Method for adaptively updating signal data used in bus simulation and testing process

Abstract

To provide a method for adaptively updating signal data and an adaptive updating system in vehicle software development.SOLUTION: The method creates the mapping relationship between a source signal and a target signal by storing a mapping expression, mapping parameters, or parameters of the mapping expression in a single mapping-execution container and by activating the mapping relationship through setting the execution switch of the mapping-execution container to an ON state, realizes adaptive updating of signal data. The method sets mapping parameters when the mapping expression is set as linear, and sets parameters of the mapping expression when the mapping expression is set as nonlinear.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] This application claims priority from Chinese Patent Application No. 202410073686.0 filed on January 18, 2024, the entire contents of which are hereby incorporated by reference.

[0002] The present invention relates to the field of vehicle software development, and more particularly to an adaptive update method for signal data used in bus simulation and testing processes. [Background technology]

[0003] During bus simulation and testing using bus tools, it is necessary to constantly perform real-time processing on received bus signals to create the necessary virtual signals. In the vehicle software development process, virtual signals are signals that do not exist in the measurement data and are set by artificial logic. For example, signals obtained through real-time processing, such as bus load rate signals, peak load rate signals, frame rate signals, and signal A and B values, and signals obtained by sum, addition, subtraction, multiplication, division, absolute value, arccosine, arctangent, cosine, power / square root, logarithm, maximum / minimum value, sine, and tangent, are all virtual signals. These virtual signals can be used to complete subsequent bus simulation and test data analysis requirements.

[0004] However, none of the related bus tools have a direct solution for performing real-time processing on bus signals to construct the required virtual signals. The main business function of a bus tool is to collect and transmit bus signals, and its functional scope does not cover the virtual and real-time calculation functions of abstract information. If real-time processing scripts are added to the bus tool to construct the required virtual signals, the script and parameter configuration will become very complicated due to the variety of signal types, occupying system resources and affecting the real-time performance of bus signal processing, thereby affecting the efficiency of bus simulation and testing.

[0005] SUMMARY OF THE INVENTION It is an object of the present invention to provide a method for adaptively updating signal data used in bus simulation and testing processes.

[0006] To solve the above technical problems, the present invention provides a signal data adaptive updating method, which includes: In step S101, the mapping equation between the source signal and the target signal is set to be linear, and mapping parameters including the mapping amplification factor, the offset amount, and the mapping direction are set. Alternatively, the mapping equation between the source signal and the target signal is nonlinear, and the parameters of the mapping equation are set. Setting the parameters of the mapping formula includes: Based on the number n of source signals, we create independent variables x1, x2...xn. Set the mapping formula y=f(x1,x2...xn). Each independent variable is related to a signal or equation result y in the system. In step S102, the mapping formula, the mapping parameter or the parameter of the mapping formula is stored in a mapping execution container to create a mapping relationship between the source signal and the target signal, and the mapping relationship is activated to realize adaptive updating of the signal data.

[0007] The beneficial effects of the present invention are as follows: The method for adaptively updating signal data of the present invention does not require a user to write a program for specially processing bus signals, and can realize real-time processing of bus signals simply by using a mapping formula, thereby solving the problem that it is difficult to update virtual signals required for bus simulation and testing in real time, and improving the efficiency of bus simulation and testing.

[0008] Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and obtained by the structure particularly pointed out in the description and drawings.

[0009] In order to make the above objects, features and advantages of the present invention more comprehensible, the following preferred embodiments will be described in detail in conjunction with the accompanying drawings. [Brief explanation of the drawings]

[0010] In order to more clearly describe the specific embodiments of the present invention or the technical solutions of the prior art, the following will briefly describe the drawings that need to be used to describe the specific embodiments or the prior art. The drawings described in the following description are some embodiments of the present invention, and it is obvious that those skilled in the art can obtain other drawings from these drawings without any creative efforts. [Figure 1] 1 is a flowchart of a method for adaptively updating signal data according to some embodiments. [Figure 2] FIG. 1 illustrates an example method for adaptively updating signal data according to some embodiments. [Figure 3] FIG. 1 illustrates an example method for adaptively updating signal data according to some embodiments. [Figure 4] FIG. 1 illustrates an example method for adaptively updating signal data according to some embodiments. [Figure 5] 1 is a principle block diagram of a system for adaptively updating signal data according to some embodiments; [Figure 6] FIG. 1 is a principle block diagram of an electronic device according to some embodiments. [Figure 7] FIG. 1 is a principle block diagram of an electronic device according to some embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0011] In order to clarify the objectives, technical aspects and advantages of the embodiments of the present invention, the technical aspects of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. However, it is clear that the described embodiments are only some of the embodiments of the present invention and do not represent all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without performing creative work fall within the scope of protection of the invention.

[0012] During bus simulation and testing using bus tools, it is necessary to constantly perform real-time processing on received bus signals to create the necessary virtual signals. In the vehicle software development process, virtual signals are signals that do not exist in the measurement data and are set by artificial logic. For example, signals obtained through real-time processing, such as bus load rate signals, peak load rate signals, frame rate signals, and signal A + signal B values, and signals obtained by sum, addition, subtraction, multiplication, division, absolute value, arccosine, arctangent, cosine, power / square root, logarithm, maximum / minimum value, sine, and tangent, are all virtual signals. These virtual signals can be used to complete subsequent bus simulation and test data analysis requirements.

[0013] However, none of the related bus tools provide a direct solution for performing real-time processing on bus signals to create the required virtual signals. The main business function of a bus tool is to collect and transmit bus signals, and its functional scope does not cover the virtual and real-time calculation functions of abstract information. Therefore, if real-time processing scripts are added to a bus tool to create the required virtual signals, the script and parameter configurations become very complicated due to the variety of signal types, occupying system resources and affecting the real-time performance of bus signal processing, thereby affecting the efficiency of bus simulation and testing.

[0014] Therefore, at least one embodiment provides a signal data adaptive update method that achieves the objective of real-time processing of bus signals using only a mapping formula and further meets the requirements for adaptive update of signal data. Specifically, the method can include the following steps: In step S101, the mapping equation between the source signal and the target signal is set to be linear, and mapping parameters including the mapping amplification factor, the offset amount, and the mapping direction are set. Alternatively, the mapping equation between the source signal and the target signal is nonlinear, and the parameters of the mapping equation are set. Setting the parameters of the mapping formula includes: Based on the number n of source signals, we create independent variables x1, x2...xn. Set the mapping formula y=f(x1,x2...xn). Each independent variable is related to a signal or equation result y in the system. In step S102, the mapping formula, mapping parameters or parameters of the mapping formula are stored in a mapping execution container to create a mapping relationship between the source signal and the target signal, and the mapping relationship is activated to realize adaptive updating of the signal data.

[0015] According to the adaptive update method for signal data of the present invention, users do not need to write programs to process bus signals specifically, but can realize real-time processing for bus signals by simply using the mapping formula. These processing include: (1) Performing a mathematical operation on two or more bus signal values, such as addition, subtraction, multiplication, or division. (2) Draw a curve based on the result signal calculated in the previous step. (3) The calculation result of the previous step is detected by the logical configuration. This solves the problem that it is difficult to update virtual signals required for bus simulation and testing in real time, thereby improving the efficiency of bus simulation and testing.

[0016] The following describes an example of how to process bus signals in this adaptive signal data update method. During the testing process of an automobile chassis, it is necessary to verify whether the ABS function triggers during the entire braking process when the vehicle speed is above 50 kph and the master cylinder pressure is above 80 bar. Using a conventional testing method, a script must be created to track the test, and three signal data must be collated: vehicle speed V, master cylinder pressure M, and ABS trigger flag A. Using this signal data adaptive update method, the following steps can be used: 1. Establish the formula y=(x1>50)&(x2>80)&(x3=1). x1 is the vehicle speed signal data V, x2 is the master cylinder pressure signal data M, and x3 is the ABS trigger flag A. y indicates a new flag R when the vehicle speed is higher than 50 kph, the master cylinder pressure is higher than 80 bar, and the ABS trigger flag is activated. The activation of this flag indicates that three signals are activated simultaneously. Therefore, the signal data of the new flag R can be determined. 2. Drag the new flag R from the signal list in the system to the graphic window of the car bus tool, and the graphic window will automatically draw a signal data curve showing the new flag R. 3. Use the signal detection function provided by the car bus tool to detect whether the new flag R signal data jumps from 0 to 1 during the test process. As can be seen from the above example, the adaptive update method for signal data does not require writing a single line of processing code, improving the efficiency of test verification.

[0017] Various non-limiting embodiments of examples of the present disclosure will now be described in detail with reference to the accompanying drawings. As shown in Figure 1, some embodiments provide a method for adaptively updating signal data. The method includes: In step S101, the mapping equation between the source signal and the target signal is set to be linear, and mapping parameters including the mapping amplification factor, the offset amount, and the mapping direction are set. Alternatively, the mapping equation between the source signal and the target signal is nonlinear, and the parameters of the mapping equation are set. Setting the parameters of the mapping formula (steps) includes: Based on the number n of source signals, we create independent variables x1, x2...xn. Set the mapping formula y=f(x1,x2...xn). Each independent variable is related to a signal or equation result y in the system. In step S102, the mapping formula, mapping parameters or parameters of the mapping formula are stored in a mapping execution container to create a mapping relationship between the source signal and the target signal, and the mapping relationship is activated to realize adaptive updating of the signal data. Specifically, a mapping execution container is a container that stores and executes mapping, and has the following functions: 1) It can store mapping formulas and mapping parameters in lists; 2) It can introduce and derive lists that store mapping formulas and mapping parameters; and 3) It can automatically execute mapping relationships, mapping source signals to target signals, or mapping target signals to source signals, or realizing bidirectional mapping.

[0018] In some embodiments, the mapping equation between the source signal and the target signal is set to be linear, ie, the mapping equation y=x. If the mapping equation between the source signal and the target signal is nonlinear, i.e., the mapping equation y is not equal to x, where x is the source signal, which may be a received bus signal or a system variable in the bus tool system. The system variable may be a variable already present in the bus tool system or a virtual signal generated by bus signal mapping. y is the target signal, which is a mapping system variable for the source signal created by the local computer. The mapping system variable is the calculation result of the equation and can also participate in the arithmetic and logic operation of the equation.

[0019] Hereinafter, the steps of setting the mapping amplification factor, offset amount, and mapping direction when setting the mapping equation y=x will be described in detail using an example. Suppose that in a functional test of an automobile ESC system, it is necessary to monitor a vehicle speed signal and use the value of the vehicle speed signal for various test conditions. Therefore, we need to create a one-way mapping from the vehicle speed CAN signal to the mapping system variable "VehicleSpeed". That is, we set the mapping equation y=x, where y is the mapping system variable "VehicleSpeed". x is the vehicle speed CAN signal, for example "0 / CAN_FD_ESC / ESC / ESCData / VehSpd", which means channel 1, CAN network CAN_FD_ESC, ESC node, ESCData message, and VehSpd signal. Based on this mapping formula, three mapping parameters can be set: the mapping amplification factor a, the offset amount δ, and the mapping direction. In this example, the mapping direction is fixed from the CAN signal to the mapping system variable, and the actual value of the mapping system variable "VehicleSpeed" is VehicleSpeed=a*VehSpd+δ. When the units of the mapping system variable VehicleSpeed ​​and the speed CAN signal VehSpd are both "km / h" or "m / s", a=1 and δ=0. If the unit of the mapping system variable VehicleSpeed ​​is "km / h" and the unit of the CAN signal VehSpd is "m / s", then a=3.6 and δ=0, thereby ensuring the unity of the two variable physical quantities. If the unit of the mapping system variable VehicleSpeed ​​is "m / s" and the unit of the CAN signal VehSpd is "km / h", then a=1 / 3.6 and δ=0, thereby ensuring the unity of the two variable physical quantities.

[0020] An example of configuring the parameters of the mapping equation when the mapping equation y is not equal to x will be described in detail below. In a functional test of an automobile ESC system, it is assumed that when the vehicle speed is in the 40km / h to 60km / h range and the ESC function is on, it is necessary to check whether another specific flag is on. In this case, a mapping formula is required that is configured depending on the vehicle speed signal and the ESC function on signal. y=(x1>40)&(x1<60)&x2 Here, y indicates that the vehicle speed is in the 40km / h to 60km / h range and the ESC function is on flag, x1 indicates the vehicle speed CAN signal, and x2 indicates the ESC function on flag CAN signal. The symbol ">" indicates a greater logic value, the symbol ">" indicates a lesser logic value, the symbol ">" indicates a logical AND, and the obtained result y is also a logical value, either True or False. Based on the mapping formula, mapping parameters need to be set, i.e., the mapping relationship between the x1 and x2 independent variables in the mapping formula is configured. In this example, x1 can be associated with "0 / CAN_FD_ESC / ESC / ESCData / VehSpd", which means channel 1, CAN network CAN_FD_ESC, ESC node, ESCData message, and VehSpd signal. x2 can be associated with "0 / CAN_FD_ESC / ESC / ESCData / ESCActv", which means channel 1, CAN network CAN_FD_ESC, ESC node, ESCData message, and ESCActv signal. When the vehicle speed is 50 km / h and the ESC function is on, the formulas give x1=50, x2=True, and finally y=True, meaning that the condition that the vehicle speed is in the 40km / h to 60km / h range and the ESC function is on is met.When the vehicle speed is 70 km / h and the ESC function is not on, the formulas give x1=70, x2=False, and finally y=False, meaning that the condition that the vehicle speed is in the 40km / h to 60km / h range and the ESC function is on is not met.

[0021] In some embodiments, the mapping direction includes one-way mapping and two-way mapping. The one-way mapping includes mapping from a source signal to a target signal and mapping from a target signal to a source signal. The bidirectional mapping involves mapping the source signal to the target signal and simultaneously mapping the target signal to the source signal. When there is only output or only input, it is a unidirectional mapping. For example, when there is only output, it is as follows: When it is necessary to output a voltage signal or a current signal to drive an external device, the unidirectional mapping direction is to map from the target signal to the source signal, where the target signal is a mapping system variable carrying control information, and the source signal is a CAN signal representing voltage or current control information. When there is only input, it is as follows: When it is necessary to monitor an external voltage or current signal, to draw a curve, or to perform related test judgment, it is as follows: When there is a need to monitor an external voltage or current signal, the unidirectional mapping direction is to map from the source signal to the target signal, where the source signal is a monitoring CAN signal representing the external voltage or current, and the target signal is the corresponding mapping system variable. Bidirectional mapping is used when both input and output are required. For example, if the maximum value signal of the solenoid valve current is output, the BASS tool can modify the mapping system variable i corresponding to the maximum value, for example, reset it to 0. For input, it can be used to monitor the region peak value of the solenoid valve current. For example, when a test case starts, the BASS tool writes the reset value 0 to the mapping system variable i, clears the previous test result, and starts a new round of current peak monitoring. During the test case operation, the BASS tool cyclically reads the mapping system variable i and monitors the current round's current peak value in real time.

[0022] In some embodiments, when mapping from a source signal to a target signal, the target signal value is calculated as follows: Mz=Yz*a+δ When mapping from a target signal to a source signal, the source signal value is calculated as follows: Yz=(Mz-δ) / a where Mz is the value of the target signal, Yz is the value of the source signal, a is the mapping amplification factor, and δ is the offset.

[0023] Hereinafter, the calculation process of the target signal value when mapping from the source signal to the target signal, and the calculation process of the source signal value when mapping from the target signal to the source signal will be described in detail using examples. In the process of reading and writing the solenoid valve current maximum value signal, the target signal is set as the corresponding mapping system variable i, with the unit being amperes (A), and the source signal is the solenoid valve current maximum value signal CurrMax of the automobile ECU, with the unit being milliamperes (mA). A bidirectional mapping must be created to map the source signal to the target signal and vice versa. When the mapping direction is mapping from the source signal to the target signal, the calculation formula for the target signal value is as follows: i=CurrMax*a+δ where i is the value of the mapping system variable of the target signal, CurrMax is the value of the source signal from the CAN bus, a=0.001, δ=0. When the mapping direction is from the target signal to the source signal, the calculation formula for the source signal value is as follows: CurrMax=(i-δ) / a where i is the value of the mapping system variable for the target signal, CurrMax is the value of the source signal from the CAN bus, a=0.001, δ=0.

[0024] In some embodiments, the mapping equation is such that if y is not equal to x, configuring the parameters of the mapping equation includes: Based on the number n of source signals, we create independent variables x1, x2...xn. Set the mapping formula y=f(x1,x2...xn). Each independent variable is related to a signal or equation result y in the system.

[0025] In the following, we will explain in detail how to configure the parameters of the mapping equation when the mapping equation y is not equal to x in one example. In a functional test of an automobile ESC system, it is assumed that when the vehicle speed is in the 40km / h to 60km / h range and the ESC function is on, it is necessary to check whether another specific flag is on. In this case, a mapping formula is required that is configured depending on the vehicle speed signal and the ESC function on signal. y=(x1>40)&(x1<60)&x2 Here, y indicates that the vehicle speed is in the 40km / h to 60km / h range and the ESC function is on flag, x1 indicates the vehicle speed CAN signal, and x2 indicates the ESC function on flag CAN signal. The symbol ">" indicates a greater logic value, the symbol ">" indicates a lesser logic value, and the symbol ">" indicates a logical product. The resulting result y is also a logical value, either True or False. Based on the mapping formula, mapping parameters must be set. That is, the mapping relationship between the x1 and x2 independent variables in the mapping formula is configured. In this example, x1 can be associated with "0 / CAN_FD_ESC / ESC / ESCData / VehSpd", which means channel 1, CAN network CAN_FD_ESC, ESC node, ESCData message, and VehSpd signal. x2 can be associated with "0 / CAN_FD_ESC / ESC / ESCData / ESCActv", which means channel 1, CAN network CAN_FD_ESC, ESC node, ESCData message, and ESCActv signal. If the vehicle speed is 50 km / h and the ESC function is on, then the formulas give x1 = 50, x2 = True, and finally y = True, meaning that the conditions are met that the vehicle speed is in the 40 km / h to 60 km / h range and the ESC function is on.If the vehicle speed is 70 km / h and the ESC function is not on, then the formulas give x1 = 70, x2 = False, and finally y = False, meaning that the conditions are met that the vehicle speed is in the 40 km / h to 60 km / h range and the ESC function is on.

[0026] In some embodiments, the signals in the system include one or more of bus signals, mapping system variables, constants, and immediate values.

[0027] In some embodiments, storing the mapping formula and mapping parameters in one mapping execution container to create a mapping relationship between the source signal and the target signal (step) includes: storing a, δ, a type value of the mapping direction, and Mz=Yz*a+δ in the mapping execution container.

[0028] The following provides an example to explain in detail the steps of storing the mapping formula and mapping parameters in the mapping execution container to create the mapping relationship between the source signal and the target signal. In the process of monitoring the ECU power supply voltage, the target signal is set as a mapping system variable v corresponding to the ECU power supply voltage, with the unit being volts (V), and the source signal is the vehicle ECU power supply voltage VMon, with the unit being millivolts (mV). A one-way mapping needs to be created from the source signal to the target signal. The formula for calculating the target signal value is as follows: v=VMon*a+δ Here, a=0.001, δ=0.

[0029] To create a one-way mapping from the source signal to the target signal, the above mapping equation and mapping parameters need to be stored as a record in the mapping execution container, and the contents of this record are as follows: (1) a = 0.001 (2) δ = 0 (3) Shift direction type value = source signal to destination signal (4) The formula for the target signal value: v = VMon * a + δ

[0030] Storing the mapping formula, mapping parameters in a mapping execution container to create a mapping relationship between the source signal and the target signal (steps) includes: Store a, δ, the type value of the mapping direction, and Yz=(Mz-δ) / a in the mapping execution container.

[0031] The following provides an example to explain in detail the steps of storing the mapping formula and mapping parameters in the mapping execution container to create the mapping relationship between the source signal and the target signal. In the process of controlling the ECU solenoid valve driving current, the target signal is set as the mapping system variable i corresponding to the ECU solenoid valve driving current, with the unit being amperes (A), and the source signal is the automobile ECU solenoid valve driving current iDrv, with the unit being milliamperes (mA). A one-way mapping from the target signal to the source signal needs to be created. The calculation formula for the source signal value is as follows: iDrv=(i-δ) / a Here, a=0.001 and δ=0.

[0032] To create a one-way mapping from the target signal to the source signal, the above mapping formula and mapping parameters need to be stored as a record in the mapping execution container, with the contents of this record being as follows: (1) a = 0.001 (2) δ = 0 (3) Shift direction type value = target signal to source signal (4) Calculation formula for source signal value: iDrv=(i-δ) / a

[0033] In some embodiments, storing the mapping equation, the parameters of the mapping equation in a mapping execution container to create a mapping relationship between the source signal and the target signal (steps) includes: The number of source signals n, the mapping formula y=f(x1, x2...xn), and information relating each independent variable to a signal in the system are stored in a mapping execution container.

[0034] The following provides an example to explain in detail the steps of storing the mapping formula and the parameters of the mapping formula in the mapping execution container to create the mapping relationship between the source signal and the target signal. In a functional test of an automobile ESC system, suppose that when the vehicle speed is between 40km / h and 60km / h and the ESC function is on, it is necessary to check whether another specific flag is on. In this case, it is composed of the vehicle speed signal and the ESC function on signal. It is necessary to rely on one formula. y=(x1>40)&(x1<60)&x2 Here, y indicates the vehicle speed is in the 40km / h to 60km / h range and the ESC function is on flag, x1 indicates the vehicle speed CAN signal, and x2 indicates the ESC function on flag CAN signal.

[0035] It is necessary to create a mapping relationship between the above source signal and the target signal, and store the following mapping equation and parameters of the mapping equation in the mapping execution container. (1) Mapping formula: y=(x1>40)&(x1<60)&x2 (2) Number of source signals n=2 (3) Independent variable x1="0 / CAN_FD_ESC / ESC / ESCData / VehSpd" (4) Independent variable x2 = “0 / CAN_FD_ESC / ESC / ESCData / ESCActv”

[0036] In some embodiments, activating the mapping relationship includes setting an execution switch of the mapping execution container to an on state. As shown in Figure 2, when the [Active] button is checked in the signal mapping setting interface, the execution switch of the mapping execution container is set to the on state. For various application scenarios, such as when y is equal to x and when y is not equal to x, one complete example is provided.

[0037] The following is a complete example that details the adaptive update method for signal data. Suppose you need to monitor the gear change in a car test, and at the same time, plot the gear change curve in real time on a graph, then you need to create a one-way mapping from the source signal to the target signal. First, set the mapping equation y=x, where y is the target signal and refers to the mapping system variable corresponding to the source signal, which in this example refers to the mapping system variable corresponding to the gear signal; x is the source signal, which in this example refers to the gear signal. The target signal y is set to the mapping system variable "GearSys". The source signal x is set to the gearbox gear signal "0 / CAN_FD_Powertrain / Engine / GearBoxInfo / Gear" from the CAN bus, which means CAN channel 1, the network name is "CAN_FD_Powertrain", the sending ECU is "Engine", the message name is "GearBoxInfo", and the signal name is "Gear". The formula for calculating the target signal value is as follows: GearSys=Gear*a+δ Here, a=1 and δ=0. A mapping relationship between the source signal and the target signal is created, and the following mapping formula and mapping parameters are stored in the mapping execution container: (1) a=1 (2) δ = 0 (3) Shift direction type value = source signal to destination signal (4) Target signal value formula: GearSys = Gear * a + δ

[0038] As shown in FIG. 3, the execution switch of the mapping execution container is reset to the on state to activate the mapping relationship. The following is a complete example that details the adaptive update method for signal data. Suppose you need to monitor the real-time power of a DC motor during automotive testing and plot the power change curve in real time on a graph. You can collect the motor's terminal voltage and current from the CAN bus. You need to create a one-way mapping from the source signal to the target signal. First, set the mapping formula as y=x1*x2, where x1 and x2 are the source signals, x1 represents the motor terminal voltage, x2 represents the motor current, and y is the target signal, which refers to the mapping system variable corresponding to the motor power. Set the target signal y to the mapping system variable "Power". Set the source signal x1 to the motor terminal voltage signal "0 / MotorTest / Motor / SensorInfo / Voltage" from the CAN bus, meaning CAN channel 1, network name "MotorTest", sending ECU "Motor", message name "SensorInfo", and signal name "Voltage". Set the source signal x2 to the motor current signal "0 / MotorTest / Motor / SensorInfo / Current" from the CAN bus, meaning CAN channel 1, network name "MotorTest", sending ECU "Motor", message name "SensorInfo", and signal name "Current". A mapping relationship between the source signal and the target signal is created, and the following mapping formula and mapping parameters are stored in the mapping execution container. (1) Mapping formula: y=x1*x2 (2) Number of source signals n=2 (3) Independent variable x1 = “0 / MotorTest / Motor / SensorInfo / Voltage” (4) Independent variable x2 = “0 / MotorTest / Motor / SensorInfo / Current”

[0039] As shown in FIG. 4, the execution switch of the mapping execution container is reset to the on state to activate the mapping relationship.

[0040] Some embodiments further provide a system for adaptively updating signal data, as shown in Figure 5. The system includes a computer device. The computer device is configured to include: The setting module is configured to set a mapping equation between the source signal and the target signal to be linear and to set mapping parameters, such as a mapping amplification factor, an offset amount, and a mapping direction, or to set a mapping equation between the source signal and the target signal to be nonlinear and to set parameters of the mapping equation. Configuring the parameters of the mapping formula includes: Based on the number n of source signals, we create independent variables x1, x2...xn. Set the mapping formula y=f(x1,x2...xn). Each independent variable is related to a signal or equation result y in the system. The association module is configured to store the mapping formula, the mapping parameter, or the parameter of the mapping formula in one mapping execution container to create a mapping relationship between the source signal and the target signal, and activate the mapping relationship to realize adaptive updating of the signal data. Here, the specific implementation functions of the setting module and the association module are realized in a computer device, and the specific details can be referred to in the content of the adaptive update method for signal data above, and the description thereof will be omitted here.

[0041] The electronic device according to the embodiment of the present disclosure will be described below from the viewpoint of hardware processing. The embodiments of the present disclosure are not limited to specific implementations of electronic devices. As shown in Figure 6, some embodiments further provide an electronic device. The electronic device includes a processor, a computer-readable storage medium, a communication bus, and a communication interface. The processor, the computer-readable storage medium, and the communication interface communicate with each other via the communication bus. The computer-readable storage medium is used to store a program that executes the adaptive update method for signal data. The program causes the processor to perform operations corresponding to the adaptive update method for signal data.

[0042] Some embodiments further provide an electronic device, as shown in Figure 7. The electronic device includes a processor, a display in communication with the processor for displaying the signal mapping configuration interface, and a computer-readable storage medium. The computer-readable storage medium stores a command program. The processor is configured to execute the command program to perform the following operations: set a mapping formula and mapping parameters, create a mapping execution container, store the mapping formula and mapping parameters in the mapping execution container to create a mapping relationship between a source signal and a target signal, and activate the mapping relationship. The display is configured to display the mapping formula and the mapping parameters through the signal mapping setting interface.

[0043] In other embodiments, computer equipment, industrial computers, etc. may also be types of electronic devices. It should be noted that the configurations shown in Figures 6 and 7 are not intended to limit the electronic device, which may include fewer or more components than those shown, may combine some components, or may have different component arrangements.

[0044] In some embodiments, the communication interface may be a communication interface connectable to an external bus adapter, such as RS232, RS485, a USB port, a TYPE port, etc. A wired or wireless network interface may also be included, and the network interface may optionally include a wired and / or wireless interface (e.g., a WI-FI interface, a Bluetooth interface, etc.) typically used to establish a communication connection between the computing device and other electronic devices.

[0045] In some embodiments, the readable storage medium or computer-readable storage medium includes at least one type of memory. Memory includes flash memory, hard disk, multimedia card, card-type memory (e.g., SD memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory may be an internal storage unit of the computer device, such as a hard disk of the computer device. In other embodiments, the memory may be an external storage device of the computer device, such as a plug-in hard disk installed in the computer device, a Smart Media Card (SMC)®, a Secure Digital Card (SD), a Flash Card, etc. Furthermore, the memory may include both an internal storage unit of the computer device and an external storage device. The memory is used to store various data, such as application software and computer program code installed in the computer device, as well as to temporarily store output data or data to be output.

[0046] In some embodiments, the processor may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data processing chip that executes program code stored in memory or processes data, for example, to execute a computer program.

[0047] In some embodiments, the communication bus may be an input / output bus, which may be a Peripheral Component Interconnect (PCI) bus or an Enhanced Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc.

[0048] Optionally, the computer device may further include a user interface. The user interface may include input units such as a display and a keyboard, and optionally, the user interface may also include a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. In this case, the display is also called a display screen or a display unit, since it displays information processed in the computer device and a visualized user interface.

[0049] When the processor executes the program, it realizes the steps in the embodiment of the method for adaptively updating signal data shown in Fig. 1. For example, steps S101 to S102 shown in Fig. 1. Alternatively, when the processor executes the computer program, it realizes the functions of each module or unit in each of the embodiments of the device.

[0050] Some embodiments further provide a computer-readable storage medium having stored thereon any of the above possible methods for adaptively updating signal data.

[0051] Some embodiments further provide a computer-readable storage medium, which stores computer-readable instructions that, when executed by at least one processor, cause the above-mentioned adaptive updating method for signal data to be performed. Specifically, the instructions include: setting a mapping formula and mapping parameters; creating a mapping execution container; storing the mapping formula and mapping parameters in the mapping execution container to create a mapping relationship between the source signal and the target signal, and activating the mapping relationship. A detailed description of the adaptive updating method for signal data is provided below, and will not be repeated here.

[0052] Some embodiments further provide a computer program product, which includes computer programs or commands that, when executed on a computer, cause the computer to perform any of the possible signal data adaptive updating methods described above.

[0053] Some embodiments also provide a computer program product including a computer-readable storage medium having stored thereon computer-readable program code including instructions that cause at least one processor (one or more computing devices) to perform the following operations: set a mapping formula and mapping parameters; create a mapping execution container; store the mapping formula and mapping parameters in the mapping execution container to create a mapping relationship between a source signal and a target signal, and activate the mapping relationship.

[0054] In some embodiments of the present invention, it should be understood that the disclosed apparatus and method may also be implemented in other manners. The apparatus embodiments described above are merely exemplary. For example, the flowcharts and block diagrams in the drawings illustrate possible architectures, functions, and operations of apparatuses, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, a program segment, or a portion of code. The module, program segment, or portion of code includes executable commands for implementing one or more predetermined logical functions. Note that in some alternative implementations, the functions depicted in the blocks may occur in a different order than depicted in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, or may sometimes be executed in the reverse order, depending on the functionality involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented in a dedicated hardware-based system that performs the predetermined functions or operations, or in a combination of dedicated hardware and computer commands.

[0055] Furthermore, each functional module in each embodiment of the present invention may be integrated together to form a single independent part, each module may exist independently, or two or more modules may be integrated to form a single independent part.

[0056] The above functions can be realized in the form of software functional modules and stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention essentially or the part that contributes to the prior art or the part of the technical solution can be expressed in the form of a software product. The computer software product is stored in a storage medium and includes multiple commands to make a computer device (which may be a personal computer, a server, a network device, etc.) perform all or part of the steps of the methods described in each embodiment of the present invention.

[0057] The above-described preferred embodiments of the present invention have been enlightened, and those skilled in the art can make various changes and modifications based on the above description without departing from the technical spirit of the present invention. The technical scope of the present invention is not limited to the content of the specification, but should be determined based on the claims.

Claims

1. 1. A method for adaptively updating signal data used in a bus simulation and testing process, comprising: Storing a mapping equation, a mapping parameter, or a parameter of the mapping equation between the source signal and the target signal in a mapping execution container to create a mapping relationship between the source signal and the target signal, and setting an execution switch of the mapping execution container to an on state to activate the mapping relationship and realize adaptive updating of signal data; If the mapping formula is set to be linear, set mapping parameters; A method for adaptively updating signal data, executed by an adaptive updating system including a computer device, further comprising the step of: setting parameters of the mapping equation when the mapping equation is set to be nonlinear.

2. the mapping parameters are one or more of a mapping amplification factor, an offset amount, and a mapping direction; the mapping direction includes one-way mapping and / or two-way mapping; the unidirectional mapping includes a mapping from a source signal to a target signal and a mapping from a target signal to a source signal; 2. The method of claim 1, wherein the bidirectional mapping includes mapping the source signal to the target signal and simultaneously mapping the target signal to the source signal.

3. When mapping from a source signal to a target signal, the formula for calculating the target signal value is: Mz=Yz*a+δ, When mapping from a target signal to a source signal, the formula for calculating the source signal value is: Yz=(Mz−δ) / a, 3. The method for adaptively updating signal data according to claim 2, wherein Mz is the value of the target signal, Yz is the value of the source signal, a is the mapping amplification factor, and δ is the offset amount.

4. 2. The method of claim 1, wherein the signals in the system include one or more of a bus signal, a mapping system variable, a constant, and an immediate value.

5. Storing the mapping formula and mapping parameters in a mapping execution container to create a mapping relationship between the source signal and the target signal includes: storing a, δ, a type value of the mapping direction, and Mz=Yz*a+δ in a mapping execution container; storing a, δ, a type value of the mapping direction, and Yz=(Mz-δ) / a in a mapping execution container; 3. The method for adaptively updating signal data according to claim 2, wherein Mz is the value of the target signal, Yz is the value of the source signal, a is the mapping amplification factor, and δ is the offset amount.

6. Storing the mapping equation and the parameters of the mapping equation in a mapping execution container to create a mapping relationship between the source signal and the target signal includes: storing in a mapping execution container the number n of source signals, the mapping formula y=f(x1, x2...xn), and information relating each independent variable to a signal or formula result y in the system; 2. The method for adaptively updating signal data according to claim 1, wherein x1, x2, . . . xn are independent variables generated based on the number n of source signals.

7. 1. A system for adaptively updating signal data used in a bus simulation and testing process, the system comprising: the computing device is configured to include an association module; the association module is configured to store a mapping equation between the source signal and the target signal, a mapping parameter when the mapping equation is linear, or a parameter of the mapping equation when the mapping equation is nonlinear, in one mapping execution container to create a mapping relationship between the source signal and the target signal, and to activate the mapping relationship by setting an execution switch of the mapping execution container to an on state, thereby realizing adaptive updating of the signal data.

8. the mapping parameters are one or more of a mapping amplification factor, an offset amount, and a mapping direction; The mapping direction includes one-way mapping and two-way mapping, the unidirectional mapping includes a mapping from a source signal to a target signal and a mapping from a target signal to a source signal; 8. The system of claim 7, wherein the bidirectional mapping includes mapping the source signal to the target signal and simultaneously mapping the target signal to the source signal.

9. When mapping from a source signal to a target signal, the formula for calculating the target signal value is: Mz=Yz*a+δ, When mapping from a target signal to a source signal, the formula for calculating the source signal value is: Yz=(Mz−δ) / a, 9. The adaptive signal data updating system according to claim 8, wherein Mz is the value of the target signal, Yz is the value of the source signal, a is the mapping amplification factor, and δ is the offset amount.

10. 8. The system for adaptively updating signal data of claim 7, wherein the signals in the system include one or more of bus signals, mapping system variables, constants, and immediate values.

11. Storing the mapping formula and mapping parameters in a mapping execution container to create a mapping relationship between the source signal and the target signal includes: storing a, δ, a type value of the mapping direction, and Mz=Yz*a+δ in a mapping execution container; Alternatively, storing a, δ, a type value of the mapping direction, and Yz=(Mz-δ) / a in a mapping execution container; 9. The adaptive signal data updating system according to claim 8, wherein Mz is the value of the target signal, Yz is the value of the source signal, a is the mapping amplification factor, and δ is the offset amount.

12. Storing the mapping equation and the parameters of the mapping equation in a mapping execution container to create a mapping relationship between the source signal and the target signal includes: storing in a mapping execution container the number n of source signals, the mapping formula y=f(x1, x2...xn), and information relating each independent variable to a signal or formula result y in the system; 8. The adaptive updating system for signal data according to claim 7, wherein x1, x2, . . . xn are independent variables generated based on the number n of source signals.

13. A computer-readable storage medium, comprising: A computer-readable storage medium having stored thereon computer-readable instructions which, when executed by at least one processor, perform the method for adaptively updating signal data used in bus simulation and testing processes according to any one of claims 1 to 6.

14. An electronic device, a processor, a display in communication with the processor for displaying a signal mapping configuration interface, and a computer-readable storage medium; The computer-readable storage medium stores a command program; The processor is configured to execute the command program, and executes the method for adaptively updating signal data used in a bus simulation and testing process according to any one of claims 1 to 6; The display is configured to display a mapping formula and a mapping parameter through a signal mapping setting interface.

15. A program causing a computer to execute the method for adaptively updating signal data used in a bus simulation and test process according to any one of claims 1 to 6.

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