A vehicle data processing method and a vehicle data processing system

Abstract

The application discloses a vehicle data processing method and a vehicle data processing system, relates to the technical field of vehicle data processing, and locks a standard change curve based on the change amplitude of an accelerator, compares the standard change curve with a normal speed curve one by one, determines whether the fuel consumption curve needs to be analyzed based on the comparison result, confirms whether the change amplitudes between the fuel consumption curve and the standard speed curve are consistent, determines whether the fuel supply is abnormal by whether the change trends between line segments are consistent, displays the fuel supply abnormal signal, locks the corresponding time period, confirms whether the change amplitudes between each different line segment are consistent based on the slope value, and does not need to be processed if they are consistent, so that the overall state of the vehicle can be analyzed one by one, the comprehensiveness of data processing is ensured, the overall effect of data processing is improved, and abnormal conditions can be locked in time.

Description

Technical Field

[0001] This invention belongs to the field of vehicle data processing technology, specifically a vehicle data processing method and a vehicle data processing system. Background Technology

[0002] Vehicle operation data refers to a series of parameters during vehicle operation, including real-time vehicle location, driving trajectory, engine start and stop time, engine temperature, engine speed, throttle opening, idling time, continuous engine operating hours, battery voltage, whether the air conditioner is on, transmission gear information, transmission shift mode, vehicle speed, and driver operating habits.

[0003] Patent application CN110390739B discloses a vehicle data processing method and system, relating to the field of vehicle communication. The vehicle data processing method is used to process data generated by the vehicle's autonomous driving, including sending real-time data generated when the vehicle is in autonomous driving mode to a cloud data analysis platform. The cloud data analysis platform receives and analyzes the real-time data and stores the real-time data analysis results, so that when a query request is received from a user, the real-time data analysis results corresponding to the query request are sent to the user. This invention also provides a corresponding system; this invention not only improves vehicle data processing efficiency but also effectively enhances user satisfaction.

[0004] The vehicle data processing simply analyzes the driving data to determine if there are any abnormalities in the vehicle's operation. However, this method of analysis and processing can only achieve a relatively superficial processing effect. It cannot delve into the internal structure of the vehicle based on the processed data and driving data, pinpoint the corresponding cause of such abnormalities, and display the information to facilitate subsequent maintenance personnel in their inspection and processing. Summary of the Invention

[0005] The present invention aims to at least solve one of the technical problems existing in the prior art; to this end, the present invention proposes a vehicle data processing method and a vehicle data processing system to solve the technical problem that simply processing driving data to determine whether vehicle driving has become abnormal is not a comprehensive approach.

[0006] To achieve the above objectives, according to an embodiment of the first aspect of the present invention, a vehicle data processing method and a vehicle data processing system are provided, comprising:

[0007] The data monitoring terminal monitors the vehicle's throttle input and speed data, and transmits the monitored throttle input and speed data to the anomaly locking terminal.

[0008] The anomaly locking end analyzes whether the acceleration between the speed data meets the standard based on the monitored throttle amplitude and speed data. If it does not meet the standard, an abnormal signal is generated and the periodic data analysis end is executed. If it meets the standard, no processing is performed.

[0009] The periodic data analysis terminal, based on the confirmed abnormal signals, defines a set of monitoring cycles and re-monitors the vehicle's throttle input and speed data through the data monitoring terminal, as well as fuel consumption parameters. Based on several sets of monitored parameters, it analyzes whether there are any fuel delivery problems during vehicle operation and generates abnormal or normal fuel delivery signals, including:

[0010] Based on the defined monitoring period T, where T is a preset value, the throttle amplitude monitored within this monitoring period T is transmitted to the standard curve generation model, where the standard curve generation model is a preset model. Based on the throttle amplitude, the standard curve generation model generates the standard speed curve of this vehicle, where the initial value of the standard speed curve is the speed data corresponding to the beginning of this monitoring period T.

[0011] Based on the speed data and fuel consumption parameters monitored within this monitoring period T, a speed change curve and a fuel consumption curve are generated.

[0012] Compare the magnitude of change between the speed change curve and the standard speed curve:

[0013] Based on the time trend, the slope of the points in the same time period within the two sets of curves is confirmed, where the point slope = Δy / Δx, and Δ is the difference between the coordinate parameters of the later point and the coordinate parameters of the earlier point. Based on the confirmed slope, it is determined whether the values ​​in the same time period are consistent. If they are consistent, no processing is performed. If there are inconsistent time periods, the fuel consumption curve is compared with the standard speed curve to confirm whether the fuel supply is abnormal.

[0014] Methods for comparing fuel consumption curves with standard speed curves include:

[0015] Identify the fluctuation points that appear within the standard velocity curve, where the acceleration of the line segments before and after the fluctuation points is different. Based on the fluctuation points, divide the standard velocity curve into several equally divided velocity segments and identify the corresponding time periods of the equally divided segments, which are then marked as equally divided velocity time periods.

[0016] The fuel consumption curve is processed in the same way to identify fluctuation points, then fuel equal segmentation line segments are identified, and then fuel equal segmentation time periods are locked based on fuel equal segmentation line segments.

[0017] The speed and fuel consumption time intervals are compared one by one to determine whether the comparison results are consistent. If they are consistent, the torque parameter analysis is executed. If they are inconsistent, an abnormal fuel supply signal is generated and displayed through the signal generation terminal.

[0018] The torque parameter analysis terminal defines a second monitoring cycle and keeps the vehicle gear constant. The data monitoring terminal monitors the torque change data for the second monitoring cycle and generates a torque change curve based on this data. The torque change curve is then compared with the speed change curve generated during this monitoring cycle to perform numerical change analysis. Based on the analysis results, a processing signal is generated. Specifically:

[0019] Based on several fluctuation points appearing within the velocity change curve, the velocity change curve is divided into several velocity change segments. The velocity change segments with an upward trend are identified and marked as upward segments.

[0020] The time period in which each climbing segment appears is marked as the climbing time period. Based on this climbing time period, a line segment is extracted from the torque change curve. The segment in the torque change curve that is the same as the climbing time period is marked as the torque segment to be compared.

[0021] The slope of different climbing segments is denoted as Xi, and the slope of different torque segments to be compared is denoted as Bi. If multiple sets of slopes appear within different torque segments to be compared, the average value is processed to determine the slope of the corresponding torque segment, where i = 1, 2, ..., n, and n represents the total number of different time periods.

[0022] Analyze whether Xi and Bi satisfy the following: If the condition is met, it means that the torque of the vehicle is normal, no signal is generated, and the vehicle is monitored again. If the condition is not met, an abnormal torque change signal is generated through the signal generation terminal.

[0023] Preferably, a vehicle data processing method includes the following steps:

[0024] Step 1: Monitor the vehicle's throttle input and speed data, analyze whether the acceleration between speed data meets the standard. If it does not meet the standard, generate an abnormal signal and execute the periodic data analysis. If it meets the standard, no processing is performed.

[0025] Step 2: Based on the confirmed abnormal signals, define a set of monitoring cycles and re-monitor the vehicle's throttle amplitude and speed data through the data monitoring terminal, and monitor the fuel consumption parameters. Based on the monitored parameters, analyze whether there is a fuel supply problem during vehicle operation, and generate a fuel supply problem signal or a normal fuel supply signal.

[0026] Step 3: Define the second monitoring cycle and keep the vehicle gear unchanged. Monitor the torque change data of the second monitoring cycle through the data monitoring terminal, generate a torque change curve based on this torque change data, and perform numerical change analysis on the torque change curve and the speed change curve generated in this monitoring cycle. Generate a processing signal based on the analysis results.

[0027] Compared with the prior art, the beneficial effects of the present invention are: locking the standard change curve based on the change range of throttle, comparing the standard change curve with the normal speed curve one by one, and determining whether the fuel consumption curve needs to be analyzed based on the comparison results. By confirming whether the change range between the fuel consumption curve and the standard speed curve is consistent, the change range can be determined by whether the change trend between the line segments is consistent, and the abnormal fuel supply signal is displayed.

[0028] If there are no issues with throttle input, then torque monitoring and analysis are performed to pinpoint the corresponding time period. Based on this time period, the torque change curve for the corresponding segment is identified. By analyzing the slope of the change, it can be determined whether the change amplitude between each segment is consistent. If they are all consistent, no action is required. If they are not consistent, it indicates that the degree of torque change is inconsistent. This method allows for a comprehensive analysis of the vehicle's overall condition, ensuring the completeness of data processing and improving the overall effectiveness of data processing, thereby promptly identifying abnormal situations. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the principle framework of the present invention;

[0030] Figure 2 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0031] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. 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.

[0032] Example 1

[0033] Please see Figure 1 This application provides a vehicle data processing system, including a data monitoring terminal, an anomaly locking terminal, a periodic data analysis terminal, a standard curve generation model, a torque parameter analysis terminal, and a signal generation terminal;

[0034] The data monitoring end is electrically connected to the input nodes of the standard curve generation model, the anomaly locking end, and the torque parameter analysis end, respectively. The anomaly locking end is electrically connected to the input node of the periodic data analysis end. The standard curve generation model, the periodic data analysis end, and the torque parameter analysis end are electrically connected sequentially from the output node to the input node. The periodic data analysis end and the torque parameter analysis end are both electrically connected to the input node of the signal generation end.

[0035] The data monitoring terminal monitors the vehicle's throttle amplitude and speed data, and transmits the monitored throttle amplitude and speed data to the variable locking terminal. The specific monitoring method is determined by the sensor, and the monitored data is all real-time data.

[0036] The anomaly locking mechanism analyzes whether the acceleration between the monitored throttle amplitude and speed data meets the standard. If it does not meet the standard, an anomaly signal is generated, and the periodic data analysis mechanism is executed. If it meets the standard, no processing is performed. The specific method for analyzing whether the acceleration meets the standard is as follows:

[0037] Based on the monitored throttle amplitude, the change in throttle amplitude per unit time is confirmed, and the acceleration parameters per unit time are confirmed based on the speed data.

[0038] The throttle amplitude change value is calibrated as FD, and the acceleration parameter is calibrated as JS. Analyze whether FD satisfies: FD×C1=JS, where C1 is a preset value, and its specific value is determined by the operator based on experience. If it is satisfied, it means that the vehicle data is running normally. If it is not satisfied, an abnormal signal is generated and the periodic data analysis terminal is executed.

[0039] Specifically, during normal operation, the vehicle's acceleration is related to the change in throttle, and there is a corresponding preset factor. When the change in throttle is changed, the corresponding acceleration can be locked based on the preset factor, thereby confirming whether the vehicle's acceleration is running normally.

[0040] The periodic data analysis module, based on the confirmed abnormal signals, defines a set of monitoring cycles and re-monitors the vehicle's throttle input and speed data, as well as fuel consumption parameters. Based on the monitored parameters, it analyzes whether there are any fuel delivery issues during vehicle operation and generates abnormal or normal fuel delivery signals. The specific analysis method is as follows:

[0041] Based on the defined monitoring period T, where T is a preset value and its specific value is determined by the operator based on experience, the throttle amplitude monitored within this monitoring period T is transmitted to the standard curve generation model, where the standard curve generation model is a preset model. The standard curve generation model generates the standard speed curve of this vehicle based on the throttle amplitude, where the initial value of the standard speed curve is the speed data corresponding to the beginning of this monitoring period T.

[0042] Based on the speed data and fuel consumption parameters monitored within this monitoring period T, a speed change curve and a fuel consumption curve are generated.

[0043] Compare the magnitude of change between the speed change curve and the standard speed curve:

[0044] Based on the time trend, the slope of the points in the same time period within the two sets of curves is confirmed, where the slope of the point = Δy / Δx, and Δ is the difference between the coordinate parameters of the later point and the coordinate parameters of the earlier point. Based on the confirmed slope, it is determined whether the values ​​in the same time period are consistent. If they are consistent, no processing is performed. If there are inconsistent time periods, subsequent analysis is performed.

[0045] Compare the fuel consumption curve with the standard speed curve:

[0046] Identify the fluctuation points that appear within the standard velocity curve, where the acceleration of the line segments before and after the fluctuation points is different. Based on the fluctuation points, divide the standard velocity curve into several equally divided velocity segments and identify the corresponding time periods of the equally divided segments, which are then marked as equally divided velocity time periods.

[0047] The fuel consumption curve is processed in the same way to identify fluctuation points, then fuel equal segmentation line segments are identified, and then fuel equal segmentation time periods are locked based on fuel equal segmentation line segments.

[0048] The system compares the calibrated speed and fuel time intervals one by one to determine if the comparison results are consistent. If they are consistent, the system executes the torque parameter analysis. If they are inconsistent, the system generates an abnormal fuel supply signal and displays it.

[0049] Specifically, based on the determined monitoring period, the different related curves that appear within this period are confirmed. Since the throttle amplitude is related to the speed curve, the corresponding standard speed curve can be confirmed by the corresponding throttle amplitude. Then, the normal speed curve is confirmed based on the normal speed change. The normal speed curve and the standard speed curve are compared one by one to confirm whether the change between the throttle and the normal speed curve is consistent.

[0050] If there is an inconsistency, the first step is to confirm whether there is an abnormality in the fuel supply. This can be done by checking whether the change range between the fuel consumption curve and the standard speed curve is consistent. The change range can be determined by whether the change trend between the line segments is consistent. At the same time, the abnormal fuel supply signal should be displayed to improve the comprehensiveness of the vehicle data processing process.

[0051] If there is a consistent situation, then there is no abnormality in the throttle delivery. In that case, the abnormality is caused by the change in the vehicle's torque. Therefore, it is necessary to re-analyze the change in the vehicle's torque by executing the torque parameter analysis terminal.

[0052] The torque parameter analysis terminal defines a second monitoring cycle and keeps the vehicle gear constant. It monitors the torque change data for the second monitoring cycle via a data monitoring terminal, generates a torque change curve based on this data, and performs numerical change analysis on the torque change curve and the speed change curve generated in the same monitoring cycle. Based on the analysis results, a processed signal is generated and displayed. The specific method for performing the numerical change analysis is as follows:

[0053] Based on several fluctuation points appearing within the velocity change curve, the velocity change curve is divided into several velocity change segments. The velocity change segments with an upward trend are identified and marked as upward segments. The method for identifying fluctuation points is the same as that for identifying fluctuation points in the standard velocity curve.

[0054] The time period in which each climbing segment appears is marked as the climbing time period. Based on this climbing time period, a line segment is extracted from the torque change curve. The segment in the torque change curve that is the same as the climbing time period is marked as the torque segment to be compared.

[0055] The slope of different climbing segments is denoted as Xi, and the slope of different torque segments to be compared is denoted as Bi. If multiple sets of slopes appear within different torque segments to be compared, the average value is processed to determine the slope of the corresponding torque segment, where i = 1, 2, ..., n, and n represents the total number of different time periods.

[0056] Analyze whether Xi and Bi satisfy the following: If the conditions are met, it means that the torque of the vehicle is normal, no signal is generated, and the vehicle is monitored again. If the conditions are not met, an abnormal torque change signal is generated through the signal generation terminal and displayed for external personnel to view.

[0057] Specifically, when the speed changes, the torque also changes accordingly. In the same gear, as the speed increases, the torque decreases. Regardless of the gear, the trend between the speed increase and the torque change is the same. Therefore, by observing the changes in the speed curve, the corresponding time period can be identified. Based on the corresponding time period, the change curve of the corresponding torque segment can be identified from the torque change. Based on the slope value of the change, it can be confirmed whether the change amplitude between each different line segment is consistent. If they are all consistent, no processing is required. If they are not consistent, it means that the degree of torque change is inconsistent.

[0058] Under normal circumstances, torque represents the corresponding force, which is to drive the wheel to rotate through the action of force. When other values ​​are stable, the greater the torque, the greater the horsepower produced by the vehicle. Therefore, when there is a problem with vehicle acceleration, it is either a problem with the accelerator or a problem with the torque.

[0059] Therefore, by analyzing each case individually, we can identify the corresponding anomalies, generate and display the corresponding anomaly signals in a timely manner, and improve the overall processing effect of vehicle data.

[0060] Example 2

[0061] Combination Figure 2 A vehicle data processing method includes the following steps:

[0062] Step 1: Monitor the vehicle's throttle input and speed data, analyze whether the acceleration between speed data meets the standard. If it does not meet the standard, generate an abnormal signal and execute the periodic data analysis. If it meets the standard, no processing is performed.

[0063] Step 2: Based on the confirmed abnormal signals, define a set of monitoring cycles and re-monitor the vehicle's throttle amplitude and speed data through the data monitoring terminal, and monitor the fuel consumption parameters. Based on the monitored parameters, analyze whether there is a fuel supply problem during vehicle operation, and generate a fuel supply problem signal or a normal fuel supply signal.

[0064] Step 3: Define the second monitoring cycle and keep the vehicle gear unchanged. Monitor the torque change data of the second monitoring cycle through the data monitoring terminal, generate a torque change curve based on this torque change data, and perform numerical change analysis on the torque change curve and the speed change curve generated in this monitoring cycle. Generate a processing signal based on the analysis results.

[0065] The data in the above formula are all calculated by removing the dimensions and taking the numerical values. The formula is the closest to the real situation obtained by software simulation of a large amount of collected data. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained through simulation of a large amount of data.

[0066] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A vehicle data processing system, characterized by, The application relates to a vehicle fuel supply abnormality monitoring system, which comprises the following parts: a data monitoring end which monitors the throttle amplitude and speed data of a vehicle and transmits the monitored throttle amplitude and speed data to a lock end; the lock end analyzes whether the acceleration between the speed data meets the standard based on the monitored throttle amplitude and speed data, generates an abnormal signal if the standard is not met, and executes a periodic data analysis end, and does not perform any processing if the standard is met; the periodic data analysis end limits a group of monitoring periods based on the confirmed abnormal signal, re-monitors the throttle amplitude and speed data of the vehicle through the data monitoring end, monitors the fuel consumption parameters, analyzes whether the vehicle has a fuel supply problem during driving based on the monitored parameters, and generates a fuel supply abnormal signal or a fuel supply normal signal; a torque parameter analysis end which limits a second group of monitoring periods, keeps the gear of the vehicle unchanged, monitors the torque change data of the second group of monitoring periods through the data monitoring end, generates a torque change curve based on the torque change data, and performs numerical change analysis on the torque change curve and a speed change curve generated in the monitoring period, generates a processing signal based on the analysis result; the periodic data analysis end includes the following preliminary analysis methods: the monitored throttle amplitude in a monitoring period T is transmitted to a standard curve generation model, the standard curve generation model is a preset model, the standard curve generation model generates a standard speed curve of the vehicle based on the throttle amplitude, and the initial value of the standard speed curve is the speed data corresponding to the start of the monitoring period T; a speed change curve and a fuel consumption curve are generated based on the monitored speed data and fuel consumption parameters in the monitoring period T; the change amplitude between the speed change curve and the standard speed curve is compared; the point position slope of the same time period in the two curves is confirmed based on the time trend, the point position slope is equal to delta y / delta x, delta is the difference between the coordinate parameters of the latter point position and the coordinate parameters of the former point position, whether the values of the same time period are consistent is determined based on the confirmed slope, if the values are consistent, no processing is performed, if there is an inconsistent time period, the fuel consumption curve and the standard speed curve are compared to confirm whether the fuel supply is abnormal; the periodic data analysis end includes the following comparison method of the fuel consumption curve and the standard speed curve: fluctuation points appearing in the standard speed curve are confirmed, the accelerations of the line segments before and after the fluctuation points are different, the standard speed curve is divided into a plurality of speed equal line segments based on the fluctuation points, the corresponding time period of the equal line segment is confirmed, and the speed equal time period is calibrated; the fuel consumption curve is processed in the same way, the fluctuation points are confirmed, the fuel equal line segments are confirmed, and the fuel equal time period is locked based on the fuel equal line segments; the speed equal time period and the fuel equal time period are compared one by one, whether each comparison result is consistent is determined, if the comparison results are consistent, the torque parameter analysis end is executed, if the comparison results are inconsistent, a fuel supply abnormal signal is generated through a signal generation end and is displayed.

2. The vehicle data processing system of claim 1, wherein The specific way of analyzing whether the acceleration meets the standard is: Based on the monitored throttle amplitude, confirm the throttle amplitude change value per unit time, and based on the speed data, confirm the acceleration parameter per unit time; Mark the throttle amplitude change value as FD and the acceleration parameter as JS, analyze whether FD meets FDxC1=JS, where C1 is a preset value, if it meets, it means that the vehicle data is running normally, if it does not meet, an abnormal signal is generated, and the periodic data analysis end is executed.

3. The vehicle data processing system of claim 1, wherein, The specific way of numerical change analysis of the torque parameter analysis end is: Based on the several fluctuation points in the speed change curve, divide the speed change curve into several speed change segments, determine the speed change segment with an upward trend in the climbing state and mark it as the climbing segment; Mark the time period of each climbing segment as the climbing time period, and according to the climbing time period, cut the line segment from the torque change curve, mark the segment of the torque change curve at the same time period as the torque segment to be compared; Mark the slope of different climbing segments as Xi and the slope of different torque segments to be compared as Bi, if there are multiple groups of slopes in the different torque segments to be compared, perform mean value processing to determine the slope of the corresponding torque segment, where i=1, 2, …, n, and n represents the total number of different time periods; Xi and Bi are analyzed to see if If the condition is met, it means that the torque of the vehicle is normal, and no signal is generated. The vehicle is monitored again. If the condition is not met, a torque change abnormality signal is generated by the signal generation end.

4. A vehicle data processing method, which is executed based on the vehicle data processing system according to any one of claims 1 to 3, characterized by, The steps include: Step one, monitor the throttle amplitude and speed data of the vehicle, analyze whether the acceleration between the speed data meets the standard, if it does not meet the standard, generate an abnormal signal and execute the periodic data analysis end, if it meets the standard, do not perform any processing; Step two, based on the confirmed abnormal signal, limit a group of monitoring periods and monitor the throttle amplitude and speed data of the vehicle again through the data monitoring end, and monitor the fuel consumption parameter, based on the monitored several groups of parameters, analyze whether there is a fueling problem in the vehicle during driving, and generate a fueling problem signal or a normal fueling signal; Step three, limit a second group of monitoring periods and keep the vehicle gear unchanged, monitor the torque change data of the second group of monitoring periods through the data monitoring end, and based on the torque change data, generate a torque change curve, and perform numerical change analysis on the torque change curve and the speed change curve generated in this monitoring period, based on the analysis result, generate a processing signal.

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