Vehicle carbon emission accounting method and device, computer equipment and storage medium

Abstract

The invention relates to the technical field of energy emission, and discloses a vehicle carbon emission accounting method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining the energy consumption carbon emission corresponding to the consumed energy consumption of a target vehicle in a use stage; acquiring training carbon emission of a cloud training intelligent driving model, and determining intelligent driving carbon emission of the target vehicle using the intelligent driving model according to the training carbon emission; determining flow carbon emission corresponding to flow consumed by interaction between the target vehicle and the cloud in the use stage; and using carbon emission data of the target vehicle in the using stage are determined by integrating the energy consumption carbon emission, the intelligent driving carbon emission and the flow carbon emission. According to the method, the energy consumption carbon emission, the intelligent driving carbon emission and the flow carbon emission are integrated, the carbon emission of the vehicle in the use stage can be more accurately determined, and the method is suitable for the carbon emission accounting scene of the intelligent driving vehicle.

Description

Technical Field

[0001] The present invention relates to the field of energy emission technology, and in particular to a method, device, computer equipment and storage medium for calculating vehicle carbon emissions. Background Art

[0002] Carbon emissions is a general term or abbreviation for greenhouse gas emissions. In order to promote the development of new energy sources such as wind power and photovoltaics, new energy vehicles such as electric vehicles are gradually emerging to reduce carbon emissions from the source. However, in order to determine whether new energy vehicles can adapt to the development of the times, it is necessary to accurately calculate the carbon emissions of various vehicles. Summary of the invention

[0003] In view of this, the present invention provides a method, apparatus, computer equipment and storage medium for calculating vehicle carbon emissions, so as to accurately calculate the vehicle's carbon emissions.

[0004] In a first aspect, the present invention provides a method for calculating vehicle carbon emissions, comprising:

[0005] Obtain the energy consumption and carbon emissions corresponding to the energy consumption of the target vehicle during the use phase;

[0006] Obtaining the training carbon emissions of the intelligent driving model trained in the cloud, and determining the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions;

[0007] Determine the traffic carbon emissions corresponding to the traffic consumed by the target vehicle in interacting with the cloud during the use phase;

[0008] The carbon emissions data of the target vehicle during the use phase is determined by comprehensively analyzing the energy consumption carbon emissions, the intelligent driving carbon emissions and the traffic carbon emissions.

[0009] In an optional implementation, the obtaining of the training carbon emissions of the intelligent driving model trained in the cloud, and determining the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions, includes:

[0010] Obtaining the training carbon emissions of the cloud-based intelligent driving model and the number of first vehicles using the intelligent driving model;

[0011] Determining a deployment carbon emission amount corresponding to deploying the intelligent driving model for the target vehicle;

[0012] Determine the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions, the number of vehicles and the deployment carbon emissions;

[0013]

[0014] Among them, E 智驾 Represents the carbon emissions of intelligent driving, E 训练 represents the training carbon emissions, N1 represents the first number of vehicles, E 部署 Represents the carbon emissions of the deployment.

[0015] In an optional embodiment, the method further includes:

[0016] When the intelligent driving model in the cloud is updated from the first version model to the second version model, determining the updated carbon emissions corresponding to the update stage;

[0017] Determining an upgraded carbon emission amount corresponding to upgrading the intelligent driving model of the target vehicle from a first version model to a second version model;

[0018] adding the updated carbon emissions to the training carbon emissions corresponding to the intelligent driving model to update the training carbon emissions corresponding to the intelligent driving model;

[0019] adding the upgraded carbon emissions to the deployed carbon emissions of the target vehicle to update the deployed carbon emissions of the target vehicle;

[0020] According to the updated training carbon emissions and the updated deployment carbon emissions, the intelligent driving carbon emissions of the target vehicle using the intelligent driving model are updated.

[0021] In an optional embodiment, the method further includes:

[0022] In case the second version model is deployed for other vehicles, determining the number of second vehicles on which the second version model is deployed;

[0023] Determining carbon emissions of the other vehicles using the intelligent driving model;

[0024]

[0025] Among them, E' 智驾 represents the carbon emissions of other vehicles using the intelligent driving model, E 更新 represents the updated carbon emissions, N2 represents the second number of vehicles, E' 部署 Indicates the carbon emissions corresponding to deploying the intelligent driving model for the other vehicles;

[0026] The intelligent driving carbon emissions of the target vehicle using the intelligent driving model are subtracted from the error carbon emissions to update the intelligent driving carbon emissions of the target vehicle using the intelligent driving model; the error carbon emissions ΔE is:

[0027] The first number of vehicles using the intelligent driving model is updated from N1 to N1+N2.

[0028] In an optional implementation, determining the traffic carbon emissions corresponding to the traffic consumed by the target vehicle in interacting with the cloud during the use phase includes:

[0029] Obtaining the traffic usage consumed by the target vehicle when interacting with the cloud based on the interaction request during the use phase;

[0030] Obtaining cloud computing carbon emissions corresponding to computing power consumed by the cloud in responding to the interaction request based on cloud computing;

[0031] Determine the traffic carbon emissions corresponding to the target vehicle according to the traffic usage and the cloud computing carbon emissions;

[0032] E 流量 =D×EF 流量 +E 云计算 ;

[0033] Among them, E 流量 represents the carbon emission of the flow, D represents the flow usage, EF 流量 The carbon emission factor of the flow, E 云计算 Represents the carbon emissions of cloud computing.

[0034] In an optional embodiment, the method further includes:

[0035] Obtaining carbon emission data of components corresponding to components in the target vehicle, carbon emission data of the target vehicle during the vehicle production stage, and transportation carbon emission data generated by transporting the target vehicle;

[0036] Determine the carbon emission data of the target vehicle throughout its life cycle by combining the carbon emission data of use, the carbon emission data of parts, the carbon emission data of vehicle production, and the carbon emission data of transportation;

[0037] E 车辆 =E0+E1+E2+E3;

[0038] Among them, E 车辆 It represents the carbon emission data of the target vehicle throughout its life cycle, E0 represents the carbon emission data of use, E1 represents the carbon emission data of parts, E2 represents the carbon emission data of vehicle production, and E3 represents the carbon emission data of transportation.

[0039] In an optional implementation, the component carbon emission data E1 is:

[0040] EM irepresents the carbon emission of raw materials of the i-th component of the target vehicle, EP i represents the carbon emission of producing the i-th component;

[0041] The vehicle production carbon emission data E2 is:

[0042] E2=E 整车工艺 +E 工艺设备 ; E 整车工艺 It represents the total carbon emissions corresponding to the energy consumed by the whole vehicle process during the whole vehicle production stage of the target vehicle, E 工艺设备 Indicates the total carbon emissions generated by process equipment during the vehicle production stage of the target vehicle;

[0043] Among them, E 整车工艺 =E 电力 +E 热力 ; E 电力 =EM 电力 ×EF 电力 , E 热力 =EM 热力 ×EF 热力 ; E 电力 represents the carbon emissions generated by the electricity consumed during the vehicle production phase of the target vehicle, E 热力 Indicates the carbon emissions generated by the heat consumption during the vehicle production stage of the target vehicle; EM 电力 represents the power consumption during the vehicle production stage of the target vehicle, EF 电力 Represents the carbon emission factor of electricity; EM 热力 represents the heat consumption of the target vehicle during the vehicle production stage, EF 热力 represents the carbon emission factor for heat;

[0044] EM 设备,i Indicates the consumption of the substances directly discharged by the i-th process equipment in the whole vehicle production stage of the target vehicle, EF 设备,i represents the carbon emission factor of the ith process equipment;

[0045] The transport carbon emission data E3 is:

[0046] E3=ET 零部件 +ET 整车 ET 零部件 represents the carbon emissions generated by transporting the parts of the target vehicle, ET 整车 Indicates the carbon emissions generated by transporting the entire vehicle;

[0047] in, M i represents the weight of the parts transported by the ith mode of transportation, S零部件,i represents the transportation distance of parts transported by the i-th mode of transportation, EF 零部件,i represents the carbon emission factor of transporting parts using the i-th mode of transportation;

[0048] ET vehicle = (S vehicle, j × EF vehicle, j) / Cj; the target vehicle is transported by the jth mode of transportation, and S 整车,j represents the transportation distance of the target vehicle using the j-th transportation method, EF 整车,j represents the carbon emission factor of transporting the target vehicle using the j-th mode of transportation, C j Represents the number of vehicles transported in a single trip using the j-th mode of transportation.

[0049] In a second aspect, the present invention provides a device for calculating vehicle carbon emissions, comprising:

[0050] The first acquisition module is used to obtain the energy consumption carbon emissions corresponding to the energy consumption of the target vehicle during the use phase;

[0051] A second acquisition module is used to obtain the training carbon emissions of the intelligent driving model trained in the cloud, and determine the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions;

[0052] The third acquisition module is used to determine the traffic carbon emissions corresponding to the traffic consumed by the target vehicle in interacting with the cloud during the use phase;

[0053] A determination module is used to comprehensively determine the carbon emissions of the target vehicle during the use phase by combining the carbon emissions of energy consumption, the carbon emissions of intelligent driving and the carbon emissions of traffic.

[0054] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method for calculating vehicle carbon emissions according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0055] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for calculating vehicle carbon emissions according to the first aspect or any corresponding embodiment thereof.

[0056] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the method for calculating vehicle carbon emissions according to the first aspect or any corresponding embodiment thereof.

[0057] When calculating the carbon emission data of the vehicle's use phase, the present invention not only determines the energy consumption carbon emissions generated by the vehicle's energy consumption, but also determines the intelligent driving carbon emissions using the intelligent driving model and the traffic carbon emissions of network interactions. The comprehensive energy consumption carbon emissions, intelligent driving carbon emissions, and traffic carbon emissions can more accurately determine the carbon emissions of the vehicle's use phase, thereby enabling more accurate carbon emission accounting for vehicles with intelligent driving functions. This carbon emission accounting method takes into account the carbon emission calculation of intelligent driving, is suitable for carbon emission accounting scenarios of intelligent driving vehicles, and is more in line with the current direction of automobile development for carbon footprint accounting of complete vehicle products. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the related technologies, the drawings required for use in the specific embodiments or the related technical descriptions will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0059] Figure 1 is a flow chart of a method for calculating vehicle carbon emissions according to an embodiment of the present invention;

[0060] Figure 2 is a flow chart of another method for calculating vehicle carbon emissions according to an embodiment of the present invention;

[0061] Figure 3 is a schematic diagram of the entire life cycle of a vehicle according to an embodiment of the present invention;

[0062] Figure 4 is a structural block diagram of a device for calculating vehicle carbon emissions according to an embodiment of the present invention;

[0063] Figure 5 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 those skilled in the art without creative work are within the scope of protection of the present invention.

[0065] In order to accurately calculate the vehicle's complete carbon emissions, we can start from the vehicle's entire life cycle and comprehensively consider the vehicle's carbon emissions from production, processing, use and other stages to accurately determine the vehicle's carbon emissions.

[0066] However, this carbon emission accounting method only considers general components in the vehicle and is applicable to traditional vehicles, such as traditional fuel vehicles. However, with the development and improvement of vehicle functions, especially the development of new energy vehicles such as electric vehicles, vehicle functions are gradually increasing, resulting in the traditional carbon emission calculation method being unsuitable for new smart cars.

[0067] For example, when using smart vehicles, they may use smart driving software, which involves a lot of computing power in the cloud and carbon emissions caused by refrigeration. In addition, the number of consumers using smart driving services is increasing day by day, and the carbon emissions of special parts such as software cannot be ignored. However, the current carbon emission accounting method does not involve these carbon emissions, resulting in inaccurate carbon emissions determined when calculating carbon emissions for smart vehicles.

[0068] The method for calculating vehicle carbon emissions provided by an embodiment of the present invention, when calculating the carbon emissions during the vehicle's use phase, in addition to determining the energy consumption carbon emissions generated by the vehicle's energy consumption, also determines the intelligent driving carbon emissions using an intelligent driving model and the traffic carbon emissions of network interactions. By combining the energy consumption carbon emissions, intelligent driving carbon emissions, and traffic carbon emissions, the carbon emissions during the vehicle's use phase can be determined more accurately. This method is suitable for carbon emission calculation scenarios for intelligent driving vehicles and is in line with current automobile development trends.

[0069] According to an embodiment of the present invention, a method embodiment for calculating vehicle carbon emissions is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0070] In this embodiment, a method for calculating vehicle carbon emissions is provided, which can be applied to a device that needs to calculate the carbon emissions of a vehicle, such as a server, or the vehicle itself. Figure 1 is a flow chart of a method for calculating vehicle carbon emissions according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps.

[0071] Step S101, obtaining the energy consumption and carbon emissions corresponding to the energy consumption of the target vehicle during the use phase.

[0072] In this embodiment, for the convenience of description, the vehicle that needs to be accounted for carbon emissions is referred to as a "target vehicle". The target vehicle is an intelligent vehicle with intelligent functions; for example, the target vehicle is a new energy vehicle with an intelligent cockpit, or the target vehicle is a fuel vehicle with an automatic driving function.

[0073] Among them, when the user uses the target vehicle, that is, during the use phase of the target vehicle, it is necessary to consume electricity, fuel and other energy. The use of these energy consumptions will generate a certain amount of carbon emissions. Therefore, the carbon emissions corresponding to the energy consumption of the target vehicle can be determined, that is, the energy consumption carbon emissions.

[0074] For example, during the use phase of the target vehicle, the more energy consumed, the greater the energy consumption carbon emissions generated. The energy consumption carbon emissions can be calculated based on the carbon emission factor (Emission Factor, EF) of the energy consumption, which is not limited in this embodiment.

[0075] Step S102, obtaining the training carbon emissions of the intelligent driving model trained in the cloud, and determining the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions.

[0076] In this embodiment, the new target vehicle is generally embedded with a neural network model for realizing intelligent driving, that is, an intelligent driving model; for example, the intelligent driving model can be an automatic driving model, an image recognition model, a target detection model, etc., which is determined based on the actual situation. When the target vehicle simply uses the intelligent driving model, it does not generate carbon emissions, or in other words, this part of carbon emissions is generated by the target vehicle running a processor or controller, and this part of carbon emissions can be determined based on energy consumption, that is, this part of carbon emissions is attributed to energy consumption carbon emissions.

[0077] However, due to the particularity of the intelligent driving model, before using the intelligent driving model, the cloud needs to first perform model training to train the intelligent driving model available to the user, which will consume the computing power of the cloud server, thereby generating carbon emissions, and will also generate carbon emissions due to cooling, etc. Therefore, in this embodiment, the carbon emissions of the cloud training intelligent driving model, that is, the training carbon emissions, are determined, and the intelligent driving carbon emissions of the target vehicle using the intelligent driving model are determined based on the training carbon emissions. It can be understood that the greater the training carbon emissions, the greater the intelligent driving carbon emissions.

[0078] For example, the training carbon emissions can be determined based on the training duration of the intelligent driving model. For example, the training carbon emissions = energy consumption per unit time when training the intelligent driving model (which may include computing power energy consumption, cooling energy consumption, etc.) × training duration × carbon emission factor of training the intelligent driving model.

[0079] Step S103, determining the traffic carbon emissions corresponding to the traffic consumed by the target vehicle in interacting with the cloud during the use phase.

[0080] In this embodiment, the new target vehicle generally also has a network function, that is, it can interact with the cloud through the network. For example, the target vehicle can play music, videos, etc. based on the network. Similar to the process of determining the above-mentioned intelligent driving carbon emissions, this part of carbon emissions is also generated by the equipment that interacts with the target vehicle and is related to the traffic consumed during the interaction. Therefore, this part of carbon emissions can be determined based on the consumed traffic, that is, traffic carbon emissions.

[0081] It can be understood that the more traffic consumed, the greater the carbon emissions of the traffic. If the target vehicle does not have a network function, or the target vehicle does not turn on the network function, the current traffic carbon emissions are 0.

[0082] Furthermore, the cloud in step S103 and step S102 may be the same cloud or different clouds, depending on actual conditions.

[0083] Step S104, comprehensively analyzing carbon emissions from energy consumption, carbon emissions from intelligent driving, and carbon emissions from traffic volume, to determine the carbon emissions data of the target vehicle during its use phase.

[0084] In this embodiment, for the target vehicle with intelligent driving function, during its use phase, in addition to the energy consumption carbon emissions, the deployment of intelligent driving models or interaction with the cloud will also result in intelligent driving carbon emissions and traffic carbon emissions. By combining these three types of carbon emissions, the carbon emissions of the target vehicle during the use phase can be more accurately determined, and this carbon emissions can be used as the carbon emissions data for the target vehicle.

[0085] For example, the target vehicle's carbon emission data E0 can be: E0 = E 能耗 +E 智驾 +E 流量 ; Among them, E 能耗 Indicates energy consumption and carbon emissions, E 智驾 Indicates the carbon emissions of intelligent driving, E 流量 Indicates the carbon emissions of traffic.

[0086] The method for calculating vehicle carbon emissions provided in this embodiment, when calculating the carbon emission data during the vehicle's use phase, in addition to determining the energy consumption carbon emissions generated by the vehicle's energy consumption, also determines the intelligent driving carbon emissions using the intelligent driving model and the traffic carbon emissions of network interactions. The comprehensive energy consumption carbon emissions, intelligent driving carbon emissions, and traffic carbon emissions can more accurately determine the carbon emissions during the vehicle's use phase, thereby enabling more accurate carbon emission accounting for vehicles with intelligent driving functions. This carbon emission accounting method takes into account the carbon emission calculation of intelligent driving, is suitable for carbon emission accounting scenarios of intelligent driving vehicles, and is more in line with the current direction of automobile development for carbon footprint accounting of complete vehicle products.

[0087] In this embodiment, a method for calculating vehicle carbon emissions is provided, which can be applied to a device that needs to calculate the carbon emissions of a vehicle, such as a server, or the vehicle itself. Figure 2 is a flow chart of a method for calculating vehicle carbon emissions according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps.

[0088] Step S201, obtaining the energy consumption and carbon emissions corresponding to the energy consumption of the target vehicle during the use phase.

[0089] For details, please see Figure 1 Step S101 of the illustrated embodiment will not be described in detail here.

[0090] Step S202, obtaining the training carbon emissions of the intelligent driving model trained in the cloud, and determining the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions.

[0091] Specifically, the above-mentioned step S202 "obtaining the training carbon emissions of the intelligent driving model trained in the cloud, and determining the intelligent driving carbon emissions of the target vehicle using the intelligent driving model based on the training carbon emissions" includes steps S2021 to S2023.

[0092] Step S2021, obtaining the training carbon emissions of the cloud-based intelligent driving model and the number of first vehicles using the intelligent driving model.

[0093] In this embodiment, since the trained intelligent driving model can be used by multiple vehicles, when determining the intelligent driving carbon emissions of the target vehicle, the number of vehicles using the intelligent driving model can be further used to determine the intelligent driving carbon emissions of the target vehicle. It can be understood that the more vehicles there are, the less carbon emissions are shared by each vehicle, so the intelligent driving carbon emissions of the target vehicle are also smaller.

[0094] Specifically, in addition to determining the training carbon emissions of the cloud-based intelligent driving model, the number of vehicles currently using the intelligent driving model, that is, the first vehicle number, is also determined.

[0095] It is understandable that most of the current intelligent driving models are run offline. Here, "using" the intelligent driving model means being equipped with the intelligent driving model, that is, after the intelligent driving model is deployed to the corresponding vehicle, the vehicle needs to share the training carbon emissions even if the intelligent driving model is not currently being used.

[0096] Step S2022, determining the deployment carbon emissions corresponding to deploying the intelligent driving model for the target vehicle.

[0097] In this embodiment, when the intelligent driving model is deployed to the target vehicle, a certain amount of carbon emissions will also be caused. For example, the intelligent driving model can be deployed to the target vehicle through OAT (over-the-air upgrade) and the corresponding deployment carbon emissions of the process can be determined.

[0098] Among them, in order to simplify the calculation, when the same intelligent driving model is deployed for different vehicles, the corresponding deployment carbon emissions can be set to the same, that is, the deployment carbon emissions are only related to the intelligent driving model.

[0099] It should be noted that when deploying the intelligent driving model for the target vehicle, the intelligent driving model can be deployed for the target vehicle when the target vehicle is manufactured (i.e., the vehicle production stage), or the user can actively choose to deploy the intelligent driving model during the user's use of the target vehicle. However, since the intelligent driving model takes effect during the use stage, the carbon emissions from the deployment are classified as carbon emissions during the use stage.

[0100] Step S2023, determining the intelligent driving carbon emissions of the target vehicle using the intelligent driving model based on the training carbon emissions, the number of vehicles and the deployed carbon emissions.

[0101]

[0102] Among them, E 智驾 Indicates the carbon emissions of intelligent driving, E 训练 represents the training carbon emissions, N1 represents the number of first vehicles, E 部署 Represents the deployment carbon emissions.

[0103] In this embodiment, the training carbon emissions caused by training the intelligent driving model are E 训练 , and there are N1 vehicles using this intelligent driving model, so the carbon emissions amortized to each vehicle are And, add the deployment carbon emissions of the target vehicle E 部署 , we can get the intelligent driving carbon emissions E generated by the target vehicle due to the use of the intelligent driving model 智驾 ,and

[0104] In this embodiment, the training carbon emissions are amortized by combining the number of vehicles using the intelligent driving model and determining the vehicle's deployment carbon emissions, so that the vehicle's intelligent driving carbon emissions can be completely and accurately determined.

[0105] Optionally, since the intelligent driving model may be updated, this embodiment also updates the intelligent driving carbon emissions of the vehicle. Specifically, after the above step S2023, the method may further include the following steps A1 to A5.

[0106] Step A1: when the intelligent driving model in the cloud is updated from a first version model to a second version model, determine the updated carbon emissions corresponding to the update stage.

[0107] In this embodiment, as the intelligent driving model is used or the technology is improved, the intelligent driving model can be updated, that is, updated from an old version of the intelligent driving model to a new version of the intelligent driving model. For ease of description, the old version of the intelligent driving model is referred to as the first version model, and the new version of the intelligent driving model is referred to as the second version model.

[0108] When there is a situation where the intelligent driving model is updated, the carbon emissions generated in the stage of updating the intelligent driving model (i.e., the update stage) can be determined, i.e., the update carbon emissions. The update carbon emissions are the carbon emissions generated when the cloud updates the intelligent driving model from the first version model to the second version model; this is related to the computing power consumed by the cloud, the energy consumption of the cooling equipment, etc., and can be determined in a similar way to the calculation of the training carbon emissions.

[0109] For example, a model is trained based on a certain training set to generate an intelligent driving model. At this time, the intelligent driving model is the first version model. If the training set is expanded later, the intelligent driving model can be retrained based on the expanded training set. The retraining process is the process of updating the intelligent driving model. Through retraining, a new intelligent driving model, that is, the second version model, can be obtained. Among them, the carbon emissions caused by retraining the intelligent driving model can be calculated, that is, the updated carbon emissions.

[0110] Step A2, determining the upgraded carbon emissions corresponding to upgrading the intelligent driving model of the target vehicle from the first version model to the second version model.

[0111] In this embodiment, if the intelligent driving model in the cloud is updated, the new intelligent driving model needs to be reconfigured to the target vehicle, that is, the second version model is configured to the target vehicle. Among them, the reconfiguration process at this time is the process of upgrading the vehicle-side intelligent driving model, for example, it can be upgraded based on OTA. In the stage of upgrading the intelligent driving model of the target vehicle, a certain amount of carbon emissions will also be generated, that is, the upgraded carbon emissions.

[0112] Among them, the upgraded carbon emissions are also the carbon emissions caused by deploying the intelligent driving model for the target vehicle, so the upgraded carbon emissions can be calculated in a similar way to the calculation of the deployment carbon emissions. The main difference between the deployment carbon emissions and the upgraded carbon emissions is that the former represents the carbon emissions generated by deploying the intelligent driving model for the vehicle from scratch, while the latter represents the carbon emissions generated by the incremental deployment of the vehicle from the first version of the model to the second version of the model.

[0113] Step A3, adding the updated carbon emissions to the training carbon emissions corresponding to the intelligent driving model to update the training carbon emissions corresponding to the intelligent driving model.

[0114] In this embodiment, if there is a process of updating the intelligent driving model, the carbon emissions caused by the intelligent driving model include two parts, one part is the carbon emissions corresponding to the initial training of the intelligent driving model, and the other part is the carbon emissions caused by the subsequent update of the intelligent driving model. In this embodiment, the carbon emissions caused by the intelligent driving model are expressed as training carbon emissions. After the intelligent driving model is updated, the updated carbon emissions corresponding to this update can be added to the original training carbon emissions to achieve the update of the training carbon emissions.

[0115] For example, the original training carbon emissions of the intelligent driving model are 100kgCO2eq (kgCO2eq is the unit of carbon emissions), and the updated carbon emissions generated when it is updated are 50kgCO2eq. After the training carbon emissions corresponding to the intelligent driving model are updated, the updated training carbon emissions are 150kgCO2eq.

[0116] Step A4, adding the upgraded carbon emissions to the deployed carbon emissions of the target vehicle to update the deployed carbon emissions of the target vehicle.

[0117] In this embodiment, if the intelligent driving model has an update process, the process of deploying the intelligent driving model for the target vehicle also involves the upgraded carbon emissions when deploying the new second version model. Therefore, by adding the upgraded carbon emissions to the deployed carbon emissions of the target vehicle, a new deployed carbon emissions can be obtained, thereby updating the deployed carbon emissions.

[0118] It can be understood that the intelligent driving model can be updated multiple times, and each time it is updated, the training carbon emissions and deployment carbon emissions can be updated in accordance with the above steps A1 to A4.

[0119] Step A5: Update the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the updated training carbon emissions and the updated deployment carbon emissions.

[0120] In this embodiment, after determining the updated training carbon emissions and the updated deployment carbon emissions, the updated carbon emissions can be calculated again based on the formula Calculate the new intelligent driving carbon emissions to update the intelligent driving carbon emissions of the target vehicle; it can be understood that at this time, E in the formula 训练 is the updated training carbon emissions, E 部署 Carbon emissions for the updated deployment.

[0121] In this embodiment, when the intelligent driving model is updated, the training carbon emissions and the deployed carbon emissions of each vehicle are updated, so that the updated intelligent driving carbon emissions of the target vehicle can be determined, and the intelligent driving carbon emissions can be updated as the intelligent driving model is updated, thereby ensuring the real-time and accurate determination of the intelligent driving carbon emissions.

[0122] Optionally, the number of vehicles deploying the intelligent driving model will also increase. When the intelligent driving model is deployed for new vehicles, the carbon emissions of the newly added vehicles can be determined directly based on the current training carbon emissions and the total number of vehicles deploying the intelligent driving model. However, if the intelligent driving model deployed for the first time on a vehicle is an updated model (such as the second version model), the vehicle has not used the old version of the intelligent driving model (such as the first version model). In order to more accurately represent the carbon emissions caused by the use of the intelligent driving model for each vehicle, the corresponding intelligent driving carbon emissions are determined based on the version of the intelligent driving model deployed for the vehicle for the first time.

[0123] Specifically, the method also includes the following steps B1 to B4.

[0124] Step B1, when the second version model is deployed for other vehicles, determine the number of second vehicles to which the second version model is deployed.

[0125] Step B1, determine the carbon emissions of other vehicles using the intelligent driving model.

[0126]

[0127] Among them, E' 智驾 represents the carbon emissions of other vehicles using the intelligent driving model, E 更新 represents the updated carbon emissions, N2 represents the number of second vehicles, E' 部署 Represents the carbon emissions corresponding to deploying intelligent driving models for other vehicles.

[0128] Step B3, subtract the error carbon emissions from the intelligent driving carbon emissions of the target vehicle using the intelligent driving model to update the intelligent driving carbon emissions of the target vehicle using the intelligent driving model; the error carbon emissions ΔE is:

[0129]

[0130] Step B4: Update the number of first vehicles using the intelligent driving model from N1 to N1+N2.

[0131] In this embodiment, if the second version of the model is deployed for the first time, the carbon emissions of the first version of the model will not be considered for the other vehicles. If the number of vehicles newly deployed with the intelligent driving model (i.e., the second number of vehicles) is N2, then there are N1+N2 vehicles with the intelligent driving model deployed. The updated carbon emissions E generated by updating the intelligent driving model is 更新 is evenly distributed to each vehicle, then the carbon emissions of each vehicle (including the target vehicle and other vehicles) are On this basis, the carbon emissions E' corresponding to the deployment of the intelligent driving model (i.e. the second version model) for other vehicles is added 部署 , then the carbon emissions of other vehicles using the intelligent driving model can be obtained E' 智驾 , which is also a kind of intelligent driving carbon emissions.

[0132] For the target vehicle, the carbon emissions caused by updating the intelligent driving model are also equal to 2. Before the model was updated, the carbon emissions in this part were Therefore, the error in carbon emissions between the two is ΔE: From this we can get:

[0133] Therefore, when N2 other vehicles are newly added to deploy the latest intelligent driving model, the error carbon emissions ΔE can be subtracted from the intelligent driving carbon emissions of the vehicle (such as the target vehicle) that previously deployed the intelligent driving model. At this time, the updated intelligent driving carbon emissions are the actual intelligent driving carbon emissions of the target vehicle when the N2 other vehicles only share the update carbon emissions but not the training carbon emissions.

[0134] In addition, the number of vehicles using the intelligent driving model (i.e. the first number of vehicles) will be updated from the original N1 to the latest N1+N2 to ensure that when other vehicles are subsequently deployed with the intelligent driving model or when the intelligent driving model is updated again, the determined intelligent driving carbon emissions of each vehicle are accurate.

[0135] In this embodiment, the intelligent driving model deployed for the first time is a vehicle of the updated second version model. The intelligent driving carbon emissions are determined in a targeted manner, and the intelligent driving carbon emissions of the target vehicle are updated to ensure that the intelligent driving carbon emissions of each vehicle are true and accurate.

[0136] Step S203, determining the traffic carbon emissions corresponding to the traffic consumed by the target vehicle in interacting with the cloud during the use phase.

[0137] For details, please see Figure 1 Step S103 of the illustrated embodiment will not be described in detail here.

[0138] In some optional implementations, the above step S203 "determining the traffic carbon emissions corresponding to the traffic consumed by the target vehicle in interacting with the cloud during the use phase" may include steps C1 to C3.

[0139] Step C1, obtaining the traffic usage consumed by the target vehicle when interacting with the cloud based on the interaction request during the use phase.

[0140] Step C2, obtaining the cloud computing carbon emissions corresponding to the computing power consumed by the cloud in responding to the interaction request based on cloud computing.

[0141] Step C3, determine the traffic carbon emissions corresponding to the target vehicle according to the traffic usage and cloud computing carbon emissions. 流量 =D×EF 流量 +E 云计算 ;

[0142] Among them, E 流量 represents the carbon emissions of traffic, D represents the traffic usage, EF 流量 The carbon emission factor of the flow, E 云计算 Represents the carbon emissions of cloud computing.

[0143] In this embodiment, the target vehicle can interact with the cloud based on an interaction request. For example, based on an interaction request to obtain audio, the voice data of certain music can be obtained from the cloud. The traffic usage D consumed during the interaction can be determined, and the carbon emission factor EF based on the traffic can be calculated. 流量 Determine the carbon emissions caused by data transmission D×EF 流量 .

[0144] In addition, when the cloud responds to the target vehicle's interactive request, it also consumes a certain amount of computing power, such as personalized push based on the target vehicle's historical data. This part of the carbon emissions generated by cloud computing is called cloud computing carbon emissions E. 云计算 Combining these carbon emissions, the carbon emissions of traffic caused by interaction can be determined: 流量 , and E 流量 =D×EF 流量 +E 云计算 .

[0145] In this embodiment, the carbon emissions caused by the interaction between the vehicle and the cloud are relatively complex and difficult to calculate directly. This embodiment uses the traffic usage to calculate this part of the carbon emissions, which can simplify the carbon emission calculation method while ensuring that the calculation results are relatively accurate; and, adding cloud computing carbon emissions can make the calculated traffic carbon emissions more accurate.

[0146] Step S204, comprehensively analyzing the carbon emissions from energy consumption, the carbon emissions from intelligent driving, and the carbon emissions from traffic flow, to determine the carbon emissions data of the target vehicle during the use phase.

[0147] For details, please see Figure 1 Step S104 of the illustrated embodiment will not be described in detail here.

[0148] In some optional embodiments, the method further includes a process for determining carbon emissions over the entire life cycle of the vehicle. Specifically, the process includes the following steps D1 to D4.

[0149] Step D1, obtaining component carbon emission data corresponding to components in the target vehicle.

[0150] In this embodiment, the whole life cycle of a vehicle is mainly divided into a parts stage, a whole vehicle production stage and a use stage, and there is also a transportation stage which requires the transportation of parts or whole vehicles. Figure 3 A schematic diagram of the vehicle's entire life cycle is shown. Figure 3 shown.

[0151] At the parts stage, the sum of the carbon emissions of all parts in the target vehicle, i.e. the carbon emissions data, can be determined based on the carbon emissions corresponding to the production of each part.

[0152] Optionally, the raw material carbon emissions EM of each component in the target vehicle can be obtained i , and the carbon emissions of producing parts EP i ; By counting the carbon emissions of raw materials and production parts of each component in the target vehicle, the carbon emission data of the components of the target vehicle can be obtained.

[0153] Specifically, the carbon emission data of parts E1 is:

[0154] EM i represents the carbon emission of raw materials of the i-th component of the target vehicle, EP i Represents the carbon emissions of producing the i-th component.

[0155] Step D2, obtaining the vehicle production carbon emission data of the target vehicle during the vehicle production stage.

[0156] Optionally, during the vehicle production stage, the carbon emissions corresponding to the target vehicle, i.e., the vehicle production carbon emissions data, can be specifically divided into carbon emissions caused by the process and carbon emissions generated by the process equipment. Among them, the vehicle production carbon emissions data E2 is:

[0157] E2=E 整车工艺 +E 工艺设备 ; E 整车工艺It represents the total carbon emissions corresponding to the energy (electricity, heat, etc.) consumed by the vehicle process (such as welding, painting, assembly, etc.) during the vehicle production stage of the target vehicle, E 工艺设备 Represents the total carbon emissions directly generated by process equipment during the vehicle production stage of the target vehicle.

[0158] Among them, E 整车工艺 =E 电力 +E 热力 ; E 电力 =EM 电力 ×EF 电力 , E 热力 =EM 热力 ×EF 热力 . E 电力 It represents the carbon emissions generated by the consumption of externally purchased electricity during the vehicle production stage of the target vehicle, E 热力 Indicates the carbon emissions generated by external heat consumption during the vehicle production stage of the target vehicle; EM 电力 Indicates the power consumption during the vehicle production phase of the target vehicle, EF 电力 Represents the carbon emission factor of electricity; EM 热力 Indicates the heat consumption during the vehicle production stage of the target vehicle, EF 热力 Represents the carbon emission factor for heat.

[0159] EM 设备,i Indicates the consumption of the direct emission substances of the i-th process equipment in the vehicle production stage of the target vehicle, EF 设备,i Represents the carbon emission factor of the ith process equipment.

[0160] Step D3, obtaining the transportation carbon emission data generated by the transportation target vehicle.

[0161] Alternatively, if Figure 3 As shown, the transportation stage of the target vehicle is divided into parts transportation and vehicle transportation. Correspondingly, the transportation carbon emission data E3 is:

[0162] E3=ET 零部件 +ET 整车 ET 零部件 Indicates the carbon emissions generated by transporting the parts of the target vehicle, ET 整车 Represents the carbon emissions generated by transporting the entire vehicle.

[0163] in, M i represents the weight of the parts transported by the ith mode of transportation, S 零部件,i represents the transportation distance of parts transported by the i-th mode of transportation, EF 零部件,iRepresents the carbon emission factor of transporting parts using the i-th mode of transportation.

[0164] ET vehicle = (S vehicle,j × EF vehicle,j) / Cj; the target vehicle is transported by the jth mode of transportation, and S vehicle,j represents the transportation distance of the target vehicle transported by the jth mode of transportation, EF 整车,j represents the carbon emission factor of the target vehicle transported by the jth mode of transportation, C j It represents the number of vehicles transported in a single trip using the jth mode of transportation.

[0165] Step D4, comprehensively using carbon emission data, parts carbon emission data, vehicle production carbon emission data, and transportation carbon emission data to determine the carbon emission data of the target vehicle throughout its life cycle.

[0166] E 车辆 =E0+E1+E2+E3;

[0167] Among them, E 车辆 It represents the carbon emission data of the target vehicle throughout its life cycle. E0 represents the carbon emission data of use, E1 represents the carbon emission data of parts and components, E2 represents the carbon emission data of vehicle production, and E3 represents the carbon emission data of transportation.

[0168] The method for calculating vehicle carbon emissions provided in this implementation takes into account the carbon footprint of smart driving software services during the use of smart cars. The method is feasible and more complete. The product carbon footprint of smart cars is divided into the parts stage, the vehicle production stage, the use stage and the supply chain transportation stage, which divides the smart car products into more universal accounting boundaries and calculation methods; and fully considers the carbon emissions of parts, the entire vehicle production process, the vehicle use process, and the carbon emissions of upstream and downstream parts supply chain transportation, and considers the calculation of smart driving carbon emissions during the use stage, which is in line with the current automobile development trend.

[0169] In this embodiment, a device for calculating vehicle carbon emissions is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and will not be repeated hereafter. As used below, the term "module" may be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0170] This embodiment provides a device for calculating vehicle carbon emissions, such as Figure 4 As shown, including:

[0171] The first acquisition module 401 is used to obtain the energy consumption carbon emission corresponding to the energy consumption of the target vehicle during the use phase;

[0172] A second acquisition module 402 is used to obtain the training carbon emissions of the intelligent driving model trained in the cloud, and determine the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions;

[0173] The third acquisition module 403 is used to determine the traffic carbon emissions corresponding to the traffic consumed by the target vehicle in interacting with the cloud during the use phase;

[0174] The determination module 404 is used to comprehensively determine the carbon emissions of the target vehicle during the use phase by combining the carbon emissions of energy consumption, the carbon emissions of intelligent driving and the carbon emissions of traffic volume.

[0175] In an optional implementation, the second acquisition module 402 acquires the training carbon emissions of the intelligent driving model trained in the cloud, and determines the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions, including:

[0176] Obtaining the training carbon emissions of the intelligent driving model trained in the cloud and the number of first vehicles using the intelligent driving model;

[0177] Determining a deployment carbon emission amount corresponding to deploying the intelligent driving model for the target vehicle;

[0178] Determine the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions, the number of vehicles and the deployment carbon emissions;

[0179]

[0180] Among them, E 智驾 Represents the carbon emissions of intelligent driving, E 训练 represents the training carbon emissions, N1 represents the first number of vehicles, E 部署 Represents the carbon emissions of the deployment.

[0181] In an optional implementation, the second acquisition module 402 is further configured to:

[0182] When the intelligent driving model in the cloud is updated from the first version model to the second version model, determining the updated carbon emissions corresponding to the update stage;

[0183] Determining an upgraded carbon emission amount corresponding to upgrading the intelligent driving model of the target vehicle from a first version model to a second version model;

[0184] adding the updated carbon emissions to the training carbon emissions corresponding to the intelligent driving model to update the training carbon emissions corresponding to the intelligent driving model;

[0185] adding the upgraded carbon emissions to the deployed carbon emissions of the target vehicle to update the deployed carbon emissions of the target vehicle;

[0186] According to the updated training carbon emissions and the updated deployment carbon emissions, the intelligent driving carbon emissions of the target vehicle using the intelligent driving model are updated.

[0187] In an optional implementation, the second acquisition module 402 is further configured to:

[0188] In case the second version model is deployed for other vehicles, determining the number of second vehicles on which the second version model is deployed;

[0189] Determining carbon emissions of the other vehicles using the intelligent driving model;

[0190]

[0191] Among them, E' 智驾 represents the carbon emissions of other vehicles using the intelligent driving model, E 更新 represents the updated carbon emissions, N2 represents the second number of vehicles, E' 部署 Indicates the carbon emissions corresponding to deploying the intelligent driving model for the other vehicles;

[0192] The intelligent driving carbon emissions of the target vehicle using the intelligent driving model are subtracted from the error carbon emissions to update the intelligent driving carbon emissions of the target vehicle using the intelligent driving model; the error carbon emissions ΔE is:

[0193] The first number of vehicles using the intelligent driving model is updated from N1 to N1+N2.

[0194] In an optional implementation, the third acquisition module 403 determines the traffic carbon emissions corresponding to the traffic consumed by the target vehicle to interact with the cloud during the use phase, including:

[0195] Obtaining the traffic usage consumed by the target vehicle when interacting with the cloud based on the interaction request during the use phase;

[0196] Obtaining cloud computing carbon emissions corresponding to computing power consumed by the cloud in responding to the interaction request based on cloud computing;

[0197] Determine the traffic carbon emissions corresponding to the target vehicle according to the traffic usage and the cloud computing carbon emissions;

[0198] E 流量 =D×EF 流量 +E 云计算 ;

[0199] Among them, E 流量 represents the carbon emission of the flow, D represents the flow usage, EF 流量 The carbon emission factor of the flow, E 云计算 Represents the carbon emissions of cloud computing.

[0200] In an optional embodiment, the device further comprises:

[0201] A fourth acquisition module is used to acquire carbon emission data of components corresponding to components in the target vehicle, carbon emission data of the target vehicle during the vehicle production stage, and transportation carbon emission data generated by transporting the target vehicle;

[0202] The determination module 404 is further used to: determine the carbon emission data of the target vehicle over its entire life cycle by integrating the carbon emission data of use, the carbon emission data of parts, the carbon emission data of vehicle production, and the carbon emission data of transportation;

[0203] E 车辆 =E0+E1+E2+E3;

[0204] Among them, E 车辆 It represents the carbon emission data of the target vehicle throughout its life cycle, E0 represents the carbon emission data of use, E1 represents the carbon emission data of parts, E2 represents the carbon emission data of vehicle production, and E3 represents the carbon emission data of transportation.

[0205] In an optional implementation, the component carbon emission data E1 is:

[0206] EM i represents the carbon emission of raw materials of the i-th component of the target vehicle, EP i represents the carbon emission of producing the i-th component;

[0207] The vehicle production carbon emission data E2 is:

[0208] E2=E 整车工艺 +E 工艺设备 ; E 整车工艺 It represents the total carbon emissions corresponding to the energy consumed by the whole vehicle process during the whole vehicle production stage of the target vehicle, E 工艺设备 Indicates the total carbon emissions generated by process equipment during the vehicle production stage of the target vehicle;

[0209] Among them, E 整车工艺 =E 电力 +E 热力 ; E 电力 =EM 电力 ×EF电力 , E 热力 =EM 热力 ×EF 热力 ; E 电力 represents the carbon emissions generated by the electricity consumed during the vehicle production phase of the target vehicle, E 热力 Indicates the carbon emissions generated by the heat consumption during the vehicle production stage of the target vehicle; EM 电力 represents the power consumption during the vehicle production stage of the target vehicle, EF 电力 Represents the carbon emission factor of electricity; EM 热力 represents the heat consumption of the target vehicle during the vehicle production stage, EF 热力 represents the carbon emission factor for heat;

[0210] EM 设备,i Indicates the consumption of the substances directly discharged by the i-th process equipment in the whole vehicle production stage of the target vehicle, EF 设备,i represents the carbon emission factor of the ith process equipment;

[0211] The transport carbon emission data E3 is:

[0212] E3=ET 零部件 +ET 整车 ET 零部件 represents the carbon emissions generated by transporting the parts of the target vehicle, ET 整车 Indicates the carbon emissions generated by transporting the entire vehicle;

[0213] in, M i represents the weight of the parts transported by the ith mode of transportation, S 零部件,i represents the transportation distance of parts transported by the i-th mode of transportation, EF 零部件,i represents the carbon emission factor of transporting parts using the i-th mode of transportation;

[0214] ET vehicle = (S vehicle, j × EF vehicle, j) / Cj; the target vehicle is transported by the jth mode of transportation, and S 整车,j represents the transportation distance of the target vehicle using the j-th transportation method, EF 整车,j represents the carbon emission factor of transporting the target vehicle using the j-th mode of transportation, C j Represents the number of vehicles transported in a single trip using the j-th mode of transportation.

[0215] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0216] The device for calculating vehicle carbon emissions in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, including a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0217] The embodiment of the present invention also provides a computer device having the above Figure 4 The device for calculating vehicle carbon emissions is shown.

[0218] See also Figure 5 , Figure 5 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 5 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 5 A processor 10 is taken as an example.

[0219] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0220] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0221] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0222] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0223] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0224] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0225] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0226] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations should all be included in the protection scope of the present invention.

Claims

1. A method for calculating vehicle carbon emissions, characterized in that: The method comprises: Obtain the energy consumption and carbon emissions corresponding to the energy consumption of the target vehicle during the use phase; Obtaining the training carbon emissions of the intelligent driving model trained in the cloud, and determining the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions; Determine the traffic carbon emissions corresponding to the traffic consumed by the target vehicle in interacting with the cloud during the use phase; The carbon emissions data of the target vehicle during the use phase is determined by comprehensively analyzing the energy consumption carbon emissions, the intelligent driving carbon emissions and the traffic carbon emissions.

2. The method according to claim 1, characterized in that The obtaining of the training carbon emissions of the intelligent driving model trained in the cloud, and determining the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions, includes: Obtaining the training carbon emissions of the intelligent driving model trained in the cloud and the number of first vehicles using the intelligent driving model; Determining a deployment carbon emission amount corresponding to deploying the intelligent driving model for the target vehicle; Determine the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions, the number of vehicles and the deployment carbon emissions; Among them, E 智驾 Represents the carbon emissions of intelligent driving, E 训练 represents the training carbon emissions, N1 represents the first number of vehicles, E 部署 Represents the carbon emissions of the deployment.

3. The method according to claim 2, characterized in that Also includes: When the intelligent driving model in the cloud is updated from the first version model to the second version model, determining the updated carbon emissions corresponding to the update stage; Determining an upgraded carbon emission amount corresponding to upgrading the intelligent driving model of the target vehicle from a first version model to a second version model; adding the updated carbon emissions to the training carbon emissions corresponding to the intelligent driving model to update the training carbon emissions corresponding to the intelligent driving model; adding the upgraded carbon emissions to the deployed carbon emissions of the target vehicle to update the deployed carbon emissions of the target vehicle; According to the updated training carbon emissions and the updated deployment carbon emissions, the intelligent driving carbon emissions of the target vehicle using the intelligent driving model are updated.

4. The method according to claim 3, characterized in that Also includes: In case the second version model is deployed for other vehicles, determining the number of second vehicles on which the second version model is deployed; Determining carbon emissions of the other vehicles using the intelligent driving model; Among them, E' 智驾 represents the carbon emissions of other vehicles using the intelligent driving model, E 更新 represents the updated carbon emissions, N2 represents the second number of vehicles, E' 部署 Indicates the carbon emissions corresponding to deploying the intelligent driving model for the other vehicles; The intelligent driving carbon emissions of the target vehicle using the intelligent driving model are subtracted from the error carbon emissions to update the intelligent driving carbon emissions of the target vehicle using the intelligent driving model; the error carbon emissions The first number of vehicles using the intelligent driving model is updated from N1 to N1+N2.

5. The method according to claim 1, characterized in that Determining the traffic carbon emissions corresponding to the traffic consumed by the target vehicle in interacting with the cloud during the use phase includes: Obtaining the traffic usage consumed by the target vehicle when interacting with the cloud based on the interaction request during the use phase; Obtaining cloud computing carbon emissions corresponding to computing power consumed by the cloud in responding to the interaction request based on cloud computing; Determine the traffic carbon emissions corresponding to the target vehicle according to the traffic usage and the cloud computing carbon emissions; AND 流量 =D×EF 流量 +E 云计算 ; Among them, E 流量 represents the carbon emission of the flow, D represents the flow usage, EF 流量 The carbon emission factor of the flow, E 云计算 Represents the carbon emissions of cloud computing.

6. The method according to any one of claims 1 to 5, characterized in that Also includes: Obtaining carbon emission data of components corresponding to components in the target vehicle, carbon emission data of the target vehicle during the vehicle production stage, and transportation carbon emission data generated by transporting the target vehicle; Determine the carbon emission data of the target vehicle throughout its life cycle by combining the carbon emission data of use, the carbon emission data of parts, the carbon emission data of vehicle production, and the carbon emission data of transportation; <h2 style=";text-align:left;direction:ltr">E<h2 style=";text-align:left;direction:ltr"> 车辆 <h2 style=";text-align:left;direction:ltr"> (E0+E1+E2+E3) Among them, E 车辆 It represents the carbon emission data of the target vehicle throughout its life cycle, E0 represents the carbon emission data of use, E1 represents the carbon emission data of parts, E2 represents the carbon emission data of vehicle production, and E3 represents the carbon emission data of transportation.

7. The method according to claim 6, characterized in that The carbon emission data E1 of the parts are: EM i represents the carbon emission of raw materials of the i-th component of the target vehicle, EP i represents the carbon emission of producing the i-th component; The vehicle production carbon emission data E2 is: E2=E 整车工艺 +E 工艺设备 ; E 整车工艺 It represents the total carbon emissions corresponding to the energy consumed by the whole vehicle process during the whole vehicle production stage of the target vehicle, E 工艺设备 Indicates the total carbon emissions generated by process equipment during the vehicle production stage of the target vehicle; Among them, E 整车工艺 =E 电力 +E 热力 ; E 电力 =EM 电力 ×EF 电力 , E 热力 =EM 热力 ×EF 热力 ; E 电力 represents the carbon emissions generated by the electricity consumed during the vehicle production phase of the target vehicle, E 热力 Indicates the carbon emissions generated by the heat consumption during the vehicle production stage of the target vehicle; EM 电力 represents the power consumption during the vehicle production stage of the target vehicle, EF 电力 Represents the carbon emission factor of electricity; EM 热力 represents the heat consumption of the target vehicle during the vehicle production stage, EF 热力 represents the carbon emission factor for heat; EM 设备,i Indicates the consumption of the substances directly discharged by the i-th process equipment in the whole vehicle production stage of the target vehicle, EF 设备,i represents the carbon emission factor of the ith process equipment; The transport carbon emission data E3 is: E3=ET 零部件 +ET 整车 ET 零部件 represents the carbon emissions generated by transporting the parts of the target vehicle, ET 整车 Indicates the carbon emissions generated by transporting the entire vehicle; in, M i represents the weight of the parts transported by the ith mode of transportation, S 零部件,i represents the transportation distance of parts transported by the i-th mode of transportation, EF 零部件,i represents the carbon emission factor of transporting parts using the i-th mode of transportation; ET vehicle = (S vehicle, j × EF vehicle, j) / Cj; the target vehicle is transported by the jth mode of transportation, and S 整车,j represents the transportation distance of the target vehicle using the j-th transportation method, EF 整车,j represents the carbon emission factor of transporting the target vehicle using the j-th mode of transportation, C j Represents the number of vehicles transported in a single trip using the j-th mode of transportation.

8. A device for calculating vehicle carbon emissions, characterized in that: The device comprises: The first acquisition module is used to obtain the energy consumption carbon emissions corresponding to the energy consumption of the target vehicle during the use phase; A second acquisition module is used to obtain the training carbon emissions of the intelligent driving model trained in the cloud, and determine the intelligent driving carbon emissions of the target vehicle using the intelligent driving model according to the training carbon emissions; The third acquisition module is used to determine the traffic carbon emissions corresponding to the traffic consumed by the target vehicle in interacting with the cloud during the use phase; A determination module is used to comprehensively determine the carbon emissions of the target vehicle during the use phase by combining the carbon emissions of energy consumption, the carbon emissions of intelligent driving and the carbon emissions of traffic.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for calculating vehicle carbon emissions according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for calculating vehicle carbon emissions according to any one of claims 1 to 7.

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