CN112550187A - Driving mode self-learning control method and vehicle control unit - Google Patents

Driving mode self-learning control method and vehicle control unit Download PDF

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Publication number
CN112550187A
CN112550187A CN202011559424.3A CN202011559424A CN112550187A CN 112550187 A CN112550187 A CN 112550187A CN 202011559424 A CN202011559424 A CN 202011559424A CN 112550187 A CN112550187 A CN 112550187A
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China
Prior art keywords
learning
statistical information
self
driving
braking
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CN202011559424.3A
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Chinese (zh)
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胡凡
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Guangxi Ningda Automobile Technology Co ltd
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Guangxi Ningda Automobile Technology Co ltd
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Priority to CN202011559424.3A priority Critical patent/CN112550187A/en
Publication of CN112550187A publication Critical patent/CN112550187A/en
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60RVEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R16/00Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
    • B60R16/02Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
    • B60R16/023Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for transmission of signals between vehicle parts or subsystems
    • B60R16/0231Circuits relating to the driving or the functioning of the vehicle

Abstract

The embodiment of the application provides a driving mode self-learning control method, which comprises the following steps: receiving a driving mode self-learning starting instruction; within a preset self-learning duration, obtaining a statistical value of driving characteristic data, wherein the statistical value of the driving characteristic data comprises the following steps: the method comprises the following steps that N pieces of time length statistical information of accelerator opening intervals, interval statistical information of accelerator change rates, time length statistical information of vehicle speed intervals, turn-on times statistical information of steering lamps, times statistical information that steering wheel turning angles are larger than a preset angle, braking times statistical information and statistical information of master cylinder pressure during braking are obtained, wherein N is larger than 1; and generating and storing a self-learning driving curve according to the driving characteristic data. The driving style requirements of consumers are met through the driving mode self-learning, and the vehicle using experience of the users is improved.

Description

Driving mode self-learning control method and vehicle control unit
Technical Field
The application relates to the technical field of electric automobiles, in particular to a driving mode self-learning control method and a vehicle control unit.
Background
With the development of economy and the demand of energy conservation and emission reduction of society, new energy automobiles become a development consensus in the automobile field, and electric automobiles are an important technical route in the development direction. An electric vehicle is a vehicle powered by a power battery.
Automobiles are becoming everyday vehicles, but the driving style of electric automobiles is basically three, for example: general mode, sport mode, economy mode. The factory-set driving mode, i.e., the driving style (power output characteristic curve), is not modifiable. The vehicle user cannot set or modify himself/herself, and it is difficult to meet the higher driving demand of the consumer.
Disclosure of Invention
In view of this, the application provides a driving mode self-learning control method and a vehicle control unit, which satisfy the driving style requirements of consumers and improve the vehicle using experience of users through driving mode self-learning.
In one implementation, the present application provides a driving pattern self-learning control method, the method comprising: receiving a driving mode self-learning starting instruction; within a preset self-learning duration, obtaining a statistical value of driving characteristic data, wherein the statistical value of the driving characteristic data comprises the following steps: the method comprises the following steps that N pieces of time length statistical information of accelerator opening intervals, interval statistical information of accelerator change rates, time length statistical information of vehicle speed intervals, turn-on times statistical information of steering lamps, times statistical information that steering wheel turning angles are larger than a preset angle, braking times statistical information and statistical information of master cylinder pressure during braking are obtained, wherein N is larger than 1; and generating and storing a self-learning driving curve according to the driving characteristic data, wherein the self-learning driving curve is a mapping relation between torque and accelerator opening.
Optionally, according to the throttle signal, counting time length statistical information of the multiple throttle opening intervals and interval statistical information of the throttle change rate; according to the braking signals, counting to obtain the statistical information of the braking times; acquiring a vehicle speed signal sent by an electronic stability system controller, and counting to obtain duration statistical information of the vehicle speed interval; acquiring a steering wheel corner signal sent by the ESC, and counting to obtain the number counting information that the steering wheel corner is larger than a preset angle; obtaining a braking pressure signal sent by the ESC, and counting to obtain statistical information of the master cylinder pressure during braking; and obtaining a steering lamp signal sent by the vehicle body controller, and counting to obtain the statistical information of the turn-on times of the steering lamp.
Optionally, after receiving the driving mode self-learning opening instruction, the method further includes converting the current driving mode of the vehicle into a normal mode, and performing self-learning in the normal mode, where the normal mode indicates that the torque and the accelerator opening degree are in a linear relationship.
Optionally, the preset self-learning duration is at least 1 hour; the duration of each accelerator opening interval is at least 1/N of the preset self-learning duration; the turning-on times of the steering lamp is greater than a preset turning-on time threshold; the braking times are larger than a preset braking time threshold.
Optionally, the method further includes receiving the self-learning driving curve selection instruction, and outputting a torque demand signal corresponding to the self-learning driving curve to a motor controller.
Optionally, the driving mode self-learning starting instruction is sent to the vehicle control unit by the user through the vehicle-mounted large screen controller.
In another implementation, the application also provides a vehicle control unit, which comprises a unit for realizing the driving mode self-learning control, wherein each step can be realized by a separate unit, and all or part of the units can be integrated together. These units may be logic units, stored in the form of software or hardware, for example, in a memory in the form of a program, which is called by a processor to implement the functions of the respective units; as another example, the instructions may be implemented in hardware circuitry, such as may be implemented by logic gates.
In one example, the present application provides a vehicle control unit, comprising: the receiving unit is used for receiving a driving mode self-learning starting instruction; the processing unit is used for acquiring the statistical value of the driving characteristic data within a preset self-learning duration, wherein the statistical value of the driving characteristic data comprises the following steps: the method comprises the following steps that N pieces of time length statistical information of accelerator opening intervals, interval statistical information of accelerator change rates, time length statistical information of vehicle speed intervals, turn-on times statistical information of steering lamps, times statistical information that steering wheel turning angles are larger than a preset angle, braking times statistical information and statistical information of master cylinder pressure during braking are obtained, wherein N is larger than 1; the processing unit is further used for generating and storing a self-learning driving curve according to the driving characteristic data, wherein the self-learning driving curve is a mapping relation between torque and accelerator opening.
Optionally, the processing unit is configured to: counting time length statistical information of the plurality of throttle opening intervals and interval statistical information of the throttle change rate according to the throttle signal; according to the braking signals, counting to obtain the statistical information of the braking times; counting according to the vehicle speed signal received by the receiving unit and sent by the electronic stability system controller to obtain duration statistical information of the vehicle speed interval; counting to obtain the number statistical information that the steering wheel corner is larger than a preset angle according to the steering wheel corner signal sent by the ESC and received by the receiving unit; counting to obtain the statistical information of the master cylinder pressure during braking according to the braking pressure signal sent by the ESC and received by the receiving unit; and counting to obtain the turn-on times counting information of the turn lights according to the turn light signals received by the receiving unit and sent by the automobile body controller.
Optionally, after the receiving unit receives the driving mode self-learning start instruction, the processing unit is further configured to: and converting the current driving mode of the vehicle into a common mode, and performing self-learning in the common mode, wherein the common mode represents that the torque and the accelerator opening degree are in a linear relation.
Optionally, the vehicle control unit further includes a sending unit, configured to output a torque demand signal corresponding to the self-learning driving curve to the motor controller after the receiving unit receives the self-learning driving curve selection instruction.
Optionally, the receiving unit is configured to receive the driving mode self-learning starting instruction sent by the user through the vehicle-mounted large-screen controller.
In another example, the present application further provides a vehicle control unit including a processor for calling a program stored in a memory to implement the above driving mode self-learning control method.
In yet another implementation, the present application further provides a storage medium having program code stored therein, which when invoked by a processor, causes the processor to implement the above driving pattern self-learning control method.
By the method, the driving mode can be learned by self, the driving style requirements of consumers are met, and the vehicle using experience of the users is improved.
Drawings
The following description of specific embodiments of the present application will be made with reference to the accompanying drawings.
FIG. 1 is a schematic diagram of a vehicle control system provided in an embodiment of the present application;
FIG. 2 is a schematic diagram of a driving mode self-learning control method provided by an embodiment of the application;
FIG. 3 is a schematic illustration of a self-learning driving curve provided by an embodiment of the present application;
fig. 4 is a schematic view of a vehicle control unit according to an embodiment of the present disclosure;
fig. 5 is a schematic view of another vehicle control unit according to an embodiment of the present disclosure.
Detailed Description
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following description will be made with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the present application, and that for a person skilled in the art, other drawings and other embodiments can be obtained from these drawings without inventive effort. For the sake of simplicity, the drawings only schematically show the parts relevant to the present application, and they do not represent the actual structure as a product.
Please refer to fig. 1, which is a schematic diagram of a vehicle control system according to an embodiment of the present disclosure. As shown in fig. 1, the system mainly includes the following parts: a Vehicle Control Unit (VCU), a Motor Control Unit (MCU), an Electronic Stability Control Unit (ESC), a Body Control Module (BCM), and a Vehicle-mounted large screen controller.
The VCU is used as a central control unit of the vehicle and is the core of the whole control system. And the MCU controls the running state of the motor according to the instruction. The ESC performs intervention control and the like on an engine and a braking system of the vehicle by monitoring the running state of the vehicle. The BCM can realize control of the electric appliance for the vehicle body. The VCU may communicate with other controllers via a Controller Area Network (CAN). The embodiment of the invention does not limit the communication mode between the controllers.
The scheme of the embodiment of the application is described below with reference to the attached drawings.
Please refer to fig. 2, which is a schematic diagram of a driving mode self-learning control method according to an embodiment of the present application. As shown in fig. 2, the method is performed by the VCU or a chip within the VCU, and includes the following steps:
s210: and receiving a driving mode self-learning starting instruction.
Optionally, the vehicle-mounted large screen controller sends a driving mode self-learning starting instruction to the VCU.
Specifically, the user opens the vehicle-mounted large screen, selects the driving mode self-learning of the vehicle-mounted large screen, and then the vehicle-mounted large screen controller sends a driving mode self-learning opening instruction to the VCU.
S220: and acquiring the statistical value of the driving characteristic data within a preset self-learning duration.
The statistical value of the driving characteristic data includes any combination of the following: the method comprises the following steps of obtaining N pieces of time length statistical information of accelerator opening intervals, interval statistical information of accelerator change rates, time length statistical information of vehicle speed intervals, turn-on times statistical information of steering lamps, times statistical information that steering wheel turning angles are larger than a preset angle, braking times statistical information, statistical information of master cylinder pressure during braking and the like, wherein N is larger than 1.
It is to be understood that the above-described statistical values of the driving characteristic data include, but are not limited to, those listed above.
S230: and generating and storing a self-learning driving curve according to the driving characteristic data.
The self-learning driving curve is a mapping relation between torque and accelerator opening.
Optionally, the user may generate and store a plurality of self-learning driving curves through the self-learning, may store the self-learning driving curves as specific names, and may delete one or more stored self-learning driving curves.
Optionally, when the user uses the vehicle, the user can select the keys through the screen, click and select the self-learning driving curve, and experience the previous self-learning driving effect of the vehicle.
Optionally, the user may also accept the saved self-learning driving curve recommended by the VCU based on the intelligent judgment while in use.
By the method, the VCU generates and stores the driving curve in the self-learning process according to the driving characteristic data acquired in the self-learning time length, and a user can select the self-learning driving curve and experience the driving feeling of the self-learning driving curve in the vehicle using process.
In the embodiment shown in fig. 2, in some embodiments, the VCU obtains statistical information of the time lengths of the plurality of accelerator opening intervals and statistical information of the interval of the accelerator change rate by statistics according to an accelerator signal. For example, the accelerator opening is divided into three types: the method comprises the following steps that a small throttle opening degree (0-30%), an intermediate throttle opening degree [ 30-65% ] and a large throttle opening degree (65% -100%), and a VCU obtains duration statistical information of the three throttle opening degree intervals through statistics according to throttle signals. It is understood that the division of the accelerator opening degree is not limited in the embodiment of the present invention. An Accelerator Position Sensor (APS) is used to generate a corresponding voltage signal to control the opening of a throttle when a driver operates an Accelerator. The accelerator opening is commonly referred to as APS.
The interval statistical information of the accelerator change rate is mainly used for reflecting the speed of the driver stepping on the accelerator.
The VCU obtains the statistical information of the braking times through statistics according to the braking signals, and the statistical information is mainly used for representing whether a driver/user brakes frequently and whether the braking is sudden or not, or the driving style of sudden acceleration and sudden deceleration.
And the VCU acquires the vehicle speed signal sent by the electronic stability system controller, and counts to obtain the duration statistical information of the vehicle speed interval. For example: the vehicle speed can be divided into 0-40km/h, 40-60 km/h, 60-80 km/h, 80-100km/h and the like, and the duration statistical information of the vehicle speed interval in the self-learning duration is obtained through statistics based on the acquired vehicle speed signals. Alternatively, a duration of greater than 100KM/h is recorded in the 80-100KM/h speed-per-hour segment. It is to be understood that the division of the vehicle speed interval is not limited in the embodiment of the present invention.
And the VCU acquires the steering wheel corner signal sent by the ESC, and counts to obtain the counting information of the times that the steering wheel corner is larger than a preset angle. The times that the steering wheel corner is not 0 or the times that the steering wheel corner is larger than a certain value (calibration value) are mainly used for assisting in recording and representing the habit of overtaking of a driver.
And the VCU acquires the braking pressure signal sent by the ESC, and counts to obtain the statistical information of the master cylinder pressure during braking. The VCU determines whether the driver has frequent braking and sudden braking, or sudden acceleration and sudden deceleration.
And the VCU acquires the steering lamp signal sent by the vehicle body controller, and counts to obtain the statistical information of the turn-on times of the steering lamp. This information is primarily used to assist in recording habits that characterize a driver's passing.
Sufficient self-learning duration can enable the VCU to collect enough driving data, and a self-learning driving curve can be generated more accurately. In some embodiments, the self-learning duration and or self-learning completion condition includes, but is not limited to: the preset self-learning duration is at least 1 hour; the duration of each accelerator opening interval is at least 1/N of the preset self-learning duration; the turning-on times of the steering lamp is greater than a preset turning-on time threshold; the braking times are larger than a preset braking time threshold. Such as: there are at least 10 vehicle take-off events, at least 10 vehicle braking events, at least 10 vehicle steering events, etc. The above thresholds can be dynamically adjusted and set according to actual needs.
In some embodiments, the maximum vehicle speed is at least equal to or greater than 100Km/h within the preset self-learning period. Optionally, the maximum vehicle speed needs to meet the setting requirement of the vehicle speed interval. The method can ensure that all preset vehicle speed sections are covered within the preset self-learning duration.
Please refer to fig. 3, which is a schematic diagram of a self-learning driving curve according to an embodiment of the present application.
The VCU generates a self-learned driving curve based on the driving characteristic data, which may be a linear driving style with a relatively linear power output, such as the driving characteristic curve D shown in FIG. 3, i.e., the normal mode;
it may be that the power of stepping on the accelerator with light force will have strong output, and the starting is very fast, such as the driving characteristic curve a shown in fig. 3;
the output power of the front half section of the accelerator is very slow, so that the accelerator is used for urban traffic jam road conditions, can well control the speed of the vehicle, and can be suitable for many urban women. Such as curve G shown in fig. 3;
it may be that the power output is stronger at the opening of the accelerator in the first half section to meet a certain power demand, the power output is gentler when the accelerator is interrupted, and the power output is quicker in the second half section of the accelerator, which is suitable for overtaking, for example, the driving characteristic curve E shown in fig. 3. It is understood that the other curves in fig. 3 do not limit the embodiments of the present invention, and are not described in detail.
Optionally, the method further includes receiving the self-learning driving curve selection instruction, and outputting a torque demand signal corresponding to the self-learning driving curve to a motor controller.
A user can select the stored self-learning driving curve through the vehicle-mounted large-screen controller, and the VCU outputs a torque demand signal corresponding to the self-learning driving curve to the motor controller based on the selection instruction.
As can be seen from the above, in the scheme of the embodiment of the application, the driving characteristic data acquired within the self-learning duration generates and stores the driving curve in the self-learning process, and the user can select the self-learning driving curve and experience the driving feeling of the self-learning driving curve in the vehicle using process.
Based on the same inventive concept, the embodiment of the application also provides a vehicle control unit, which comprises a unit for realizing the self-learning control of the driving mode, wherein each step can be realized by an independent unit, and all or part of the units can be integrated together. These units may be logic units for performing the methods performed by the vehicle control unit in the above method embodiments.
In an implementation, please refer to fig. 4, which is a schematic diagram of a vehicle control unit according to an embodiment of the present disclosure. As shown in fig. 4, the vehicle control unit 400 includes a receiving unit 410 and a processing unit 420.
The receiving unit 410 is configured to receive a driving mode self-learning start instruction;
the processing unit 420 is configured to obtain a statistical value of the driving characteristic data within a preset self-learning duration, where the statistical value of the driving characteristic data includes: the method comprises the following steps that N pieces of time length statistical information of accelerator opening intervals, interval statistical information of accelerator change rates, time length statistical information of vehicle speed intervals, turn-on times statistical information of steering lamps, times statistical information that steering wheel turning angles are larger than a preset angle, braking times statistical information and statistical information of master cylinder pressure during braking are obtained, wherein N is larger than 1;
the processing unit 420 is further configured to generate and store a self-learning driving curve according to the driving characteristic data, where the self-learning driving curve is a mapping relationship between a torque and an accelerator opening.
Optionally, the processing unit 420 is configured to obtain, according to an accelerator signal, time duration statistical information of the accelerator opening intervals and interval statistical information of the accelerator change rate through statistics; according to the braking signals, counting to obtain the statistical information of the braking times; counting according to the vehicle speed signal received by the receiving unit and sent by the electronic stability system controller to obtain duration statistical information of the vehicle speed interval; counting to obtain the number statistical information that the steering wheel corner is larger than a preset angle according to the steering wheel corner signal sent by the ESC and received by the receiving unit; counting to obtain the statistical information of the master cylinder pressure during braking according to the braking pressure signal sent by the ESC and received by the receiving unit; and counting to obtain the turn-on times counting information of the turn lights according to the turn light signals received by the receiving unit and sent by the automobile body controller.
Optionally, after the receiving unit receives the driving mode self-learning start instruction, the processing unit is further configured to: and converting the current driving mode of the vehicle into a common mode, and performing self-learning in the common mode, wherein the common mode represents that the torque and the accelerator opening degree are in a linear relation.
Optionally, the vehicle control unit further includes a sending unit 430, configured to output a torque demand signal corresponding to the self-learning driving curve to the motor controller after the receiving unit 410 receives the self-learning driving curve selection instruction.
Optionally, the receiving unit 410 is configured to receive the driving mode self-learning starting instruction sent by the user through the vehicle-mounted large-screen controller.
The method for the operation performed by each unit may specifically refer to the method embodiment shown in fig. 2, and is not described herein again.
The division of each unit of the vehicle control unit is only a division of a logic function, and the actual implementation may be wholly or partially integrated on a physical entity, or may be physically separated. And the units can be realized in a form that all the units are called by the processor through software, or in a form that all the units are called by the processor through hardware, or in a form that part of the units are called by the processor through software, or in a form that part of the units are called by the hardware.
For example, the functions of the above units may be stored in a memory in the form of program codes, which are scheduled by a processor to implement the functions of the above units. The Processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling programs. As another example, the above units may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more Digital Signal Processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), etc. For another example, in combination with the above two methods, part of the functions is implemented in the form of a scheduler code of the processor, and part of the functions is implemented in the form of a hardware integrated circuit. And when the above functions are integrated together, the functions can be realized in the form of a system-on-a-chip (SOC).
In yet another implementation, please refer to fig. 5, which is a schematic diagram of another vehicle control unit provided in an embodiment of the present application. As shown in fig. 5, the vehicle control unit includes a processor 510 and a memory 520, and the processor is configured to call a program stored in the memory to implement the driving mode self-learning control method.
Based on the same inventive concept, embodiments of the present application also provide a program product, such as a computer-readable storage medium, which includes program code, which, when invoked by a processor, causes the processor to implement the above method of driving pattern self-learning control.
Those skilled in the art will understand that: all or part of the steps of implementing the above method embodiments may be implemented by hardware related to program instructions, and the above program may be stored in a computer readable storage medium, where the program codes are called by a processor, and the processor is used to execute the methods executed by the VCU in the above method embodiments. The embodiment of the present application does not limit the form and number of the memory and the processor, for example, the memory may be a CPU or other processor capable of calling a program, and the memory may be various media capable of storing program codes, such as a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
The foregoing is only a partial embodiment of the present application, and it should be noted that, for those skilled in the art, several modifications and decorations can be made without departing from the principle of the present application, and these modifications and decorations should also be regarded as the protection scope of the present application.

Claims (12)

1. A driving pattern self-learning control method, the method comprising:
receiving a driving mode self-learning starting instruction;
within a preset self-learning duration, obtaining a statistical value of driving characteristic data, wherein the statistical value of the driving characteristic data comprises the following steps: the method comprises the following steps that N pieces of time length statistical information of accelerator opening intervals, interval statistical information of accelerator change rates, time length statistical information of vehicle speed intervals, turn-on times statistical information of steering lamps, times statistical information that steering wheel turning angles are larger than a preset angle, braking times statistical information and statistical information of master cylinder pressure during braking are obtained, wherein N is larger than 1;
and generating and storing a self-learning driving curve according to the driving characteristic data, wherein the self-learning driving curve is a mapping relation between torque and accelerator opening.
2. The method of claim 1, wherein the obtaining statistics of driving characteristic data comprises:
according to the throttle signals, counting time length statistical information of the multiple throttle opening intervals and interval statistical information of the throttle change rate;
according to the braking signals, counting to obtain the statistical information of the braking times;
acquiring a vehicle speed signal sent by an electronic stability system (ESC) controller, and counting to obtain duration statistical information of the vehicle speed interval;
acquiring a steering wheel corner signal sent by the ESC, and counting to obtain the number counting information that the steering wheel corner is larger than a preset angle;
obtaining a braking pressure signal sent by the ESC, and counting to obtain statistical information of master cylinder pressure during braking;
and obtaining a steering lamp signal sent by the BCM of the vehicle body controller, and counting to obtain the statistical information of the turn-on times of the steering lamp.
3. The method of claim 1, wherein after receiving the driving pattern self-learning turn-on command, the method further comprises:
and converting the current driving mode of the vehicle into a common mode, and performing self-learning in the common mode, wherein the common mode represents that the torque and the accelerator opening degree are in a linear relation.
4. The method according to claim 1, wherein the preset self-learning duration is at least 1 hour;
the duration of each accelerator opening interval is at least 1/N of the preset self-learning duration;
the turning-on times of the steering lamp is greater than a preset turning-on time threshold;
the braking times are larger than a preset braking time threshold.
5. The method of claim 1, further comprising:
and receiving the self-learning driving curve selection instruction, and outputting a torque demand signal corresponding to the self-learning driving curve to a motor controller MCU.
6. The method of any one of claims 1 to 5, wherein receiving a driving pattern self-learning turn-on command comprises:
and receiving the driving mode self-learning starting instruction sent by the user through the vehicle-mounted large screen controller.
7. A Vehicle Control Unit (VCU), comprising:
the receiving unit is used for receiving a driving mode self-learning starting instruction;
the processing unit is used for acquiring the statistical value of the driving characteristic data within the preset self-learning duration, wherein the statistical value of the driving characteristic data comprises the following steps: the method comprises the following steps that N pieces of time length statistical information of accelerator opening intervals, interval statistical information of accelerator change rates, time length statistical information of vehicle speed intervals, turn-on times statistical information of steering lamps, times statistical information that steering wheel turning angles are larger than a preset angle, braking times statistical information and statistical information of master cylinder pressure during braking are obtained, wherein N is larger than 1;
the processing unit is further used for generating and storing a self-learning driving curve according to the driving characteristic data, wherein the self-learning driving curve is a mapping relation between torque and accelerator opening.
8. The VCU of claim 7, wherein the processing unit is configured to:
according to the throttle signals, counting time length statistical information of the multiple throttle opening intervals and interval statistical information of the throttle change rate;
according to the braking signals, counting to obtain the statistical information of the braking times;
counting to obtain duration statistical information of the vehicle speed interval according to a vehicle speed signal received by the receiving unit and sent by an electronic stability system controller (ESC);
counting to obtain the number statistical information that the steering wheel corner is larger than a preset angle according to the steering wheel corner signal sent by the ESC and received by the receiving unit;
counting to obtain statistical information of master cylinder pressure during braking according to the braking pressure signal sent by the ESC and received by the receiving unit;
and counting to obtain the turn-on times counting information of the turn lights according to the turn light signals sent by the BCM of the vehicle body received by the receiving unit.
9. The VCU of claim 7, wherein after the receiving unit receives the driving mode self-learning enable instruction, the processing unit is further configured to:
and converting the current driving mode of the vehicle into a common mode, and performing self-learning in the common mode, wherein the common mode represents that the torque and the accelerator opening degree are in a linear relation.
10. The VCU of claim 7, wherein the predetermined self-learning duration is at least 1 hour;
the duration of each accelerator opening interval is at least 1/N of the preset self-learning duration;
the turning-on times of the steering lamp is greater than a preset turning-on time threshold;
the braking times are larger than a preset braking time threshold.
11. The VCU of claim 7, wherein the receiving unit is further configured to receive the self-learned driving curve selection command;
the VCU further comprises a transmitting unit, and the transmitting unit is used for outputting a torque demand signal corresponding to the self-learning driving curve to the motor controller MCU.
12. The VCU according to any one of claims 7 to 11, wherein the receiving unit is configured to: and receiving the driving mode self-learning starting instruction sent by the user through the vehicle-mounted large screen controller.
CN202011559424.3A 2020-12-25 2020-12-25 Driving mode self-learning control method and vehicle control unit Pending CN112550187A (en)

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