Data display methods, electronic equipment and diagnostic equipment for automotive diagnostics

Abstract

This invention discloses a data display method, electronic device, and diagnostic device for automotive diagnostic equipment. The method includes obtaining user identity and acquiring vehicle operation data during vehicle operation based on diagnostic items. A first unit for displaying the vehicle operation data is determined based on the requirements of the diagnostic items, user identity, and the data characteristics of the vehicle operation data. The vehicle operation data is then displayed using the first unit. After obtaining the vehicle operation data, the automotive diagnostic equipment automatically determines the first unit for display based on the data characteristics, eliminating the need for manual unit selection. Furthermore, the first unit, determined in conjunction with the data characteristics, more easily meets diagnostic needs, reducing the need to switch units. This increases the automation level of the automotive diagnostic equipment, reduces manual operation steps, and improves diagnostic efficiency.

Description

Technical Field

[0001] This invention relates to the field of automotive diagnostic technology, and more particularly to a data display method, electronic device, and diagnostic device for automotive diagnostic equipment. Background Technology

[0002] During vehicle diagnostics, diagnostic equipment is used to identify vehicle faults. After maintenance personnel connect the diagnostic equipment to the vehicle's control system, real-time operating data is sent to the equipment. The personnel then record and analyze this data to arrive at a diagnostic result.

[0003] Because cars come from many brands and different brands are manufactured in different countries, unit switching is frequently required during car diagnostics. Current car diagnostic equipment uses a limited method for switching data units, relying entirely on manual switching, which reduces diagnostic efficiency. Summary of the Invention

[0004] The purpose of this invention is to provide a data display method, electronic device, and diagnostic device for automotive diagnostic equipment, aiming to solve the problem of low efficiency in existing automotive diagnostics.

[0005] A data display method for automotive diagnostic equipment, applied to automotive diagnostic equipment, the method comprising: The vehicle diagnostic equipment is configured with multiple diagnostic items, each of which corresponds to the vehicle operation data that needs to be acquired. The first unit used when displaying the vehicle operation data is determined based on the project requirements of the diagnostic project, the user identity, and the data status of the vehicle operation data. The vehicle operation data is displayed using the first unit, wherein the value of the vehicle operation data changes with the unit.

[0006] An electronic device, including a memory and a processor; The memory stores a data display program; The processor implements the method described above when executing the data display program.

[0007] A computer storage medium storing a program that implements the method described above.

[0008] An automotive diagnostic device includes a main body, a display screen, and a controller; The controller stores a data display program, and the controller implements the method described above when running the data display program.

[0009] The embodiments of the present invention have the following beneficial effects: After determining the diagnostic items, the automotive diagnostic equipment automatically selects the vehicle operating data to be acquired based on those items, reducing the need for manual selection. Furthermore, once the vehicle operating data is obtained, the equipment automatically determines the first unit to be used for display based on the diagnostic requirements, user identity, and the data's characteristics. This eliminates the need for manual unit selection, and the first unit, determined in conjunction with the data, is more likely to meet diagnostic needs, reducing the need to switch units. This increases the automation level of the automotive diagnostic equipment, reduces manual operation steps, and improves diagnostic efficiency. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] in: Figure 1 This is a flowchart of a data display method for an automotive diagnostic device in one embodiment; Figure 2 This is a schematic diagram of the structure of an electronic device in one embodiment. Detailed Implementation

[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0013] Existing automotive diagnostic tablet devices typically employ a single display layer architecture for their data flow interface. Under this architecture, the interface design is laid out around the data display requirements of a single unit system (metric or imperial).

[0014] Therefore, the data stream interface suffers from several technical shortcomings in terms of unit display and switching, including a simplistic interface architecture, cumbersome unit switching processes, low data processing efficiency, and unfriendly user interaction design. It fails to meet users' needs for simultaneously viewing metric and imperial data within the data stream interface. This application provides a data display method for automotive diagnostic equipment, which simultaneously displays metric and imperial data stream values ​​in the data stream interface of the automotive diagnostic tablet equipment and provides a convenient unit switching button, effectively solving the problems existing in the prior art and improving the efficiency, accuracy and user experience of automotive diagnostics.

[0015] In one application scenario, when automotive diagnostic equipment performs diagnostics, it needs to establish a stable connection with the vehicle's electronic control unit (ECU) to ensure that the ECU can reliably transmit relevant vehicle data to the diagnostic equipment. Therefore, before the diagnostic equipment can display the vehicle's data, a communication link needs to be established. The process includes: Automotive diagnostic equipment establishes a stable and reliable connection with the vehicle's electronic control unit (ECU) via wired (such as OBDII interface cable) or wireless (such as Bluetooth, Wi-Fi) communication methods. This connection is fundamental to data transmission, ensuring that the equipment can acquire various critical data during the vehicle's operation in real time.

[0016] After the communication link is established, the data display method provided in this embodiment is executed, such as... Figure 1 As shown, it specifically includes the following content.

[0017] S100: Obtain user identity and vehicle operation data during vehicle operation based on diagnostic items.

[0018] User identity can be determined based on user ID. User identity represents a user's experience in vehicle diagnostics. For example, user identities can include advanced users, intermediate users, and basic users. Advanced users represent users with the most vehicle diagnostic experience (i.e., the most frequent vehicle diagnostics performed), while basic users represent users with the least experience. Another example is that user identities include novice mechanics and expert mechanics. When the historical data of a user ID indicates that the number of diagnostics performed exceeds a preset threshold, the user identity is determined to be either an advanced user or an expert mechanic.

[0019] The vehicle diagnostic equipment is configured with multiple diagnostic items, each corresponding to vehicle operating data that needs to be acquired. Specifically, diagnostic items may include vehicle function diagnostic items, used to diagnose whether the vehicle's functions are abnormal. In this case, the vehicle operating data may include data related to vehicle functions, such as engine operating data and brake operating data. Another example is vehicle service diagnostic items, used to diagnose whether the vehicle's services are abnormal. In this case, the vehicle operating data may include data related to vehicle services, such as Bluetooth operating data and control panel operating data.

[0020] In other words, the operator of the automotive diagnostic equipment selects a preset diagnostic item. Once the diagnostic item is determined, the diagnostic equipment retrieves corresponding vehicle operating data from the vehicle's electronic control unit based on the data type matched to the diagnostic item. It's important to note that different data types of vehicle operating data are retrieved at different frequencies. For example, engine operating data is retrieved relatively frequently, while tire pressure data is retrieved relatively infrequently. Therefore, multiple data sets of each type of vehicle operating data are retrieved, forming a data stream. These data types include engine speed, vehicle speed, tire pressure, intake air temperature, and exhaust air temperature.

[0021] In one embodiment, after obtaining vehicle operation data, the data is preprocessed. Preprocessing includes noise filtering and outlier detection. Noise filtering includes: Due to factors such as sensor accuracy and electromagnetic interference, the raw data collected may contain noise. Digital filtering algorithms are used to process the data to remove noise interference. For example, for vehicle speed data, the Kalman filter algorithm can be used. This algorithm can effectively estimate and filter noise based on the statistical characteristics of the data, while preserving the true trend of data change, thereby improving the accuracy and reliability of the data.

[0022] Outlier detection includes: Set reasonable data range thresholds and perform validity checks on the collected data. If the data exceeds the preset threshold range, it is identified as an outlier. For outliers, interpolation is used to process them. That is, based on the normal data points adjacent to the outlier, reasonable replacement values ​​are calculated through linear interpolation or other suitable interpolation methods to fill the data gaps caused by the outlier and ensure the continuity and integrity of the data.

[0023] In one embodiment, after obtaining vehicle operation data, the data display interface is also planned, including: Plan the display area for each data item. Based on the importance and frequency of use of the data, place key data (such as engine speed and vehicle speed) in prominent positions on the interface, such as the top or center area; place secondary data (such as intake air temperature and exhaust air temperature) on the edge or bottom area of ​​the interface. At the same time, ensure that the display area for each data item is of appropriate size and that the data is clearly readable.

[0024] S102. Determine the first unit used when displaying the vehicle operation data based on the project requirements of the diagnostic project, the user identity, and the data status of the vehicle operation data.

[0025] In one embodiment, the project requirements include requirements for the units used. That is, different diagnostic projects require different vehicle operation data, and the project requirements specify the units used for each vehicle operation data point. These units can be considered standard units for each vehicle operation data point, such as km / h for speed and km for distance. Specifically, the project requirements for different diagnostic projects can be preset, or the units used in the region where the diagnostic project is located can be determined as the standard units.

[0026] When the vehicle's operating data varies, the initial unit will also change accordingly. The "data conditions" refer to aspects such as the amount and precision of the vehicle's operating data. Specifically, when the vehicle's electronic control unit transmits operating data to the diagnostic equipment, each data point has an initial unit. Displaying the data using this initial unit may result in either excessively high precision or an excessive amount of data. Excessively high precision can reduce data clarity; for example, a value of 0.0001 MPa might not be easily identifiable. However, by changing the unit to keep the value above 1, the change becomes readily apparent. Conversely, excessive data volume can prevent the display from showing all vehicle operating data completely. Therefore, a new unit, the "first unit," is determined for the vehicle's operating data to ensure that changes are visible or that the diagnostic equipment's display shows all the vehicle's operating data completely.

[0027] It's important to note that vehicle operation data values ​​will change depending on the unit. This can be achieved using a preset unit conversion formula. When the first unit for displaying vehicle operation data needs to be used, the corresponding conversion formula will convert the value from the initial unit to the first unit. In other words, vehicle operation data includes both a numerical value and a unit. For example, 2 meters is the numerical value, and meters is the unit. When the first unit is centimeters, the numerical value changes from 2 to 200, and the unit changes from meters to centimeters. Different data types of vehicle operation data correspond to multiple units, including imperial and metric units, as well as units used in specific regions.

[0028] S104. Display the vehicle operation data using the first unit.

[0029] Once the first unit is determined, the vehicle operation data value can be calculated using the conversion formula between the initial unit and the first unit. The vehicle operation data is then displayed in the first unit, showing both the value and the unit.

[0030] Based on the above, after determining the diagnostic items, the automotive diagnostic equipment automatically selects the vehicle operating data to be acquired, reducing the need for manual selection of the required operating data. Furthermore, after obtaining the vehicle operating data, the equipment automatically determines the first unit to be used for display based on the data's characteristics, eliminating the need for manual unit selection. Moreover, determining the first unit based on the data's characteristics makes it easier to meet diagnostic needs, reducing the need to switch units. This increases the automation level of the automotive diagnostic equipment, reduces manual operation steps, and improves diagnostic efficiency.

[0031] In another embodiment of this application, the project requirements include requirements for the standard units used for the first type of operational data, the user identity includes novice repairmen and repair experts, the data conditions include numerical values, and the vehicle operational data includes the first type of operational data and a second type of operational data other than the first type of operational data; The step of determining the first unit used when displaying the vehicle operation data based on the project requirements of the diagnostic project, user identity, and the data status of the vehicle operation data includes: If the user is a new maintenance worker, then the standard unit is determined as the first unit of the first type of operating data, and the first unit of the second type of operating data is determined as the unit pre-associated with the standard unit, wherein the pre-associated unit is the unit that is used most often with the standard unit. If the user is the maintenance expert, then it is determined whether the value of the first type of operating data using the standard unit is less than a preset value threshold and whether the value of the second type of operating data using the initial unit is less than the value threshold, wherein the initial unit is the unit used when collecting the vehicle operating data; If the value of the first type of operating data using the standard unit is less than the value threshold, then the first unit of the first type of operating data is determined from the candidate units of the first type of operating data. If the value of the initial unit used by the second type of operating data is less than the value threshold, then the first unit of the second type of operating data is determined from the candidate units of the second type of operating data. The value of the vehicle operating data using the first unit is greater than the value threshold and is within a preset value range. Otherwise, the standard unit and the initial unit are determined to be the corresponding first unit.

[0032] In one embodiment, the project requirements may include only a portion of the standard units of vehicle operation data, that is, only the standard units of the first type of operation data. Therefore, vehicle operation data without standard units is regarded as the second type of operation data.

[0033] The numerical values ​​include, for example, 20, 50, 2000, 0.1, and 0.002, where 20 is less than 50 and 50 is greater than 0.1. By determining the relationship between the initial unit of the vehicle operation data and a numerical threshold, it is determined whether the initial unit needs to be changed. If a change is needed, one of several preset alternative units for the vehicle operation data is selected as the first unit, ensuring that the value of the vehicle operation data is greater than the numerical threshold and within the numerical range when changing from the initial unit to the first unit. For example, if a certain type of data (such as fuel trim value or oxygen sensor voltage) is too small in metric units (e.g., less than 0.01), it would require displaying mostly decimals to reflect the change. In this case, it is determined that the data is difficult to read in metric units because the value is less than the numerical threshold of 0.01. The data is automatically switched to imperial units (e.g., from volts (V) to millivolts (mV), or from liters per second to gallons per minute), ensuring that the displayed value remains within the range of 10-999 for easy human visual recognition.

[0034] For example, the formula can be expressed as: If |V metric ∣< (in If the threshold value is 0.1, then the display of V will be automatically triggered. imperial .

[0035] It should be noted that the numerical thresholds and ranges for vehicle operation data of different data types can be different. The numerical thresholds and ranges can be set according to actual needs, and this embodiment does not impose specific limitations on them. For example, to display larger values, the numerical threshold is set to a larger value, such as 0.1, 10, or 100; to display smaller values, the numerical threshold is set to a smaller value, such as 0.01, 0.001, or 0.0001. The numerical range directly determines the display range of the value, such as 1-10, 10-999, etc.

[0036] In one preferred embodiment, the process of determining whether the value of vehicle operating data is less than a preset value threshold can adopt an adaptive threshold mechanism that dynamically adjusts according to vehicle operating conditions and data types.

[0037] For example, the system pre-configures a basic threshold library for different types of vehicle operation data. The basic thresholds are set according to the physical magnitude and normal fluctuation range of the data: voltage data: basic threshold is 0.01 V; pressure data: basic threshold is 0.1 kPa; flow data (such as intake flow): basic threshold is 0.05 g / s.

[0038] Based on this, the system collects vehicle operating parameters in real time, dynamically corrects the basic thresholds, and generates real-time working thresholds. Specifically, this includes: real-time calculation of the fluctuation range of the target data over the most recent N consecutive sampling periods. When the vehicle is idling and the data fluctuates slightly at high frequency (fluctuation amplitude < 5% of the basic range), the threshold is lowered by 20% to 50% to improve the switching sensitivity and prevent small values ​​from failing to trigger a better unit due to an excessively large threshold. When the vehicle is in high-speed / high-load conditions and the data changes stably (fluctuation amplitude > 20% of the basic range), the threshold will be increased by 50%~100% to reduce the switching frequency and avoid visual interference caused by frequent unit switching.

[0039] Data type characteristic correction adjusts thresholds differently based on the physical characteristics of different data types: For high-frequency small signal data (such as weak sensor voltage or small pressure difference), the threshold is lowered by default, and the data is switched to smaller measurement units (such as mV or mbar) to ensure numerical readability. For low-frequency large signal data (such as battery voltage or coolant temperature), the threshold is raised by default, and the data is kept in the conventional units to avoid unnecessary unit conversions.

[0040] In actual operation, the system recalculates the real-time operating threshold at preset intervals and determines whether to switch to the first unit based on this dynamic threshold. For example, when the oxygen sensor voltage fluctuates slightly at idle, the real-time operating threshold is lowered from the base threshold of 0.01V to 0.004V. When the detected value is 0.008V (less than the dynamic threshold), it automatically switches from volts (V) to millivolts (mV) and displays 8mV, making the value intuitive and easy to read. When the vehicle accelerates and the voltage fluctuation increases, the real-time operating threshold is raised to 0.015V to avoid frequent switching.

[0041] The above information, including the numerical values, allows for the consideration of vehicle operation data values ​​when determining the first unit. This helps control the displayed values ​​of vehicle operation data within an easily observable range, improving the ease and comfort of reading vehicle operation data.

[0042] In another embodiment of this application, if the user is the maintenance expert, and the method further includes determining whether the value of the first type of operational data using the standard unit is less than a preset value threshold and whether the value of the second type of operational data using the initial unit is less than the value threshold, the method further includes: The numerical threshold is dynamically adjusted based on vehicle operating parameters and data type characteristics.

[0043] Specifically, including: Under idling conditions, the numerical threshold is lowered to improve the unit switching sensitivity of the vehicle operation data; Under high-speed or high-load conditions, the numerical threshold is increased to reduce the unit switching frequency of the vehicle operation data; For high-frequency small-signal data types, the numerical threshold is lowered by default, and the vehicle operation data is preferentially switched to a smaller range unit. For low-frequency, large-signal data types, the numerical threshold is increased by default to prioritize maintaining the conventional units of the vehicle operation data.

[0044] Specifically, when the user is a maintenance expert, the system no longer uses fixed values ​​to judge numerical thresholds. Instead, it introduces a dynamic adjustment mechanism based on vehicle operating parameters and data type characteristics to achieve more accurate automatic unit switching.

[0045] In terms of operating parameters, the system collects real-time information about the vehicle's current operating conditions, including engine speed, throttle opening, and vehicle speed, to comprehensively determine the vehicle's operating condition category. When the vehicle is idling, various sensor data generally exhibit small, high-frequency fluctuations. If the numerical threshold is set too high, many minute values ​​will not trigger unit switching, forcing repair technicians to make judgments based on excessively small values, thus affecting diagnostic efficiency. Therefore, under idling conditions, the system lowers the numerical threshold, for example, by 20% to 50% from the base threshold of 0.01V to 0.004V to 0.008V, thereby improving unit switching sensitivity and allowing more minute values ​​to automatically switch to more intuitive units for display. Conversely, when the vehicle is traveling at high speed or under high load, the vehicle's operating data values ​​are generally larger and fluctuate significantly. In this case, frequent unit switching can cause visual interference, hindering repair technicians from quickly reading the data. Therefore, under high-speed or high-load conditions, the system will increase the numerical threshold, for example, by 50% to 100%, thereby reducing the unit switching frequency and maintaining the stability of the data display.

[0046] Whether a condition is considered idling is determined by the following conditions: The system collects three parameters from the ECU in real time: engine speed (RPM), throttle position (TPS), and vehicle speed (VSS). The system determines that the vehicle is in idle condition when all of the following conditions are met: engine speed is within a preset idle speed range (e.g., 600 rpm to 1200 rpm); throttle position is below a preset idle position threshold (e.g., less than or equal to 5%); and vehicle speed is below a preset low-speed threshold (e.g., less than or equal to 5 km / h).

[0047] If all three conditions are met simultaneously and the duration exceeds the preset stable operating condition confirmation time (e.g., 2 consecutive seconds), the current operating condition can be marked as idling, and the corresponding numerical threshold reduction logic will be triggered.

[0048] High-speed and high-load operating conditions, as opposed to idling conditions, are determined by the following conditions: High-speed operating condition judgment conditions: The vehicle speed exceeds the preset high-speed threshold (e.g., greater than or equal to 80km / h) and the duration exceeds the preset operating condition stability confirmation time (e.g., 2 consecutive seconds).

[0049] High load condition judgment conditions: The throttle opening exceeds the preset high load opening threshold (e.g., greater than or equal to 60%), or the engine speed exceeds the preset high speed threshold (e.g., greater than or equal to 3500 rpm), and the duration exceeds the preset stable condition confirmation time (e.g., 2 consecutive seconds).

[0050] When any of the above conditions are met, the current operating condition is marked as a high-speed or high-load operating condition, and the logic for adjusting the numerical threshold is triggered.

[0051] In terms of data type characteristics, different types of vehicle operation data have different physical magnitudes and signal characteristics. The system presets differentiated threshold adjustment strategies for each data type. For high-frequency, small-signal data types, such as oxygen sensor voltage, fuel trim value, and minute pressure differentials, the numerical values ​​themselves are small. If a high numerical threshold is maintained, the data will be displayed as extremely small values ​​for a long time, which is not conducive to maintenance experts identifying signal change trends. Therefore, the system defaults to lowering the numerical threshold for this type of data, prioritizing switching the vehicle operation data to smaller units, such as switching from V to mV, or from kPa to mbar, to ensure that the displayed values ​​fall within an easily observable range. For low-frequency, large-signal data types, such as battery voltage, coolant temperature, and intake air temperature, the numerical values ​​are large and change slowly. Maintaining conventional units is sufficient for display requirements. Frequent unit switching would increase the cognitive burden. Therefore, the system defaults to raising the numerical threshold for this type of data, prioritizing maintaining conventional units for the vehicle operation data and avoiding unnecessary unit conversions.

[0052] Among them, high-frequency small-signal data types are identified through the following two dimensions of conditions, which must be met simultaneously: Signal frequency dimension: The ECU reporting frequency of this data type is higher than the preset high frequency threshold (e.g., greater than or equal to 10Hz, i.e., reporting 10 times or more per second).

[0053] Signal amplitude dimension: Under the initial unit, the upper limit of the range of this data type is lower than the preset small signal amplitude threshold (for example, the upper limit of the range is less than or equal to 1.0, corresponding to units such as V, kPa, etc.), or the absolute value of the average value in the most recent N consecutive sampling periods (for example, N is 20) is lower than the preset small signal average threshold (for example, less than or equal to 0.1).

[0054] During system initialization, each data type is categorized and labeled according to the two dimensions mentioned above, assigning a high-frequency, small-signal tag. Subsequent processing directly reads these tags, eliminating the need for recalculation. Data types belonging to this category include oxygen sensor voltage, fuel trim value, and minute pressure differentials.

[0055] Low-frequency large-signal data types are also identified through the following two quantization conditions, which must be met simultaneously: Signal frequency dimension: The ECU reporting frequency of this data type is lower than the preset low frequency threshold (e.g., less than 1Hz, i.e., less than once per second).

[0056] Signal amplitude dimension: Under the initial unit, the upper limit of the range of this data type is higher than the preset large signal amplitude threshold (e.g., the upper limit of the range is greater than or equal to 10.0, corresponding units such as V, ℃, etc.), or the absolute value of the average value of its values ​​in the most recent consecutive N sampling periods (e.g., N is 20) is higher than the preset large signal average threshold (e.g., greater than or equal to 10.0).

[0057] During system initialization, each data type is categorized and labeled according to the two dimensions mentioned above, and tagged with a low-frequency, high-signal tag. Data types belonging to this category include battery voltage, coolant temperature, and intake air temperature.

[0058] By combining the mechanism of determining the first unit based on the numerical value under the identity of a maintenance expert user with the adaptive threshold mechanism, the numerical threshold can be dynamically adjusted according to the actual vehicle operating conditions and data type characteristics. On the one hand, this avoids the problem of insufficient adaptability of fixed thresholds under different operating conditions. On the other hand, it provides differentiated processing for the physical characteristics of different data types, which is conducive to improving the data reading efficiency and the level of intelligence of unit switching for maintenance experts in complex diagnostic scenarios.

[0059] In another embodiment of this application, the project requirements include requirements for the standard units used for the first type of operational data, the user identity includes novice repairmen and repair experts, the data situation includes the number of data types, wherein the vehicle operational data includes the first type of operational data and a second type of operational data other than the first type of operational data; The step of determining the first unit used when displaying the vehicle operation data based on the project requirements of the diagnostic project, user identity, and the data status of the vehicle operation data includes: If the user is a new maintenance worker, then the standard unit is determined as the first unit of the first type of operating data, and the first unit of the second type of operating data is determined as the unit pre-associated with the standard unit, wherein the pre-associated unit is the unit that is used most often with the standard unit. If the user is the maintenance expert, then determine whether the number of data types of the vehicle operation data exceeds the preset screen capacity threshold. If so, the unit with a character count less than the initial unit is determined as the first unit, wherein the character count refers to the number of characters in the unit or the total number of characters in the unit and the corresponding value, and the initial unit is the unit used when collecting vehicle operation data.

[0060] The number of data types can be, for example, 5, 20, or 50. The amount of vehicle operation data for each data type may increase with the frequency of acquisition. Parameters such as engine speed, vehicle speed, tire pressure, intake air temperature, and exhaust air temperature are examples of data types.

[0061] If 50 types of vehicle operation data need to be displayed on the same screen, and the number of data points for each type continues to increase, it will become impossible to display all 50 data points simultaneously, making viewing inconvenient. In this case, if the number of data types (e.g., 50) exceeds the screen's capacity threshold (e.g., 30), the display is in congestion mode. The unit with fewer characters is then selected as the primary unit. For example, km / h has two more characters than mph, and kPa has one more character than psi. The shorter unit format is chosen to maximize the amount of information displayed on a single screen and reduce page-turning operations.

[0062] The screen occupancy threshold is determined based on the screen area and the character type displayed. For example, if the screen area is 100 and the character type is 10 (the area of ​​a single data type is 10), then the screen occupancy threshold is 10.

[0063] Based on the above, the data situation includes the number of data types. When there are many data types, the initial unit is automatically switched to the first unit. Using the first unit can reduce the number of characters or the length of characters in the vehicle operation data, so that all vehicle operation data can be displayed without flipping through pages, thus improving the convenience of data viewing.

[0064] In another embodiment of this application, after displaying the vehicle operation data using the first unit, the method further includes: The vehicle operation data is converted from the initial unit or the first unit to the second unit to obtain implicit data. The initial unit is the unit used when the vehicle operation data is collected. The first unit is different from the second unit. The numerical precision corresponding to the second unit is greater than that corresponding to the first unit. The implicit data corresponding to the target operating data is displayed on one side, and the implicit data is continuously displayed following the acquisition frequency of the target operating data, wherein the target operating data is the selected vehicle operating data.

[0065] In one embodiment, in addition to displaying the first unit of vehicle operation data, a second unit of vehicle operation data is also calculated and treated as implicit data. Conversely, the first unit of vehicle operation data is explicit data. Implicit data is not constantly displayed on the screen; instead, it is displayed next to the selected vehicle operation data. It should be noted that the refresh rate of the implicit data is higher than the refresh rate corresponding to the first unit. Whether a vehicle operation data point is selected can be determined based on the cursor dwell time; for example, if the cursor dwells on a vehicle operation data point for 2 seconds, it is considered selected.

[0066] By setting implicit data, users can see the vehicle operation data of the second unit without switching units, which helps reduce the user's need to switch units and improves the convenience of viewing the displayed vehicle operation data.

[0067] In another embodiment of this application, the step of displaying the corresponding implicit data on one side of the target running data, and the implicit data being continuously displayed following the acquisition frequency of the target running data, includes: A first data list is formed according to the order in which the target running data is acquired; The target running data in the first data list is represented using the second unit to obtain the implicit data and form a second data list; A highlighted floating window is displayed on one side of the target running data. The implicit data is displayed one by one in the order of the data in the second data list in the highlighted floating window, and the switching frequency of the implicit data is the same as the acquisition frequency.

[0068] First, a first data list is generated based on the target data. This first data list has an order, specifically the order in which the data was retrieved. Then, the first data list is converted into a second data list, and finally, the implicit data is displayed one by one according to the sorting of the data in the second list.

[0069] Specifically, in one application scenario, the first unit of the vehicle operating data displayed on the interface is imperial mph, with one decimal place. When a cursor hovers over or a finger long-presses on a vehicle operating data point, a microscope mode is triggered. The microscope mode involves a highlighted floating window appearing next to the original unit, displaying implicit data in a second unit, such as a higher-precision value in metric km / h. This implicit data not only has a different unit but also has 3-4 decimal places, fluctuating in milliseconds following the sampling frequency (i.e., acquisition frequency) of the original data stream. For example, if the idle speed fluctuation is displayed as 60 mph, after the user clicks, the floating window displays "96.542 km / h" with slight fluctuations, helping the user determine if there is high-frequency noise from the sensor.

[0070] As described above, displaying implicit data in a highlighted floating window improves its display effect. Furthermore, the switching frequency of implicit data matches its acquisition frequency, ensuring a consistent switching frequency and facilitating the reflection of changes in vehicle operation data through implicit data.

[0071] In another embodiment of this application, when displaying the implicit data one by one in the second data list in the highlighted floating window, the method further includes: The number of decimal places in the implicit data is determined based on the data type of the target running data and the precision level of the second unit.

[0072] Specifically, for voltage and pressure data types, the number of decimal places of the implicit data is expanded to three to four digits; For data types such as temperature and rotation speed, the number of decimal places of the implicit data is kept to one or two.

[0073] This enables the implicit data to reflect the high-frequency, minute fluctuations of the target operating data at the second unit.

[0074] Specifically, when displaying implicit data in a highlighted floating window, the precision requirements of vehicle operation data of different data types vary significantly. By dynamically determining the number of decimal places, the display precision of implicit data is matched with the physical characteristics of the data type and the precision level of the second unit.

[0075] For voltage-related data, such as oxygen sensor voltage and fuel injection voltage, the numerical changes are often on the order of millivolts or even microvolts. High-precision display is crucial for judging the sensor's operating status and identifying signal drift and high-frequency noise. When the target operating data is voltage-related and the second unit is mV or V, the system expands the decimal places of the implicit data to three to four digits. For example, the oxygen sensor voltage is displayed as "456.3421mV". Repair experts can quickly determine whether there are abnormal fluctuations or poor contact problems in the sensor by observing the high-frequency fluctuations of the last decimal place. For pressure-related data, such as intake manifold pressure and tire pressure, the precise values ​​are also important references for judging the engine's intake status and sealing performance. Therefore, the system also expands the decimal places of such implicit data to three to four digits, for example, displaying it as "101.3254kPa", which helps repair experts identify minute pressure fluctuations.

[0076] For temperature-related data, such as coolant temperature, intake air temperature, and exhaust air temperature, the numerical changes are usually relatively slow. When expressed in degrees Celsius or Fahrenheit, one to two decimal places are sufficient to reflect the actual temperature change trend. Too many decimal places would increase the difficulty of reading the data. Therefore, the system keeps the implicit decimal places of temperature-related data to one to two, for example, displaying it as "92.3℃". For speed-related data, such as engine speed and turbo speed, the values ​​are usually sufficient for diagnostic needs to be expressed as integers or one decimal place. The system also keeps the implicit decimal places of this type of data to one to two, for example, displaying it as "1250.5rpm", ensuring data readability while avoiding visual interference caused by too many decimal places.

[0077] It should be noted that the switching frequency of the implicit data is the same as the acquisition frequency of the target operating data. Therefore, in the highlighted floating window, implicit data of different data types are updated at a frequency of milliseconds. For high-precision data types such as voltage and pressure, since the decimal places are extended to three to four, maintenance experts can clearly observe the high-frequency micro-fluctuations at the end of the value, thereby judging the stability of the sensor signal. For conventional precision data types such as temperature and speed, maintaining one to two decimal places can reflect the actual changes in the data without causing visual fatigue due to too many decimal places.

[0078] By combining the mechanism of displaying implicit data sequentially in the second data list in the highlighted floating window with the dynamic determination of the numerical precision of the implicit data, implicit data of different data types can be displayed with the precision most suitable for their physical characteristics. On the one hand, this helps maintenance experts identify the high-frequency micro-fluctuations of sensors through high-precision implicit data, thereby improving the accuracy of fault diagnosis. On the other hand, it avoids the visual interference caused by excessive precision expansion of conventional precision data types, thus improving the convenience and comfort of data viewing.

[0079] In another embodiment of this application, after displaying the vehicle operation data using the first unit, the method further includes: In response to a unit switching signal, specific operational data requiring unit switching is determined, wherein the specific operational data is the data in the vehicle operational data that requires unit switching upon triggering the unit switching signal; If the data type of the specific operational data belongs to a preset core type and the third unit after switching is the regional unit of the vehicle's place of origin, then the associated operational data is determined based on the vehicle's place of origin and the unit of the associated operational data is switched to the regional unit.

[0080] In one embodiment, when the unit switching button is triggered, a unit switching signal is generated, at which point the units of all vehicle operating data are switched. Prior to this, specific operating data is determined, and then the unit of that specific operating data after switching is designated as the third unit.

[0081] For example, multiple "diagnostic scenario configurations" are pre-set, binding the units of different physical quantities. When a user switches a core unit, the system automatically deduces and switches the associated subordinate units to conform to the standards of a specific region or a specific maintenance manual.

[0082] Scenario A: American muscle car tuning mode.

[0083] Trigger: The user switches the vehicle speed unit from "km / h" to "mph".

[0084] Linkage: The system automatically switches the intake pressure unit from "kPa" to "inHg" (inches of mercury, commonly used in American cars) and the torque unit to "lb-ft" (pounds-feet).

[0085] Scene B: European performance car track mode.

[0086] Trigger: The user switches the temperature unit from "℉" to "℃".

[0087] Linkage: The system automatically locks the boost pressure unit to "Bar" (instead of psi) and the tire pressure unit to "Bar".

[0088] Principle: It conforms to the common standards of European and F1 racing engineering data.

[0089] Principle: Conforms to the data expression conventions of SAE (Society of Automotive Engineers).

[0090] In other words, a "unit compatibility matrix" is maintained. When the main parameter Pmain changes, the matrix is ​​traversed to find the associated parameter Psub. Psub_unit=f(Pmain_unit,Region_Standard); Among them, Region_Standard is the country of origin standard (such as VIN) automatically identified by the system based on the vehicle model's VIN code. (Items starting with 1 will automatically recommend US-made collaborations, while those starting with W will recommend European-made collaborations).

[0091] Specifically, when the unit of a core parameter (such as vehicle speed) is changed, the system will automatically change the units of other related parameters (such as tire pressure and torque) to the matching unit system at once, based on the vehicle's "nationality" (where the vehicle is produced).

[0092] Pmain (main parameter): This is the "trigger" for the operation. For example, clicking on the screen switches the "speed" from km / h to mph.

[0093] Region_Standard: This is the system's "knowledge base." The system reads the vehicle's VIN (Vehicle Identification Number) to determine whether the car is an American (e.g., Ford), European (e.g., BMW), or Japanese (e.g., Toyota). Repair practices differ across regions.

[0094] Psub_unit (unit of associated parameters): This is a "chain reaction" that is automatically executed by the system. Once the main parameter changes, the system will automatically switch the units of tire pressure, intake pressure, torque, etc., to the standard used in that region.

[0095] The unit compatibility matrix is ​​as follows: The above features demonstrate how the automatic switching of units associated with Xining data to regional units through core unit type switching improves the intelligence of unit switching and reduces the need for users to manually switch units.

[0096] In another embodiment of this application, the step of determining the associated operational data based on the vehicle's place of origin and switching the unit of the associated operational data to a regional unit includes: Obtain the vehicle identification number (VIN) of the vehicle corresponding to the vehicle operation data; The vehicle's place of origin is determined based on the vehicle identification number (VIN). The target data type corresponding to the vehicle's place of origin and the regional unit of the target data type are searched in the preset unit compatibility matrix. The unit compatibility matrix is ​​a matrix showing the correspondence between the core type, vehicle place of origin, target data type and regional unit. The vehicle operation data of the target data type is determined as the associated operation data; The associated operational data is represented using the corresponding regional units.

[0097] Through the above content and the association between units, the entire set of units is automatically adapted, reducing the risk of misjudgment caused by unit confusion.

[0098] In one embodiment, the vehicle diagnostic device includes a front-facing camera and a light intensity detector, and the method further includes: It acquires user facial images captured by the front-facing camera and light intensity data collected by the light intensity detector; The positional relationship between the user and the display screen of the vehicle diagnostic equipment is determined based on the camera parameters of the front-facing camera and the user's facial image. Determine the direction of light outside the display screen based on light intensity data; Determine the display area with relatively low reflectivity in the display screen based on the positional relationship and the direction of light; The display area shows vehicle operation data.

[0099] Specifically, in one embodiment, the process of determining the positional relationship between the user and the display screen of the vehicle diagnostic equipment includes: The diagnostic device uses a built-in front-facing camera or infrared sensor to capture images of the user's face (facial or eye images). Image processing algorithms (such as pupil localization) are then used to determine the user's lateral offset angle (θ) relative to the screen (θ represents the angle by which the user's gaze deviates horizontally from the center of the screen – i.e., looking left or right) and vertical offset angle (φ) (φ represents the angle by which the user's gaze deviates vertically from the center of the screen – i.e., looking up or down)), as well as the distance (D) between the user and the screen. This process can be achieved through the following steps: Image frames are acquired, and face regions are detected using a Haar cascade classifier or a deep learning model (such as MTCNN). The gaze direction vector is calculated based on facial key points (such as the center of the eyes). Combining the camera intrinsic parameter matrix and calibration parameters, the angle between the user's gaze and the screen normal is calculated, thereby determining the user's position coordinates (X,Y,Z).

[0100] The specific steps are as follows: (a) Hardware deployment and parameter preset (system calibration).

[0101] Before performing real-time calculations, obtain the device's inherent parameters (intrinsic parameters) and sensor layout parameters (extrinsic parameters, including camera parameters).

[0102] 1. Hardware layout: Infrared camera: Installed in the center of the screen bezel, with its optical axis perpendicular to the screen plane.

[0103] Infrared LED light source: arranged on both sides or coaxially with the camera, used to generate corneal reflective light spots (Pulchin image) on the surface of the eyeball.

[0104] 2. Parameter acquisition method: Focal length (f): Obtained from the camera module specifications or calculated using the checkerboard calibration method (unit: pixels).

[0105] Principal point (Cx, Cy): The coordinates of the optical center on the image sensor, usually set to half the image resolution (e.g., 640 / 2), and fine-tuned through calibration.

[0106] Baseline distance (b): If a binocular infrared camera is used, it refers to the physical distance between the optical centers of the two cameras (unit: mm).

[0107] (II) Image processing and feature extraction process.

[0108] The system acquires infrared image streams in real time and extracts the coordinates of key feature points through the following algorithm steps: Step 1: Image preprocessing.

[0109] Operation: Since the pupil appears bright (bright pupil effect) or a high-contrast dark area under infrared light, the acquired grayscale image is first denoised by Gaussian filtering, and then the Otsu method is used for adaptive threshold segmentation to separate the eye area from the background.

[0110] Step 2: Pupil center positioning P pixel .

[0111] Algorithm: Extract the eye contour using edge detection operators (such as Canny or Sobel). Fit the pupil edge using Hough Circle Transform or ellipse fitting algorithm.

[0112] Output value: The pixel coordinates (u) of the pupil center on the image sensor. p ,v p ).

[0113] Step 3: Corneal Reflection Spot Localization G pixel .

[0114] Principle: The reflected light spot (Glare) formed by the infrared LED on the corneal surface is relatively fixed in position and does not move significantly with eye movement.

[0115] Algorithm: Find the cluster of pixels with the highest brightness within the eye region and calculate its centroid.

[0116] Output value: The pixel coordinates of the center of the light spot (u) g ,v g ).

[0117] (III) Formula for calculating spatial coordinates.

[0118] Using the extracted pixel coordinates and preset parameters, the user's three-dimensional spatial position (X,Y,Z) is inferred through a geometric optics model.

[0119] 1. Determine the line-of-sight vector and distance (Z).

[0120] This utilizes the relationship between the pupil-corneal vector (P-CR Vector) and distance. As the user moves further away from the screen, the pixel distance between the pupil center and the corneal spot on the image changes proportionally (parallax).

[0121] Vector computation: First, calculate the vectors on the image plane: : =(u p -u g ,v p -v g ); Distance (Z) estimation formula: Based on the pinhole imaging model and eyeball geometry, distance Z and vector magnitude | |Approximately inversely proportional (needs to be considered in conjunction with calibration coefficient k): Z≈ ; "The coefficient k is a system calibration constant. Its initial value is determined based on the geometric difference between the standard human corneal curvature radius (approximately 7.8 mm) and pupil depth (approximately 3.5 mm), and is corrected during the device initialization phase through the user distance calibration procedure." A more accurate method is to use binocular vision (if equipped with dual infrared cameras) and directly calculate the depth using the parallax formula: Z= ; in, It is the horizontal parallax of the same feature point in the left and right camera images.

[0122] 2. Determine the horizontal (X) and vertical (Y) positions.

[0123] Once the depth Z is obtained, the pixel coordinates can be mapped back to physical space coordinates using the principle of similar triangles.

[0124] Calculation formula: ; ; illustrate: X: The horizontal offset distance (mm) of the user relative to the center of the screen, i.e., whether the user's eyes are on the left or right side of the screen, and how many millimeters off.

[0125] Y: The vertical offset distance (mm) of the user relative to the center of the screen, i.e., whether the user's eyes are above or below the screen, and how many millimeters off.

[0126] Z: Vertical distance (mm) from the user's eyes to the screen plane, i.e., how far the user's face is from the screen.

[0127] 3. Determine the line-of-sight angle (θ, ) To accurately calculate the "sharp position" on the screen, the system needs to know not only the user's distance from the screen (depth Z), but also the specific direction the user's eyes are looking at the screen. This requires deducing the gaze angle in three-dimensional space from two-dimensional image features. The specific steps are as follows: (1) Constructing the optical axis vector ( ) .

[0128] The optical axis is the axis of symmetry of the eye's geometry, and is usually defined as a vector pointing from the center of eye rotation to the center of the pupil.

[0129] Step description: The three-dimensional coordinates of the pupil center calculated using the aforementioned steps (That is, (X,Y,Z) mentioned above is the bridge connecting "2D image pixels" and "3D spatial angles". It is the virtual position of the user's eyes constructed in the computer after mathematical conversion of the image captured by the camera).

[0130] Estimating the center of eye rotation Because the eyeball rotates within the eye socket, its center of rotation is relatively fixed. In the simplified model, It can be considered as a point located behind the center of the pupil, offset by a distance equal to the radius of the eyeball along the normal direction of the face (the "center of eyeball rotation" is a point calculated further back from this (X,Y,Z) (usually a position about 12mm back in the Z-axis direction)).

[0131] Calculation formula: First, calculate the uncorrected optical axis unit vector. : ; in, The three-dimensional coordinates of the pupil center in the camera coordinate system. The three-dimensional coordinates of the center of eye rotation. Represents the magnitude of a vector, used for vector normalization.

[0132] (2) View axis correction and rotation matrix Rk.

[0133] The optical axis (anatomical axis) of the human eye does not coincide with the visual axis (the axis of the actual gaze direction). There is a fixed angle k (Kappa angle) between the two, usually about 5°, and the direction is usually biased towards the nasal side (temporal side).

[0134] Step description: To obtain the true gaze direction, the optical axis vector must be rotated. This transformation is achieved using the rotation matrix R(κ).

[0135] Parameters determined: k-value: The initial value can be set to 5° (approximately 0.087 radians). In the device's advanced settings, the user can use the "five-point calibration method" to fixate on a specific point on the screen, and the system will automatically calculate and update the device's unique k-value.

[0136] Rotation matrix formula: Assuming the main deviations occur in the horizontal direction (X-axis) and the vertical direction (Y-axis), the rotation matrix R(κ) can be expressed as the product of the horizontal rotation matrix Rx(κx) and the vertical rotation matrix Ry(κy): R(κ) = Ry(κy)·Rx(κx); ; (3) Calculate the final line-of-sight vector ( ) .

[0137] By combining the optical axis vector and the correction matrix, the user's actual line-of-sight direction vector is obtained.

[0138] • Calculation formula: ; It is a three-dimensional unit vector.

[0139] (4) Calculate the line-of-sight angle (θ, ) Finally, the 3D view vector is converted into an angle in spherical coordinates for subsequent calculation of the projection position on the screen.

[0140] definition: θ (Theta): Horizontal viewing angle, representing the angle at which the line of sight deviates from the center normal of the screen on the horizontal plane.

[0141] (Phi): Vertical viewing angle, which represents the angle at which the line of sight deviates from the horizontal plane on the vertical plane.

[0142] Calculation formula: Using the arctangent and arcsine functions for conversion: θ = arctan2(Vx, Vz); =arcsin(Vy); arctan2(Vx,Vz) is a two-parameter arctangent function.

[0143] (IV) Summary: Parameter Acquisition and Calculation Flow.

[0144] Through the above process, the diagnostic device can not only determine "where the user is looking" (gaze point), but also accurately calculate "where the user is sitting" (spatial coordinates (X, Y, Z)), thus providing precise input parameters for subsequent calculation of the screen's clear position based on light direction. 2. Determine the direction of the light outside the display screen.

[0145] The device collects ambient light intensity data from different directions using a built-in ambient light sensor (ALS) or a multi-point light intensity detection module. Combining this with sensor placement (such as four-quadrant photodiodes), it estimates the direction vectors (Lx, Ly, Lz) of the main interfering light source using triangulation or weighted averaging algorithms. For example, if the light intensity on the left is significantly higher than on the right, the main light source is determined to be from the left, with a direction angle of α.

[0146] The core objective of this step is to detect interfering light sources in the environment (such as overhead lights or sunlight coming from the window) and determine the direction from which the light is directed toward the screen.

[0147] 1. Data Source Hardware carrier: Ambient light sensor: It is usually installed around the screen bezel of the diagnostic device (such as the top, bottom, left, and right sides) or at the four corners.

[0148] Multi-point light intensity detection module: can use four-quadrant photodiodes, or arrange multiple independent photodiodes in different positions on the device casing.

[0149] Data collection: Illumination intensity value: Each sensor outputs an analog or digital signal representing the illumination intensity in that direction (usually measured in Lux).

[0150] Data set: Assuming four sensors are arranged around the device, the system will obtain a set of data {Itop, Ibottom, Ileft, Iright}, which represent the light intensity in the four directions of up, down, left, and right, respectively.

[0151] 2. Basis for calculation.

[0152] The system uses geometric relationships to infer the azimuth angle of the light source by comparing the differences in light intensity received by sensors in different directions.

[0153] Basic principle: Light intensity difference positioning method.

[0154] If the light source is directly in front, the light intensity received by the surrounding sensors will theoretically be similar.

[0155] If the light source is on the left, the reading of the left sensor will be significantly higher than that of the right sensor.

[0156] Algorithm logic (taking horizontal angle α as an example): The angle is estimated using the ratio of the light intensity difference to the sum of the light intensity from the left and right sensors, through the arctangent function. ; Where k h This is the geometric correction factor in the horizontal direction (used to correct the effect of sensor layout on angle calculation).

[0157] The calculation of the vertical direction angle β is similar: ; If the sensor is installed at the four corners of the screen bezel (with a relatively wide spacing), the coefficient k is usually between 0.6 and 0.9.

[0158] 3. Explanation of meaning Direction vector L = (Lx, Ly, Lz): This is a three-dimensional unit vector that describes the direction in which interfering light rays enter the screen.

[0159] For example, vector (1,0,0) represents light entering horizontally from the right; vector (0,0,1) represents light entering vertically from the front of the screen.

[0160] Direction angles α and β: α (horizontal angle): Represents the left and right deflection angle of the main light source relative to the screen normal. If Ileft If Iright, then α points to the left, meaning that glare is more likely to occur on the right side of the screen.

[0161] β (vertical angle): Represents the vertical tilt angle of the main light source relative to the screen normal. If Itop Ibottom, β points downwards (top light), meaning that the lower half of the screen is prone to reflections.

[0162] 3. Determine the display area with relatively low reflectivity in the display screen.

[0163] Based on the user's position and the direction of the main light source, calculate the "clear display area" on the screen that is least affected by glare and has the highest visual contrast. This area can be quantified using the following formula: Define the screen coordinate system: with the center of the screen as the origin O(0,0), the positive x-axis is horizontal to the right, and the positive y-axis is vertical upward.

[0164] This step is the core algorithm. It uses the user's line of sight (from step one) and the direction of the light source (from step two) to calculate where the screen is brightest and where there is reflection, thereby avoiding displaying icons in reflective areas.

[0165] 1. Data Source Input parameters: User gaze vector V: from the calculation result in step one (sinθ) cos sin cosθ cos ).

[0166] The main light source vector L: derived from the calculation result in step two (sinα) cosβ, sinβ, cosα cosβ).

[0167] Screen normal vector N: fixed at (0,0,1), representing that the screen is perpendicular to the Z-axis.

[0168] 2. Basis for calculation.

[0169] The system quantifies the "unreadable degree" of each point (x,y) on the screen by constructing a glare impact factor model G(x,y).

[0170] Core formula: ; Formula Explanation: The first term (specular reflection term): k1·max(0,L·R(x,y)); Principle: Based on the law of optical reflection. When the incident light L and the reflected light R (pointing from the screen to the human eye) are in the same direction, the dot product L·R is at its maximum, indicating that strong specular reflection (glare) has occurred.

[0171] Parameter description: R(x,y) is the reflection direction vector from point (x,y) to the user's eye; Objective: To identify the area on the screen with the most severe glare.

[0172] Second item (viewpoint correction): k2·∣V·N cosγ∣; Principle: Consider the angle between the user's line of sight and the screen normal. When the user looks at the screen from the side, the contrast usually decreases.

[0173] Parameter description: γ is the angle between the line of sight and the screen normal; Objective: To perform weighted correction of image clarity based on the user's viewing angle.

[0174] Weighting coefficients k1, k2: The brightness is dynamically adjusted based on the overall brightness detected by the ambient light sensor. The stronger the ambient light, the larger k1 becomes, and the higher the weight of the influence of reflected light.

[0175] Finding the optimal position (the clear position (xc, yc) is the position that minimizes the glare effect): By minimizing the glare effect factor, the optimal display coordinates (xc, yc) are found: ; This means that the system will search for the point with the smallest G(x,y) value within the selectable area of ​​the current icon.

[0176] 3. Explanation of meaning.

[0177] Clear location (xc, yc): These are the calculated optimal display coordinates.

[0178] At this location, ambient light reflection interference is minimal, and it meets the user's optimal viewing angle.

[0179] Focus icon displays dynamically: Final result: The system will not rigidly fix the "hand icon" or highlight box in the center or lower right corner of the icon, but will dynamically shift it to the vicinity of (xc, yc) based on the calculation results.

[0180] For example, if strong light is detected coming from the left (α points to the left), a reflection will occur on the left side of the screen. The algorithm calculates (xc, yc) and automatically shifts it to the right side of the icon to ensure that the highlighted tooltip is always displayed on the backlit side (dark side), thus guaranteeing that it is clearly visible to the user.

[0181] Based on the above, the system can automatically calculate the clear position of the screen and display the vehicle operation data in the clear position, that is, the display area with relatively low reflectivity, which helps to improve the clarity and ease of viewing of the display content of the vehicle diagnostic equipment.

[0182] This application also provides an electronic device, including a memory and a processor; The memory stores a data display program; The processor implements the method described above when executing the data display program.

[0183] Specifically, such as Figure 2 As shown, the electronic device includes a processor 100, at least one communication bus 200, a user interface 300, at least one external communication interface 400, and a memory 500. The communication bus 200 is configured to enable communication between these components. The user interface 300 may include a display screen, and the external communication interface 400 may include standard wired and wireless interfaces. The memory 500 stores a vehicle logo display method. The processor 100 is used to employ the aforementioned method when executing the vehicle logo display method stored in the memory 500.

[0184] This application also provides a computer storage medium storing a program that implements the method described above.

[0185] This application also provides an automotive diagnostic device, including a device body, a display screen, and a controller; The controller stores a data display program, and the controller implements the method described above when running the data display program.

[0186] The above description discloses only preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A data display method for an automotive diagnostic device, applied to an automotive diagnostic device, the method comprising: The vehicle diagnostic equipment is configured with multiple diagnostic items, each of which corresponds to the vehicle operation data that needs to be acquired. The first unit used when displaying the vehicle operation data is determined based on the project requirements of the diagnostic project, the user identity, and the data status of the vehicle operation data. The vehicle operation data is displayed using the first unit, wherein the value of the vehicle operation data changes with the unit.

2. The data display method for automotive diagnostic equipment according to claim 1, characterized in that, The project requirements include requirements for the standard units used in the first type of operational data; the user identities include novice repairmen and repair experts; the data conditions include numerical values; and the vehicle operational data includes the first type of operational data and the second type of operational data other than the first type of operational data. The step of determining the first unit used when displaying the vehicle operation data based on the project requirements of the diagnostic project, user identity, and the data status of the vehicle operation data includes: If the user is a new maintenance worker, then the standard unit is determined as the first unit of the first type of operating data, and the first unit of the second type of operating data is determined as the unit pre-associated with the standard unit, wherein the pre-associated unit is the unit that is used most often with the standard unit. If the user is the maintenance expert, then it is determined whether the value of the first type of operating data using the standard unit is less than a preset value threshold and whether the value of the second type of operating data using the initial unit is less than the value threshold, wherein the initial unit is the unit used when collecting the vehicle operating data; If the value of the first type of operating data using the standard unit is less than the value threshold, then the first unit of the first type of operating data is determined from the candidate units of the first type of operating data. If the value of the initial unit used by the second type of operating data is less than the value threshold, then the first unit of the second type of operating data is determined from the candidate units of the second type of operating data. The value of the vehicle operating data using the first unit is greater than the value threshold and is within a preset value range. Otherwise, the standard unit and the initial unit are determined to be the corresponding first unit.

3. The data display method for the automotive diagnostic equipment according to claim 2, characterized in that, The project requirements include requirements for the standard units used in the first type of operational data; the user identities include novice repairmen and repair experts; the data information includes the number of data types; and the vehicle operational data includes the first type of operational data and the second type of operational data in addition to the first type of operational data. The step of determining the first unit used when displaying the vehicle operation data based on the project requirements of the diagnostic project, user identity, and the data status of the vehicle operation data includes: If the user is a new maintenance worker, then the standard unit is determined as the first unit of the first type of operating data, and the first unit of the second type of operating data is determined as the unit pre-associated with the standard unit, wherein the pre-associated unit is the unit that is used most often with the standard unit. If the user is the maintenance expert, then determine whether the number of data types of the vehicle operation data exceeds the preset screen capacity threshold. If so, the unit with a character count less than the initial unit is determined as the first unit, wherein the character count refers to the number of characters in the unit or the total number of characters in the unit and the corresponding value, and the initial unit is the unit used when collecting vehicle operation data.

4. The data display method of the automotive diagnostic equipment according to claim 1, characterized in that, After displaying the vehicle operation data using the first unit, the method further includes: The vehicle operation data is converted from the initial unit or the first unit to the second unit to obtain implicit data. The initial unit is the unit used when the vehicle operation data is collected. The first unit is different from the second unit. The numerical precision corresponding to the second unit is greater than that corresponding to the first unit. The implicit data corresponding to the target operating data is displayed on one side, and the implicit data is continuously displayed following the acquisition frequency of the target operating data, wherein the target operating data is the selected vehicle operating data.

5. The data display method of the automotive diagnostic equipment according to claim 4, characterized in that, The step of displaying the corresponding implicit data on one side of the target running data, with the implicit data being displayed continuously following the acquisition frequency of the target running data, includes: A first data list is formed according to the order in which the target running data is acquired; The target running data in the first data list is represented using the second unit to obtain the implicit data and form a second data list; A highlighted floating window is displayed on one side of the target running data. The implicit data is displayed one by one in the order of the data in the second data list in the highlighted floating window, and the switching frequency of the implicit data is the same as the acquisition frequency.

6. The data display method of the automotive diagnostic equipment according to claim 1, characterized in that, After displaying the vehicle operation data using the first unit, the method further includes: In response to a unit switching signal, specific operational data requiring unit switching is determined, wherein the specific operational data is the data in the vehicle operational data that requires unit switching upon triggering the unit switching signal; If the data type of the specific operational data belongs to a preset core type and the third unit after switching is the regional unit of the vehicle's place of origin, then the associated operational data is determined based on the vehicle's place of origin and the unit of the associated operational data is switched to the regional unit.

7. The data display method of the automotive diagnostic equipment according to claim 6, characterized in that, The step of determining the associated operational data based on the vehicle's place of origin and switching the unit of the associated operational data to a regional unit includes: Obtain the vehicle identification number (VIN) of the vehicle corresponding to the vehicle operation data; The vehicle's place of origin is determined based on the vehicle identification number (VIN). The target data type corresponding to the vehicle's place of origin and the regional unit of the target data type are searched in the preset unit compatibility matrix. The unit compatibility matrix is ​​a matrix showing the correspondence between the core type, vehicle place of origin, target data type and regional unit. The vehicle operation data of the target data type is determined as the associated operation data; The associated operational data is represented using the corresponding regional units.

8. An electronic device, characterized in that, Including memory and processor; The memory stores a data display program; The processor implements the method of any one of claims 1-7 when executing the data display program.

9. A computer storage medium, characterized in that, The system contains a program for implementing the method described in any one of claims 1-7.

10. An automotive diagnostic device, characterized in that, Includes the main body of the equipment, the display screen, and the controller; The controller stores a data display program, and when the controller runs the data display program, it implements the method described in any one of claims 1-7.

Images