Vehicle carbon emission monitoring and early warning system based on Internet of Things technology

Abstract

The present invention relates to the field of carbon emission monitoring technology, and in particular to a vehicle carbon emission monitoring and early warning system based on the Internet of Things technology. The system comprises a processor and a memory, and the processor executes a computer program stored in the memory to implement the following steps: for any vehicle, according to the carbon emissions, vehicle speed and environmental parameters with preset weather type labels of the vehicle at each historical sampling moment, respectively obtaining carbon emission correction factors of a standard environmental parameter interval and each remaining environmental parameter interval; obtaining real-time carbon emissions and real-time environmental parameters, obtaining a target carbon emission correction factor corresponding to the real-time carbon emissions according to the real-time environmental parameters, correcting the real-time carbon emissions using the target carbon emission correction factor to obtain the corrected carbon emissions, and performing carbon emission monitoring and early warning on the vehicle according to the corrected carbon emissions, thereby reducing the influence of environmental factors and improving monitoring accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission monitoring, and in particular to a vehicle carbon emission monitoring and early warning system based on the Internet of Things technology. Background Art

[0002] Vehicle carbon emissions are the abbreviation for greenhouse gas emissions during the operation of vehicles powered by internal combustion engines. Greenhouse gases include hydrocarbons, , nitrogen oxides, etc. Vehicle carbon emissions are one of the main sources of urban air pollution, and the pollutants they emit have a great impact on the environment and human health. In order to reduce the impact of vehicle carbon emissions on the environment and human health, it is necessary to monitor vehicle carbon emissions and then formulate emission standards to reduce pollutant emissions.

[0003] At present, vehicle carbon emissions are monitored by installing sensors at the exhaust pipe outlet of motor vehicles, using the sensors to detect greenhouse gases (including but not limited to hydrocarbons, At the same time, environmental sensors are installed to monitor environmental parameters to provide background information for data analysis of greenhouse gas concentrations. The collected data (greenhouse gas concentrations and environmental parameters) are then transmitted from the sensors to the cloud or local server. Users can view the vehicle's carbon emissions in real time. When the vehicle's carbon emissions are monitored to exceed the standard, the system will automatically send an early warning message to the owner and management department.

[0004] However, when dynamically monitoring vehicle carbon emissions, the sensors installed at the exhaust pipe outlet will be affected by environmental factors (temperature, humidity, etc.). For example, high temperature will affect the gas density and the response characteristics of the sensor, and high humidity will increase the water vapor content in the gas, which may interfere with the sensor's measurement, etc., resulting in inaccurate measurement of greenhouse gas concentrations, which in turn affects subsequent data analysis and early warning results.

[0005] Therefore, how to ensure the measurement accuracy of temperature gas concentration to improve the monitoring and early warning of vehicle carbon emissions based on greenhouse gas concentration has become an urgent problem to be solved. Summary of the invention

[0006] In view of this, an embodiment of the present invention provides a vehicle carbon emission monitoring and early warning system based on Internet of Things technology to solve the problem of how to ensure the measurement accuracy of temperature gas concentration to improve the monitoring and early warning of vehicle carbon emissions based on greenhouse gas concentration.

[0007] In an embodiment of the present invention, a vehicle carbon emission monitoring and early warning system based on the Internet of Things technology is provided, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the following steps when executing the computer program:

[0008] For any vehicle, the carbon emissions, vehicle speed, and environmental parameters with preset weather type labels of the vehicle at each historical sampling moment are obtained, and a standard environmental parameter interval and multiple remaining environmental parameter intervals are obtained according to the environmental parameters with preset weather type labels at all historical sampling moments;

[0009] According to the carbon emissions and vehicle speed at each of the historical sampling moments, a carbon emissions-vehicle speed standard curve for the standard environmental parameter interval and a carbon emissions-vehicle speed curve for each of the remaining environmental parameter intervals are respectively constructed; and according to the difference in curve trends between each of the carbon emissions-vehicle speed curves and the carbon emissions-vehicle speed standard curve, carbon emissions correction factors for the standard environmental parameter interval and each of the remaining environmental parameter intervals are respectively obtained;

[0010] The real-time carbon emissions and real-time environmental parameters of the vehicle at the real-time sampling moment are obtained, and according to the real-time environmental parameters, a target carbon emissions correction factor corresponding to the real-time carbon emissions is obtained from the carbon emissions correction factors in the standard environmental parameter interval and each of the remaining environmental parameter intervals, and the real-time carbon emissions are corrected using the target carbon emissions correction factor to obtain corrected carbon emissions, and carbon emissions monitoring and early warning are performed on the vehicle according to the corrected carbon emissions.

[0011] Preferably, the step of obtaining a standard environmental parameter interval and a plurality of remaining environmental parameter intervals according to environmental parameters with preset weather type labels at all historical sampling moments includes:

[0012] According to the environmental parameters with preset weather type labels at all historical sampling moments, all environmental parameters under the target weather type are obtained, wherein the environmental parameters include temperature and humidity, all temperatures under the target weather type are counted to obtain a temperature range, and all humidity under the target weather type are counted to obtain a humidity range, and the temperature range and the humidity range are combined into a standard environmental parameter range;

[0013] The temperature range outside the temperature interval is divided to obtain a temperature division result, the humidity range outside the humidity interval is divided to obtain a humidity division result, and the temperature division result and the humidity division result are combined into temperature and humidity intervals to obtain a plurality of corresponding remaining environmental parameter intervals.

[0014] Preferably, the carbon emission-vehicle speed standard curve of the standard environmental parameter interval and the carbon emission-vehicle speed curve of each of the remaining environmental parameter intervals are constructed according to the carbon emission and vehicle speed at each of the historical sampling moments, including:

[0015] According to the carbon emissions and vehicle speed at each historical sampling moment corresponding to the target weather type, a carbon emissions-vehicle speed standard curve in the standard environmental parameter interval is constructed using the least squares method;

[0016] For any remaining environmental parameter interval, according to the environmental parameters at each historical sampling moment corresponding to the non-target weather type, the historical sampling moment of the environmental parameters in the remaining environmental parameter interval is obtained as the target historical sampling moment, and according to the carbon emissions and vehicle speed at each of the target historical sampling moments, the carbon emissions-vehicle speed curve of the remaining environmental parameter interval is constructed using the least squares method.

[0017] Preferably, the step of respectively obtaining the carbon emission correction factor for the standard environmental parameter interval and each of the remaining environmental parameter intervals according to the curve trend difference between each of the carbon emission-vehicle speed curves and the carbon emission-vehicle speed standard curve comprises:

[0018] Setting the carbon emission correction factor for the standard environmental parameter range to a preset value;

[0019] For any carbon emission-vehicle speed curve, according to the curve correlation between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve, obtaining the curve trend difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve;

[0020] According to the carbon emission difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve, obtaining the numerical difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve;

[0021] A weighted sum is taken for the curve trend difference and the numerical difference to obtain a carbon emission correction factor for the remaining environmental parameter interval corresponding to the carbon emission-vehicle speed curve.

[0022] Preferably, the obtaining the curve trend difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve according to the curve correlation between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve includes:

[0023] Obtaining an extreme point on the carbon emission-vehicle speed standard curve, taking the extreme point as a cutoff point, dividing the carbon emission-vehicle speed standard curve into n sub-standard curves, where n is greater than 1, and dividing the carbon emission-vehicle speed curve into n sub-curves according to the vehicle speed corresponding to each cutoff point;

[0024] The Spearman correlation coefficients between the sub-standard curve and the sub-curve corresponding to the same vehicle speed range are respectively obtained, and the weight of each sub-curve is obtained according to the proportion of the number of data points of each sub-curve in the total number of data points of the carbon emission-vehicle speed curve. According to the weight of each sub-curve, all Spearman correlation coefficients are weighted summed to obtain the corresponding weighted summation result, and according to the negative number of the weighted summation result, the curve trend difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve is obtained.

[0025] Preferably, obtaining the numerical difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve according to the carbon emission difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve includes:

[0026] Calculating the carbon emission difference between the carbon emission corresponding to the kth data point on the carbon emission-vehicle speed curve and the carbon emission corresponding to the kth data point on the carbon emission-vehicle speed standard curve to obtain a carbon emission difference sequence;

[0027] Calculate the average value of the absolute values ​​of all elements in the carbon emission difference sequence, use the average value as the independent variable of the hyperbolic tangent function, obtain a first function value, construct a difference change curve corresponding to the carbon emission difference sequence, obtain the derivative of each element in the carbon emission difference sequence according to the difference change curve, obtain the average value of all derivatives, use the average value as the independent variable of the hyperbolic tangent function, and obtain a second function value;

[0028] The numerical difference between the carbon emission amount-vehicle speed curve and the carbon emission amount-vehicle speed standard curve is obtained according to the average value of the first function value and the second function value.

[0029] Preferably, the step of obtaining the target carbon emission correction factor corresponding to the real-time carbon emission from the carbon emission correction factors in the standard environmental parameter interval and each of the remaining environmental parameter intervals according to the real-time environmental parameter includes:

[0030] In the standard environmental parameter interval and all remaining environmental parameter intervals, the environmental parameter interval to which the real-time environmental parameter belongs is determined as the target environmental parameter interval, and the carbon emission correction factor of the target environmental parameter interval is used as the target carbon emission correction factor corresponding to the real-time carbon emissions.

[0031] Preferably, the using the target carbon emission correction factor to correct the real-time carbon emission to obtain the corrected carbon emission includes:

[0032] The difference between the constant 1 and the target carbon emission correction factor is obtained, and the product of the difference and the real-time carbon emission is used as the corrected carbon emission.

[0033] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0034] The present invention analyzes the carbon emissions and environmental characteristics of vehicles in the past, classifies the environmental characteristics, obtains the standard environmental parameter interval with the smallest impact on carbon emissions and the remaining environmental parameter intervals, which are used to characterize the carbon emission characteristics of vehicles under different environments, and then constructs the change curves of carbon emissions and vehicle speeds in different environmental parameter intervals according to the carbon emissions and vehicle speeds in the past, thereby obtaining a carbon emission-vehicle speed standard curve of a standard environmental parameter interval and a carbon emission-vehicle speed curve of each remaining environmental parameter interval, and uses the carbon emission-vehicle speed standard curve of the standard environmental parameter interval as a reference benchmark, and compares the difference between the carbon emission-vehicle speed standard curve and each carbon emission-vehicle speed curve to determine the carbon emission correction factor corresponding to each environmental parameter interval, which is used to correct the inaccurate carbon emission monitoring problem caused by environmental factors, and then after collecting new carbon emissions, by determining the environmental parameter interval to which the new carbon emissions belong when collected, to determine the corresponding carbon emission correction factor, and using the determined carbon emission correction factor to correct the new carbon emissions, the interference of environmental factors can be eliminated, and the accuracy of excessive emission monitoring based on the corrected carbon emissions is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0036] Figure 1 This is a flow chart of a vehicle carbon emission monitoring and early warning method based on Internet of Things technology provided in Embodiment 1 of the present invention;

[0037] Figure 2 It is a schematic diagram of a change curve between carbon emissions and vehicle speed provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0038] Embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, but should not be understood as limiting the present disclosure.

[0039] It should be noted that the terms "first", "second", etc. in the specification of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure.

[0040] In order to illustrate the technical solution of the present invention, specific embodiments are provided below for illustration.

[0041] See also Figure 1 , is a structural block diagram of a vehicle carbon emission monitoring and early warning system based on the Internet of Things technology provided by Embodiment 1 of the present invention, including a processor and a memory, wherein the processor executes a computer program stored in the memory to implement a vehicle carbon emission monitoring and early warning method based on the Internet of Things technology, such as Figure 1 As shown, the vehicle carbon emission monitoring and early warning method based on the Internet of Things technology includes the following steps:

[0042] Step S101, for any vehicle, obtain the vehicle's carbon emissions, vehicle speed and environmental parameters with preset weather type labels at each historical sampling moment, and obtain a standard environmental parameter interval and multiple remaining environmental parameter intervals based on the environmental parameters with preset weather type labels at all historical sampling moments.

[0043] At present, the detection of excessive carbon emissions from vehicles is carried out by installing emission detection equipment on the vehicle to monitor the carbon emissions of the vehicle in real time or regularly. Among them, the emission detection equipment can be an OSEN-TP model device, which can measure the concentration of gases such as CO2, CH4, NH3, N2O in automobile exhaust and calculate the emissions. The device integrates the Internet of Things, big data and cloud computing technologies, and can realize real-time, remote and automatic monitoring of environmental parameters. Since the concentration of gases such as CO2, CH4, NH3, N2O in automobile exhaust is affected by environmental factors (temperature and humidity), the measurement of the gas concentration in automobile exhaust is inaccurate, which in turn affects the accuracy of the monitoring of excessive carbon emissions of the vehicle. Therefore, in the embodiment of the present invention, for any vehicle, the historical monitoring data of the vehicle is collected and analyzed, and the analysis results are used as the basis for the subsequent correction of the real-time monitoring data of the vehicle to improve the accuracy of the monitoring of excessive carbon emissions of the vehicle.

[0044] Since vehicle carbon emissions The concentration is closely related to the vehicle speed. Therefore, in the embodiment of the present invention, The concentration is carbon emissions, and the temperature and humidity measured by environmental sensors are used as environmental parameters. At the same time, 4 preset weather type labels are set, including but not limited to sunny, cloudy, rainy and snowy. For any sampling moment, the carbon emissions, vehicle speed, temperature and humidity of the vehicle at the sampling moment can be collected. At the same time, the weather type at the sampling moment is obtained according to the weather data of the meteorological service at the location of the vehicle at the sampling moment, and then the weather type label is set for the temperature and humidity at the sampling moment according to the determined weather type, and the corresponding environmental parameters with preset weather type labels can be obtained.

[0045] Based on the above data collection method, the carbon emissions, vehicle speed and environmental parameters with preset weather type labels at each historical sampling moment can be obtained. Since the carbon emissions monitored by the vehicle on sunny days are least affected by temperature and humidity, the influence can be ignored. Therefore, the weather type corresponding to sunny days is used as the target weather type, and then based on the target weather type and the environmental parameters with preset weather type labels at all historical sampling moments, a standard environmental parameter interval and multiple remaining environmental parameter intervals are obtained, where the standard environmental parameter interval refers to the environmental parameter range that is least affected by environmental factors.

[0046] Specifically, a method for obtaining a standard environmental parameter interval and multiple remaining environmental parameter intervals is as follows:

[0047] According to the environmental parameters with preset weather type labels at all historical sampling moments, all environmental parameters under the target weather type are obtained, wherein the environmental parameters include temperature and humidity, all temperatures under the target weather type are counted to obtain a temperature range, and all humidity under the target weather type are counted to obtain a humidity range, and the temperature range and the humidity range are combined into a standard environmental parameter range;

[0048] The temperature range outside the temperature interval is divided to obtain a temperature division result, the humidity range outside the humidity interval is divided to obtain a humidity division result, and the temperature division result and the humidity division result are combined into temperature and humidity intervals to obtain a plurality of corresponding remaining environmental parameter intervals.

[0049] In one implementation, at all historical sampling moments, the environmental parameters with the weather type label of sunny days are counted, and the temperature and humidity in these environmental parameters are counted separately to obtain the temperature range and humidity range corresponding to sunny days. The temperature range and humidity range corresponding to sunny days can be combined into a standard environmental parameter range. At the same time, based on the obtained standard environmental parameter range, multiple remaining environmental parameter ranges are obtained. The number of remaining environmental parameter ranges is not limited and can be set according to the implementation scenario. Assumption: Temperature range and humidity range The standard environmental parameter range is formed, based on which the remaining temperature range is divided into four ranges: , the residual humidity range is divided into two intervals: , and then combine these 8 intervals into temperature and humidity intervals to obtain 14 remaining environmental parameter intervals: , , , , , , , , , , , , , It is worth noting that .

[0050] At this point, based on the environmental parameters under the four weather types at the historical sampling moments, a standard environmental parameter interval and 14 remaining environmental parameter intervals are obtained.

[0051] Step S102, based on the carbon emissions and vehicle speed at each historical sampling moment, respectively construct a carbon emissions-vehicle speed standard curve for the standard environmental parameter interval and a carbon emissions-vehicle speed curve for each remaining environmental parameter interval; based on the difference in curve trends between each carbon emissions-vehicle speed curve and the carbon emissions-vehicle speed standard curve, respectively obtain the carbon emissions correction factors for the standard environmental parameter interval and each remaining environmental parameter interval.

[0052] Due to vehicle carbon emissions The concentration is closely related to the vehicle speed. The concentration changes with the speed. The concentration curve is analyzed to obtain the influence of environmental factors on the concentration, without considering the influence of vehicle speed. The effect of concentration, There will still be deviations in the correction of actual monitoring of concentration. Therefore, in the embodiment of the present invention, a carbon emission-vehicle speed curve is constructed under various environments. That is, the vehicle speed is used as the horizontal axis and the carbon emissions are used as the vertical axis to construct a change curve between carbon emissions and vehicle speed. Then, according to the difference between the change curves between carbon emissions and vehicle speed under different environments, the corresponding carbon emission correction factor under each environment is obtained to correct the measurement error of carbon emissions caused by environmental factors.

[0053] First, according to the carbon emissions and vehicle speed at each historical sampling moment, the carbon emissions-vehicle speed standard curve for the standard environmental parameter interval and the carbon emissions-vehicle speed curve for each remaining environmental parameter interval are constructed respectively. The specific construction method is as follows:

[0054] According to the carbon emissions and vehicle speed at each historical sampling moment corresponding to the target weather type, a carbon emissions-vehicle speed standard curve in the standard environmental parameter interval is constructed using the least squares method;

[0055] For any remaining environmental parameter interval, according to the environmental parameters at each historical sampling moment corresponding to the non-target weather type, the historical sampling moment of the environmental parameters in the remaining environmental parameter interval is obtained as the target historical sampling moment, and according to the carbon emissions and vehicle speed at each of the target historical sampling moments, the carbon emissions-vehicle speed curve of the remaining environmental parameter interval is constructed using the least squares method.

[0056] In one embodiment, the carbon emissions and vehicle speeds collected on sunny days during historical sampling moments are extracted. When the same vehicle speed corresponds to multiple carbon emissions, the average of the multiple carbon emissions is calculated as the final carbon emissions corresponding to the vehicle speed, thereby obtaining multiple coordinate points (v, c) consisting of vehicle speed and carbon emissions, where v represents vehicle speed and c represents carbon emissions, that is, Concentration, map all coordinate points in a two-dimensional plane, and use the least squares method to obtain a Figure 2 The change curve between the carbon emissions and the vehicle speed shown is recorded as the carbon emissions-vehicle speed standard curve for the standard environmental parameter interval, wherein the least squares method belongs to the prior art and will not be described in detail here. Similarly, for any remaining environmental parameter interval, if the environmental parameters at any historical sampling moment are within the remaining environmental parameter interval, the historical sampling moment is taken as the target sampling moment, and then the carbon emissions and vehicle speeds at multiple target historical sampling moments are obtained. When the same vehicle speed corresponds to multiple carbon emissions, the average of the multiple carbon emissions is calculated as the final carbon emissions corresponding to the vehicle speed, so that multiple coordinate points consisting of vehicle speed and carbon emissions can be obtained, all coordinate points are mapped in a two-dimensional plane, and a change curve between carbon emissions and vehicle speed is obtained using the least squares method, recorded as the carbon emissions-vehicle speed curve for the remaining environmental parameter interval.

[0057] Then, considering that the environmental interference to the carbon emissions collected within the standard environmental parameter interval is negligible, while the carbon emissions collected in the remaining environmental parameter interval will be affected by environmental interference, there must be a curve difference between the carbon emissions-vehicle speed curve mapped in the remaining environmental parameter interval and the carbon emissions-vehicle speed standard curve in the standard environmental parameter interval. Therefore, according to the curve trend difference between each carbon emissions-vehicle speed curve and the carbon emissions-vehicle speed standard curve, the carbon emissions correction factors for the standard environmental parameter interval and each remaining environmental parameter interval are obtained respectively.

[0058] Specifically, the method for obtaining the carbon emission correction factor for the standard environmental parameter interval and each remaining environmental parameter interval is as follows:

[0059] (1) The carbon emission correction factor in the standard environmental parameter range is set to a preset value.

[0060] In one implementation, since the interference to the carbon emissions collected in the standard environmental parameter interval is negligible, the carbon emissions correction factor in the standard environmental parameter interval is set to 0.

[0061] (2) For any carbon emission-vehicle speed curve, according to the curve correlation between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve, the curve trend difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve is obtained.

[0062] Specifically, an extreme point on the carbon emission-vehicle speed standard curve is obtained, and the extreme point is used as a cutoff point to divide the carbon emission-vehicle speed standard curve into n sub-standard curves, where n is greater than 1, and the carbon emission-vehicle speed curve is divided into n sub-curves according to the vehicle speed corresponding to each cutoff point;

[0063] The Spearman correlation coefficients between the sub-standard curve and the sub-curve corresponding to the same vehicle speed range are respectively obtained, and the weight of each sub-curve is obtained according to the proportion of the number of data points of each sub-curve in the total number of data points of the carbon emission-vehicle speed curve. According to the weight of each sub-curve, all Spearman correlation coefficients are weighted summed to obtain the corresponding weighted summation result, and according to the negative number of the weighted summation result, the curve trend difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve is obtained.

[0064] In one implementation, taking the ith carbon emission-vehicle speed curve as an example, the extreme point on the carbon emission-vehicle speed standard curve is used as a cutoff point, and the carbon emission-vehicle speed standard curve is divided into n sub-standard curves. According to the vehicle speed corresponding to the extreme point on the carbon emission-vehicle speed standard curve, a coordinate point corresponding to the same vehicle speed is determined on the ith carbon emission-vehicle speed curve as a cutoff point, and the ith carbon emission-vehicle speed curve is divided into n sub-curves. The difference between the n sub-standard curves and the n sub-curves is compared to obtain the curve trend difference between the ith carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve:

[0065]

[0066] in, represents the curve trend difference between the ith carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve, n represents the number of sub-curves or sub-standard curves, represents the number of data points on the jth sub-curve, represents the total number of data points on the i-th carbon emission-vehicle speed curve, represents the Spearman correlation coefficient between the j-th sub-curve and the j-th sub-standard curve.

[0067] It should be noted that the acquisition of extreme points and Spearman correlation coefficients belongs to the prior art and will not be described in detail here. The number of data points on the j-th sub-curve represents the proportion of the number of data points on the i-th carbon emission-vehicle speed curve. The larger the proportion, the greater the weight of the corresponding j-th sub-curve. The larger the value of is, the more similar the curve change trends between the j-th sub-curve and the j-th sub-standard curve are, and the smaller the difference in curve trends between the i-th carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve is.

[0068] (3) Obtaining a numerical difference between the carbon emission amount-vehicle speed curve and the carbon emission amount-vehicle speed standard curve according to a carbon emission amount difference between the carbon emission amount-vehicle speed curve and the carbon emission amount-vehicle speed standard curve.

[0069] Specifically, the carbon emission difference between the carbon emission corresponding to the kth data point on the carbon emission-vehicle speed curve and the carbon emission corresponding to the kth data point on the carbon emission-vehicle speed standard curve is calculated to obtain a carbon emission difference sequence;

[0070] Calculate the average value of the absolute values ​​of all elements in the carbon emission difference sequence, use the average value as the independent variable of the hyperbolic tangent function, obtain a first function value, construct a difference change curve corresponding to the carbon emission difference sequence, obtain the derivative of each element in the carbon emission difference sequence according to the difference change curve, obtain the average value of all derivatives, use the average value as the independent variable of the hyperbolic tangent function, and obtain a second function value;

[0071] The numerical difference between the carbon emission amount-vehicle speed curve and the carbon emission amount-vehicle speed standard curve is obtained according to the average value of the first function value and the second function value.

[0072] In one embodiment, the carbon emission difference between the carbon emission corresponding to the kth data point on the carbon emission-vehicle speed curve and the carbon emission corresponding to the kth data point on the carbon emission-vehicle speed standard curve is calculated and recorded as , thus obtaining the carbon emission difference sequence, using the least squares method to perform polynomial fitting on the carbon emission difference sequence to obtain the corresponding difference change curve, and taking the derivative of each data point on the difference change curve to obtain the derivative of each carbon emission difference in the carbon emission difference sequence, recorded as , then the numerical difference between the i-th carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve is:

[0073]

[0074] in, represents the numerical difference between the ith carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve, tanh() represents the hyperbolic tangent function, and maps the value to [-1, 1]. represents the carbon emission corresponding to the kth data point on the i-th carbon emission-vehicle speed curve, represents the carbon emission corresponding to the kth data point on the carbon emission-vehicle speed standard curve, represents the total number of data points on the i-th carbon emission-vehicle speed curve, represents the derivative of the w-th carbon emission difference in the carbon emission difference sequence, Represents the number of elements in the carbon emission difference sequence corresponding to the i-th carbon emission-vehicle speed curve.

[0075] It should be noted that The larger the value of is, the greater the difference between the carbon emissions corresponding to the kth data point on the i-th carbon emissions-vehicle speed curve and the carbon emissions corresponding to the kth data point on the carbon emissions-vehicle speed standard curve is, and the corresponding utilization Characterizes the overall numerical difference between the ith carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve. The larger the overall numerical difference, the more dissimilar the ith carbon emission-vehicle speed curve is to the carbon emission-vehicle speed standard curve, and the greater the numerical difference between the ith carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve.

[0076] (4) Performing a weighted summation on the curve trend difference and the numerical difference to obtain a carbon emission correction factor for the remaining environmental parameter interval corresponding to the carbon emission-vehicle speed curve.

[0077] In one embodiment, the carbon emission correction factor for the remaining environmental parameter interval corresponding to the i-th carbon emission-vehicle speed curve is:

[0078]

[0079] in, represents the carbon emission correction factor for the remaining environmental parameter interval corresponding to the i-th carbon emission-vehicle speed curve, represents the weight of the curve trend difference, represents the curve trend difference between the i-th carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve, Indicates the numerical difference between the ith carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve, The weight that represents the difference in value.

[0080] It should be noted that the trend difference and the value difference are equally important for the calculation of the carbon emission correction factor of the remaining environmental parameter interval corresponding to the i-th carbon emission-vehicle speed curve. Therefore, . The larger the value is, the greater the difference between the ith carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve is, and the greater the influence of the environmental parameters in the corresponding remaining environmental parameter interval on the carbon emission collection is, that is, the greater the error of the collected carbon emissions is, the greater the degree of correction required, and the greater the carbon emission correction factor of the remaining environmental parameter interval corresponding to the ith carbon emission-vehicle speed curve is; similarly, The larger the value of , the greater the error of the carbon emissions collected in the remaining environmental parameter interval corresponding to the i-th carbon emission-vehicle speed curve, and the greater the corresponding correction degree, the greater the carbon emission correction factor in the remaining environmental parameter interval corresponding to the i-th carbon emission-vehicle speed curve.

[0081] At this point, the carbon emission correction factor for the standard environmental parameter interval and the carbon emission correction factor for each remaining environmental parameter interval can be obtained.

[0082] Step S103, obtain the real-time carbon emissions and real-time environmental parameters of the vehicle at the real-time sampling moment, obtain the target carbon emissions correction factor corresponding to the real-time carbon emissions from the carbon emissions correction factors in the standard environmental parameter interval and each remaining environmental parameter interval according to the real-time environmental parameters, correct the real-time carbon emissions using the target carbon emissions correction factor to obtain the corrected carbon emissions, and perform carbon emissions monitoring and early warning on the vehicle according to the corrected carbon emissions.

[0083] Step S102 obtains the carbon emission correction factor under each environment based on the historical sampling data of the vehicle, which are the carbon emission correction factor of the standard environmental parameter interval and the carbon emission correction factor of each remaining environmental parameter interval, respectively. Then, these environmental parameter intervals are used as the basis for correcting the real-time carbon emissions to ensure that the carbon emissions collected from the vehicle in real time are more accurate. Therefore, in an embodiment of the present invention, the real-time carbon emissions and real-time environmental parameters of the vehicle at the real-time sampling moment are obtained, wherein the real-time sampling moment and all historical sampling moments can form a time series, and then determine which environmental parameter interval the real-time environmental parameters belong to in the standard environmental parameter interval and all remaining environmental parameter intervals, so as to correct the real-time carbon emissions using the corresponding carbon emission correction factor. Specifically: in the standard environmental parameter interval and all remaining environmental parameter intervals, determine the environmental parameter interval to which the real-time environmental parameter belongs as the target environmental parameter interval, and use the carbon emission correction factor of the target environmental parameter interval as the target carbon emission correction factor corresponding to the real-time carbon emissions.

[0084] After determining the target carbon emission correction factor corresponding to the real-time carbon emission, the difference between the constant 1 and the target carbon emission correction factor is obtained, and the product of the difference and the real-time carbon emission is used as the corrected carbon emission. The calculation expression of the corrected carbon emission is:

[0085]

[0086] in, represents the corrected carbon emissions, c represents the real-time carbon emissions, 1 represents a constant, Indicates the target carbon emissions correction factor corresponding to the real-time carbon emissions.

[0087] After correcting the real-time carbon emissions, the impact of environmental factors on vehicle carbon emissions is largely avoided. The influence of concentration measurement increases the measured The reference value of concentration is used for subsequent calculation based on vehicle carbon emissions. The concentration value provides a more accurate reference for further analysis and early warning, and then the vehicle is monitored and warned of carbon emissions according to the corrected carbon emissions. It is worth noting that the monitoring and early warning of carbon emissions for vehicles according to the corrected carbon emissions belongs to the prior art and is not the focus of the present invention, and will not be described in detail here. For example: a carbon emission threshold is set. If the corrected carbon emissions are greater than the carbon emission threshold, it is determined that the vehicle is exceeding the emission standard.

[0088] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A vehicle carbon emission monitoring and early warning system based on Internet of Things technology, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: For any vehicle, the carbon emissions, vehicle speed, and environmental parameters with preset weather type labels of the vehicle at each historical sampling moment are obtained, and a standard environmental parameter interval and multiple remaining environmental parameter intervals are obtained according to the environmental parameters with preset weather type labels at all historical sampling moments; According to the carbon emissions and vehicle speed at each of the historical sampling moments, a carbon emissions-vehicle speed standard curve for the standard environmental parameter interval and a carbon emissions-vehicle speed curve for each of the remaining environmental parameter intervals are respectively constructed; and according to the difference in curve trends between each of the carbon emissions-vehicle speed curves and the carbon emissions-vehicle speed standard curve, carbon emissions correction factors for the standard environmental parameter interval and each of the remaining environmental parameter intervals are respectively obtained; Acquire the real-time carbon emissions and real-time environmental parameters of the vehicle at the real-time sampling moment, and according to the real-time environmental parameters, obtain the target carbon emissions correction factor corresponding to the real-time carbon emissions from the carbon emissions correction factors in the standard environmental parameter interval and each of the remaining environmental parameter intervals, correct the real-time carbon emissions using the target carbon emissions correction factor to obtain the corrected carbon emissions, and perform carbon emissions monitoring and early warning on the vehicle according to the corrected carbon emissions; The obtaining, according to the curve trend difference between each of the carbon emission-vehicle speed curves and the carbon emission-vehicle speed standard curve, respectively the carbon emission correction factor for the standard environmental parameter interval and each of the remaining environmental parameter intervals comprises: Setting the carbon emission correction factor for the standard environmental parameter range to a preset value; For any carbon emission-vehicle speed curve, according to the curve correlation between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve, obtaining the curve trend difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve; According to the carbon emission difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve, obtaining the numerical difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve; A weighted sum is taken for the curve trend difference and the numerical difference to obtain a carbon emission correction factor for the remaining environmental parameter interval corresponding to the carbon emission-vehicle speed curve.

2. The vehicle carbon emission monitoring and early warning system based on Internet of Things technology according to claim 1 is characterized in that: The method of obtaining a standard environmental parameter interval and a plurality of remaining environmental parameter intervals according to the environmental parameters with preset weather type labels at all historical sampling moments includes: According to the environmental parameters with preset weather type labels at all historical sampling moments, all environmental parameters under the target weather type are obtained, wherein the environmental parameters include temperature and humidity, all temperatures under the target weather type are counted to obtain a temperature range, and all humidity under the target weather type are counted to obtain a humidity range, and the temperature range and the humidity range are combined into a standard environmental parameter range; The temperature range outside the temperature interval is divided to obtain a temperature division result, the humidity range outside the humidity interval is divided to obtain a humidity division result, and the temperature division result and the humidity division result are combined into temperature and humidity intervals to obtain a plurality of corresponding remaining environmental parameter intervals.

3. The vehicle carbon emission monitoring and early warning system based on Internet of Things technology according to claim 2 is characterized in that: The step of constructing the carbon emission-vehicle speed standard curve for the standard environmental parameter interval and the carbon emission-vehicle speed curve for each of the remaining environmental parameter intervals according to the carbon emission and vehicle speed at each of the historical sampling moments includes: According to the carbon emissions and vehicle speed at each historical sampling moment corresponding to the target weather type, a carbon emissions-vehicle speed standard curve in the standard environmental parameter interval is constructed using the least squares method; For any remaining environmental parameter interval, according to the environmental parameters at each historical sampling moment corresponding to the non-target weather type, the historical sampling moment of the environmental parameters in the remaining environmental parameter interval is obtained as the target historical sampling moment, and according to the carbon emissions and vehicle speed at each of the target historical sampling moments, the carbon emissions-vehicle speed curve of the remaining environmental parameter interval is constructed using the least squares method.

4. The vehicle carbon emission monitoring and early warning system based on Internet of Things technology according to claim 1 is characterized in that: The obtaining, according to the curve correlation between the carbon emission amount-vehicle speed curve and the carbon emission amount-vehicle speed standard curve, a curve trend difference between the carbon emission amount-vehicle speed curve and the carbon emission amount-vehicle speed standard curve, comprises: Obtaining an extreme point on the carbon emission-vehicle speed standard curve, taking the extreme point as a cutoff point, dividing the carbon emission-vehicle speed standard curve into n sub-standard curves, where n is greater than 1, and dividing the carbon emission-vehicle speed curve into n sub-curves according to the vehicle speed corresponding to each cutoff point; The Spearman correlation coefficients between the sub-standard curve and the sub-curve corresponding to the same vehicle speed range are respectively obtained, and the weight of each sub-curve is obtained according to the proportion of the number of data points of each sub-curve in the total number of data points of the carbon emission-vehicle speed curve. According to the weight of each sub-curve, all Spearman correlation coefficients are weighted summed to obtain the corresponding weighted summation result, and according to the negative number of the weighted summation result, the curve trend difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve is obtained.

5. The vehicle carbon emission monitoring and early warning system based on Internet of Things technology according to claim 1 is characterized in that: The obtaining, according to the carbon emission difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve, a numerical difference between the carbon emission-vehicle speed curve and the carbon emission-vehicle speed standard curve comprises: Calculating the carbon emission difference between the carbon emission corresponding to the kth data point on the carbon emission-vehicle speed curve and the carbon emission corresponding to the kth data point on the carbon emission-vehicle speed standard curve to obtain a carbon emission difference sequence; Calculate the average value of the absolute values ​​of all elements in the carbon emission difference sequence, use the average value as the independent variable of the hyperbolic tangent function, obtain a first function value, construct a difference change curve corresponding to the carbon emission difference sequence, obtain the derivative of each element in the carbon emission difference sequence according to the difference change curve, obtain the average value of all derivatives, use the average value as the independent variable of the hyperbolic tangent function, and obtain a second function value; The numerical difference between the carbon emission amount-vehicle speed curve and the carbon emission amount-vehicle speed standard curve is obtained according to the average value of the first function value and the second function value.

6. The vehicle carbon emission monitoring and early warning system based on Internet of Things technology according to claim 1 is characterized in that: The step of obtaining, according to the real-time environmental parameter, a target carbon emission correction factor corresponding to the real-time carbon emission from the carbon emission correction factors in the standard environmental parameter interval and each of the remaining environmental parameter intervals comprises: In the standard environmental parameter interval and all remaining environmental parameter intervals, the environmental parameter interval to which the real-time environmental parameter belongs is determined as the target environmental parameter interval, and the carbon emission correction factor of the target environmental parameter interval is used as the target carbon emission correction factor corresponding to the real-time carbon emissions.

7. The vehicle carbon emission monitoring and early warning system based on Internet of Things technology according to claim 1 is characterized in that: The step of correcting the real-time carbon emissions by using the target carbon emissions correction factor to obtain the corrected carbon emissions includes: The difference between the constant 1 and the target carbon emission correction factor is obtained, and the product of the difference and the real-time carbon emission is used as the corrected carbon emission.

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