can adapt to the power response requirements of different people.

Description

Vehicle power control method, device, electronic device and storage medium

technical field

The present application relates to vehicle control technology, in particular to a vehicle power control method, device, electronic equipment and computer-readable storage medium.

Background technique

At present, the power control of the vehicle for steering is generally unified, and anyone who drives the vehicle can perform the same power adjustment control. However, people with different driving habits or driving styles have different power response requirements for vehicle steering, and the existing technology cannot adapt to the needs of different people.

Contents of the invention

Embodiments of the present application provide a vehicle power control method, device, electronic device, and computer-readable storage medium, which can make the vehicle adapt to different people's power response requirements.

The technical scheme of the embodiment of the application is realized in this way:

An embodiment of the present application provides a vehicle power control method, including:

Obtain the sample dynamic characteristics of the vehicle when the sample user is driving the vehicle;

Collect the power characteristics of the vehicle to be tested when the user is driving the vehicle;

determining a relative characteristic to be measured of the dynamic characteristic to be measured relative to the dynamic characteristic of the sample according to the dynamic characteristic of the sample and the dynamic characteristic to be measured;

The power of the vehicle is controlled according to the relative characteristic to be measured.

In the above solution, the acquisition of the sample power characteristics of the vehicle when the sample user is driving the vehicle includes:

Obtain sample data of the vehicle at multiple sampling times when the sample user is driving the vehicle, the sample data including sample vehicle speed, sample throttle opening, and sample throttle opening change rate;

Construct the first data set according to the corresponding relationship between the sample vehicle speed and the sample throttle opening, and construct the second data set according to the corresponding relationship between the sample vehicle speed and the sample throttle opening rate of change;

The sample kinetic characteristic is determined based on the first data set and the second data set.

In the above solution, the determination of the dynamic characteristics of the sample according to the first data set and the second data set includes:

Using a density clustering algorithm to perform density clustering processing on the first data set to obtain the first boundary data of the first data set, and using a density clustering algorithm to perform density clustering processing on the second data set to obtain the second data set The second boundary data of the second data set;

Determine the dynamic characteristics of the sample according to the first boundary data and the second boundary data.

In the above solution, the sample dynamic characteristics include first sample characteristics and second sample characteristics, and the determination of the sample dynamic characteristics according to the first boundary data and the second boundary data includes:

determining a first amount of first data in the first data set outside the first boundary data, and determining a second amount of first data in the first data set;

calculating a first ratio of the first quantity to the second quantity;

determining a third amount of second data in the second data set that is outside the second boundary data, and determining a fourth amount of second data in the second data set;

calculating a second ratio of the third quantity to the fourth quantity;

The first ratio is used as the first sample feature, and the second ratio is used as the second sample feature.

In the above solution, the power characteristic to be measured includes a first characteristic to be measured and a second characteristic to be measured, and according to the power characteristic of the sample and the power characteristic to be measured, it is determined that the power characteristic to be measured is relative to the power characteristic of the sample. The relative characteristics of the characteristics to be measured, including:

calculating a third ratio of the first feature to be measured to the first sample feature, and calculating a fourth ratio of the second feature to be tested to the second sample feature;

The relative feature to be tested is determined according to the third ratio and the fourth ratio.

In the above scheme, the determination of the relative characteristics to be measured according to the third ratio and the fourth ratio includes:

Obtain a first confidence parameter and a second confidence parameter;

calculating a first product of the first confidence parameter and the third ratio, and calculating a second product of the second confidence parameter and the fourth ratio;

summing the first product and the second product to obtain the relative feature to be measured.

In the above solution, the control of the power of the vehicle according to the relative characteristics to be measured includes:

Obtain the corresponding relationship between relative features and correction parameters;

determining a target correction parameter corresponding to the relative feature to be measured according to the relative feature to be measured and the corresponding relationship between the relative feature and the correction parameter;

The torque of the vehicle is adjusted according to the target correction parameter, so as to control the power of the vehicle.

An embodiment of the present application provides a vehicle power control device, including:

An obtaining module, configured to obtain sample power characteristics of the vehicle when the sample user is driving the vehicle;

The collection module is used to collect the dynamic characteristics of the vehicle to be tested when the user to be tested drives the vehicle;

A determining module, configured to determine a relative characteristic of the dynamic characteristic to be measured relative to the dynamic characteristic of the sample according to the dynamic characteristic of the sample and the dynamic characteristic to be measured;

The control module is used to control the power of the vehicle according to the relative characteristics to be measured.

An embodiment of the present application provides an electronic device, including:

memory for storing executable instructions;

The processor is configured to implement the vehicle power control method provided in the embodiment of the present application when executing the executable instructions stored in the memory.

An embodiment of the present application provides a computer-readable storage medium, storing executable instructions for causing a processor to execute the vehicle power control method provided in the embodiment of the present application.

In the embodiment of the present application, by obtaining the sample power characteristics of the vehicle when the sample user is driving the vehicle; collecting the power characteristics of the vehicle to be tested when the user is driving the vehicle; according to the sample power characteristics and the power characteristics to be tested, determine the The relative characteristics of the power characteristics relative to the sample power characteristics to be measured; according to the relative characteristics to be measured, the power of the vehicle is controlled, so that the vehicle can adapt to the power response requirements of different people.

Description of drawings

FIG. 1 is an optional structural schematic diagram of an electronic device 100 provided in an embodiment of the present application;

FIG. 2 is an optional schematic flow chart of a vehicle power control method provided in an embodiment of the present application;

FIG. 3 is an optional detailed flow diagram of step 201 provided in the embodiment of the present application;

FIG. 4 is an optional detailed flow diagram of step 303 provided by the embodiment of the present application;

FIG. 5 is an optional detailed flow diagram of step 402 provided by the embodiment of the present application;

FIG. 6 is an optional detailed flow diagram of step 203 provided by the embodiment of the present application;

FIG. 7 is an optional detailed flow diagram of step 602 provided by the embodiment of the present application;

FIG. 8 is a schematic flowchart of an optional refinement of step 204 provided by the embodiment of the present application.

detailed description

In order to make the purpose, technical solutions and advantages of the application clearer, the application will be further described in detail below in conjunction with the accompanying drawings. All other embodiments obtained under the premise of creative labor belong to the scope of protection of this application.

In the following description, references to "some embodiments" describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or a different subset of all possible embodiments, and Can be combined with each other without conflict.

In the following description, the term "first\second\third" is only used to distinguish similar objects, and does not represent a specific ordering of objects. Understandably, "first\second\third" Where permitted, the specific order or sequencing may be interchanged such that the embodiments of the application described herein can be practiced in sequences other than those illustrated or described herein.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application, and are not intended to limit the present application.

Embodiments of the present application provide a vehicle power control method, device, electronic device, and computer-readable storage medium, which can make the vehicle adapt to the power response needs of different people.

Firstly, an electronic device for implementing the above-mentioned vehicle power control method provided in the embodiment of the present application will be described. Referring to FIG. 1 , FIG. 1 is a schematic structural diagram of an optional electronic device 100 provided by an embodiment of the present application. In practical applications, the electronic device 100 may be implemented as a vehicle controller. The electronic device 100 shown in FIG. 1 includes: at least one processor 101 , a memory 105 , at least one network interface 102 and a user interface 103 . Various components in the electronic device 100 are coupled together through the bus system 104 . It can be understood that the bus system 104 is used to realize connection and communication between these components. In addition to the data bus, the bus system 104 also includes a power bus, a control bus and a status signal bus. However, for clarity of illustration, the various buses are labeled as bus system 104 in FIG. 1 .

The processor 101 may be an integrated circuit chip, having signal processing capabilities, such as a general-purpose processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware Components, etc., wherein the general-purpose processor can be a microprocessor or any conventional processor, etc.

User interface 103 includes one or more output devices 1031 that enable presentation of media content, including one or more speakers and/or one or more visual displays. The user interface 103 also includes one or more input devices 1032, including user interface components that facilitate user input, such as a keyboard, mouse, microphone, touch screen display, camera, other input buttons and controls.

Memory 105 may be removable, non-removable or a combination thereof. Exemplary hardware devices include solid state memory, hard drives, optical drives, and the like. Memory 105 optionally includes one or more storage devices located physically remote from processor 101 .

Memory 105 includes volatile memory or nonvolatile memory, and may include both volatile and nonvolatile memory. The non-volatile memory may be a read only memory (ROM, Read Only Memory), and the volatile memory may be a random access memory (RAM, Random Access Memory). The memory 105 described in the embodiment of the present application is intended to include any suitable type of memory.

In some embodiments, the memory 105 can store data to support various operations. Examples of these data include programs, modules and data structures or their subsets or supersets. In the embodiment of the present application, an operating system 1051 is stored in the memory 105 , a network communication module 1052, a presentation module 1053, an input processing module 1054, and a vehicle power control device 1055; specifically,

Operating system 1051, including system programs for processing various basic system services and performing hardware-related tasks, such as framework layer, core library layer, driver layer, etc., for implementing various basic services and processing hardware-based tasks;

Network communication module 1052 for reaching other computing devices via one or more (wired or wireless) network interfaces 102, exemplary network interfaces 102 include: Bluetooth, Wireless Compatibility Authentication (WiFi), and Universal Serial Bus ( USB, Universal Serial Bus), etc.;

Presentation module 1053 for enabling presentation of information via one or more output devices 1031 (e.g., display screen, speakers, etc.) associated with user interface 103 (e.g., a user interface for operating peripherals and displaying content and information );

The input processing module 1054 is configured to detect one or more user inputs or interactions from one or more of the input devices 1032 and translate the detected inputs or interactions.

In some embodiments, the vehicle power control device provided in the embodiment of the present application may be realized by software. FIG. 1 shows a vehicle power control device 1055 stored in the memory 105, which may be software in the form of programs and plug-ins. It includes the following software modules: acquisition module 10551, collection module 10552, determination module 10553, and control module 10554. These modules are logical, so they can be combined or further divided arbitrarily according to the realized functions. The function of each module will be explained below.

In some other embodiments, the vehicle power control device provided in the embodiment of the present application may be implemented in a hardware manner. As an example, the vehicle power control device provided in the embodiment of the present application may be a processor in the form of a hardware decoding processor, which Be programmed to execute the vehicle power control method provided by the embodiment of the present application, for example, the processor in the form of a hardware decoding processor can adopt one or more application-specific integrated circuits (ASIC, Application Specific Integrated Circuit), DSP, programmable logic device (PLD, Programmable Logic Device), Complex Programmable Logic Device (CPLD, Complex Programmable Logic Device), Field Programmable Gate Array (FPGA, Field-Programmable Gate Array) or other electronic components.

The vehicle power control method provided by the embodiment of the present application will be described below in conjunction with the exemplary application and implementation of the terminal provided in the embodiment of the present application.

Referring to FIG. 2 , FIG. 2 is an optional flowchart of a vehicle power control method provided by an embodiment of the present application, which will be described in conjunction with the steps shown in FIG. 2 .

Step 201, obtaining the sample dynamic characteristics of the vehicle when the sample user is driving the vehicle;

Step 202, collecting the power characteristics of the vehicle to be tested when the user to be tested is driving the vehicle;

Step 203, according to the dynamic characteristics of the sample and the dynamic characteristics to be measured, determine the relative characteristics of the dynamic characteristics to be measured relative to the dynamic characteristics of the sample;

Step 204, controlling the power of the vehicle according to the relative characteristics to be measured.

In actual implementation, the sample power characteristics of the sample user when driving the vehicle are obtained. Exemplarily, a driver with regular driving habits can be selected to obtain the sample power characteristics in the process of driving the vehicle.

Specifically, in some embodiments, refer to FIG. 3. FIG. 3 is an optional detailed flow diagram of step 201 provided in the embodiment of the present application. Step 201 can be implemented in the following manner:

Step 301, obtaining sample data of the vehicle at multiple sampling times when the sample user is driving the vehicle, the sample data including sample vehicle speed, sample throttle opening, and sample throttle opening change rate;

Step 302, constructing a first data set according to the corresponding relationship between the sample vehicle speed and the sample throttle opening, and constructing a second data set according to the corresponding relationship between the sample vehicle speed and the sample throttle opening change rate;

Step 303: Determine the dynamic characteristics of the sample according to the first data set and the second data set.

During actual implementation, the sample vehicle speed, sample throttle opening and sample throttle opening change rate signal of the sample user in the process of driving the vehicle are collected. Driving scenarios include urban areas, suburban areas, and high-speed roads, and the vehicle speed coverage ranges from 0-120km/h. The acquisition condition is that the gear position is D, and the throttle opening > 0. The rate of change of the sample throttle opening is calculated through the signal of the rate of change of the sample throttle opening. The sample data includes multiple sample data points, and one sample data point corresponds to one time point. Here, the first data in the first data set are data points composed of two-dimensional data such as sample vehicle speed and sample accelerator opening. The second data in the second data set are data points composed of data in two dimensions, such as sample vehicle speed and sample accelerator opening change rate.

In some embodiments, refer to FIG. 4 . FIG. 4 is an optional detailed flowchart of step 303 provided in the embodiment of the present application. Step 303 can be implemented in the following manner:

Step 401: Perform density clustering processing on the first data set using a density clustering algorithm to obtain first boundary data of the first data set, and perform density clustering processing on the second data set using a density clustering algorithm , to obtain the second boundary data of the second data set;

Step 402: Determine the dynamic characteristics of the sample according to the first boundary data and the second boundary data.

In actual implementation, the density clustering method (DBSCAN) is used for data analysis. First boundary data composed of sample vehicle speed-sample throttle opening and second boundary data composed of sample vehicle speed-sample throttle opening change rate are respectively established. Here, both the first boundary data and the second boundary data may constitute a boundary line, the first boundary data corresponds to the first boundary line, and the second boundary data corresponds to the second boundary line. Specifically, in the embodiment of the present application, the boundary line is determined when the number of points within a radius Eps centered on the point (Vn, Pn) is less than a set minimum number of points minP.

In some embodiments, the sample dynamic features include the first sample feature and the second sample feature, see Fig. 5, Fig. 5 is an optional detailed flow diagram of step 402 provided by the embodiment of the present application, step 402 This can be achieved by:

Step 501, determining a first quantity of first data outside the first boundary data in the first data set, and determining a second quantity of first data in the first data set;

Step 502, calculating a first ratio of the first quantity to the second quantity;

Step 503, determining a third quantity of the second data outside the second boundary data in the second data set, and determining a fourth quantity of the second data in the second data set;

Step 504, calculating a second ratio of the third quantity to the fourth quantity;

Step 505, use the first ratio as the first sample feature, and use the second ratio as the second sample feature.

During actual implementation, a first quantity of first data outside the first boundary data in the first data set is determined, and a second quantity of first data in the first data set is determined. Specifically, the first boundary data forms the first boundary line, counts the first quantity of the first data outside the first boundary line and the second quantity of the first data, and calculates the entropy value Ra1 (i.e. the first ratio), Ra1= First Quantity/Second Quantity. At the same time, a third quantity of second data outside the second boundary data in the second data set is determined, and a fourth quantity of second data in the second data set is determined. Specifically, the second boundary data forms the second boundary line, counts the third quantity of the second data outside the second boundary line and the fourth quantity of the second data, and calculates the entropy value Ra2 (i.e. the second ratio), Ra2= Third Quantity/Fourth Quantity. Specifically, Ra1 is used as the first sample feature, and Ra2 is used as the second sample feature. Exemplarily, the first boundary data example is as follows:

An example of the second boundary data is as follows:

In some embodiments, the power feature to be tested includes a first feature to be tested and a second feature to be tested, see FIG. 6 , which is an optional detailed flow diagram of step 203 provided by the embodiment of the present application. Step 203 can be implemented in the following manner:

Step 601, calculating a third ratio between the first feature to be tested and the first sample feature, and calculating a fourth ratio between the second feature to be tested and the second sample feature;

Step 602: Determine the relative feature to be measured according to the third ratio and the fourth ratio.

Here, the dynamic characteristics to be measured are obtained in the same manner as the dynamic characteristics of the sample. The first feature to be tested is acquired in the same way as the first sample feature, and the second feature to be tested is acquired in the same way as the second sample feature. In actual implementation, the driving data of the current driver in the process of driving the vehicle is acquired. Driving data includes vehicle speed, accelerator opening and rate of change of accelerator opening. Wherein, the vehicle speed and the accelerator opening are obtained through direct collection, and the rate of change of the accelerator opening is obtained by collecting the signal of the rate of change of the accelerator opening and calculating the signal of the rate of change of the accelerator opening. Here, the acquisition condition is that the gear is D, and the throttle opening is >0. Specifically, the third data set is constructed according to the corresponding relationship between the vehicle speed and the throttle opening, and the fourth data set is constructed according to the corresponding relationship between the vehicle speed and the rate of change of the throttle opening. Here, the third data in the third data set are data points composed of two-dimensional data such as speed and accelerator opening. The fourth data in the fourth data set are data points composed of data in two dimensions, such as speed and accelerator opening change rate. Next, according to the third data set and the fourth data set, the power characteristic to be measured is determined. Next, according to the same method as in the foregoing embodiments of the present application, the third boundary data corresponding to the third data set is constructed and the fourth boundary data corresponding to the fourth data set is constructed. When the number of driving data points in the collected driving data is greater than the set minimum number of points, start to calculate the entropy values Rb1 and Rb2, Rb1=the number of points of the third data other than the third boundary data/the total number of points of the third data, Rb2=the fourth Points of 4th data other than boundary data/total number of 4th data points. Next, calculate a third ratio between the first feature to be tested and the first sample feature, and calculate a fourth ratio between the second feature to be tested and the second sample feature, according to the third ratio and the fourth ratio to determine the relative characteristic to be measured.

In some embodiments, refer to FIG. 7 . FIG. 7 is an optional detailed flowchart of step 602 provided in the embodiment of the present application. Step 602 may be implemented in the following manner:

Step 701, obtaining a first confidence parameter and a second confidence parameter;

Step 702, calculating a first product of the first confidence parameter and the third ratio, and calculating a second product of the second confidence parameter and the fourth ratio;

Step 703, summing the first product and the second product to obtain the relative feature to be measured.

In actual implementation, the relative feature to be measured is the sum of the first product and the second product, the first product is the product of the first confidence parameter and the third ratio, and the second product is the product of the second confidence parameter and the fourth ratio. Exemplarily, an evaluation coefficient θ (that is, the relative characteristic to be measured) is defined, θ=a*Rb1/Ra1+b*Rb2/Ra2, wherein, a represents the degree of confidence of the throttle opening (ie, the first confidence parameter), and Rb1 /Ra1 is the third ratio, b represents the degree of confidence in the rate of change of the throttle opening (that is, the second confidence parameter), the value range of a and b is 0-1, and a+b=1, b>a, Rb1/Ra1 is the third ratio, and Rb2/Ra2 is the fourth ratio. The evaluation coefficient θ is used as the characteristic of the driver’s driving habits. The larger the value of θ, the more aggressive the driving habit and the higher the demand for power; the smaller the value of θ, the more stable the driving habit and the higher the demand for power.

In some embodiments, refer to FIG. 8 . FIG. 8 is an optional detailed flowchart of step 204 provided in the embodiment of the present application. Step 204 may be implemented in the following manner:

Step 801, obtaining the corresponding relationship between relative features and correction parameters;

Step 802, according to the relative feature to be measured and the corresponding relationship between the relative feature and the correction parameter, determine the target correction parameter corresponding to the relative feature to be measured;

Step 803, adjust the torque of the vehicle according to the target correction parameter, so as to control the power of the vehicle.

In actual implementation, the corresponding relationship between the relative feature and the correction parameter is obtained, and the corresponding target correction parameter is determined according to the corresponding relationship and the relative feature to be measured, and the distortion of the vehicle is adjusted according to the target correction parameter. Here, post-correction demand torque=before correction demand torque*target correction parameter. The required torque before correction refers to the torque defined according to the size of the accelerator opening, which is conventionally referred to as the pedal MAP torque. The corrected demand torque has different demand values according to different vehicle models. For example, taking the power system capability as the boundary, for traditional models, it is usually the external characteristics of the engine; for pure electric vehicles, it is usually the smaller value of the external characteristics of the motor and the maximum charge and discharge power allowed by the battery; for hybrid vehicles, according to The power coupling is determined.

In the embodiment of the present application, by obtaining the sample power characteristics of the vehicle when the sample user is driving the vehicle; collecting the power characteristics of the vehicle to be tested when the user is driving the vehicle; according to the sample power characteristics and the power characteristics to be tested, determine the The relative characteristics of the power characteristics relative to the sample power characteristics to be measured; according to the relative characteristics to be measured, the power of the vehicle is controlled, so that the vehicle can adapt to the power response requirements of different people.

The following continues to illustrate the exemplary structure of the vehicle power control device 1055 provided by the embodiment of the present application implemented as a software module. In some embodiments, as shown in FIG. 1 , the software modules stored in the vehicle power control device 1055 of the memory Can include:

Obtaining module 10551, used to obtain the sample power characteristics of the vehicle when the sample user is driving the vehicle;

The collection module 10552 is used to collect the power characteristics of the vehicle to be tested when the user to be tested is driving the vehicle;

A determination module 10553, configured to determine the relative characteristics of the dynamic characteristics to be measured relative to the dynamic characteristics of the sample according to the dynamic characteristics of the sample and the dynamic characteristics to be measured;

The control module 10554 is used to control the power of the vehicle according to the relative characteristics to be measured.

In some embodiments, the obtaining module 10551 is also used to obtain the sample data of the vehicle at multiple sampling times when the sample user is driving the vehicle, the sample data includes the sample vehicle speed, the sample throttle opening and the sample throttle opening change rate; according to Construct the first data set according to the corresponding relationship between the sample vehicle speed and the sample throttle opening, and construct the second data set according to the corresponding relationship between the sample vehicle speed and the sample throttle opening change rate; according to the first data set and the second data set , to determine the dynamic characteristics of the sample.

In some embodiments, the obtaining module 10551 is further configured to use a density clustering algorithm to perform density clustering processing on the first data set to obtain the first boundary data of the first data set, and use a density clustering algorithm to perform density clustering on the first data set Performing density clustering processing on the second data set to obtain second boundary data of the second data set; determining the dynamic characteristics of the sample according to the first boundary data and the second boundary data.

In some embodiments, the sample dynamic features include a first sample feature and a second sample feature, and the obtaining module 10551 is further configured to determine the first value of the first data outside the first boundary data in the first data set. quantity, and determine the second quantity of the first data in the first data set; calculate the first ratio of the first quantity to the second quantity; determine the second data outside the second boundary data in the second data set and determine the fourth quantity of the second data in the second data set; calculate the second ratio of the third quantity to the fourth quantity; use the first ratio as the first sample feature , and use the second ratio as the second sample feature.

In some embodiments, the dynamic characteristics to be measured include a first characteristic to be measured and a second characteristic to be measured, so the determining module 10553 is also used to calculate the first characteristic to be measured and the first sample characteristic and calculating a fourth ratio between the second feature to be tested and the second sample feature; and determining the relative feature to be tested according to the third ratio and the fourth ratio.

In some embodiments, the determination module 10553 is also used to obtain the first confidence parameter and the second confidence parameter; calculate the first product of the first confidence parameter and the third ratio, and calculate the second confidence parameter and the second product of the fourth ratio; summing the first product and the second product to obtain the relative feature to be measured.

In some embodiments, the control module 10554 is also used to obtain the corresponding relationship between the relative feature and the correction parameter; according to the corresponding relationship between the relative feature to be tested and the corresponding relationship between the relative feature and the correction parameter, determine the corresponding relationship between the relative feature to be tested the target correction parameter; adjust the torque of the vehicle according to the target correction parameter, so as to control the power of the vehicle.

It should be noted that the description of the device in the embodiment of the present application is similar to the description of the above-mentioned method embodiment, and has similar beneficial effects to the method embodiment, so details are not repeated here.

An embodiment of the present application provides a computer program product or computer program, where the computer program product or computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the above-mentioned vehicle power control method in the embodiment of the present application.

An embodiment of the present application provides a computer-readable storage medium storing executable instructions, wherein executable instructions are stored, and when the executable instructions are executed by a processor, the processor will be caused to execute the vehicle power control provided by the embodiment of the present application method.

In some embodiments, the computer-readable storage medium can be memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; Various equipment.

In some embodiments, executable instructions may take the form of programs, software, software modules, scripts, or code written in any form of programming language, including compiled or interpreted languages, or declarative or procedural languages, and its Can be deployed in any form, including as a stand-alone program or as a module, component, subroutine or other unit suitable for use in a computing environment.

As an example, executable instructions may, but do not necessarily correspond to files in a file system, may be stored as part of a file that holds other programs or data, for example, in a hypertext markup language (HTML, HyperTextMarkupLanguage) document. or multiple scripts, in a single file dedicated to the program in question, or in multiple cooperating files (for example, files that store one or more modules, subroutines, or sections of code).

As an example, executable instructions may be deployed to be executed on one computing device, or on multiple computing devices located at one site, or alternatively, on multiple computing devices distributed across multiple sites and interconnected by a communication network. to execute.

In summary, through the embodiments of the present application, the vehicle can be adapted to the power response requirements of different people.

The above descriptions are merely examples of the present application, and are not intended to limit the protection scope of the present application. Any modifications, equivalent replacements and improvements made within the spirit and scope of the present application are included in the protection scope of the present application.

Claims (10)

1. A vehicle power control method, characterized in that, comprising: Obtain the sample dynamic characteristics of the vehicle when the sample user is driving the vehicle; Collect the power characteristics of the vehicle to be tested when the user is driving the vehicle; determining a relative characteristic to be measured of the dynamic characteristic to be measured relative to the dynamic characteristic of the sample according to the dynamic characteristic of the sample and the dynamic characteristic to be measured; The power of the vehicle is controlled according to the relative characteristic to be measured. 2. The method according to claim 1, wherein said obtaining the sample power characteristics of the vehicle when the sample user is driving the vehicle comprises: Obtain sample data of the vehicle at multiple sampling times when the sample user is driving the vehicle, the sample data including sample vehicle speed, sample throttle opening, and sample throttle opening change rate; Construct the first data set according to the corresponding relationship between the sample vehicle speed and the sample throttle opening, and construct the second data set according to the corresponding relationship between the sample vehicle speed and the sample throttle opening rate of change; The sample kinetic characteristic is determined based on the first data set and the second data set. 3. The method according to claim 2, wherein said determining said dynamic characteristics of said sample according to said first data set and said second data set comprises: Using a density clustering algorithm to perform density clustering processing on the first data set to obtain the first boundary data of the first data set, and using a density clustering algorithm to perform density clustering processing on the second data set to obtain the second data set The second boundary data of the second data set; Determine the dynamic characteristics of the sample according to the first boundary data and the second boundary data. 4. The method according to claim 2, wherein the sample dynamic features include a first sample feature and a second sample feature, and according to the first boundary data and the second boundary data, determine The dynamic characteristics of the sample include: determining a first amount of first data in the first data set outside the first boundary data, and determining a second amount of first data in the first data set; calculating a first ratio of the first quantity to the second quantity; determining a third amount of second data in the second data set that is outside the second boundary data, and determining a fourth amount of second data in the second data set; calculating a second ratio of the third quantity to the fourth quantity; The first ratio is used as the first sample feature, and the second ratio is used as the second sample feature. 5. The method according to claim 4, wherein the dynamic characteristic to be measured comprises a first characteristic to be measured and a second characteristic to be measured, and according to the dynamic characteristic of the sample and the dynamic characteristic to be measured, Determining the relative characteristics of the dynamic characteristics to be measured relative to the dynamic characteristics of the sample, including: calculating a third ratio of the first feature to be measured to the first sample feature, and calculating a fourth ratio of the second feature to be tested to the second sample feature; The relative feature to be tested is determined according to the third ratio and the fourth ratio. 6. The method according to claim 4, wherein said determining said relative feature to be measured according to said third ratio and said fourth ratio comprises: Obtain a first confidence parameter and a second confidence parameter; calculating a first product of the first confidence parameter and the third ratio, and calculating a second product of the second confidence parameter and the fourth ratio; summing the first product and the second product to obtain the relative feature to be measured. 7. The method according to claim 1, wherein the controlling the power of the vehicle according to the relative characteristics to be measured comprises: Obtain the corresponding relationship between relative features and correction parameters; determining a target correction parameter corresponding to the relative feature to be measured according to the relative feature to be measured and the corresponding relationship between the relative feature and the correction parameter; The torque of the vehicle is adjusted according to the target correction parameter, so as to control the power of the vehicle. 8. A vehicle power control device, characterized in that it comprises: An obtaining module, configured to obtain sample power characteristics of the vehicle when the sample user is driving the vehicle; The collection module is used to collect the dynamic characteristics of the vehicle to be tested when the user to be tested drives the vehicle; A determining module, configured to determine a relative characteristic of the dynamic characteristic to be measured relative to the dynamic characteristic of the sample according to the dynamic characteristic of the sample and the dynamic characteristic to be measured; The control module is used to control the power of the vehicle according to the relative characteristics to be measured. 9. An electronic device, characterized in that it comprises: memory for storing executable instructions; The processor is configured to implement the vehicle power control method according to any one of claims 1 to 7 when executing the executable instructions stored in the memory. 10. A computer-readable storage medium, characterized by storing executable instructions for implementing the vehicle power control method according to any one of claims 1 to 7 when executed by a processor.

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