Vehicle emission detection methods, devices, equipment, and storage media based on the Internet of Vehicles

Abstract

This invention discloses a vehicle emission detection method, apparatus, device, and storage medium based on the Internet of Vehicles (IoV). Applied to an IoV platform that communicates with multiple vehicles, the method includes: acquiring vehicle driving data and emission data uploaded by each vehicle; for any vehicle, determining the vehicle driving scenario based on the vehicle driving data; extracting emission data corresponding to each type of vehicle driving scenario to form emission data to be detected; and detecting the emission data to be detected based on a preset time window to obtain the vehicle's emission detection result. This solution, by combining the IoV platform, processes the acquired vehicle driving data and emission data to determine the data to be detected, and uses a moving average algorithm and judgment rules to detect the data to be detected, thereby determining the vehicle's emission detection result. This enables the detection of vehicle emission data under different operating conditions, determining whether a vehicle's emissions exceed standards, and improving the efficiency of detecting excessive vehicle emissions.

Description

Technical Field

[0001] This invention relates to the field of vehicle emission testing technology, and in particular to vehicle emission testing methods, devices, equipment and storage media based on the Internet of Vehicles. Background Technology

[0002] Air pollution is becoming an increasingly serious problem. Regarding vehicle emissions, the government is constantly formulating increasingly stringent emission regulations. To better monitor vehicle emissions, network technology is being used as a primary method for monitoring vehicle emissions.

[0003] Currently, the detection of vehicle exhaust emissions data requires limiting factors such as the vehicle's operating conditions or vehicle type. Detecting emissions under specific conditions for a specific vehicle type limits the results and fails to meet the requirement of comprehensive vehicle exhaust emission monitoring, thus significantly reducing the efficiency of vehicle exhaust emission monitoring. Summary of the Invention

[0004] This invention provides a vehicle emission detection method, device, equipment, and storage medium based on the Internet of Vehicles (IoV) to address the limitations of vehicle exhaust emission detection results and the low efficiency of vehicle exhaust emission monitoring.

[0005] According to one aspect of the present invention, a vehicle emission detection method based on a vehicle-to-everything (V2X) network is provided, applied to a V2X platform, the V2X platform being communicatively connected to multiple vehicles, the method comprising:

[0006] Obtain vehicle driving data and emissions data uploaded by each vehicle;

[0007] For any vehicle, the vehicle driving scenario is determined based on the vehicle's driving data;

[0008] Extract emission data corresponding to various types of vehicle driving scenarios to form emission data to be tested;

[0009] The emission data to be tested is tested based on a preset time window to obtain the emission test results of the vehicle.

[0010] Optionally, vehicle driving data includes vehicle speed data;

[0011] Determining vehicle driving scenarios based on vehicle driving data includes:

[0012] Determine the average vehicle speed data and maximum vehicle speed data corresponding to the vehicle speed data within the first preset time period;

[0013] The system acquires average vehicle speed and maximum vehicle speed data based on driving scenarios for each vehicle. It then determines the average vehicle speed based on the average vehicle speed data and the maximum vehicle speed based on the maximum vehicle speed data.

[0014] The vehicle driving scenario is determined based on the judgment results of average vehicle speed data and maximum vehicle speed data.

[0015] Optionally, vehicle driving data may also include vehicle location data and exhaust gas inlet temperature data;

[0016] The method also includes:

[0017] The vehicle driving scenario is verified based on vehicle positioning data and / or exhaust gas inlet temperature data.

[0018] Optionally, emission data corresponding to various vehicle driving scenarios can be extracted to form emission data to be tested, including:

[0019] Emission data to be detected for the second preset time period is extracted from the emission data corresponding to each vehicle driving scenario, and the emission data to be detected is sorted based on timestamps to form emission data to be detected.

[0020] Optionally, emissions data to be tested are performed based on a preset time window to obtain vehicle emissions test results, including:

[0021] During the sliding process of the preset time window, the preset time window corresponds to the average data of the emission data to be detected;

[0022] Based on the detection threshold, the emission data to be detected and the average data within each preset time window are judged to obtain the emission detection results of the vehicle.

[0023] Optionally, the detection thresholds include a first data detection threshold and a first average detection threshold corresponding to the exceeding state, and a second data detection threshold and a second average detection threshold corresponding to the warning state, wherein the first data detection threshold is greater than or equal to the second data detection threshold, and the first average detection threshold is greater than the second average detection threshold.

[0024] Based on the detection threshold, the emission data to be detected and the average data within each preset time window are judged to obtain the vehicle's emission test results, including:

[0025] If the emission data to be detected in any preset time window is greater than the first data detection threshold, and the average data corresponding to the preset time window is greater than the first average detection threshold, then the emission detection result of the preset time window is determined to be an emission exceeding the standard.

[0026] If the emission data to be detected in any preset time window is greater than the second data detection threshold in the second preset proportion, and the average data corresponding to the preset time window is less than the first average detection threshold but greater than the second average detection threshold, then the emission detection result of the preset time window is determined to be an emission warning.

[0027] Optionally, the method also includes:

[0028] The emission test results are marked with time information for exceeding emission standards and emission warnings, latitude and longitude information, and one or more of the total fuel consumption, average vehicle speed, and average engine speed within the corresponding preset time window.

[0029] According to another aspect of the present invention, a vehicle emissions detection device based on the Internet of Vehicles is provided, comprising:

[0030] The vehicle data acquisition module is used to acquire vehicle driving data and emission data uploaded by each vehicle.

[0031] The vehicle driving scenario determination module is used to determine the vehicle driving scenario for any given vehicle based on the vehicle's driving data.

[0032] The data to be tested determination module is used to extract emission data corresponding to various types of vehicle driving scenarios and form emission data to be tested.

[0033] The test result determination module is used to test the emission data to be tested based on a preset time window to obtain the emission test results of the vehicle.

[0034] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0035] At least one processor; and

[0036] A memory that is communicatively connected to at least one processor; wherein,

[0037] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to execute the vehicle emissions detection method based on the Internet of Vehicles according to any embodiment of the present invention.

[0038] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the vehicle emission detection method based on the Internet of Vehicles of any embodiment of the present invention.

[0039] The technical solution of this invention, by combining a vehicle network platform, processes vehicle driving data and emission data, and adopts a vehicle driving scenario judgment strategy and a vehicle emission exceeding standard judgment strategy to automatically determine the vehicle driving scenario and its corresponding vehicle emission detection results. This solves the problems of the limitations of vehicle exhaust emission detection results and the low efficiency of vehicle exhaust emission monitoring, and realizes real-time monitoring of vehicle emissions, thereby improving the efficiency of vehicle emission information acquisition and monitoring.

[0040] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0042] Figure 1 This is a flowchart of a vehicle emission detection method based on the Internet of Vehicles provided in Embodiment 1 of the present invention;

[0043] Figure 2 This is a schematic diagram of a vehicle networking application applicable to an embodiment of the present invention;

[0044] Figure 3 This is a flowchart of a vehicle emission detection method based on the Internet of Vehicles provided in Embodiment 2 of the present invention;

[0045] Figure 4 This is a schematic diagram of a vehicle emission detection device based on the Internet of Vehicles provided in Embodiment 3 of the present invention;

[0046] Figure 5 This is a schematic diagram of the structure of an electronic device that implements the vehicle emission detection method based on the Internet of Vehicles in this embodiment of the invention. Detailed Implementation

[0047] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0048] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0049] Example 1

[0050] Figure 1 This is a flowchart of a vehicle emission detection method based on the Internet of Vehicles (IoV) according to Embodiment 1 of the present invention. This embodiment is applicable to the detection of vehicle exhaust emissions. The method can be executed by an IoV-based vehicle emission detection device, which can be implemented in hardware and / or software. This IoV-based vehicle emission detection device can be configured in electronic devices such as computers and intelligent monitoring systems. In some embodiments, the IoV-based vehicle emission detection device can be configured on an IoV platform. This IoV platform is communicatively connected to the vehicle, can receive data uploaded by the vehicle, and can store and process the received data for vehicle emission detection. Figure 1 As shown, the method includes:

[0051] S110. Obtain vehicle driving data and emission data uploaded by each vehicle.

[0052] Vehicle driving data can be specifically understood as vehicle-related data generated during vehicle operation, including but not limited to vehicle mileage, total fuel consumption, vehicle speed, engine speed, and the latitude and longitude of the route traveled. Emissions data can be specifically understood as exhaust emission data generated by the vehicle during operation, including but not limited to NOx concentration. The acquisition frequency and time interval of vehicle driving data and emissions data can be set according to actual needs, such as a daily, weekly, or monthly interval, determined based on emissions data monitoring requirements; no specific limitation is set here.

[0053] Specifically, vehicles can upload their driving and emission data to a monitoring and management system via wireless communication terminal devices. The monitoring and management system receives the uploaded driving and emission data, for example, through a vehicle-to-everything (V2X) cloud platform, receiving the vehicle's driving and emission data for the past minute every 10 seconds. The wireless communication terminal devices can include wireless routers, wireless modems, and remote terminal devices.

[0054] In this embodiment, remote wireless communication technology is used to acquire vehicle driving data and emission data uploaded by each vehicle. This allows for the acquisition of data from vehicles at long distances, which helps improve the efficiency of vehicle data acquisition and the completeness of monitoring data, thereby helping to improve the accuracy of vehicle emission test results.

[0055] S120. For any vehicle, determine the vehicle driving scenario based on the vehicle's driving data.

[0056] Among them, the vehicle driving scenario can be specifically understood as the scenario in which the vehicle is in the process of driving, or the vehicle driving condition, which includes three scenarios: urban area, suburbs, and highway.

[0057] Specifically, for any given vehicle, the vehicle's driving data is acquired and processed to determine the vehicle's driving scenario. For example, the vehicle's driving scenario can be determined by using its speed.

[0058] Optionally, vehicle driving data includes vehicle speed data; determining vehicle driving scenarios based on vehicle driving data includes: determining the average vehicle speed data and maximum vehicle speed data corresponding to the vehicle speed data within a first preset time period; acquiring average vehicle speed judgment data and maximum vehicle speed judgment data based on each vehicle driving scenario; judging the average vehicle speed data based on the average vehicle speed judgment data; and judging the maximum vehicle speed data based on the maximum vehicle speed judgment data; determining the vehicle driving scenario based on the judgment results of the average vehicle speed data and the judgment results of the maximum vehicle speed data.

[0059] The first preset time period can be understood as the time period in which the vehicle driving data and emission data uploaded by each vehicle are acquired. It can be preset according to actual needs and may include, but is not limited to, ten seconds, one minute, ten minutes, etc.

[0060] Specifically, a first preset time period is set to one minute. The acquired vehicle driving data is cleaned, and the corresponding vehicle speed data is extracted. The average speed of each vehicle within the first preset time period is calculated using an averaging algorithm. The maximum speed of each vehicle within the first preset time period can be determined using a maximum value algorithm. The vehicle driving scenario is determined based on the average and maximum speeds of each vehicle within the first preset time period. The vehicle driving scenario can be determined by pre-setting vehicle driving scenario judgment rules.

[0061] For example, the first preset time period can be set to ten minutes. If the average speed of any vehicle is >= 15 km / h and the average speed of any vehicle is <= 30 km / h and the maximum speed of any vehicle is <= 55 km / h, the driving scenario of the vehicle is determined to be urban area; if the average speed of any vehicle is >= 45 km / h and the average speed of any vehicle is <= 60 km / h and the maximum speed of any vehicle is <= 75 km / h, the driving scenario of the vehicle is determined to be suburban area.

[0062] Optionally, the vehicle driving data may also include vehicle location data and exhaust gas inlet temperature data. The method may further include: validating the vehicle driving scenario based on the vehicle location data and / or exhaust gas inlet temperature data.

[0063] Specifically, vehicle positioning data can be understood as the latitude and longitude data of the vehicle's location during its journey.

[0064] Specifically, in determining the vehicle driving scenario, vehicle positioning data can be used to verify the driving scenario, as can vehicle positioning data and exhaust gas inlet temperature data. For example, it can be set that if the average speed of any vehicle is >= 75 km / h and the average inlet temperature of the vehicle's SCR (Silicon Controlled Rectifier) ​​is > 230°C, the driving scenario of that vehicle can be determined to be high speed.

[0065] In this embodiment, the vehicle driving scenario is determined by pre-setting vehicle driving scenario judgment rules. The vehicle driving scenario can be determined by the vehicle's average speed and maximum speed in a first preset time period. Vehicle positioning data and exhaust gas inlet temperature data can also be added to verify the vehicle driving scenario, which improves the accuracy of vehicle driving scenario judgment and helps to improve the accuracy of vehicle emission monitoring.

[0066] S130. Extract emission data corresponding to various types of vehicle driving scenarios to form emission data to be tested.

[0067] Specifically, among the data uploaded by the vehicles, emission data corresponding to different types of vehicle driving scenarios are identified, which may include, but are not limited to, the time of vehicle exhaust emission and the NOx concentration of vehicle emissions, and this data is used as the data to be tested.

[0068] Optionally, emission data corresponding to various types of vehicle driving scenarios can be extracted to form emission data to be tested, including: extracting emission data to be tested for a second preset time period from the emission data corresponding to each vehicle driving scenario, and sorting the emission data to be tested based on timestamps to form emission data to be tested.

[0069] The second preset time period can be specifically understood as the time period used to extract the data to be detected for vehicle emissions testing.

[0070] Specifically, a second preset time period can be set to 5 minutes. From the emission data corresponding to each vehicle driving scenario, any five consecutive minutes of vehicle emission data can be extracted. The emission data within each five-minute period is then sorted in ascending or descending order according to its corresponding timestamp, ultimately forming the data to be tested. It should be noted that ascending order is generally used for arranging emission data according to timestamps.

[0071] In this embodiment, emission data for a second preset time period is extracted from the emission data corresponding to each vehicle driving scenario. The emission data is then sorted in ascending or descending order according to the timestamp to form the data to be detected. Extracting vehicle emission data within a specific time period according to different vehicle driving scenarios helps improve the accuracy of vehicle emission detection in different scenarios.

[0072] S140. Based on a preset time window, the emission data to be tested is tested to obtain the emission test results of the vehicle.

[0073] Specifically, a time window can be understood as a movable time period. The length of this time period determines the size of the time window. Time windows come in two forms: scrolling time windows and sliding time windows. Scrolling time windows have a fixed window size; if the time window is set to 1 minute, it only calculates data within the current minute. Sliding time windows, on the other hand, have a sliding window size. For example, if the window time is set to 1 minute and the sliding time is 10 seconds, each slide lasts 10 seconds, and the data within the sliding time window is processed after the slide. This sliding time can be preset.

[0074] Specifically, a sliding time window can be used to detect the emission data to be tested. The prediction time window is set to 30 seconds, and the sliding length is 1 second. That is, the data to be tested is detected every 1 second, and the time period of the data to be tested is 30 seconds. By pre-setting the emission exceedance standard, the vehicle emission data can be judged to determine whether the vehicle emission exceeds the standard.

[0075] In this embodiment, the emission data to be tested is detected based on a preset time window to obtain the vehicle's emission test results. The smaller the sliding window is set, the smoother the window slides, and the more accurate the emission results are.

[0076] Furthermore, this vehicle emission detection method based on the Internet of Vehicles (IoV) is applied to an IoV platform, which communicates with multiple vehicles.

[0077] Among them, the Internet of Vehicles (IoV) leverages next-generation information and communication technologies to achieve comprehensive network connectivity between vehicles, roads, people, and service platforms. This allows for the effective utilization of all dynamic vehicle information within the information network platform, providing various functional services during vehicle operation. Specifically, an IoV platform can be understood as a service system that applies IoV technology.

[0078] Specifically, Figure 2 This is a schematic diagram of a vehicle-to-everything (V2X) application applicable to an embodiment of the present invention. It includes a visualization front-end device 1001, a V2X platform 1002, and a vehicle 1003. The V2X platform 1002 receives vehicle data information sent by the vehicle 1003 via wireless communication technology. The vehicle 1003 uses a built-in telematics box (Tbox) to send vehicle data information to the V2X platform 1002. Users can view the analyzed vehicle emissions test results through the visualization front-end device 1001, which may include, but is not limited to, a computer.

[0079] The technical solution of this embodiment, by combining a vehicle network platform, receives and processes vehicle driving data and emission data, and adopts a vehicle driving scenario judgment strategy and a vehicle emission exceedance judgment strategy to automatically determine the vehicle driving scenario and its corresponding vehicle emission detection results, and promptly issues an exceedance warning based on the vehicle emission detection results. This eliminates the need to restrict vehicle exhaust emission detection based on factors such as vehicle driving scenario, solves the problems of limitations in vehicle exhaust emission detection results and low efficiency in vehicle exhaust emission monitoring, and enables real-time monitoring of vehicle emissions, improving the efficiency of vehicle emission information acquisition and monitoring.

[0080] Example 2

[0081] Figure 3This is a flowchart of a vehicle emission detection method based on the Internet of Vehicles (IoV) provided in Embodiment 2 of the present invention. This embodiment is a further optimization of the above embodiment. Optionally, during the sliding process of the preset time window, the preset time window corresponds to the average data of the emission data to be detected; based on the detection threshold, the emission data to be detected and the average data within each preset time window are judged to obtain the vehicle emission detection result. Figure 3 As shown, the method includes:

[0082] S210. Obtain vehicle driving data and emission data uploaded by each vehicle.

[0083] S220. For any vehicle, determine the vehicle driving scenario based on the vehicle's driving data.

[0084] S230. Extract emission data corresponding to various types of vehicle driving scenarios to form emission data to be tested.

[0085] S240. During the sliding process of the preset time window, the preset time window corresponds to the average data of the emission data to be detected.

[0086] Specifically, a 30-second moving average algorithm is used. With a preset time window of 30 seconds, the algorithm slides once per second to calculate the real-time vehicle data within these 30 seconds and determine the average data of the emissions data to be tested within that 30-second period.

[0087] S250: Based on the detection threshold, the emission data to be detected and the average data within each preset time window are judged to obtain the emission detection results of the vehicle.

[0088] Specifically, the detection threshold can be understood as a critical value set to determine whether the emission data to be detected and the average data exceed the standard. The monitoring thresholds for the emission data to be detected and the average data can be preset based on experimental data.

[0089] Specifically, the system determines whether vehicle emissions exceed standards based on pre-set detection thresholds and pre-set exceedance criteria. For example, if both the emission data to be tested and the average data exceed the set detection thresholds, then the vehicle's emission test result can be determined to be excessive; otherwise, it is not excessive.

[0090] Optionally, the detection thresholds include a first data detection threshold and a first average detection threshold corresponding to the exceeding state, and a second data detection threshold and a second average detection threshold corresponding to the warning state, wherein the first data detection threshold is greater than or equal to the second data detection threshold, and the first average detection threshold is greater than the second average detection threshold.

[0091] Specifically, the data detection threshold can be understood as the threshold for allowing vehicle emission data, while the average detection threshold can be understood as the threshold for the average value of vehicle emission data. The terms "first" and "second" are merely used to distinguish the detection thresholds and have no other special meaning. Both the first data detection threshold and the first average detection threshold are used to determine if a vehicle's emissions exceed the standard. Both the second data detection threshold and the second average detection threshold are used to determine if a vehicle is in an emission warning state.

[0092] Specifically, a first data detection threshold and a first average detection threshold, as well as a second data detection threshold and a second average detection threshold, can be preset based on experimental data. Within a preset time window, the emission data and the average emission data for each vehicle are calculated. If both the calculated emission data and the average value are greater than the first data detection threshold and the first average detection threshold, the vehicle's emission data is determined to be in an excessive state; if both the calculated emission data and the average value are greater than the second data detection threshold and the second average detection threshold, the vehicle's emission data is determined to be in a warning state. Based on the meaning of excessive state and warning state, the detection threshold for excessive state can be set to be greater than or equal to the detection threshold for warning state, that is, the first data detection threshold is greater than or equal to the second data detection threshold, and the first average detection threshold is greater than the second average detection threshold.

[0093] Optionally, the emission data to be detected and the average data within each preset time window are judged based on the detection threshold to obtain the emission detection result of the vehicle, including: if the emission data to be detected in a first preset proportion within any preset time window is greater than the first data detection threshold, and the average data corresponding to the preset time window is greater than the first average detection threshold, then the emission detection result of the preset time window is determined to be an emission exceedance; if the emission data to be detected in a second preset proportion within any preset time window is greater than the second data detection threshold, and the average data corresponding to the preset time window is less than the first average detection threshold and greater than the second average detection threshold, then the emission detection result of the preset time window is determined to be an emission warning.

[0094] The first preset ratio can be understood as the proportion of data that meets a certain indicator within the overall data. It can be preset based on experimental data. The second preset ratio has the same meaning as the first preset ratio; the first and second are only used to distinguish the preset ratios. The first preset ratio is used to determine whether the emission detection result is an exceedance of emission standards, while the second preset ratio is used to determine whether the emission detection result is an emission warning.

[0095] Specifically, within any preset time window, the proportion of emission data for each vehicle exceeding a first detection threshold, the proportion of emission data exceeding a second detection threshold, and the average emission data for each vehicle within that time window are calculated. It is then determined whether any data within the preset time window meets the criteria of having a proportion greater than or equal to a first preset threshold and whether the average data for that time window exceeds a first average detection threshold. If both are true, the vehicle's emission test result indicates excessive emissions; otherwise, it does not. Similarly, it is determined whether any data within the preset time window meets the criteria of having a proportion greater than or equal to a second preset threshold and whether the average data for that time window exceeds a second average detection threshold and is less than a first average detection threshold. If both are true, the vehicle's emission test result indicates an emission warning; otherwise, it does not.

[0096] For example, for determining if emissions exceed standards, a preset time window can be set to 30 seconds, a first data detection threshold can be set to 550 ppm, and a first average detection threshold can be set to 550 ppm. If 50% of the data exceeds 550 ppm and the average instantaneous NOx concentration within the preset time window exceeds 550 ppm, then the vehicle's NOx emissions exceed standards. For determining if emissions exceed standards and issuing a warning, a preset time window can be set to 30 seconds, a second data detection threshold can be set to 550 ppm, and a second average detection threshold can be set to 450 ppm. If 50% of the data exceeds 550 ppm and the average instantaneous NOx concentration within the preset time window exceeds 450 ppm, then a NOx emission warning is issued for the vehicle.

[0097] Furthermore, the method also includes: marking the emission test results as time information of emission exceeding standards and emission warning, latitude and longitude information, and one or more of the total fuel consumption, average vehicle speed, and average engine speed within the corresponding preset time window.

[0098] Specifically, during the process of determining vehicle emissions test results, the system can record the time information of emissions exceeding standards and emissions warnings, the latitude and longitude information of the vehicle's current location, and the total fuel consumption, average speed, and average engine speed within the current preset time window. After determining the vehicle emissions test results, one or more of the information recorded during the process needs to be marked, and these results can be viewed through a front-end visual interface.

[0099] The technical solution of this embodiment, by combining a vehicle network platform, receives and processes vehicle driving data and emission data. It employs vehicle driving scenario judgment strategies and vehicle emission exceedance judgment strategies, and uses a moving average algorithm to detect vehicle driving data and emission data corresponding to different vehicle driving scenarios, determines the vehicle emission detection results, and provides timely warnings of exceedance based on the vehicle emission detection results. This eliminates the need to restrict vehicle exhaust emission detection to factors such as vehicle driving scenarios, solving the problems of limitations in vehicle exhaust emission detection results and low efficiency in vehicle exhaust emission monitoring. It can monitor vehicle emissions in real time, and by using a moving average algorithm to determine whether vehicle emissions exceed standards, it improves the accuracy of emission detection result judgment and the efficiency of vehicle emission data detection and monitoring.

[0100] Example 3

[0101] Figure 4 This is a schematic diagram of a vehicle emission detection device based on the Internet of Vehicles (IoV) provided in Embodiment 3 of the present invention. Figure 4 As shown, the device includes:

[0102] The vehicle data acquisition module 310 is used to acquire vehicle driving data and emission data uploaded by each vehicle.

[0103] The vehicle driving scenario determination module 320 is used to determine the vehicle driving scenario for any vehicle based on the vehicle's driving data.

[0104] The data to be detected module 330 is used to extract emission data corresponding to various types of vehicle driving scenarios to form emission data to be detected.

[0105] The test result determination module 340 is used to test the emission data to be tested based on a preset time window to obtain the emission test results of the vehicle.

[0106] Optionally, the vehicle driving scenario determination module 320 is specifically used for: determining the vehicle driving scenario based on the vehicle driving data, including vehicle speed data, including:

[0107] Determine the average vehicle speed data and maximum vehicle speed data corresponding to the vehicle speed data within the first preset time period;

[0108] The system acquires average vehicle speed and maximum vehicle speed data based on driving scenarios for each vehicle. It then determines the average vehicle speed based on the average vehicle speed data and the maximum vehicle speed based on the maximum vehicle speed data.

[0109] The vehicle driving scenario is determined based on the judgment results of average vehicle speed data and maximum vehicle speed data.

[0110] Vehicle driving data also includes vehicle location data and exhaust gas inlet temperature data.

[0111] The method also includes: verifying vehicle driving scenarios based on vehicle positioning data and / or exhaust gas inlet temperature data.

[0112] Optionally, the data to be detected determination module 330 is specifically used to extract emission data corresponding to various types of vehicle driving scenarios to form emission data to be detected, including: extracting emission data to be detected for a second preset time period from the emission data corresponding to each vehicle driving scenario, and sorting the emission data to be detected based on timestamps to form emission data to be detected.

[0113] Optionally, the test result determination module 340 is specifically used to test the emission data to be tested based on a preset time window to obtain the vehicle's emission test results, including:

[0114] During the sliding process of the preset time window, the preset time window corresponds to the average data of the emission data to be detected;

[0115] Based on the detection threshold, the emission data to be detected and the average data within each preset time window are judged to obtain the emission detection results of the vehicle.

[0116] The detection thresholds include a first data detection threshold and a first average detection threshold corresponding to the exceeding state, and a second data detection threshold and a second average detection threshold corresponding to the warning state, wherein the first data detection threshold is greater than or equal to the second data detection threshold, and the first average detection threshold is greater than the second average detection threshold.

[0117] Based on the detection threshold, the emission data to be detected and the average data within each preset time window are judged to obtain the vehicle's emission test results, including:

[0118] If the emission data to be detected in any preset time window is greater than the first data detection threshold, and the average data corresponding to the preset time window is greater than the first average detection threshold, then the emission detection result of the preset time window is determined to be an emission exceeding the standard.

[0119] If the emission data to be detected in any preset time window is greater than the second data detection threshold in the second preset proportion, and the average data corresponding to the preset time window is less than the first average detection threshold but greater than the second average detection threshold, then the emission detection result of the preset time window is determined to be an emission warning.

[0120] The method also includes: marking the emission test results as time information, latitude and longitude information, and one or more of the total fuel consumption, average vehicle speed, and average engine speed within the corresponding preset time window for emission exceedance and emission warning.

[0121] The vehicle emission testing device based on the Internet of Vehicles provided in this embodiment of the invention can execute the vehicle emission testing method based on the Internet of Vehicles provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0122] Example 4

[0123] Figure 5 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0124] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0125] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0126] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as vehicle emissions detection methods based on vehicle-to-everything (V2X) communication.

[0127] In some embodiments, the vehicle emissions detection method based on the Internet of Vehicles (IoV) can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the IoV-based vehicle emissions detection method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the IoV-based vehicle emissions detection method by any other suitable means (e.g., by means of firmware).

[0128] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0129] Computer programs for implementing the vehicle emissions detection method based on the Internet of Vehicles (IoV) of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0130] Example 5

[0131] Embodiment 5 of the present invention also provides a computer-readable storage medium storing computer instructions for causing a processor to execute a vehicle emissions detection method based on a vehicle network, the method comprising:

[0132] Obtain vehicle driving data and emissions data uploaded by each vehicle;

[0133] For any vehicle, the vehicle driving scenario is determined based on the vehicle's driving data;

[0134] Extract emission data corresponding to various types of vehicle driving scenarios to form emission data to be tested;

[0135] The emission data to be tested is tested based on a preset time window to obtain the emission test results of the vehicle.

[0136] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0137] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0138] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0139] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0140] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0141] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A vehicle emission detection method based on the Internet of Vehicles, characterized in that, Applied to a vehicle networking platform, which communicates with multiple vehicles, the method includes: Obtain vehicle driving data and emissions data uploaded by each vehicle; For any vehicle, the vehicle driving scenario is determined based on the vehicle's driving data; Extract emission data corresponding to various types of vehicle driving scenarios to form emission data to be tested; The emission data to be tested is detected based on a preset time window to obtain the emission test results of the vehicle; The vehicle driving data includes vehicle speed data; The process of determining the vehicle driving scenario based on the vehicle's driving data includes: Determine the average vehicle speed data and maximum vehicle speed data corresponding to the vehicle speed data within the first preset time period; The system acquires average vehicle speed judgment data and maximum vehicle speed judgment data based on each vehicle driving scenario, determines the average vehicle speed data based on the average vehicle speed judgment data, and determines the maximum vehicle speed data based on the maximum vehicle speed judgment data. The vehicle driving scenario is determined based on the determination results of the average vehicle speed data and the determination results of the maximum vehicle speed data. The step of detecting the emission data to be tested based on a preset time window to obtain the emission test results of the vehicle includes: During the sliding process of the preset time window, the average data of the emission data to be detected corresponding to the preset time window is determined; Based on the detection threshold, the emission data to be detected and the average data within each preset time window are judged to obtain the emission detection result of the vehicle. The detection thresholds include a first data detection threshold and a first average detection threshold corresponding to the exceeding state, and a second data detection threshold and a second average detection threshold corresponding to the warning state, wherein the first data detection threshold is greater than or equal to the second data detection threshold, and the first average detection threshold is greater than the second average detection threshold. The step of determining the emission data to be detected and the average data within each preset time window based on the detection threshold to obtain the vehicle's emission detection result includes: If the emission data to be detected in any preset time window is greater than the first data detection threshold, and the average data corresponding to the preset time window is greater than the first average detection threshold, then the emission detection result of the preset time window is determined to be an emission exceeding the standard. If the emission data to be detected in any preset time window is greater than the second data detection threshold, and the average data corresponding to the preset time window is less than the first average detection threshold but greater than the second average detection threshold, then the emission detection result of the preset time window is determined to be an emission warning.

2. The method according to claim 1, characterized in that, The vehicle driving data also includes vehicle positioning data and exhaust gas inlet temperature data; The method further includes: The vehicle driving scenario is verified based on the vehicle positioning data and / or the exhaust gas inlet temperature data.

3. The method according to claim 1, characterized in that, The process involves extracting emission data corresponding to various vehicle driving scenarios to form emission data to be detected, including: Emission data for a second preset time period is extracted from the emission data corresponding to each vehicle driving scenario, and the extracted emission data is sorted based on timestamps to form emission data to be detected.

4. The method according to claim 1, characterized in that, The method further includes: The emission test results are marked with time information for exceeding emission standards and emission warnings, latitude and longitude information, and one or more of the total fuel consumption, average vehicle speed, and average engine speed within the corresponding preset time window.

5. A vehicle emission detection device based on the Internet of Vehicles, characterized in that, include: The vehicle data acquisition module is used to acquire vehicle driving data and emission data uploaded by each vehicle. The vehicle driving scenario determination module is used to determine the vehicle driving scenario for any vehicle based on the vehicle's driving data. The data to be tested determination module is used to extract emission data corresponding to various types of vehicle driving scenarios and form emission data to be tested. The detection result determination module is used to detect the emission data to be detected based on a preset time window to obtain the emission detection result of the vehicle; The vehicle driving data includes vehicle speed data; the vehicle driving scenario determination module is specifically used to determine the average vehicle speed data and maximum vehicle speed data corresponding to the vehicle speed data within a first preset time period; acquire average vehicle speed judgment data and maximum vehicle speed judgment data based on each vehicle driving scenario; determine the average vehicle speed data based on the average vehicle speed judgment data; and determine the maximum vehicle speed data based on the maximum vehicle speed judgment data; and determine the vehicle driving scenario based on the determination results of the average vehicle speed data and the determination results of the maximum vehicle speed data. Specifically, the detection result determination module is used to determine the average data of the emission data to be detected corresponding to the preset time window during the sliding process of the preset time window; and to determine the emission data to be detected and the average data in each preset time window based on the detection threshold to obtain the emission detection result of the vehicle. The detection thresholds include a first data detection threshold and a first average detection threshold corresponding to the exceedance state, and a second data detection threshold and a second average detection threshold corresponding to the warning state, wherein the first data detection threshold is greater than or equal to the second data detection threshold, and the first average detection threshold is greater than the second average detection threshold; the detection result determination module is further specifically used to determine the emission detection result of the preset time window as exceeding the emission standard if the emission data to be detected in any preset time window of a first preset proportion is greater than the first data detection threshold, and the average data corresponding to the preset time window is greater than the first average detection threshold; if the emission data to be detected in any preset time window of a second preset proportion is greater than the second data detection threshold, and the average data corresponding to the preset time window is less than the first average detection threshold but greater than the second average detection threshold, then the emission detection result of the preset time window is an emission warning.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the vehicle emission detection method based on the Internet of Vehicles as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the vehicle emission detection method based on any one of claims 1-4.

Images