CN117681810B - A method, system, device and medium for adjusting the load rate of a vehicle controller - Google Patents

Abstract

The application provides a method, a system, equipment and a medium for adjusting the load rate of a vehicle controller, wherein the method comprises the following steps: after receiving a power-on signal of a vehicle, acquiring load rate related information of the vehicle and a target load rate corresponding to the load rate related information in real time; inputting the real-time acquired load factor related information into a load factor model to obtain a real-time preset load factor; when the real-time preset load rate is judged to be larger than the target load rate at the corresponding moment, obtaining a target fault signal total amount based on the target load rate obtained in real time, and adjusting the fault signal total amount reported to the whole vehicle controller to the target fault signal total amount so as to reduce the live load rate of the whole vehicle controller at the current moment to the target load rate; according to the scheme, when the VCU load rate is predicted to be too high, the total quantity of the read fault signals is timely reduced, so that the normal live load rate of the VCU is ensured, and the problem of resetting caused by overload of the VCU in the driving process is avoided.

Description

A method, system, device and medium for adjusting the load rate of a vehicle controller

Technical Field

The present application relates to the technical field of vehicle controllers, and in particular to a method, system, device, and medium for adjusting the load rate of a vehicle controller.

Background Art

As the functions of automotive electronic controllers continue to increase and the complexity of software continues to increase, the load rate of related tasks or cores has increased significantly. If the load rate exceeds a certain limit, certain tasks or functions in the automotive electronic controller will be executed less frequently or will never be executed, which will affect the vehicle's operating safety and endanger the personal safety of the driver and other personnel.

When multiple faults occur simultaneously in various controller components of current electric vehicles, or when the power controller area network (CAN) or chassis CAN is disconnected during driving, the diagnostic module in the vehicle control unit (VCU) will report multiple fault signals, which may cause the vehicle controller load rate to be too high and the VCU to reset, thereby causing a driving safety accident.

Summary of the invention

In view of the above-mentioned defects or deficiencies in the prior art, the present application aims to provide a method, system, device and medium for adjusting the load rate of a vehicle controller.

The first aspect of the present application provides a method for adjusting a load rate of a vehicle controller, comprising the following steps:

After receiving the vehicle power-on signal, the vehicle load rate related information and the target load rate corresponding to the load rate related information are obtained in real time; the load rate related information obtained in real time is input into the load rate model to obtain a real-time preset load rate; the load rate related information at least includes the total amount of fault signals, CAN line data frames, vehicle voltage, and driving mode;

When it is determined that the real-time preset load rate is greater than the target load rate at the corresponding moment, the target total amount of fault signals is obtained based on the target load rate obtained in real time, and the total amount of fault signals reported to the vehicle controller is adjusted to the target total amount of fault signals, so that the actual load rate of the vehicle controller at the current moment is reduced to the target load rate.

According to the technical solution provided in the embodiment of the present application, obtaining the target load rate corresponding to the load rate related information includes at least the following steps:

Determine the optimization goal and constraint conditions, and use the load rate related information as decision variables;

Under the optimization objective and constraints, based on the decision variables, the load rate of the vehicle controller is optimized to obtain the minimum load rate corresponding to the load rate related information, and the minimum load rate is used as the target load rate.

According to the technical solution provided in the embodiment of the present application, obtaining the target total amount of fault signals based on the target load rate obtained in real time includes at least the following steps:

The target load rate obtained in real time is substituted into the load rate model, and the CAN line data frame, vehicle voltage and driving mode obtained at the corresponding time are input into the load rate model to obtain the corresponding total amount of fault signals, which is used as the target total amount of fault signals.

According to the technical solution provided in the embodiment of the present application, real-time acquisition of vehicle load rate related information includes at least the following steps:

Acquire a number of calibration items corresponding to each fault signal and a calibration position of each calibration item, and read a calibration mark of each calibration position, wherein the calibration mark includes at least a first mark; the first mark is used to indicate that a fault exists in the calibration item at the calibration position;

Searching for the calibration item whose calibration position is the first mark, and generating a corresponding original fault signal for each calibration item whose calibration position is the first mark;

The sum of all the original fault signals is calculated, and the sum of all the original fault signals is used as the total amount of fault signals.

According to the technical solution provided in the embodiment of the present application, real-time acquisition of vehicle load rate related information also includes the following steps:

Acquire a first sample set, the first sample set including a plurality of groups of generator shaft speeds and a vehicle voltage corresponding to each group of the shaft speeds;

The shaft speed is used as an input of an initial model, and the vehicle voltage is used as an output of the initial model, and the initial model is trained to obtain a voltage model;

The real-time shaft speed of the generator is obtained, and the real-time shaft speed is input into the voltage model to obtain the real-time whole vehicle voltage.

According to the technical solution provided in the embodiment of the present application, the calibration mark further includes a second mark; the second mark is used to indicate that there is no fault in the calibration item of the calibration position;

Adjusting the total amount of the fault signals reported to the vehicle controller to the target total amount of fault signals comprises at least the following steps:

For each of the fault signals, a calibration item with a calibration position as a first identifier is set as a characteristic calibration item of the fault signal, and calibration items other than the characteristic calibration item are set as redundant calibration items of the fault signal;

The calibration identifiers of the calibration positions of the plurality of redundant calibration items are switched to the second identifiers.

According to the technical solution provided in the embodiment of the present application, adjusting the total amount of the fault signal reported to the vehicle controller to the target total amount of the fault signal includes at least the following steps:

The same original fault signals are searched, and a plurality of the same original fault signals are combined into one fault signal.

A second aspect of the present application provides a vehicle controller load rate adjustment system, comprising:

A calculation module, wherein the calculation module is configured to obtain, in real time, information related to the vehicle's load rate and a target load rate corresponding to the information related to the load rate after receiving a vehicle power-on signal; input the information related to the load rate obtained in real time into a load rate model to obtain a real-time preset load rate; the information related to the load rate at least includes a total amount of fault signals, a CAN line data frame, a whole vehicle voltage, and a driving mode;

The adjustment module is configured to determine that when the real-time preset load rate is greater than the target load rate at the corresponding moment, obtain a target total amount of fault signals based on the target load rate obtained in real time, and adjust the total amount of fault signals reported to the vehicle controller to the target total amount of fault signals, so that the actual load rate of the vehicle controller at the current moment is reduced to the target load rate.

The third aspect of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for adjusting the load rate of the vehicle controller as described above when executing the computer program.

A fourth aspect of the present application provides a computer-readable storage medium, which has a computer program. When the computer program is executed by a processor, the steps of the method for adjusting the load rate of the vehicle controller as described above are implemented.

Compared with the prior art, the beneficial effect of the present application is that: based on the vehicle's load rate related information, the present application predicts the VCU preset load rate at that moment through a load rate model, and compares the preset load rate with the target load rate at the corresponding moment. When the preset load rate is greater than the target load rate, it means that the predicted VCU load rate at that moment is at too high a risk. At this time, the corresponding target total amount of fault signals is calculated through the target load rate, and the total amount of fault signals reported by the CAN is reduced to the target total amount of fault signals. The corresponding total amount of fault signals read by the VCU is reduced, and the corresponding actual load rate of the VCU at the current moment also decreases accordingly. Therefore, the scheme predicts the load rate of the VCU through a model in advance. When the predicted preset load rate is too high, corresponding adjustments are made to keep the actual actual load rate of the VCU normal, thereby avoiding the problem of VCU overload and reset during driving, thereby improving the safety and stability of vehicle driving.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flowchart of a method for adjusting a vehicle controller load rate according to an embodiment of the present application;

FIG2 is a schematic diagram of the structure of a vehicle controller load rate adjustment system provided in an embodiment of the present application;

FIG3 is a schematic diagram of the structure of a terminal device provided in an embodiment of the present application.

DETAILED DESCRIPTION

The present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant inventions, rather than to limit the inventions. It should also be noted that, for ease of description, only the parts related to the invention are shown in the accompanying drawings.

It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

Example 1

As mentioned in the background technology, in view of the problems in the prior art, the present application proposes a method for adjusting the load rate of a vehicle controller, comprising the following steps:

S101, after receiving a vehicle power-on signal, obtaining in real time information related to the vehicle's load rate and a target load rate corresponding to the load rate related information; inputting the load rate related information obtained in real time into a load rate model to obtain a real-time preset load rate; the load rate related information at least includes a total amount of fault signals, a CAN line data frame, a vehicle voltage, and a driving mode;

Specifically, the load rate related information is information related to the load rate of the vehicle controller (VCU). According to previous research and development experience, the load rate of the VCU is related to the total amount of fault signals, CAN line data frames, vehicle voltage, and driving mode. Among them, the total amount of fault signals and CAN line data frames are reported by CAN for VCU to read. CAN will obtain the fault signals of each electronic controller. The driving mode can be read through the in-vehicle instrument. Further, each group of different total amount of fault signals, CAN line data frames, vehicle voltage, and driving mode corresponds to a target load rate of the VCU. When the load rate of the VCU is at the target load rate, it can ensure that the diagnostic module of the VCU is in a normal working state, thereby ensuring that the fault diagnosis results of the VCU for each electronic controller are accurate. Among them, the input of the load rate model is the total amount of fault signals, CAN line data frames, vehicle voltage, and driving mode, and the output is the preset load rate of the corresponding VCU. The preset load rate is the load rate of the VCU predicted by the model under the real-time total amount of fault signals, CAN line data frames, vehicle voltage, and driving mode.

Furthermore, the VCU diagnostic module will also be affected by the vehicle voltage and driving mode during the diagnostic process. For example, the vehicle voltage includes high voltage, low voltage, sleep mode, etc., and the fault triggering will be different under different types of voltages. The driving modes include economic driving, energy saving, and ejection mode. At this time, the vehicle speed, acceleration, torque, etc. are different, and the probability of communication loss is also different. Therefore, these two are also used as inputs to the load rate model to improve the accuracy of the target load rate.

S102. When it is determined that the real-time preset load rate is greater than the target load rate at the corresponding moment, a target total amount of fault signals is obtained based on the target load rate obtained in real time, and the total amount of fault signals reported to the vehicle controller is adjusted to the target total amount of fault signals, so that the actual load rate of the vehicle controller at the current moment is reduced to the target load rate.

Specifically, by default, when the total amount of fault signals is too large, the VCU will be overloaded, which is reflected in the preset load rate output by the load rate model, that is, the real-time preset load rate exceeds the target load rate at the corresponding moment, and there may be a risk of VCU overload at this moment. Among them, the preset load rate is a prediction of the VCU load rate at the current moment, and the actual load rate is the actual load rate of the VCU under the actual working conditions at the current moment.

Furthermore, the load rate model is constructed by BP neural network algorithm. The neural network is a network composed of three parts: input layer, hidden layer and output layer. The data from the input layer is processed by linear transformation of weight value and bias term, and then passes through the activation layer to obtain the output of the hidden layer, which is the input of the next layer; the data from the hidden layer to the output layer is processed by linear transformation of weight value and bias term, and then passes through the activation layer to obtain the output layer. This is forward propagation, and the error is back propagation. It can learn and store a large number of input-output mode mapping relationships without revealing the mathematical equations describing this mapping relationship in advance. Its learning rule is to use the steepest descent method to continuously adjust the weights and thresholds of the network through back propagation to minimize the sum of square errors of the network.

The input layer signal of the load rate model in this embodiment is the total amount of fault signals, CAN line data frames, vehicle voltage, and driving mode. The output layer signal is the load rate of the corresponding vehicle controller. The number of hidden layer nodes of the BP neural network is determined according to an empirical formula. Optionally, one hidden layer is used in this embodiment.

Specifically, the vehicle has several electronic controllers that implement various functions. When a certain type of fault occurs in an electronic controller, the fault signals corresponding to these faults will be reported through CAN. The VCU then reads these fault signals from CAN to determine which electronic controller has which type of fault. For a certain type of fault in an electronic controller, there are several fault signals. Therefore, if there are too many faults, there will also be too many corresponding fault signals, and there will also be too many fault signals stored in CAN for the VCU to read, which will lead to an excessively high load rate for the VCU.

Furthermore, the present application predicts a preset load rate (predicted, not real) of the VCU at a certain moment through a load rate model. When it is predicted that there may be an overload risk, the fault signals reported by the CAN are reduced, and the fault signals obtained by the CAN are reduced so that the total amount of the fault signals stored therein is reduced to the target total amount of fault signals. Accordingly, when the VCU reads the fault signals from the CAN, the total amount of fault signals read will be reduced, thereby ensuring that the actual load rate of the VCU under the actual working conditions at that moment remains normal (maintained at the target load rate), avoiding the problem of VCU overload and reset during driving, and improving the safety and stability of vehicle driving.

In an optional embodiment, obtaining the target load rate corresponding to the load rate related information comprises at least the following steps:

Determine the optimization goal and constraint conditions, and use the load rate related information as decision variables;

Under the optimization objective and constraints, based on the decision variables, the load rate of the vehicle controller is optimized to obtain the minimum load rate corresponding to the load rate related information, and the minimum load rate is used as the target load rate.

Specifically, the genetic algorithm target optimization is performed through the above neural network model to obtain the target load rate, the VCU load rate is used as the optimization target, the remaining power of the power battery (English: State of Charge, English abbreviation: SOC) maintenance range and the vehicle operating power are used as constraints, the SOC maintenance range is constrained to be no less than 25% of the total capacity of the power battery, and the vehicle operating power does not exceed 75% of the maximum power of the vehicle. The total amount of fault signals, CAN line data frames, vehicle voltage, and driving mode are used as decision variables to optimize the VCU load rate. The objective function is to obtain the minimum value of the VCU load rate. Through genetic algorithm target optimization, the minimum load rate corresponding to the total amount of fault signals and CAN line data frames at this moment is obtained, which is the target load rate.

This embodiment proposes a method for obtaining a target load rate by genetic algorithm target optimization, which can obtain the current total amount of fault signals and the target load rate corresponding to the CAN line data frame in real time and accurately, providing an accurate basis for subsequently obtaining the corresponding target total amount of fault signals and further adjusting the total amount of fault signals.

In an optional embodiment, obtaining a target total amount of fault signals based on the target load rate acquired in real time includes at least the following steps:

The target load rate obtained in real time is substituted into the load rate model, and the CAN line data frame, vehicle voltage and driving mode obtained at the corresponding time are input into the load rate model to obtain the corresponding total amount of fault signals, which is used as the target total amount of fault signals.

Specifically, after the current target load rate is found by using genetic algorithm target optimization, the load rate model constructed by the BP neural network algorithm is used, and the target load rate is used as the output layer signal of the load rate model, that is, the input layer signal of the load rate model is obtained by reverse deduction, and the total amount of fault signals in the input layer signal is the target total amount of fault signals.

This embodiment proposes a method based on an existing model (load rate model) to obtain the corresponding target total amount of fault signals by outputting and inferring the input, which can realize online calculation and real-time output of calculation results, and the calculation process is direct and highly operable.

In an optional embodiment, obtaining the vehicle load rate related information in real time includes at least the following steps:

Acquire a number of calibration items corresponding to each fault signal and a calibration position of each calibration item, and read a calibration mark of each calibration position, wherein the calibration mark includes at least a first mark; the first mark is used to indicate that a fault exists in the calibration item at the calibration position;

Searching for the calibration item whose calibration position is the first mark, and generating a corresponding original fault signal for each calibration item whose calibration position is the first mark;

The sum of all the original fault signals is calculated, and the sum of all the original fault signals is used as the total amount of fault signals.

Specifically, each fault signal corresponds to several calibration items. For example, when the electronic stability controller (ESC) fails, there may be fault signals corresponding to calibration items such as ESC122 frame communication loss fault, ESC2A3 frame communication loss fault, ESC252 frame communication loss fault, ESC142 frame communication loss fault, and ESC232 frame communication loss fault. These calibration items have their own calibration positions. When the ESC122 frame communication is lost, at its corresponding calibration position, its calibration identifier is the first identifier, and the first identifier is marked 1 at the corresponding calibration position. As long as the calibration item at the calibration position is marked 1, a corresponding original fault signal will be generated. These original fault signals are obtained through CAN and reported to the VCU. The total amount of original fault signals reported by CAN is the total amount of fault signals.

Specifically, each calibration item with the calibration position as the first identifier will generate an original fault signal. Therefore, the total amount of the original fault signals stored in the CAN and reported to the VCU at a certain moment is the total amount of fault signals at the current moment. The total amount of fault signals is also sent to the CAN, so that the VCU can read the total amount of fault signals at the same time as reading the fault signals, thereby achieving synchronization of data acquisition.

This embodiment provides a method for obtaining the total amount of fault signals, which can effectively and accurately calibrate the faults existing in the in-vehicle controller for CAN to obtain and report.

In an optional embodiment, obtaining the vehicle load rate related information in real time further includes the following steps:

Acquire a first sample set, the first sample set including a plurality of groups of generator shaft speeds and a vehicle voltage corresponding to each group of the shaft speeds;

The shaft speed is used as an input of an initial model, and the vehicle voltage is used as an output of the initial model, and the initial model is trained to obtain a voltage model;

The real-time shaft speed of the generator is obtained, and the real-time shaft speed is input into the voltage model to obtain the real-time whole vehicle voltage.

Specifically, the vehicle voltage can be understood as the output voltage of the generator. The speed of the generator can be measured by a speed sensor provided on the generator, and then the speed is converted into voltage. The conversion process can be realized by a voltage model. The input of the voltage model is the generator speed, and the output is the vehicle voltage.

This embodiment provides a method for effectively obtaining the voltage of the entire vehicle for use in predicting the preset load rate of the VCU, which is simple to use and highly operable.

In an optional embodiment, the calibration mark further includes a second mark; the second mark is used to indicate that there is no fault in the calibration item of the calibration position;

Adjusting the total amount of the fault signals reported to the vehicle controller to the target total amount of fault signals comprises at least the following steps:

For each of the fault signals, a calibration item with a calibration position as a first identifier is set as a characteristic calibration item of the fault signal, and calibration items other than the characteristic calibration item are set as redundant calibration items of the fault signal;

The calibration identifiers of the calibration positions of the plurality of redundant calibration items are switched to the second identifiers.

Specifically, the second mark is to mark 0 at the corresponding calibration position.

Further, for a certain fault signal, such as an ESC controller fault signal, there are ESC122 frame communication calibration items, ESC2A3 frame communication calibration items, ESC252 frame communication calibration items, ESC142 frame communication calibration items, and ESC232 frame communication calibration items. The ESC controller fault signal corresponds to 5 calibration items, and there are 5 corresponding calibration positions. Each calibration position has a calibration identifier. The calibration identifier of the calibration position corresponding to the frame in which the fault originally occurred is set to the first identifier (i.e. 1). If there is a fault in more than one frame (for example, 3 frames), then If the calibration marks of three calibration positions are 1, then three original fault signals (actually the same) will be generated accordingly, and the total amount of fault signals will be large. However, in this embodiment, any one of the calibration marks of the calibration position marked 1 is used as a characteristic calibration item, and the other two are used as redundant calibration items. The calibration marks of the redundant calibration items are set to the second mark (i.e. 0). In this way, only one original fault signal is generated for the ESC controller fault signal, which reduces the total amount of fault signals. Thus, the purpose of reducing the total amount of fault signals read by the VCU is achieved without affecting the accuracy of the VCU fault judgment.

In an optional embodiment, adjusting the total amount of the fault signals reported to the vehicle controller to the target total amount of fault signals comprises at least the following steps:

The same original fault signals are searched, and a plurality of the same original fault signals are combined into one fault signal.

In addition to the above-mentioned method of switching the calibration identifier of the calibration position of the redundant calibration item to the second identifier, the present embodiment provides another more direct method of reducing the total amount of fault signals. Taking the ESC controller fault signal as an example, since the calibration positions corresponding to the ESC122 frame communication calibration item, the ESC2A3 frame communication calibration item, the ESC252 frame communication calibration item, the ESC142 frame communication calibration item, and the ESC232 frame communication calibration item are the first identifier, and all report the same original fault signal through CAN, then the same original fault signal can be directly synthesized into one. Furthermore, traditionally speaking, when CAN recognizes a calibration item with a calibration position as the first identifier, it will generate an original fault signal in real time. In fact, the faults calibrated by many calibration items are the same. At this time, reading and merging the original fault signals calibrated with the same fault at any time can effectively reduce the number of generated fault signals, so as to achieve the purpose of adjusting the total amount of fault signals to the target total amount of fault signals.

Furthermore, the two adjustment methods may be mixed or used alone, depending on the specific situation, as long as the total amount of fault signals is reduced to the target total amount of fault signals.

This embodiment provides another more direct method for reducing the total amount of CAN reported fault signals, which can be mixed with the above method or used alone, improving the feasibility and diversity of the process of adjusting the total amount of fault signals, so as to achieve the effect of reducing the total amount of fault signals more quickly and in real time, thereby reducing the load rate of the vehicle controller more quickly and avoiding the risk of VCU overload.

Example 2

Please refer to FIG. 2 , the present embodiment provides a vehicle controller load rate adjustment system, including:

A calculation module, wherein the calculation module is configured to obtain, in real time, information related to the vehicle's load rate and a target load rate corresponding to the information related to the load rate after receiving a vehicle power-on signal; input the information related to the load rate obtained in real time into a load rate model to obtain a real-time preset load rate; the information related to the load rate at least includes a total amount of fault signals, a CAN line data frame, a whole vehicle voltage, and a driving mode;

The adjustment module is configured to determine that when the real-time preset load rate is greater than the target load rate at the corresponding moment, obtain a target total amount of fault signals based on the target load rate obtained in real time, and adjust the total amount of fault signals reported to the vehicle controller to the target total amount of fault signals, so that the actual load rate of the vehicle controller at the current moment is reduced to the target load rate.

Example 3

Please refer to FIG. 3 , the computer system 600 of the terminal device includes a CPU (central processing unit) 601, which can perform various appropriate actions and processes according to the program stored in the ROM (read-only memory) 602 or the program loaded from the storage part 608 to the RAM (random access memory) 603. In the RAM 603, various programs and data required for system operation are also stored. The CPU 601, the ROM 602 and the RAM 603 are connected to each other through the bus 604. The I/O (input/output) interface 605 is also connected to the bus 604. The following components are connected to the I/O interface 605: an input part 606 including a keyboard, a mouse, etc.; an output part 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage part 608 including a hard disk, etc.; and a communication part 609 including a network interface card such as a LAN card, a modem, etc. The communication part 609 performs communication processing via a network such as the Internet. A drive is also connected to the I/O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 610 as needed, so that a computer program read therefrom is installed into the storage section 608 as needed.

In particular, according to an embodiment of the present application, the process described above with reference to flowchart 1 can be implemented as a computer software program. For example, embodiment 1 of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part, and/or installed from a removable medium. When the computer program is executed by CPU 601, the above-mentioned functions defined in the present computer system 600 are executed.

It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

The flowchart and block diagram in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the method, system and computer program product according to embodiment 1 and embodiment 2 of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

The units involved in the embodiments of the present application may be implemented by software or hardware, and the units described may also be provided in a processor. The names of these units do not, in some cases, limit the units themselves. The units or modules described may also be provided in a processor, for example, they may be described as: a processor includes a computing module and an adjustment module. The names of these units or modules do not, in some cases, limit the units or modules themselves, for example, the computing module may also be described as "a computing module for obtaining, in real time, an instance of information related to the vehicle's load rate after receiving a vehicle power-on signal."

Example 4

As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method for adjusting the load rate of the vehicle controller as described in the above embodiment.

For example, the electronic device can implement as shown in Figure 1: S101, after receiving the vehicle power-on signal, obtain the vehicle's load rate related information and the target load rate corresponding to the load rate related information in real time; input the load rate related information obtained in real time into the load rate model to obtain a real-time preset load rate; the load rate related information at least includes the total amount of fault signals, CAN line data frames, vehicle voltage, and driving mode; S102, when it is determined that the real-time preset load rate is greater than the target load rate at the corresponding moment, based on the target load rate obtained in real time, obtain the target total amount of fault signals, and adjust the total amount of fault signals reported to the vehicle controller to the target total amount of fault signals, so that the actual load rate of the vehicle controller at the current moment is reduced to the target load rate. For another example, the electronic device can implement the various steps described in this application.

It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments disclosed in the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

In addition, although the steps of the method in the present application are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and/or one step may be decomposed into multiple steps, etc.

Through the description of the above implementations, those skilled in the art can easily understand that the example implementations described here can be implemented by software, or by combining software with necessary hardware.

The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of application involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the concept of the application. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other.

Claims (10)

1. A method for adjusting the load rate of a vehicle controller, characterized in that it comprises the following steps: After receiving the vehicle power-on signal, the vehicle load rate related information and the target load rate corresponding to the load rate related information are obtained in real time; the load rate related information obtained in real time is input into the load rate model to obtain a real-time preset load rate; the load rate related information at least includes the total amount of fault signals, CAN line data frames, vehicle voltage, and driving mode; When it is determined that the preset load rate is greater than the target load rate at the corresponding moment, the target total amount of fault signals is obtained based on the target load rate, and the total amount of fault signals reported to the vehicle controller is adjusted to the target total amount of fault signals, so that the actual load rate of the vehicle controller at the current moment is reduced to the target load rate. 2. The method for adjusting the load rate of a vehicle controller according to claim 1, characterized in that obtaining the target load rate corresponding to the load rate related information comprises at least the following steps: Determine the optimization goal and constraint conditions, and use the load rate related information as decision variables; Under the optimization objective and constraints, based on the decision variables, the load rate of the vehicle controller is optimized to obtain the minimum load rate corresponding to the load rate related information, and the minimum load rate is used as the target load rate corresponding to the load rate related information. 3. The method for adjusting the load rate of a vehicle controller according to claim 1, characterized in that: obtaining a target total amount of fault signals based on the target load rate obtained in real time, at least comprises the following steps: The target load rate obtained in real time is substituted into the load rate model, and the CAN line data frame, vehicle voltage and driving mode obtained at the corresponding time are input into the load rate model to obtain the corresponding total amount of fault signals, which is used as the target total amount of fault signals. 4. The method for adjusting the load rate of a vehicle controller according to claim 1 is characterized in that: obtaining the vehicle load rate related information in real time comprises at least the following steps: Acquire a number of calibration items corresponding to each fault signal and a calibration position of each calibration item, and read a calibration mark of each calibration position, wherein the calibration mark includes at least a first mark; the first mark is used to indicate that a fault exists in the calibration item at the calibration position; Searching for the calibration item whose calibration position is the first mark, and generating a corresponding original fault signal for each calibration item whose calibration position is the first mark; The sum of all the original fault signals is calculated, and the sum of all the original fault signals is used as the total amount of fault signals. 5. The method for adjusting the load rate of a vehicle controller according to claim 1 is characterized in that: the vehicle load rate related information is obtained in real time, and further comprising the following steps: Acquire a first sample set, the first sample set including a plurality of groups of generator shaft speeds and a vehicle voltage corresponding to each group of the shaft speeds; The shaft speed is used as an input of an initial model, and the vehicle voltage is used as an output of the initial model, and the initial model is trained to obtain a voltage model; The real-time shaft speed of the generator is obtained, and the real-time shaft speed is input into the voltage model to obtain the real-time whole vehicle voltage. 6. The method for adjusting the load rate of a vehicle controller according to claim 4, characterized in that: the calibration mark further includes a second mark; the second mark is used to indicate that there is no fault in the calibration item of the calibration position; Adjusting the total amount of the fault signals reported to the vehicle controller to the target total amount of fault signals comprises at least the following steps: For each of the fault signals, a calibration item with a calibration position as a first identifier is set as a characteristic calibration item of the fault signal, and calibration items other than the characteristic calibration item are set as redundant calibration items of the fault signal; The calibration identifiers of the calibration positions of the plurality of redundant calibration items are switched to the second identifiers. 7. The method for adjusting the load rate of a vehicle controller according to claim 4, characterized in that: adjusting the total amount of the fault signals reported to the vehicle controller to the target total amount of fault signals comprises at least the following steps: The same original fault signals are searched, and a plurality of the same original fault signals are combined into one fault signal. 8. A vehicle controller load rate adjustment system, characterized in that it includes: A calculation module, wherein the calculation module is configured to obtain, in real time, information related to the vehicle's load rate and a target load rate corresponding to the information related to the load rate after receiving a vehicle power-on signal; input the information related to the load rate obtained in real time into a load rate model to obtain a real-time preset load rate; the information related to the load rate at least includes a total amount of fault signals, a CAN line data frame, a whole vehicle voltage, and a driving mode; The adjustment module is configured to determine that when the preset load rate is greater than the target load rate at the corresponding moment, obtain a target total amount of fault signals based on the target load rate, and adjust the total amount of fault signals reported to the vehicle controller to the target total amount of fault signals, so that the actual load rate of the vehicle controller at the current moment is reduced to the target load rate. 9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for adjusting the load rate of a vehicle controller as described in any one of claims 1 to 7 when executing the computer program. 10. A computer-readable storage medium, wherein the computer-readable storage medium has a computer program, wherein when the computer program is executed by a processor, the computer program implements the steps of the method for adjusting the load rate of a vehicle controller as described in any one of claims 1 to 7.