Intelligent processing method for carbon emission reduction data of new energy transportation tool

Abstract

The method comprises data acquisition and carbon emission reduction calculation, the data acquisition comprises battery replacement data acquisition and charging data acquisition, and the carbon emission reduction calculation comprises mileage calculation, daily fuel saving amount calculation, daily carbon emission reduction calculation and enterprise daily carbon emission reduction calculation. The invention provides a method for accurately calculating the carbon emission reduction of an enterprise in the transportation industry, and aims to provide a solution for accurately calculating the carbon emission reduction for the enterprise by effectively collecting various energy consumption indexes under the operation condition of an electric vehicle and effectively filtering and processing data. The method has the advantages that electric vehicle data acquisition is complete and accurate, and carbon emission reduction index data of the electric vehicle can be calculated more accurately by considering various factors such as electric vehicle operation environment and battery life.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and in particular to a method for intelligently processing carbon emission reduction data of new energy transportation vehicles. Background Art

[0002] New energy transportation tools are gradually becoming the mainstream of the market, especially in the field of new energy electric transport trucks and all-electric pallet trucks. These tools are favored by the market for their environmental protection and high efficiency.

[0003] With the increasing global awareness of environmental protection and the pursuit of sustainable energy, the new energy vehicle industry has ushered in unprecedented development opportunities. In particular, as an important force in new energy logistics and transportation, the market demand for electric trucks is growing rapidly. However, the calculation of carbon emission reduction for corporate electric trucks involves many factors. Currently, there is no method to accurately calculate carbon emission reduction based on corporate business scenarios, and it is unable to meet the effective monitoring of corporate carbon emissions.

[0004] At present, the main technical difficulties involved in calculating carbon emission reductions of electric vehicles are reflected in the following aspects: data collection is difficult. Due to the complex vehicle operating environment, complex network environment, and multiple equipment transmission protocol specifications, data collection may be missing, lost, delayed, or misreported. The standards for calculating carbon emission reductions are complex, and the national and European standards have different calculation methods for carbon emission reductions in various industries and fields. At this stage, the calculation method of carbon emission reduction at the enterprise operation level is relatively broad and cannot meet the refined operation of enterprises. For this reason, we propose a method for intelligent processing of carbon emission reduction data for new energy transportation tools. Summary of the invention

[0005] The purpose of the present invention is to provide a method for intelligently processing carbon emission reduction data of new energy transportation vehicles to solve the problems that need to be solved in the background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a method for intelligently processing carbon emission reduction data of new energy transportation tools, the method for intelligently processing carbon emission reduction data of new energy transportation tools comprising data collection and carbon emission reduction calculation;

[0007] The data collection comprises the following steps:

[0008] Step A1: Battery replacement data collection: The driver replaces the battery for the vehicle through the Elenergy App or the station control staff manually, and reports the battery serial number and battery SOC information;

[0009] Step A2: Charging data collection: The driver initiates the operation of charging or stopping the vehicle through the Elenergy App, communicates with the charging pile through the OCPP protocol, and collects data during the charging process;

[0010] The carbon reduction calculation includes the following steps:

[0011] Step B1: Calculation of the current mileage: The total mileage data reported by the vehicle dashboard is subtracted from the mileage data reported last time to obtain the current mileage;

[0012] Step B2: Calculation of daily fuel saving: First, the corresponding seasonal impact factor is obtained according to the season, and the amount of fuel saved by the electric vehicle compared with the fuel vehicle is calculated according to the seasonal impact factor, and then the daily fuel saving is obtained by multiplying the daily mileage by the seasonal impact factor;

[0013] Step B3: Calculation of daily carbon emission reduction: multiply the daily fuel saving obtained in step B1 and step B2 by the amount of carbon dioxide produced per liter of oil to obtain the corresponding daily carbon emission reduction;

[0014] Step B4: Calculation of the company's daily carbon emission reduction: The company's daily carbon emission reduction is the total carbon emission reduction of all operating vehicles on that day.

[0015] At present, the main technical difficulties in calculating carbon emission reduction of electric vehicles are reflected in the following aspects: data collection is difficult, due to the complex vehicle operating environment, complex network environment, and multiple equipment transmission protocol specifications, which lead to missing, lost, delayed, and false reports in data collection. The calculation standards for carbon emission reduction are complex, and the calculation methods of carbon emission reduction in various industries and fields corresponding to national and European standards are different. At present, the calculation methods for carbon emission reduction at the enterprise operation level are relatively broad and cannot meet the needs of enterprise refined operations. The present invention provides a method suitable for the transportation industry to accurately calculate enterprise carbon emission reduction. It aims to effectively collect various energy consumption indicators under the operation of electric vehicles, and through effective filtering and processing of data, provide enterprises with a set of solutions for accurate calculation of carbon emission reduction. The carbon emission reduction calculation method proposed in the present invention has the advantages of complete and accurate collection of electric vehicle data, and can more accurately calculate the carbon emission reduction index data of electric vehicles by considering various factors such as the operating environment of electric vehicles and battery life. When collecting data, battery replacement data and charging data can be collected, and the collected data can be used to calculate the charging and replacement data. Subsequently, the vehicle TBOX protocol is used to realize the interconnection between the Elenergy platform and the vehicle, thereby ensuring the accuracy of vehicle data and the timeliness of transmission.

[0016] As a further description of the above technical solution:

[0017] The data collection also includes vehicle data collection, which uses the vehicle TBOX protocol to achieve interconnection between the Elenergy platform and the vehicle, and transmits the basic information of the vehicle to the platform through the TBOX protocol.

[0018] As a further description of the above technical solution:

[0019] The vehicle data collection platform establishes a unified vehicle data collection gateway and a combination of multiple vehicle model communication protocol adapters to support data collection of multiple models.

[0020] As a further description of the above technical solution:

[0021] The vehicle data collection comprises the following steps:

[0022] Step C1: Obtain the vehicle's reported data from the message queue;

[0023] Step C2: Check the validity of the data. When the speed, mileage, battery SOC in the vehicle data is zero or the vehicle frame number is empty, the data is determined to be invalid;

[0024] Step C3: Obtain vehicle information and vehicle status data in the cache data, add the vehicle's driving log, update the collected vehicle real-time data, and add the vehicle's driving trajectory log;

[0025] Step C4: Substituting the cache data obtained in step C3 into the carbon emission reduction calculation can complete the vehicle carbon emission reduction calculation.

[0026] As a further description of the above technical solution:

[0027] The selection of seasonal influencing factors in step B2 is divided into two groups. The first group of seasonal factors is set from May to September, and the seasonal factor is set to 0.45. The second group of seasonal factors is set from October to April, and the seasonal factor is set to 0.4.

[0028] As a further description of the above technical solution:

[0029] In step B1, the validity of the vehicle data needs to be verified in the mileage calculation. The vehicle data is considered to be accurate if the vehicle reports accurate data during actual operation, performs transportation tasks, the vehicle frame number matches the IMEI number of the TBOX, the reporting time sequence is consistent, the vehicle speed is non-zero, and the difference between the two reported mileages is greater than zero.

[0030] As a further description of the above technical solution:

[0031] The daily mileage calculation formula is:

[0032]

[0033] The daily fuel saving calculation formula is:

[0034] D fsc =Ds*Sf

[0035] The daily carbon reduction calculation formula is:

[0036] Dc=D fsc *Cdo

[0037] The daily carbon reduction calculation formula is:

[0038]

[0039] Among them, Dd is the mileage of this trip, Ds is the daily mileage, Sf is the seasonal impact factor, Dfsc is the daily fuel saving, Cdo is the carbon dioxide produced per liter of oil, Dc is the daily carbon emission reduction, and Edc is the daily carbon emission reduction of the enterprise;

[0040] Among them, n in the daily mileage refers to all mileage segments of the vehicle on that day, and n in the daily carbon emission reduction calculation formula refers to the number of all vehicles on that day.

[0041] As a further description of the above technical solution:

[0042] The calculation formula for the enterprise's daily carbon emission reduction is:

[0043]

[0044] Among them, Edc is the daily carbon emission reduction of the enterprise, and n is the number of days required to count the carbon emission reduction of the enterprise.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. The present invention provides a method suitable for accurately calculating carbon emission reduction of enterprises in the transportation industry, aiming to provide enterprises with a set of solutions for accurately calculating carbon emission reduction by effectively collecting various energy consumption indicators under the operation of electric vehicles and effectively filtering and processing data.

[0047] 2. The carbon emission reduction calculation method proposed in the present invention has the advantages of complete and accurate data collection of electric vehicle data, and can more accurately calculate the carbon emission reduction index data of electric vehicles by considering various factors such as the operating environment of electric vehicles and battery life;

[0048] 3. During data collection, the battery swap data and charging data can be collected, and the charging and swap data can be calculated from the collected data. Then, the vehicle TBOX protocol is used to realize the interconnection between the Elenergy platform and the vehicle, ensuring the accuracy of vehicle data and the timeliness of transmission;

[0049] 4. The carbon emission reduction calculation formula is set up by establishing a mathematical model, combining multiple factors such as the actual vehicle mileage, seasonal influencing factors, and the amount of carbon dioxide produced per liter of oil, to achieve accurate calculation of the carbon emission reduction of electric vehicles; comprehensive analysis of carbon emissions: This calculation method not only takes into account the actual driving conditions of electric vehicles, but also takes into account multiple factors such as the battery SOC status and the vehicle's working environment, providing a more comprehensive analysis perspective and improving data collection integrity and accuracy: Data collection for electric vehicles is optimized to ensure the integrity and accuracy of data collection, which helps to more accurately calculate the carbon emission reduction indicator data of electric vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of the system principle of the present invention;

[0051] Figure 2 The vehicle data processing logic diagram of the present invention;

[0052] Figure 3 This is a schematic diagram of the vehicle data collection service architecture of the present invention;

[0053] Figure 4 This is a diagram of the steps for calculating carbon emission reduction for an enterprise according to the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] Example 1: Please refer to Figure 1-Figure 4 , the present invention provides a technical solution: a method for intelligently processing carbon emission reduction data of new energy transportation tools, the method for intelligently processing carbon emission reduction data of new energy transportation tools comprising data collection and carbon emission reduction calculation;

[0056] The data collection comprises the following steps:

[0057] Step A1: Battery replacement data collection: The driver replaces the battery for the vehicle through the Elenergy App or the station control staff manually, and reports the battery serial number and battery SOC information;

[0058] Step A2: Charging data collection: The driver initiates the operation of charging or stopping the vehicle through the Elenergy App, communicates with the charging pile through the OCPP protocol, and collects data during the charging process;

[0059] The carbon reduction calculation includes the following steps:

[0060] Step B1: Calculation of the current mileage: The total mileage data reported by the vehicle dashboard is subtracted from the mileage data reported last time to obtain the current mileage;

[0061] Step B2: Calculation of daily fuel saving: First, the corresponding seasonal impact factor is obtained according to the season, and the amount of fuel saved by the electric vehicle compared with the fuel vehicle is calculated according to the seasonal impact factor, and then the daily fuel saving is obtained by multiplying the daily mileage by the seasonal impact factor;

[0062] Step B3: Calculation of daily carbon emission reduction: multiply the daily fuel saving obtained in step B1 and step B2 by the amount of carbon dioxide produced per liter of oil to obtain the corresponding daily carbon emission reduction;

[0063] Step B4: Calculation of the company's daily carbon emission reduction: The company's daily carbon emission reduction is the total carbon emission reduction of all operating vehicles on that day.

[0064] Among them, the above method provides a complete solution for data collection of electric vehicles, ensuring the integrity and accuracy of the data, which is crucial for the subsequent carbon emission reduction calculation. By establishing a mathematical model, various factors affecting carbon emissions are linked, so that the carbon emission reduction of electric vehicles can be accurately calculated. This helps companies to more accurately grasp their carbon footprint and make more effective emission reduction strategies based on this, solving the problem of data collection: and solving common problems in the data collection process, such as data missing, loss, delays, etc., improving the quality of the data, and ensuring the reliability of the basic data for carbon emission reduction calculations. Compared with the existing broad carbon emission reduction calculation methods, this method is more meticulous and can support the company's refined operation management and help companies better meet the needs of carbon emission monitoring.

[0065] The data collection also includes vehicle data collection, which uses the vehicle TBOX protocol to achieve interconnection between the Elenergy platform and the vehicle, and transmits the basic information of the vehicle to the platform through the TBOX protocol.

[0066] Among them, the set vehicle data collection can use the vehicle TBOX protocol to realize the interconnection between the Elenergy platform and the vehicle. The electric vehicle battery replacement is a process in which the driver drives the vehicle to the battery replacement station equipment, and the driver replaces the power battery for the vehicle automatically through the Elenergy App or manually by the station control personnel. The battery to be replaced and the relevant information of the replaced battery are reported to the platform, such as the SN and SOC of the corresponding battery, so as to ensure the integrity and accuracy of the vehicle information.

[0067] The vehicle data collection platform establishes a unified vehicle data collection gateway and a combination of multiple vehicle model communication protocol adapters to support data collection of multiple models.

[0068] Among them, the Elenergy platform receives data sent from vehicles to the platform through each vehicle communication protocol adapter, unifies the vehicle data into the platform standard data format through the protocol adapter, and then sends it to the receiving data message queue; the unified vehicle data processing service obtains vehicle data from the message queue and executes related business processing logic. This architecture implements the expansion support of various protocols on the market by implementing a variety of vehicle protocol receivers, and can also be connected with the proprietary protocols of car companies in the future. In addition, the vehicle data message queue is used to decouple each vehicle receiver from the unified vehicle data processing logic service; because the platform vehicles are generally configured to synchronize data every 5 seconds, it also plays the role of buffering, peak shaving, and asynchrony when there are many online vehicles.

[0069] The vehicle data collection comprises the following steps:

[0070] Step C1: Obtain the vehicle's reported data from the message queue;

[0071] Step C2: Check the validity of the data. When the speed, mileage, battery SOC in the vehicle data is zero or the vehicle frame number is empty, the data is determined to be invalid;

[0072] Step C3: Obtain vehicle information and vehicle status data in the cache data, add the vehicle's driving log, update the collected vehicle real-time data, and add the vehicle's driving trajectory log;

[0073] Step C4: Substituting the cache data obtained in step C3 into the carbon emission reduction calculation can complete the vehicle carbon emission reduction calculation.

[0074] Among them, vehicle data can be collected and uploaded during vehicle data collection, and invalid data in the uploaded data can be eliminated during the uploading process, so as to ensure the accuracy of the uploaded data, and facilitate the use of uploaded data for calculation, so as to obtain carbon emission reduction data.

[0075] The selection of seasonal influencing factors in step B2 is divided into two groups. The first group of seasonal factors is set from May to September, and the seasonal factor is set to 0.45. The second group of seasonal factors is set from October to April, and the seasonal factor is set to 0.4.

[0076] Among them, when calculating the daily fuel savings, the daily fuel savings calculation formula is used to estimate based on the mileage of electric vehicles and the fuel efficiency of fuel vehicles, and the seasonal factor is set to take seasonal reasons into consideration, so that the seasonal factor coefficient is adjusted to adjust the fuel efficiency of fuel vehicles, and then the fuel savings are calculated. When calculating the daily fuel savings, the calculation formula does not need to consider factors such as the specific vehicle model, driving conditions and maintenance status.

[0077] In step B1, the validity of the vehicle data needs to be verified in the mileage calculation. The vehicle data is considered to be accurate if the vehicle reports accurate data during actual operation, performs transportation tasks, the vehicle frame number matches the IMEI number of the TBOX, the reporting time sequence is consistent, the vehicle speed is non-zero, and the difference between the two reported mileages is greater than zero.

[0078] Embodiment 2:

[0079] The daily mileage calculation formula is:

[0080]

[0081] The daily fuel saving calculation formula is:

[0082] D fsc =Ds*Sf

[0083] The daily carbon reduction calculation formula is:

[0084] Dc=D fsc *Cdo

[0085] The daily carbon reduction calculation formula is:

[0086]

[0087] Among them, Dd is the mileage of this trip, Ds is the daily mileage, Sf is the seasonal impact factor, Dfsc is the daily fuel saving, Cdo is the carbon dioxide produced per liter of oil, Dc is the daily carbon emission reduction, and Edc is the daily carbon emission reduction of the enterprise;

[0088] Among them, n in the daily mileage refers to all mileage segments of the vehicle on that day, and n in the daily carbon emission reduction calculation formula refers to the number of all vehicles on that day.

[0089] The calculation formula for the enterprise's daily carbon emission reduction is:

[0090]

[0091] Among them, Edc is the daily carbon emission reduction of the enterprise, and n is the number of days required to count the carbon emission reduction of the enterprise.

[0092] Among them, the setting of the carbon emission reduction calculation formula realizes the accurate calculation of the carbon emission reduction of electric vehicles by establishing a mathematical model, combining multiple factors such as the actual vehicle mileage, seasonal influencing factors, and the amount of carbon dioxide produced per liter of oil; comprehensive analysis of carbon emissions: This calculation method not only takes into account the actual driving conditions of electric vehicles, but also takes into account multiple factors such as the battery SOC status and the vehicle's working environment, providing a more comprehensive analysis perspective and improving the integrity and accuracy of data collection: Data collection for electric vehicles is optimized to ensure the integrity and accuracy of data collection, which helps to more accurately calculate the carbon emission reduction index data of electric vehicles.

[0093] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for intelligently processing carbon emission reduction data of new energy transportation tools, characterized by: The method for intelligently processing carbon emission reduction data of new energy transportation tools includes data collection and carbon emission reduction calculation; The data collection comprises the following steps: Step A1: Battery replacement data collection: The driver replaces the battery for the vehicle through the Elenergy App or the station control staff manually, and reports the battery serial number and battery SOC information; Step A2: Charging data collection: The driver initiates the operation of charging or stopping the vehicle through the Elenergy App, communicates with the charging pile through the OCPP protocol, and collects data during the charging process; The carbon reduction calculation includes the following steps: Step B1: Calculation of the current mileage: The total mileage data reported by the vehicle dashboard is subtracted from the mileage data reported last time to obtain the current mileage; Step B2: Calculation of daily fuel saving: First, the corresponding seasonal impact factor is obtained according to the season, and the amount of fuel saved by the electric vehicle compared with the fuel vehicle is calculated according to the seasonal impact factor, and then the daily fuel saving is obtained by multiplying the daily mileage by the seasonal impact factor; Step B3: Calculation of daily carbon emission reduction: multiply the daily fuel saving obtained in step B1 and step B2 by the amount of carbon dioxide produced per liter of oil to obtain the corresponding daily carbon emission reduction; Step B4: Calculation of the company's daily carbon emission reduction: The company's daily carbon emission reduction is the total carbon emission reduction of all operating vehicles on that day.

2. The method for intelligently processing carbon emission reduction data of new energy transportation tools according to claim 1 is characterized by: The data collection also includes vehicle data collection, which uses the vehicle TBOX protocol to achieve interconnection between the Elenergy platform and the vehicle, and transmits the basic information of the vehicle to the platform through the TBOX protocol.

3. The method for intelligently processing carbon emission reduction data of new energy transportation tools according to claim 2 is characterized by: The vehicle data collection platform establishes a unified vehicle data collection gateway and a combination of multiple vehicle model communication protocol adapters to support data collection of multiple models.

4. The method for intelligently processing carbon emission reduction data of new energy transportation tools according to claim 3 is characterized by: The vehicle data collection comprises the following steps: Step C1: Obtain the vehicle's reported data from the message queue; Step C2: Check the validity of the data. When the speed, mileage, battery SOC in the vehicle data is zero or the vehicle frame number is empty, the data is determined to be invalid; Step C3: Obtain vehicle information and vehicle status data in the cache data, add the vehicle's driving log, update the collected vehicle real-time data, and add the vehicle's driving trajectory log; Step C4: Substituting the cache data obtained in step C3 into the carbon emission reduction calculation can complete the vehicle carbon emission reduction calculation.

5. The method for intelligently processing carbon emission reduction data of new energy transportation tools according to claim 4 is characterized by: The selection of seasonal influencing factors in step B2 is divided into two groups. The first group of seasonal factors is set from May to September, and the seasonal factor is set to 0.

45. The second group of seasonal factors is set from October to April, and the seasonal factor is set to 0.

4.

6. The method for intelligently processing carbon emission reduction data of new energy transportation tools according to claim 5 is characterized by: In step B1, the validity of the vehicle data needs to be verified in the mileage calculation. The vehicle data is considered to be accurate if the vehicle reports accurate data during actual operation, performs transportation tasks, the vehicle frame number matches the IMEI number of the TBOX, the reporting time sequence is consistent, the vehicle speed is non-zero, and the difference between the two reported mileages is greater than zero.

7. The method for intelligently processing carbon emission reduction data of new energy transportation tools according to claim 6 is characterized by: The daily mileage calculation formula is: The daily fuel saving calculation formula is: D fsc =Ds*Sf The daily carbon reduction calculation formula is: Dc=D fsc *Cdo The daily carbon reduction calculation formula is: Among them, Dd is the mileage of this trip, Ds is the daily mileage, Sf is the seasonal impact factor, Dfsc is the daily fuel saving, Cdo is the carbon dioxide produced per liter of oil, Dc is the daily carbon emission reduction, and Edc is the daily carbon emission reduction of the enterprise; Among them, n in the daily mileage refers to all mileage segments of the vehicle on that day, and n in the daily carbon emission reduction calculation formula refers to the number of all vehicles on that day.

8. The method for intelligently processing carbon emission reduction data of new energy transportation tools according to claim 7 is characterized by: The calculation formula for the enterprise's daily carbon emission reduction is: Among them, Edc is the daily carbon emission reduction of the enterprise, and n is the number of days required to count the carbon emission reduction of the enterprise.

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