Adaptive update method of signal data used for bus simulation and test process

Abstract

To relate to the field of vehicular software development technologies, and in particular to an adaptive update method of signal data.SOLUTION: An adaptive update method of signal data includes: setting a mapping expression between a source signal and a target signal to a linear type, and configuring mapping parameters, which are a mapping amplification factor, an offset amount and a mapping direction; or, setting the mapping expression between the source signal and the target signal to a nonlinear type, and configuring parameters of the mapping expression, configuring the parameters of the mapping expression including: based on the quantity of the source signals n, creating independent variables x1, x2 ...xn; setting the mapping expression to y=f (x1, x2 ...xn); associating each independent variable with the signal in a system or an expression result y; and storing the mapping expression, the mapping parameters or the parameters of the mapping expression into a mapping execution container to create a mapping relationship between the source signal and the target signal, and activating the mapping relationship for adaptive update of signal data.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] This application claims the Chinese Patent Application No. 202410073686.0 filed on January 18, 2024 based on priority, and all its contents are incorporated herein by reference.

[0002] The present invention belongs to the technical field of vehicle software development, and specifically relates to an adaptive update method for signal data used in bus simulation and test processes.

Background Art

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

[0004] There is no direct solution in any of the related bus tools to perform real-time processing on bus signals to construct the required virtual signals. The main business function of bus tools is the collection and transmission of bus signals, and this function range does not cover the virtual and real-time computing functions of abstract information. If a real-time processing script is added to the bus tool to construct the required virtual signals, due to the diversity of signal types, the script and parameter configuration will become very complex, occupy system resources, affect the real-time effect of bus signal processing, and thereby affect the efficiency of bus simulation and test.

[0005] The object of the present invention is to provide an adaptive update method for signal data used in bus simulation and test processes.

[0006] To solve the above technical problem, the present invention provides an adaptive update method for signal data. This method includes the following. In step S101, the mapping formula between the source signal and the target signal is set as a linear type, and mapping parameters including a mapping amplification factor, an offset amount, and a mapping direction are set. Alternatively, the mapping formula between the source signal and the target signal is set as a non-linear type, and the parameters of the mapping formula are set. Setting the parameters of the mapping formula includes the following. Based on the number n of source signals, independent variables x1, x2... xn are created. A mapping formula y = f(x1, x2... xn) is set. Each independent variable is associated with a signal in the system or the result y of the formula. In step S102, the mapping formula, the mapping parameters, or the parameters of the mapping formula are stored in the mapping execution container to create a mapping relationship between the source signal and the target signal, and the mapping relationship is activated to realize the adaptive update of the signal data.

[0007] The beneficial effects of the present invention are as follows. The adaptive update method for signal data of the present invention does not require the user to write a program for specially processing bus signals. By simply using the mapping formula, real-time processing of bus signals can be realized, thereby solving the problem that the virtual signals required in the bus simulation and test processes are difficult to update in real time, and improving the efficiency of bus simulation and test.

[0008] Other features and advantages of the present invention are described in the following specification, and some will be apparent from the specification or understood by implementing the present invention. The objects and other advantages of the present invention are realized and obtained by the structure specifically pointed out in the specification and drawings.

[0009] To make the above objects, features, and advantages of the present invention clearer, the following provides preferred embodiments and, in conjunction with the accompanying drawings, will be described in detail.

Brief Description of the Drawings

[0010] To more clearly illustrate the specific embodiments of the present invention or the technical solutions of the prior art, the following briefly describes the drawings that need to be used in the description of 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 creative effort.

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Modes for Carrying Out the Invention

[0011] To make the objectives, technical aspects, and advantages of the embodiments of the present invention clearer, the technical aspects of the present invention will be clearly and completely described below in connection with the accompanying drawings. It is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained on the premise that those skilled in the art do not perform creative labor belong to the scope of protection of the invention.

[0012] In the process of bus simulation and test based on a bus tool, it is necessary to always perform real-time processing on the received bus signal to construct the required virtual signal. In the process of vehicle software development, a virtual signal is a signal that does not exist in the measurement data set by artificial logic. For example, signals such as the bus load rate signal, peak load rate signal, frame rate signal, sum of any signal values such as A signal value + B signal value, addition, subtraction, multiplication, division, absolute value, inverse cosine, inverse tangent, cosine, power / square root, logarithm, maximum / minimum value, sine, tangent, etc. obtained by real-time processing are all virtual signals. These virtuals can complete the subsequent bus simulation and analysis requirements of test data.

[0013] There is no direct solution in any of the related bus tools to perform real-time processing on the bus signal to construct the required virtual signal. The main business function of the bus tool is the collection and transmission of bus signals, and its function scope does not cover the virtual and real-time computing functions of abstract information. If a real-time processing script is added to the bus tool to construct the required virtual signal, due to the diversity of signal types, the script and parameter configuration will become very complicated, occupying system resources and affecting the real-time effect of bus signal processing, thereby affecting the efficiency of bus simulation and test.

[0014] Therefore, at least one embodiment achieves the purpose of realizing real-time processing on the bus signal only by the mapping method by providing an adaptive update method for signal data, and can further meet the adaptive update requirements of signal data. Specifically, this method can include the following steps. In step S101, the mapping formula between the source signal and the target signal is set as a linear type, and mapping parameters including the mapping amplification factor, the offset amount, and the mapping direction are set. Alternatively, the mapping formula between the source signal and the target signal is set as a non-linear type, and the parameters of the mapping formula are set. Setting the parameters of the mapping formula includes the following. Based on the number n of source signals, independent variables x1, x2... xn are created. A mapping formula y = f(x1, x2... xn) is set. Each independent variable is associated with a signal or the result y of an expression within the system. In step S102, the mapping formula, the mapping parameters, or the parameters of the mapping formula are stored in the mapping execution container to create the mapping relationship between the source signal and the target signal, and the mapping relationship is activated to realize the adaptive update of the signal data.

[0015] According to the method for adaptively updating signal data of the present invention, the user does not need to write a program for specially processing the bus signal, and real-time processing of the bus signal can be realized only by using the mapping formula. These processes include the following. (1) Perform mathematical operations on two or more bus signal values. For example, addition, subtraction, multiplication, and division. (2) Plot the result signal calculated in the previous step as a curve. (3) Detect the calculation result of the previous step by means of a logical configuration. Thereby, the problem that the virtual signals required in the bus simulation and test process are difficult to update in real time is solved, and the efficiency of bus simulation and test is improved.

[0016] The following is an example to explain the process of processing the bus signal in the method for adaptively updating the present signal data. Specifically, it is as follows. In the test process of an automobile chassis, it is necessary to verify whether the ABS function is triggered during the full braking process when the vehicle speed is higher than 50 kph and the master cylinder pressure is higher than 80 bar. Using the conventional test method, it is necessary to create a script for tracking the test and collate three signal data: the vehicle speed V, the master cylinder pressure M, and the ABS trigger flag A. The following steps can be used by applying the adaptive update method for this signal data. 1. Establish the formula y = (x1 > 50) & (x2 > 80) & (x3 = 1). Here, 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 represents a new flag R indicating that 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 the three signals are simultaneously activated. Therefore, it is only necessary to judge the signal data of the new flag R. 2. Drag the new flag R from the signal list in the system to the graphic window of the automotive bus tool. The graphic window can automatically draw the signal data curve that displays the new flag R. 3. Using the signal detection function provided by the automotive bus tool, it is only necessary to detect whether the new flag R signal data generates a jump from 0 to 1 during the test process. As can be seen from the above example, the adaptive update method for this signal data does not require creating a line of processing code, which improves the efficiency of test verification.

[0017] Hereinafter, various non-limiting embodiments of the examples of the present disclosure will be described in detail with reference to the accompanying drawings. As shown in FIG. 1, some embodiments provide an adaptive update method for signal data. This method includes the following. In step S101, the mapping formula between the source signal and the target signal is set as a linear type, and mapping parameters including the mapping amplification factor, the offset amount, and the mapping direction are set. Alternatively, set the mapping formula between the source signal and the target signal to be a non-linear type and set the parameters of the mapping formula. Setting the parameters of the mapping formula (step) includes the following. Based on the number n of source signals, create independent variables x1, x2... xn. Set the mapping formula y = f(x1, x2... xn). Associate each independent variable with a signal in the system or the result y of the formula. In step S102, store the mapping formula, mapping parameters, or the parameters of the mapping formula in the mapping execution container to create the mapping relationship between the source signal and the target signal, and activate the mapping relationship to realize the adaptive update of the signal data. Specifically, the mapping execution container is a container for storing and executing mappings and has the following functions. 1) It can store the mapping formula and mapping parameters in a list. 2) It can import and export the list storing the mapping formula and mapping parameters. 3) It automatically executes the mapping relationship, maps the source signal to the target signal, or maps the target signal to the source signal, or realizes bidirectional mapping.

[0018] In some embodiments, when setting the mapping formula between the source signal and the target signal to be a linear type, that is, setting the mapping formula y = x. When setting the mapping formula between the source signal and the target signal to be a non-linear type, that is, setting that the mapping formula y is not equal to x. Here, x is the source signal, which may be a received bus signal, a system variable in the bus tool system, the system variable may be a variable that already exists 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 related to the source signal created by the local computer. The mapping system variable is the calculation result of the formula and can also participate in the arithmetic logic operation of the formula.

[0019] Next, when setting the mapping formula y = x in one example, the steps of setting the mapping amplification factor, offset amount, and mapping direction will be described in detail. In the functional test of an automotive ESC system, it is assumed that the vehicle speed signal needs to be monitored and the value of the vehicle speed signal is used for various test conditions. Therefore, it is necessary to create a one-way mapping from the vehicle speed CAN signal to the mapping system variable "VehicleSpeed". That is, set the mapping formula y = x, where y refers to 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 of the mapping amplification factor a, offset amount δ, and mapping direction can be set. The mapping direction is fixed from the CAN signal to the mapping system variable in this example. The value of the actual mapping system variable "VehicleSpeed" is VehicleSpeed = a * VehSpd + δ. When the units of both the mapping system variable VehicleSpeed and the speed CAN signal VehSpd are "km / h" or "m / s", a = 1 and δ = 0. When the unit of the mapping system variable VehicleSpeed is "km / h" and the unit of the CAN signal VehSpd is "m / s", a = 3.6 and δ = 0, thereby ensuring the unity of the two variable physical quantities. When the unit of the mapping system variable VehicleSpeed is "m / s" and the unit of the CAN signal VehSpd is "km / h", a = 1 / 3.6 and δ = 0, thereby ensuring the unity of the two variable physical quantities.

[0020] Next, when the mapping formula y is not equal to x, an example of the steps of configuring the parameters of the mapping formula will be described in detail. In the automotive ESC system function test, assume that it is necessary to check whether other specific flags are on when the vehicle speed is in the range of 40 km / h to 60 km / h and the ESC function is on. At this time, it is configured depending on the vehicle speed signal and the ESC function on signal. One mapping formula is required. y=(x1>40)&(x1<60)&x2 Here, y refers to the flag that the vehicle speed is in the range of 40 km / h to 60 km / h and the ESC function is on, x₁ refers to the vehicle speed CAN signal, and x₂ refers to the ESC function on flag CAN signal. The symbol ">" indicates that the logic is greater, the symbol "<" indicates that the logic is smaller, the symbol "&" indicates the logical product (Logical AND), and the resulting value of y is also a logical value, either True or False. Based on this mapping formula, it is necessary to set mapping parameters, that is, to construct the mapping relationship of the independent variables x₁ and x₂ in the mapping formula. In this example, "0 / CAN_FD_ESC / ESC / ESCData / VehSpd" can be associated with x₁, which means channel 1, CAN network CAN_FD_ESC, ESC node, ESCData message, and VehSpd signal. "0 / CAN_FD_ESC / ESC / ESCData / ESCActv" can be associated with x₂, 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, according to the formula, x₁ = 50, x₂ = True, and the final y = True, that is, the condition that the vehicle speed is in the range of 40 km / h to 60 km / h and the ESC function is on is satisfied. When the vehicle speed is 70 km / h and the ESC function is off, according to the formula, x₁ = 70, x₂ = False, and the final y = False, that is, the condition that the vehicle speed is in the range of 40 km / h to 60 km / h and the ESC function is on is not satisfied.

[0021] In some embodiments, the above mapping directions include unidirectional mapping and bidirectional mapping. The above-mentioned unidirectional mapping includes mapping from a source signal to a target signal and mapping from a target signal to a source signal. The above-mentioned bidirectional mapping includes mapping from a source signal to a target signal and at the same time mapping the target signal to the source signal. In the case of only output or only input, it is unidirectional mapping. For example, in the case of only output, it is as follows. It is necessary to output a voltage signal or a current signal to drive an external device. At this time, the unidirectional mapping direction is to map from the target signal to the source signal, among which 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. In the case of only input, it is as follows. It is necessary to monitor an external voltage or current signal, draw a curve, or perform related test judgments. At this time, the unidirectional mapping direction is to map from the source signal to the target signal, among which the source signal is a CAN signal for monitoring representing an external voltage or current, and the target signal is a corresponding mapping system variable. Bidirectional mapping is used when both input and output are required. For example, for the maximum value signal of the solenoid valve current, when outputting, the mapping system variable i corresponding to the maximum value can be modified by a bus tool, for example, reset to 0. In the case of input, it can be used to monitor the region peak value of the current of the solenoid valve. For example, when starting a test case, the bus 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 operation of the test case, the bus tool reads the mapping system variable i cyclically and monitors the current peak value of this round in real time.

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

[0023] Hereinafter, the calculation process of the target signal value when mapping from the source signal to the target signal in an example, and the calculation process of the source signal value when mapping from the target signal to the source signal will be described in detail. In the process of reading and writing the maximum solenoid valve current signal, the target signal is set to the corresponding mapping system variable i, with the unit being ampere (A). The source signal is the maximum solenoid valve current signal CurrMax of an automotive ECU, with the unit being milliampere (mA). It is necessary to create a bidirectional mapping to map from the source signal to the target signal and to realize the bidirectional mapping from the target signal to the source signal. When the mapping direction is from the source signal to the target signal, the calculation formula for the target signal value is as follows. i = CurrMax * a + δ Here, 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, and 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 Here, 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, and δ = 0

[0024] In some embodiments, when the mapping formula is such that y is not equal to x, configuring the parameters of the mapping formula includes the following. Based on the number n of source signals, independent variables x1, x2... xn are created. The mapping formula y = f(x1, x2... xn) is set. Each independent variable is associated with a signal or the result y of an expression within the system.

[0025] The following details how to configure the parameters of the mapping formula when the mapping formula y is not equal to x in one example. In the automotive ESC system function test, assume that it is necessary to check whether another specific flag is on when the vehicle speed is in the range of 40 km / h to 60 km / h and the ESC function is on. At this time, it is configured depending on the vehicle speed signal and the ESC function on signal. One mapping formula is required. y=(x1>40)&(x1<60)&x2 Here, y refers to the flag indicating that the vehicle speed is in the range of 40 km / h to 60 km / h and the ESC function is on, x1 refers to the vehicle speed CAN signal, and x2 refers to the ESC function on flag CAN signal. The symbol ">" indicates that the logic is greater, the symbol "<" indicates that the logic is smaller, the symbol "&" indicates the logical product, and the resulting value of y is also a logical value, either True or False. Based on this mapping formula, it is necessary to set the mapping parameters. That is, to configure the mapping relationship of the independent variables x1 and x2 in the mapping formula. In this example, "0 / CAN_FD_ESC / ESC / ESCData / VehSpd" can be associated with x1, which means Channel 1, CAN network CAN_FD_ESC, ESC node, ESCData message, VehSpd signal. "0 / CAN_FD_ESC / ESC / ESCData / ESCActv" can be associated with x2, which means Channel 1, CAN network CAN_FD_ESC, ESC node, ESCData message, ESCActv signal. When the vehicle speed is 50 km / h and the ESC function is on, according to the formula, x1 = 50, x2 = True, and the final y = True, that is, the vehicle speed is in the range of 40 km / h to 60 km / h and the condition that the ESC function is on is satisfied. When the vehicle speed is 70 km / h and the ESC function is off, according to the formula, x1 = 70, x2 = False, and the final y = False, that is, the condition that the vehicle speed is in the range of 40 km / h to 60 km / h and the ESC function is on is not satisfied.

[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 the mapping relationship between the source signal and the target signal (step) includes the following. Store a, δ, the type value of the mapping direction, and Mz = Yz * a + δ in the mapping execution container.

[0028] The following will describe in detail the step 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 by way of examples. Suppose in the process of monitoring the ECU power supply voltage, the target signal is set to the mapping system variable v corresponding to the ECU power supply voltage, with the unit being volts (V), the source signal is the automotive ECU power supply voltage VMon, with the unit being millivolts (mV), and it is necessary to create a unidirectional mapping from the source signal to the target signal. The calculation formula for the target signal value is as follows. v = VMon * a + δ Here, a = 0.001 and δ = 0.

[0029] To create a unidirectional mapping from the source signal to the target signal, it is necessary to store the above mapping formula and mapping parameters in the mapping execution container as one record, and the content of this record is as follows. (1) a = 0.001 (2) δ = 0 (3) Shift direction type value = from source signal to target signal (4) Formula for target signal value: v = VMon * a + δ

[0030] 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 (step) includes the following. a, δ, the type value of the mapping direction, and Yz = (Mz - δ) / a are stored in the mapping execution container.

[0031] The following will explain in detail the steps of storing the mapping formula and mapping parameters in the mapping execution container with examples to create the mapping relationship between the source signal and the target signal. Suppose in the process of controlling the ECU solenoid valve drive current, the target signal is set to the mapping system variable i corresponding to the ECU solenoid valve drive current, with the unit of ampere (A), the source signal is the automotive ECU solenoid valve drive current iDrv, with the unit of milliampere (mA), and it is necessary to create a unidirectional mapping from the target signal to the source signal. 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 unidirectional mapping from the target signal to the source signal, it is necessary to store the above mapping formula and mapping parameters in the mapping execution container as one record, and the content of this record is as follows. (1) a = 0.001 (2) δ = 0 (3) Shift direction type value = from the target signal to the source signal (4) Calculation formula for the source signal value: iDrv = (i - δ) / a

[0033] In some embodiments, 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 include the following. Store the number n of source signals, the mapping formula y = f(x1, x2... xn), and the information associating each independent variable with the signals in the system in the mapping execution container.

[0034] The following is a detailed explanation of creating the mapping relationship between the source signal and the target signal by listing examples, storing the parameters of the mapping formula in the mapping execution container (steps). In the automotive ESC system function test, assume that it is necessary to check whether another specific flag is on when the vehicle speed is in the range of 40 km / h to 60 km / h and the ESC function is on. At this time, it is composed of a vehicle speed signal and an ESC function on signal. It is necessary to depend on one formula. y=(x1>40)&(x1<60)&x2 Here, y refers to the flag that the vehicle speed is in the range of 40 km / h to 60 km / h and the ESC function is on, x1 refers to the vehicle speed CAN signal, and x2 refers to the ESC function on flag CAN signal.

[0035] It is necessary to create the mapping relationship between the above source signal and the target signal, and store the following mapping formula and the parameters of the mapping formula 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, the step of activating the mapping relationship includes setting the execution switch of the mapping execution container to the 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, for example, when y is equal to x and when y is not equal to x, one complete example is supplemented respectively.

[0037] The following is a complete example to explain in detail the adaptive update method of signal data. In automotive testing, assuming that it is necessary to monitor gear changes and at the same time draw the gear change curve in real time on a graph, it is necessary to create a one-way mapping from the source signal to the target signal. First, set the mapping formula y = x, where y is the target signal, referring to the mapping system variable corresponding to the source signal, and in this example, it refers to the mapping system variable corresponding to the gear signal. x is the source signal, and in this example, it refers to the gear signal. Set the target signal y to the mapping system variable "GearSys". Set the source signal x to the gear signal "0 / CAN_FD_Powertrain / Engine / GearBoxInfo / Gear" of the gearbox from the CAN bus, where the meaning is CAN channel 1, the network name is "CAN_FD_Powertrain", the transmitting ECU is "Engine", the message name is "GearBoxInfo", and the signal name is "Gear". The calculation formula for the target signal value is as follows. GearSys = Gear * a + δ Here, a = 1 and δ = 0. Create the mapping relationship between the above source signal and target signal, and store the following mapping formula and mapping parameters in the mapping execution container. (1) a = 1 (2) δ = 0 (3) Shift direction type value = source signal to target signal (4) Formula for target signal value: GearSys = Gear * a + δ

[0038] As shown in Figure 3, reset the execution switch of the mapping execution container to the on state to activate this mapping relationship. The following is a complete example to explain in detail the method for adaptively updating signal data. In an automotive test, assume that it is necessary to monitor the real-time power of a DC motor and at the same time draw the power change curve in real-time on a graph. The terminal voltage and current of the motor can be collected from the CAN bus, and it is necessary to create a one-way mapping from the source signal to the target signal. First, set the mapping formula to y = x1 * x2. Here, x1 and x2 are the source signals, x1 represents the voltage at the motor terminal, x2 represents the motor current, y is the target signal, and it refers to the mapping system variable corresponding to the motor power. Set the target signal y to the mapping system variable "Power". The source signal x1 is set to the motor terminal voltage signal "0 / MotorTest / Motor / SensorInfo / Voltage" from the CAN bus, which means CAN channel 1, the network name is "MotorTest", the transmitting ECU is "Motor", the message name is "SensorInfo", and the signal name is "Voltage". The source signal x2 is set to the motor current signal "0 / MotorTest / Motor / SensorInfo / Current" from the CAN bus, which means CAN channel 1, the network name is "MotorTest", the transmitting ECU is "Motor", the message name is "SensorInfo", and the signal name is "Current". Create the mapping relationship between the above source signal and target signal, and store the following mapping formula and mapping parameters 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 Figure 4, reset the execution switch of the mapping execution container to the on state to activate the mapping relationship.

[0040] As shown in FIG. 5, some embodiments further provide an adaptive update system for signal data. This system includes a computer device. The computer device is configured to include the following. A setting module configured to set the mapping formula between the source signal and the target signal to a linear type, and set the mapping parameters including the mapping amplification factor, the offset amount, and the mapping direction. Alternatively, it is configured to set the mapping formula between the source signal and the target signal to a non-linear type and set the parameters of the mapping formula. Configuring the parameters of the mapping formula includes the following. Based on the number n of source signals, create independent variables x1, x2... xn. Set the mapping formula y = f(x1, x2... xn). Associate each independent variable with a signal or the result y of the formula within the system. An association module configured to store the mapping formula, the mapping parameters, or the parameters of the mapping formula in a single mapping execution container to create the mapping relationship between the source signal and the target signal, and activate the mapping relationship to achieve the adaptive update of the signal data. Here, the specific implementation functions of the setting module and the association module are realized in the computer device. Specifically, reference can be made to the content of the above-mentioned adaptive update method for signal data, and the description is omitted here.

[0041] The electronic device in the embodiments of the present disclosure will be described below from the perspective of hardware processing. The embodiments of the present disclosure do not limit the specific implementation of the electronic device. As shown in FIG. 6, some embodiments further provide an electronic device. This electronic device includes a processor, a computer-readable storage medium, a communication bus, and a communication interface. The above-mentioned processor, the above-mentioned computer-readable storage medium, and the above-mentioned communication interface realize communication with each other via the above-mentioned communication bus. The above-mentioned computer-readable storage medium is used to store a program for executing the adaptive update method of the above-mentioned signal data. The above-mentioned program causes the processor to execute an operation corresponding to the adaptive update method of the above-mentioned signal data.

[0042] As shown in FIG. 7, some embodiments further provide an electronic device. This electronic device includes a processor, a display for communicating with the processor to display a signal mapping setting interface, and a computer-readable storage medium. The above-mentioned computer-readable storage medium stores a command program. The above-mentioned processor is configured to execute the following operations by executing the above-mentioned command program. 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 the source signal and the target signal, and activate the mapping relationship. The above-mentioned display is configured to display a mapping formula and mapping parameters through a signal mapping setting interface.

[0043] In other embodiments, a computer device and an industrial computer can also be regarded as a kind of electronic device. It should be noted that the configurations shown in FIGS. 6 and 7 do not limit the electronic device, and it can include fewer or more components than shown in the figures, some components can be combined, or different components can be arranged.

[0044] In some embodiments, the communication interface may be a communication interface connectable to an external bus adapter, such as RS232, RS485, USB port, and TYPE port. A wired or wireless network interface may also be included, and the network interface may optionally include wired and / or wireless interfaces (e.g., WI-FI interface, Bluetooth interface, etc.) typically used to establish a communication connection between the computer 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. The memory includes flash memory, hard disk, multimedia card, card-type memory (e.g., SD memory, etc.), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, it may be an internal storage unit of the computer device, such as the 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 equipped on the computer device, Smart Media Card (SMC) (registered trademark), Secure Digital (SD) card, Flash Card, etc. Further, the memory may include both the internal storage unit and the external storage device of the computer device. The memory is used to store various data such as application software installed on the computer device and the code of computer programs, and is also used to temporarily store the output data and the data to be output.

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

[0047] In some embodiments, the communication bus may be an input / output bus such as a Peripheral Component Interconnect (PCI) bus or an Enhanced Industry Standard Architecture (EISA) bus. This bus can be divided into an address bus, a data bus, a control bus, and the like.

[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 and a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. In this case, the display is also called a display screen or a display unit for displaying the information processed in the computer device and for displaying the visualized user interface.

[0049] When the processor executes the above program, it realizes the steps in the embodiment of the adaptive update method of the signal data shown in FIG. 1 above. For example, steps S101 to S102 shown in FIG. 1. Alternatively, when the processor executes a computer program, it realizes the functions of each module or unit in the embodiment of each of the above devices.

[0050] Some embodiments further provide a computer-readable storage medium. This storage medium stores any of the above possible adaptive update methods of signal data.

[0051] Some embodiments further provide a computer-readable storage medium. This storage medium stores computer-readable instructions that, when executed by at least one processor, cause the above-described adaptive update method for signal data to be executed. Specifically, a mapping formula and mapping parameters are set. A mapping execution container is created. The mapping formula and mapping parameters are stored in the mapping execution container to create a mapping relationship between the source signal and the target signal, and the mapping relationship is activated. Refer to the specific description of the adaptive update method for signal data, and the description is omitted here.

[0052] Some embodiments further provide a computer program product. This product includes a computer program or command. When the computer executes the above computer program or command, the computer is caused to execute any of the above possible adaptive update methods for signal data.

[0053] Some embodiments also provide a computer program product including a computer-readable storage medium storing computer-readable program code including commands that cause at least one processor (one or more computer devices) to perform the following operations: 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.

[0054] In some embodiments provided by the present invention, naturally, the disclosed apparatus and method can also be implemented in other ways. The embodiments of the apparatus described above are merely illustrative. For example, the flowcharts and block diagrams in the drawings show the architectures, functions, and operations that can be realized by the apparatus, method, and computer program product according to multiple embodiments of the present invention. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of the code. The above module, program segment, or part of the code includes executable commands for realizing one or more predetermined logical functions. It should be noted that in some alternative implementation methods, the functions represented by the blocks may occur in an order different from the order shown in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and sometimes in the reverse order depending on the related functions. Also, each block of the block diagram and / or flowchart, as well as the combination of the blocks of the block diagram and / or flowchart, may be realized by a dedicated hardware-based system for executing a predetermined function or operation, or may be realized by a combination of dedicated hardware and computer commands.

[0055] In addition, each functional module in each embodiment of the present invention may be integrated together to form an independent part, or each module may exist alone, or two or more modules may be integrated to form an independent part.

[0056] When the above functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence or the part that contributes to the prior art or the part of the technical solution, can be represented in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of commands to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention.

[0057] Inspired by the preferred embodiments of the present invention described above, those skilled in the art can make various changes and modifications without departing from the technical idea of the present invention from the above description. The technical scope of the present invention is not limited to the content of the specification, and the technical scope must be determined based on the scope of the claims.

Claims

1. An adaptive update method for signal data, comprising: Setting the mapping formula between the source signal and the target signal as a linear type, and configuring mapping parameters including a mapping amplification factor, an offset amount, and a mapping direction; Alternatively, setting the mapping formula between the source signal and the target signal as a non-linear type, and configuring the parameters of the mapping formula; Here, configuring the parameters of the mapping formula includes the following: Creating independent variables x1, x2... xn based on the number n of source signals; Setting a mapping formula y = f(x1, x2... xn); Associating each independent variable with a signal or the result y of an expression in the system; Storing the mapping formula, mapping parameters, or parameters of the mapping formula in a mapping execution container to create a mapping relationship between the source signal and the target signal, and activating the mapping relationship to realize adaptive update of signal data.

2. The mapping direction includes unidirectional mapping and bidirectional mapping. The unidirectional mapping includes mapping from the source signal to the target signal and mapping from the target signal to the source signal. The bidirectional mapping includes mapping from the source signal to the target signal and simultaneously mapping the target signal to the source signal. The adaptive update method for signal data according to claim 1 is characterized by this.

3. When mapping from the source signal to the target signal, the calculation formula for the target signal value is: Mz = Yz * a + δ When mapping from the target signal to the source signal, the calculation formula for the source signal value is: Yz = (Mz - δ) / a Here, 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. The adaptive update method for signal data according to claim 2 is characterized by this.

4. The signal in the system includes one or more of a bus signal, a mapping system variable, a constant, and an immediate value. The adaptive update method for signal data according to claim 1 is characterized by this.

5. 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 includes: Storing a, δ, the type value of the mapping direction, and Mz = Yz * a + δ in the mapping execution container. Storing a, δ, the type value of the mapping direction, and Yz = (Mz - δ) / a in a mapping execution container, and the method for adaptively updating signal data according to claim 3, characterized by including the above.

6. Creating a mapping relationship between a source signal and a target signal by storing a mapping formula and parameters of the mapping formula in a mapping execution container, including storing the number n of source signals, the mapping formula y = f(x1, x2... xn), and information associating each independent variable with a signal or the result y of a formula in the system in a mapping execution container, Activating the mapping relationship includes setting the execution switch of the mapping execution container to the on state, and the method for adaptively updating signal data according to claim 1, characterized by including the above.

7. An adaptive update system for signal data, including a computer device, wherein the computer device is configured to include a setting module and an association module, the setting module is configured to set the mapping formula between the source signal and the target signal to a linear type and set the mapping parameters including the mapping amplification factor, the offset amount, and the mapping direction, or to set the mapping formula between the source signal and the target signal to a non-linear type and set the parameters of the mapping formula, wherein configuring the parameters of the mapping formula includes the following, creating independent variables x1, x2... xn based on the number n of source signals, setting the mapping formula y = f(x1, x2... xn), associating each independent variable with a signal in the system or the result y of a formula, the association module is configured to store the mapping formula, the mapping parameters, or the parameters of the mapping formula in a mapping execution container to create a mapping relationship between the source signal and the target signal, and activate the mapping relationship to realize the adaptive update of signal data, and the adaptive update system for signal data, characterized by the above.

8. The mapping direction includes unidirectional mapping and bidirectional mapping, the unidirectional mapping includes mapping from the source signal to the target signal and mapping from the target signal to the source signal, The adaptive update system for signal data according to claim 7, wherein the bidirectional mapping includes mapping from a source signal to a target signal and simultaneously mapping the target signal to the source signal.

9. When mapping from a source signal to a target signal, the calculation formula for the target signal value is Mz = Yz * a + δ, When mapping from a target signal to a source signal, the calculation formula for the source signal value is 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 amount. The adaptive update system for signal data according to claim 8.

10. The signal in the system includes one or more of a bus signal, a mapping system variable, a constant, and an immediate value. The adaptive update system for signal data according to claim 7.

11. 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 includes storing a, δ, the type value of the mapping direction, and Mz = Yz * a + δ in the mapping execution container; or storing a, δ, the type value of the mapping direction, and Yz = (Mz - δ) / a in the mapping execution container. The adaptive update system for signal data according to claim 9.

12. 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 includes storing the number n of source signals, the mapping formula y = f(x1, x2... xn), and information associating each independent variable with a signal or the result y of a formula in the system in the mapping execution container. Activating the mapping relationship includes setting the execution switch of the mapping execution container to the on state. The adaptive update system for signal data according to claim 7.

13. A computer-readable storage medium, in which computer-readable commands are stored and, when executed by at least one processor, execute the adaptive update method for signal data according to any one of claims 1 to 6. A computer-readable storage medium.

14. An electronic device, A processor, a display that communicates with the processor to display a signal mapping setting interface, and a computer-readable storage medium, wherein the computer-readable storage medium stores a command program, the processor is configured to execute the command program and execute the adaptive update method for signal data according to any one of claims 1 to 6, and the display is configured to display a mapping formula and mapping parameters through the signal mapping setting interface. An electronic device characterized by the above.

15. A computer program product including a computer program or command, wherein when the computer executes the computer program or command, the computer is caused to execute the adaptive update method for signal data according to any one of claims 1 to 8. A computer program product characterized by the above.

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