A vehicle control method and storage medium for vehicle-cloud collaboration

Abstract

The present application provides a vehicle control method and storage medium for vehicle-cloud collaboration, relating to the field of vehicle control technology, wherein the method comprises: obtaining historical operating data of a target vehicle within a preset unit historical time period; performing operating condition feature recognition on the historical operating data to determine the historical operating condition features of the target vehicle within the preset unit historical time period; using a preset operating condition feature threshold based on the historical operating condition features of the target vehicle to determine the historical operating scenario operating conditions of the target vehicle within the preset unit historical time period; determining a target control strategy based on the historical operating scenario operating conditions; and issuing the target control strategy to a vehicle controller of the target vehicle, so that the vehicle controller controls the energy distribution of the power battery and fuel cell on the target vehicle according to the target control strategy. The present application adapts to changes in vehicle operating conditions in different scenarios and optimizes vehicle performance and energy management.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and more specifically, to a vehicle control method and storage medium for vehicle-cloud collaboration. Background Art

[0002] With the continuous development of new energy vehicle technologies, hybrid vehicles (HEVs) have garnered widespread attention. These vehicles typically utilize both a battery and a fuel cell as power sources, effectively improving energy efficiency, reducing reliance on traditional fuels, and lowering exhaust emissions. Rationally allocating energy between the battery and fuel cell to adapt to varying vehicle operating conditions and optimize vehicle performance and energy management remains a key technical challenge.

[0003] Currently, hybrid vehicles use relatively simple energy management strategies, such as allocating energy between power batteries and fuel cells based on fixed ratios or preset rules.

[0004] However, a fixed allocation ratio often cannot fully adapt to the actual operation of the vehicle under complex working conditions. It is also difficult to adapt to the dynamic changes in vehicle operating conditions in different scenarios, and it is impossible to accurately adjust the vehicle's operating strategy to optimize performance and energy management. Summary of the Invention

[0005] The purpose of this application is to address the deficiencies in the above-mentioned existing technologies and provide a vehicle control method and storage medium with vehicle-cloud collaboration, so as to adapt to changes in vehicle operating conditions in different scenarios and optimize vehicle performance and energy management.

[0006] To achieve the above objectives, the technical solutions adopted in the embodiments of the present application are as follows:

[0007] In a first aspect, an embodiment of the present application provides a vehicle control method for vehicle-cloud collaboration, which is applied to a cloud device. The method includes:

[0008] Obtain historical operating data of the target vehicle within a preset unit historical time period;

[0009] Performing operating condition feature recognition on the historical operating data to determine the historical operating condition features of the target vehicle in the preset unit historical time period;

[0010] According to the historical operating condition characteristics of the target vehicle, a preset operating condition characteristic threshold is used to determine the historical operating scenario operating condition of the target vehicle in the preset unit historical time period;

[0011] Determining a target control strategy based on the historical operating scenario conditions, wherein the target operating scenario conditions are a control strategy for long-distance operating conditions or a control strategy for short-distance operating conditions;

[0012] The target control strategy is issued to a vehicle controller of the target vehicle, so that the vehicle controller controls energy distribution of a power battery and a fuel cell on the target vehicle according to the target control strategy.

[0013] Optionally, the historical operating data includes: positioning data of multiple historical trajectory points, power take-off enable time, parking time, and air pump enable time; the operating condition feature identification of the historical operating data to determine the historical operating condition features of the target vehicle in the preset unit historical time period includes:

[0014] Calculating the maximum running distance of the target vehicle within the preset unit historical time period based on the positioning data of the multiple historical trajectory points;

[0015] Calculating the interval between two adjacent power take-off activations within the preset unit historical time period based on the positioning data of the multiple historical trajectory points and the activation time of the power take-off;

[0016] Calculating the number of unit distance stops within the preset unit historical time period based on the positioning data of the multiple historical trajectory points and the parking time;

[0017] Calculate the number of times the air pump is enabled per unit distance within the preset unit historical time period based on the positioning data of the multiple historical trajectory points and the air pump enabling time;

[0018] The historical operating condition characteristics include: the longest running distance, the power take-off enabling interval distance, the number of stops per unit distance, and the number of air pump enabling times per unit distance.

[0019] Optionally, the preset operating condition characteristic thresholds include: a preset running distance threshold, a preset power take-off enabling interval distance threshold, a preset parking number threshold, and a preset pumping enabling number threshold;

[0020] The determining of the historical operating scenario operating condition of the target vehicle in the preset unit historical time period based on the historical operating condition characteristics of the target vehicle and using a preset operating condition characteristic threshold comprises:

[0021] Normalizing the farthest running distance according to the preset running distance threshold to obtain a first evaluation parameter;

[0022] Normalizing the power take-off enabling interval distance according to the preset power take-off enabling interval distance threshold to obtain a second evaluation parameter;

[0023] Normalizing the number of stops per unit distance according to the preset stop number threshold to obtain a third evaluation parameter;

[0024] Normalizing the number of times the air pump is enabled per unit distance according to the preset air pump enable number threshold to determine a fourth evaluation parameter;

[0025] The historical operating scenario operating conditions are determined based on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter.

[0026] Optionally, determining the historical operating scenario condition according to the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter includes:

[0027] performing a weighted sum operation on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter to obtain a target evaluation parameter;

[0028] If the target evaluation parameter is greater than or equal to a preset threshold, determining that the historical operating scenario operating condition is a long-distance operating condition;

[0029] If the target evaluation parameter is less than the preset threshold, it is determined that the historical operating scenario condition is a short-distance condition.

[0030] Optionally, performing a weighted sum operation on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter to obtain a target evaluation parameter includes:

[0031] performing a weighted sum operation on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter according to the first preset weight, the second preset weight, the third preset weight, and the fourth preset weight to obtain the target evaluation parameter;

[0032] The sum of the first preset weight, the second preset weight, the third preset weight and the third preset weight is 1, and the first preset weight and the second preset weight are both greater than the third preset weight and the third preset weight.

[0033] Optionally, determining a target control strategy based on the historical operating scenario conditions includes:

[0034] Determine, based on the historical operating scenario operating conditions, whether there is an operating condition change in the preset unit historical time period;

[0035] If there is no change in the operating condition, determining the preset control strategy corresponding to the historical operating scenario operating condition as the target control strategy;

[0036] If there is a change in the operating condition, and the latest operating scenario operating condition is maintained within a preset number of unit historical time periods, the preset control strategy corresponding to the latest operating scenario operating condition is determined to be the target control strategy.

[0037] In a second aspect, another embodiment of the present application provides another vehicle-cloud collaborative vehicle control method, which is applied to a vehicle controller of a target vehicle, and the method includes:

[0038] Uploading the historical operating data of the target vehicle collected by the on-board device of the target vehicle within a preset unit historical time period to the cloud device;

[0039] Receiving a target control strategy issued by the cloud device, where the target control strategy is a control strategy determined by the cloud device according to any vehicle control method for vehicle-cloud collaboration described in the first aspect above;

[0040] According to the target control strategy, the energy distribution of the power battery and the fuel cell on the target vehicle is controlled.

[0041] Optionally, controlling the energy distribution of the power battery and the fuel cell on the target vehicle according to the target control strategy includes:

[0042] If the target control strategy is a long-distance control strategy, obtaining the current driving state of the target vehicle;

[0043] If the current driving state is constant speed driving, controlling the fuel cell to output energy based on a preset rated power;

[0044] If the current driving state is accelerating or climbing, controlling the fuel cell to output energy based on the preset rated power, and controlling the power battery to supplement power;

[0045] If the current driving state is a braking state, the power battery is controlled to recover energy so that the state of charge of the power battery is within a preset range; if the state of charge after energy recovery is still not within the preset range, the fuel cell is controlled to charge the power battery so that the state of charge of the power battery is within the preset range.

[0046] Optionally, controlling the energy distribution of the power battery and the fuel cell on the target vehicle according to the target control strategy includes:

[0047] If the target control strategy is a short-distance operating condition control strategy, obtaining the current state of charge of the power battery;

[0048] If the current state of charge is within the first charge interval, controlling the power battery to output energy at the full required power of the target vehicle, and controlling the fuel cell to enter a standby state;

[0049] If the current state of charge is not within the first charge range but within the second charge range, controlling the power battery to output a first proportion of the required power for energy output, controlling the fuel cell to start and maintain a second proportion of the rated power for energy output, and using the redundant power of the fuel cell to charge the power battery;

[0050] If the current state of charge is not within the second charge interval but within the third charge interval, the fuel cell is controlled to output energy at a third ratio of the rated power, and the power battery is controlled to output energy at a fourth ratio of the required power, and the power battery is charged using the redundant power of the fuel cell; wherein the third ratio is greater than the second ratio, and the fourth ratio is less than the first ratio.

[0051] In a third aspect, another embodiment of the present application provides a vehicle-cloud collaborative vehicle control device, which is applied to a cloud device, and the device includes:

[0052] An acquisition module is used to obtain historical operation data of a target vehicle within a preset unit historical time period;

[0053] An identification module is used to identify the operating condition characteristics of the historical operating data and determine the historical operating condition characteristics of the target vehicle in the preset unit historical time period;

[0054] A determination module, configured to determine the historical operating scenario operating condition of the target vehicle in the preset unit historical time period based on the historical operating condition characteristics of the target vehicle and using a preset operating condition characteristic threshold;

[0055] a determination module, configured to determine a target control strategy based on the historical operating scenario conditions, wherein the target operating scenario conditions are a control strategy for long-distance operating conditions or a control strategy for short-distance operating conditions;

[0056] The sending module is used to send the target control strategy to the vehicle controller of the target vehicle, so that the vehicle controller controls the energy distribution of the power battery and the fuel cell on the target vehicle according to the target control strategy.

[0057] In a fourth aspect, another embodiment of the present application provides another vehicle-cloud collaborative vehicle control device, which is applied to a vehicle controller of a target vehicle, and includes:

[0058] A collection module, used to upload the historical operation data of the target vehicle collected by the on-board equipment of the target vehicle within a preset unit historical time period to a cloud device;

[0059] a receiving module, configured to receive a target control strategy issued by the cloud device, wherein the target control strategy is a control strategy determined by the cloud device according to any one of the vehicle-cloud collaborative vehicle control methods described in the first aspect;

[0060] A control module is used to control the energy distribution of the power battery and the fuel cell on the target vehicle according to the target control strategy.

[0061] In the fifth aspect, another embodiment of the present application provides a cloud device, comprising: a first processor, a first memory and a first bus, wherein the first memory stores machine-readable instructions executable by the first processor. When the cloud device is running, the first processor communicates with the first memory through the first bus, and the first processor executes the machine-readable instructions to perform the steps of the vehicle control method for vehicle-cloud collaboration as described in any of the above-mentioned first aspects.

[0062] In the sixth aspect, another embodiment of the present application provides a vehicle controller, comprising: a second processor, a second memory and a bus, wherein the second memory stores machine-readable instructions executable by the second processor. When the vehicle controller is running, the second processor communicates with the second memory through the second bus, and the second processor executes the machine-readable instructions to perform the steps of the vehicle control method of vehicle-cloud collaboration as described in any of the above-mentioned second aspects.

[0063] In the seventh aspect, another embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, the steps of the vehicle control method for vehicle-cloud collaboration as described in any of the first and second aspects above are executed.

[0064] The beneficial effects of this application are:

[0065] The present application provides a vehicle control method and storage medium for vehicle-cloud collaboration, which obtains the historical operating data of the target vehicle within a preset unit historical time period, identifies the operating condition characteristics of the historical operating data, and determines the historical operating condition characteristics of the target vehicle within the preset unit historical time period. The vehicle operating status can be accurately understood, thereby optimizing the vehicle control strategy. Based on the historical operating condition characteristics of the target vehicle, a preset operating condition characteristic threshold is adopted to determine the historical operating scenario operating condition of the target vehicle within the preset unit historical time period; based on the historical operating scenario operating condition, a target control strategy is determined. In this way, the energy of the target vehicle is accurately managed, thereby optimizing the vehicle's energy management mode and improving the vehicle's performance and life. The target control strategy is sent to the vehicle controller of the target vehicle, so that the vehicle controller controls the energy distribution of the power battery and fuel cell on the target vehicle according to the target control strategy. The present application determines the target control strategy of the target vehicle based on the historical operating data of the target vehicle within a preset unit historical time period, and can adapt to changes in vehicle operating conditions in different scenarios, thereby accurately adjusting the vehicle's control strategy to optimize vehicle performance and energy management. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0067] Figure 1 A schematic diagram of a scenario of a vehicle control method for vehicle-cloud collaboration provided in an embodiment of the present application;

[0068] Figure 2 A schematic diagram of a process flow applied to a cloud device in a vehicle control method for vehicle-cloud collaboration provided in an embodiment of the present application;

[0069] Figure 3 A schematic diagram of a process for determining historical operating condition characteristics in a vehicle-cloud collaborative vehicle control method provided in an embodiment of the present application;

[0070] Figure 4 A schematic diagram of determining the maximum running distance provided in an embodiment of the present application;

[0071] Figure 5 A schematic diagram of a process for determining historical operating scenario conditions in a vehicle-cloud collaborative vehicle control method provided in an embodiment of the present application;

[0072] Figure 6 A schematic diagram of a process flow of historical operating scenarios in another vehicle-cloud collaborative vehicle control method provided in an embodiment of the present application;

[0073] Figure 7 A schematic diagram of a flow chart for determining a target control strategy in a vehicle-cloud collaborative vehicle control method provided in this application;

[0074] Figure 8 A process of a vehicle control method for vehicle-cloud collaboration provided in another embodiment of the present application;

[0075] Figure 9 A schematic diagram of a process for controlling energy distribution in a vehicle control method for vehicle-cloud collaboration provided in an embodiment of the present application;

[0076] Figure 10 A schematic diagram of a process for controlling energy distribution in another vehicle-cloud collaborative vehicle control method provided in an embodiment of the present application;

[0077] Figure 11 A schematic diagram of a vehicle control device for vehicle-cloud collaboration provided in an embodiment of the present application;

[0078] Figure 12 A schematic diagram of a vehicle control device for vehicle-cloud collaboration provided in another embodiment of the present application;

[0079] Figure 13 A schematic diagram of the structure of a cloud device provided in an embodiment of the present application;

[0080] Figure 14 A schematic structural diagram of a vehicle controller provided in another embodiment of the present application. DETAILED DESCRIPTION

[0081] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of illustration and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowcharts can be implemented out of sequence, and steps without logical context can be reversed or implemented simultaneously. In addition, those skilled in the art, under the guidance of the contents of this application, can add one or more other operations to the flowchart, or remove one or more operations from the flowchart.

[0082] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application.

[0083] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0084] Currently, fuel cell vehicles are entering the market to address the energy crisis and environmental pollution caused by automobile emissions. These fuel cell vehicles can be hydrogen fuel cell vehicles. While ensuring vehicle performance, range, and mileage, hydrogen fuel cell vehicles can convert hydrogen and oxygen into electricity through a chemical reaction, with water as the product. Because hydrogen fuel cell vehicles have relatively fixed routes, they typically communicate with a cloud device through a vehicle controller during driving. The cloud device determines the vehicle's control strategy based on vehicle status parameters sent by the vehicle controller and transmits this control strategy to the vehicle, allowing the vehicle to determine the output power of the power battery and fuel cell based on the control strategy. However, existing technologies can only determine the corresponding control strategy for a vehicle based on a single parameter or a simple threshold. However, a single parameter often fails to fully reflect the actual operating conditions of a vehicle under complex operating conditions, easily leading to misjudgments. This makes traditional methods difficult to adapt to the dynamic changes in vehicle operating conditions in different scenarios and prevents timely adjustment of the vehicle's operating strategy to optimize performance and energy management.

[0085] To this end, the present application provides a vehicle control method for vehicle-cloud collaboration, which obtains historical operating data of a target vehicle within a preset unit historical time period, identifies operating condition characteristics of the historical operating data, determines the historical operating condition characteristics of the target vehicle within the preset unit historical time period, and uses a preset operating condition characteristic threshold based on the historical operating condition characteristics of the target vehicle to determine the historical operating scenario operating condition of the target vehicle within the preset unit historical time period. Based on the historical operating scenario operating condition, a target control strategy is determined, and the target control strategy is issued to the vehicle controller of the target vehicle, so that the vehicle controller controls the energy distribution of the power battery and fuel cell on the target vehicle according to the target control strategy. The present application determines the target control strategy of the target vehicle based on the historical operating data within a preset unit historical time period, and can consider multiple types of data to more comprehensively understand the performance and needs of the vehicle, ensure the accuracy of the control strategy, and thus optimize the performance and energy management of the vehicle.

[0086] In order to clearly describe the method provided in the embodiment of the present application, the vehicle control method of vehicle-cloud collaboration provided in the embodiment of the present application is explained below in combination with multiple drawings. The vehicle control method of vehicle-cloud collaboration provided in the present application is applied to cloud devices and vehicle controllers respectively. Figure 1 A schematic diagram of a vehicle control method for vehicle-cloud collaboration provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, the vehicle controller 100 uploads the historical operating data of the target vehicle collected by the on-board equipment of the target vehicle within a preset unit historical time period to the cloud device 200, and the cloud device 200 identifies the working condition characteristics of the historical operating data to determine the historical working condition characteristics of the target vehicle within the preset unit historical time period. Based on the historical working condition characteristics of the target vehicle, a preset working condition characteristic threshold is used to determine the historical operating scenario working condition of the target vehicle within the preset unit historical time period. Based on the historical operating scenario working condition, a target control strategy is determined and the target control strategy is sent to the vehicle controller of the target vehicle. The vehicle controller 100 receives the target control strategy sent by the cloud device 200, and controls the energy distribution of the power battery and fuel cell on the target vehicle according to the target control strategy.

[0087] Figure 2 A schematic diagram of a process flow for a vehicle control method for vehicle-cloud collaboration provided in an embodiment of the present application is applied to a cloud device, such as Figure 2 As shown, the method includes:

[0088] Step 201: Obtain historical operating data of a target vehicle within a preset unit historical time period.

[0089] The preset unit historical time period can be a driving cycle, i.e., the target vehicle travels from the starting point to the end point. Alternatively, it can be a day, i.e., from 0:00 to 24:00. The historical operating data can include the target vehicle's daily mileage, target vehicle location, target vehicle speed, target vehicle power take-off activation times, and target vehicle electric power steering activation times.

[0090] Optionally, the vehicle controller of the target vehicle periodically sends historical operation data to the cloud device within a preset unit historical time period. Specifically, the historical operation data can be sent to the cloud device every second. The cloud device periodically receives the historical operation data according to the period sent by the vehicle controller.

[0091] Step 202: Identify the operating condition characteristics of the historical operating data to determine the historical operating condition characteristics of the target vehicle in a preset unit historical time period.

[0092] Among them, the historical operating condition characteristics are used to determine the historical operating scenario conditions of the target vehicle in a preset historical unit time period.

[0093] Optionally, the historical operating data is analyzed to determine the operating condition characteristics of each historical operating data, thereby determining the historical operating condition characteristics of the target vehicle in a preset unit historical time period.

[0094] Step 203: Based on the historical operating condition characteristics of the target vehicle, a preset operating condition characteristic threshold is used to determine the historical operation scenario operating condition of the target vehicle in a preset unit historical time period.

[0095] Among them, the preset operating condition characteristic threshold is used to judge the scenario corresponding to the historical operating condition characteristics of the target vehicle. Different historical operating condition characteristics correspond to different preset operating condition thresholds. Specifically, it is determined according to the type of target vehicle and the actual operating scenario. The embodiment of this application does not limit this.

[0096] Optionally, the historical operating condition characteristics of the target vehicle are compared with preset operating condition characteristic thresholds respectively, so as to determine the historical operation scenario operating conditions of the target vehicle in a preset unit historical time period.

[0097] Step 204: Determine the target control strategy based on historical operating scenario conditions.

[0098] The historical operating scenario operating condition may be a long-distance operating condition or a short-distance operating condition, and accordingly, the target control strategy may be a control strategy for a long-distance operating condition or a control strategy for a short-distance operating condition.

[0099] Optionally, when the historical operating condition characteristics of the target vehicle all meet the historical operating scenario conditions corresponding to the control strategy for long-distance operating conditions, the historical operating scenario conditions of the target vehicle within a preset unit historical time period are determined to be long-distance operating conditions; or when some of the historical operating condition characteristics of the target vehicle meet the historical operating scenario conditions corresponding to the control strategy for long-distance operating conditions, the historical operating scenario conditions of the target vehicle within a preset unit historical time period are determined to be long-distance operating conditions; or by comparing the historical operating condition characteristics of the target vehicle with the preset operating condition characteristic threshold through preset weight parameters to obtain corresponding parameters, the historical operating scenario conditions of the target vehicle within the preset unit historical time period are determined to be long-distance operating conditions based on the parameters. The method for determining the control strategy for short-distance operating conditions is the same as that for long-distance operating conditions, which will not be repeated here.

[0100] Step 205: Send the target control strategy to the vehicle controller of the target vehicle, so that the vehicle controller controls the energy distribution of the power battery and the fuel cell on the target vehicle according to the target control strategy.

[0101] Among them, the target control strategy is used to control the energy distribution of the power battery and fuel cell on the target vehicle.

[0102] In an embodiment of the present application, by obtaining the historical operating data of the target vehicle within a preset unit historical time period, the operating condition characteristics of the historical operating data are identified, and the historical operating condition characteristics of the target vehicle within the preset unit historical time period are determined. The vehicle operating status can be accurately understood, thereby optimizing the vehicle control strategy. Based on the historical operating condition characteristics of the target vehicle, a preset operating condition characteristic threshold is adopted to determine the historical operating scenario operating condition of the target vehicle within the preset unit historical time period; based on the historical operating scenario operating condition, a target control strategy is determined. The energy of the target vehicle is accurately managed, thereby optimizing the vehicle's energy management mode and improving the vehicle's performance and life. The target control strategy is sent to the vehicle controller of the target vehicle, so that the vehicle controller controls the energy distribution of the power battery and fuel cell on the target vehicle according to the target control strategy. The present application determines the target control strategy of the target vehicle based on the historical operating data of the target vehicle within a preset unit historical time period, adapts to changes in vehicle operating conditions under different scenarios, and accurately adjusts the vehicle's control strategy to optimize vehicle performance and energy management.

[0103] Based on the above embodiment, the historical operation data includes: positioning data of multiple historical trajectory points, the enabling time of the power take-off, the parking time, and the enabling time of the air pump. To this end, this application also provides a process for determining the historical operating condition characteristics in the vehicle control method of vehicle-cloud collaboration. Figure 3 A flow chart of determining historical operating condition characteristics in a vehicle control method for vehicle-cloud collaboration provided in an embodiment of the present application is shown as follows: Figure 3 As shown, in the above step 202, the operating condition characteristics of the historical operating data are identified to determine the historical operating condition characteristics of the target vehicle in the preset unit historical time period, including:

[0104] Step 301: Calculate the maximum running distance of the target vehicle within a preset unit historical time period based on the positioning data of multiple historical trajectory points.

[0105] The positioning data of the historical track points include the latitude data and longitude data of the track points.

[0106] Optionally, the latitude mean and latitude standard deviation of the multiple historical trajectory points are calculated based on the latitude data of the historical trajectory points, and the longitude mean and longitude standard deviation of the multiple historical trajectory points are calculated based on the longitude data of the historical trajectory points. A bounding box is calculated for the multiple historical trajectory points based on the latitude mean, latitude standard deviation, longitude mean, and longitude standard deviation of the multiple historical trajectory points, and the maximum travel distance of the target vehicle within a preset unit historical time period is determined based on the diagonal of the bounding box. For example, the diagonal of the bounding box can be used as the maximum travel distance of the target vehicle within the preset unit historical time period.

[0107] Optionally, the difference between the latitude mean of multiple historical trajectory points and twice the latitude standard deviation is used as the latitude lower limit of the bounding box, the sum of the latitude mean of multiple historical trajectory points and twice the latitude standard deviation is used as the latitude upper limit of the bounding box, the difference between the longitude mean of multiple historical trajectory points and twice the longitude standard deviation is used as the longitude lower limit of the bounding box, and the sum of the longitude mean of multiple historical trajectory points and twice the longitude standard deviation is used as the longitude upper limit of the bounding box.

[0108] For example, Figure 4 A schematic diagram of determining the farthest running distance provided in an embodiment of the present application is shown as follows: Figure 4 As shown in the figure, the dotted double arrow represents the maximum distance between the start and end points, the dotted box represents the bounding box constructed based on multiple historical trajectory points, and the solid double arrow represents the diagonal of the bounding box. The actual maximum travel distance of the target vehicle is 4 kilometers, and the diagonal distance of the bounding box is 3.5 kilometers. Therefore, the maximum travel distance of the target vehicle can be determined based on the diagonal of the bounding box.

[0109] Step 302: Calculate the interval between two adjacent power take-off activations within a preset unit historical time period based on the positioning data of the plurality of historical trajectory points and the activation time of the power take-off.

[0110] The enabling of the power take-off is used to instruct the target vehicle to load or unload cargo, and the interval between two adjacent power take-off enabling times within a preset unit historical time period may be the interval between loading and unloading cargo for the target vehicle.

[0111] Optionally, based on the positioning data of multiple historical trajectory points and the enabling time of the power take-off, the historical trajectory point of the target vehicle when the power take-off is enabled is determined, and the interval distance between two adjacent power take-off enabling times within a preset unit historical time period is determined based on the vehicle instrument mileage value corresponding to the historical trajectory point.

[0112] Step 303: Calculate the number of unit distance stops within a preset unit historical time period based on the positioning data and parking times of the multiple historical trajectory points.

[0113] The unit distance may be one kilometer, which is determined based on actual conditions and is not limited in this embodiment of the present application.

[0114] Optionally, based on the positioning data and parking time of multiple historical trajectory points, the positioning data of the target vehicle when the target vehicle is parked is determined, and the number of unit distance parking times within a preset unit historical time period is calculated based on the positioning data of the target vehicle when the target vehicle is parked.

[0115] For example, if a vehicle travels 10 kilometers in 1 hour and stops 5 times, the number of stops per unit distance is 0.5 times / kilometer.

[0116] Step 304: Calculate the number of times the air pump is enabled per unit distance within a preset unit historical time period based on the positioning data of the multiple historical trajectory points and the air pump enabling time.

[0117] Among them, the historical operating condition characteristics include: the longest running distance, the power take-off enabling interval distance, the number of stops per unit distance, and the number of air pump enabling times per unit distance.

[0118] The unit distance may be one kilometer, which is determined based on actual conditions and is not limited in the present embodiment. The air pump enable is used to indicate whether the air pump of the target vehicle is in a working state.

[0119] Optionally, based on the positioning data and air pump enable time of multiple historical trajectory points, the positioning data of the target vehicle when the air pump is enabled is determined, and the number of air pump enablements per unit distance within a preset unit historical time period is calculated based on the positioning data of the target vehicle when the air pump is enabled.

[0120] For example, if the vehicle travels 10 kilometers in one hour and the air pump is enabled five times, the number of times the air pump is enabled per unit distance is 0.5 times / kilometer.

[0121] In an embodiment of the present application, by calculating the longest running distance within a preset unit historical time period, the interval distance between two adjacent power take-off enablements per unit distance, the number of stops per unit distance, and the number of air pump enablements per unit distance, the historical operating condition characteristics are determined. The historical operating condition characteristics of the target vehicle can be accurately determined, thereby optimizing the control strategy of the target vehicle and reducing unnecessary energy consumption and losses.

[0122] Based on the above embodiment, the preset operating condition characteristic thresholds include: a preset running distance threshold, a preset power take-off enable interval distance threshold, a preset parking number threshold, and a preset pumping enable number threshold. To this end, the present application also provides a process for determining the historical operating scenario operating conditions in a vehicle control method for vehicle-cloud collaboration. Figure 5 A schematic diagram of a process for determining historical operating scenario conditions in a vehicle control method for vehicle-cloud collaboration provided in an embodiment of the present application is shown in FIG. Figure 5 As shown, in the above step 203, based on the historical operating condition characteristics of the target vehicle, a preset operating condition characteristic threshold is used to determine the historical operating scenario operating condition of the target vehicle in the preset unit historical time period, including:

[0123] Step 501: normalize the longest running distance according to a preset running distance threshold to obtain a first evaluation parameter.

[0124] Among them, the preset running distance threshold can be 20 kilometers, and the standardization processing is to determine the first evaluation parameter to be 1 or 0.

[0125] Optionally, the maximum running distance is compared with a preset running distance threshold, thereby achieving normalization of the maximum running distance to obtain a first evaluation parameter. If the maximum running distance is greater than the preset running distance threshold, the first evaluation parameter is determined to be 1, otherwise the first evaluation parameter is 0.

[0126] Step 502: normalize the power take-off enabling interval distance according to a preset power take-off enabling interval distance threshold to obtain a second evaluation parameter.

[0127] Among them, the preset power take-off enabling interval distance threshold can be 20 kilometers, and the standardization processing is to determine the second evaluation parameter to be 1 or 0.

[0128] Optionally, the PTO enabling distance is compared with a preset PTO enabling distance threshold, thereby normalizing the PTO enabling distance to obtain a second evaluation parameter. If the PTO enabling distance is greater than the preset PTO enabling distance threshold, the second evaluation parameter is determined to be 1; otherwise, the second evaluation parameter is 0.

[0129] Step 503: Normalize the number of stops per unit distance according to a preset stop number threshold to obtain a third evaluation parameter.

[0130] The preset parking number threshold may be two times per kilometer, and the normalization process is to determine the third evaluation parameter to be 1 or 0.

[0131] Optionally, the number of stops per unit distance is compared with a preset stop count threshold, thereby normalizing the number of stops per unit distance to obtain a third evaluation parameter. If the number of stops per unit distance is greater than the preset stop count threshold, the third evaluation parameter is determined to be 0; otherwise, the third evaluation parameter is 1.

[0132] Step 504: Standardize the number of times the air pump is enabled per unit distance according to a preset threshold value of the number of times the air pump is enabled, and determine a fourth evaluation parameter.

[0133] The preset pumping enable times threshold may be twice per kilometer, and the standardization process is to determine that the fourth evaluation parameter is 1 or 0.

[0134] Optionally, the number of pump activations per unit distance is compared with a preset pump activation threshold, thereby standardizing the number of pump activations per unit distance to obtain a fourth evaluation parameter. If the number of pump activations per unit distance is greater than the preset pump activation threshold, the third evaluation parameter is determined to be 0; otherwise, the third evaluation parameter is 1.

[0135] Step 505: Determine the historical operating scenario conditions based on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter.

[0136] Optionally, the first evaluation parameter, the second evaluation parameter, the third evaluation parameter and the fourth evaluation parameter can be averaged to determine the historical operating scenario conditions based on the average; or the first evaluation parameter, the second evaluation parameter, the third evaluation parameter and the fourth evaluation parameter can be weightedly calculated to determine the historical operating scenario conditions; or other calculation methods can be used, which are not limited in the embodiments of the present application.

[0137] In an embodiment of the present application, the historical operating scenario conditions are determined by determining the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter. The historical operating scenario conditions are determined by weighted calculation based on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter. The present application can quickly identify the historical operating scenario conditions through multi-dimensional evaluation.

[0138] Based on the above embodiment, this application also provides another process of historical operating scenario conditions in a vehicle control method of vehicle-cloud collaboration. Figure 6 A flow chart of historical operating scenario conditions in another vehicle-cloud collaborative vehicle control method provided in an embodiment of the present application, such as Figure 6 As shown, in the above step 505, the historical operating scenario conditions are determined according to the first evaluation parameter, the second evaluation parameter, the third evaluation parameter and the fourth evaluation parameter, including:

[0139] Step 601: Perform a weighted sum operation on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter to obtain a target evaluation parameter.

[0140] Optionally, based on historical data corresponding to the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter, weights corresponding to the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter are assigned, and the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter are weighted and calculated to obtain the target evaluation parameter. The specific weights corresponding to the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter are determined based on the parameters of the target vehicle itself and the operating conditions, and this embodiment of the application does not limit this.

[0141] Step 602: If the target evaluation parameter is greater than or equal to the preset threshold, it is determined that the historical operating scenario condition is a long-distance condition.

[0142] The preset threshold can be 0.5. Since the total score of long-distance operating conditions after the features are combined is usually higher than that of short-distance operating conditions, setting a threshold can effectively distinguish operating scenarios.

[0143] Step 603: If the target evaluation parameter is less than the preset threshold, it is determined that the historical operating scenario condition is a short-distance condition.

[0144] In the embodiment of the present application, a weighted sum operation is performed on the first, second, third, and fourth evaluation parameters to obtain a target evaluation parameter, and the historical operating scenario conditions are determined based on the target evaluation parameter. The target evaluation parameter can be dynamically adjusted to optimize the control strategy.

[0145] Based on the above embodiment, the present application further provides a process for determining target evaluation parameters in a vehicle control method for vehicle-cloud collaboration. In step 601, a weighted sum operation is performed on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter to obtain the target evaluation parameter, including:

[0146] performing a weighted sum operation on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter according to the first preset weight, the second preset weight, the third preset weight, and the fourth preset weight to obtain a target evaluation parameter;

[0147] The sum of the first preset weight, the second preset weight, the third preset weight, and the fourth preset weight is 1, and the first preset weight and the second preset weight are both greater than the third preset weight and the fourth preset weight. The first preset weight and the second preset weight may be the same or different, and the third preset weight and the fourth preset weight may be the same or different.

[0148] For example, the first preset weight and the second preset weight are 0.4 respectively, the third preset weight and the fourth preset weight are 0.1 respectively, and the preset threshold value can be 0.5. According to the first preset weight, the second preset weight, the third preset weight and the fourth preset weight, the first evaluation parameter, the second evaluation parameter, the third evaluation parameter and the fourth evaluation parameter are weighted and calculated to obtain the target evaluation parameter. If the target evaluation parameter is greater than 0.5, it is a long-distance working condition, otherwise it is a short-distance working condition.

[0149] In an embodiment of the present application, the first evaluation parameter, the second evaluation parameter, the third evaluation parameter and the fourth evaluation parameter are weighted and calculated according to the first preset weight, the second preset weight, the third preset weight and the fourth preset weight to obtain the target evaluation parameter, which can dynamically adapt to business needs, enhance the accuracy of determining the operating scenario, and avoid a certain parameter dominating the result.

[0150] Based on the above embodiments, this application also provides a process for determining a target control strategy in a vehicle control method of vehicle-cloud collaboration. Figure 7 This is a flow chart of determining the target control strategy in a vehicle-cloud collaborative vehicle control method provided by this application, such as Figure 7As shown, in the above step 204, the target control strategy is determined based on the historical operating scenario conditions, including:

[0151] Step 701: Determine whether there is any change in operating conditions in a preset unit historical time period based on historical operating scenario operating conditions.

[0152] Optionally, if the preset unit historical time period is one day, then the historical operating scenario working conditions are compared with the historical operating scenario working conditions of the previous preset unit historical time period to determine whether there is a working condition change in the preset unit historical time period.

[0153] Step 702: If there is no change in the operating condition, determine the preset control strategy corresponding to the historical operating scenario operating condition as the target control strategy.

[0154] Optionally, if the historical operating scenario working condition is the same as the historical operating scenario working condition of the previous preset unit historical time period, there is no working condition change, and the preset control strategy corresponding to the historical operating scenario working condition is determined as the target control strategy.

[0155] Step 703: If there is a change in the operating condition, and the latest operating scenario operating condition is maintained within a preset number of unit historical time periods, the preset control strategy corresponding to the latest operating scenario operating condition is determined as the target control strategy.

[0156] The preset number of unit historical time periods may be two unit historical time periods.

[0157] Optionally, if the historical operating scenario conditions are different from the historical operating scenario conditions of the previous preset unit historical time period, then there is a change in operating conditions. If the latest operating scenario conditions are maintained in both unit historical time periods, then the preset control strategy corresponding to the latest operating scenario conditions is determined as the target control strategy.

[0158] For example, if the historical operating scenario condition is a long-distance condition and the historical operating scenario condition in the previous preset unit historical time period is a short-distance condition, then there is a change in operating condition. If the long-distance condition is maintained in both unit historical time periods, the preset control strategy corresponding to the long-distance condition is determined to be the target control strategy.

[0159] In the embodiment of the present application, based on the historical operating scenario conditions, it is determined whether there is a change in the operating conditions in a preset unit historical time period, thereby determining the target control strategy. This application can quickly identify changes in vehicle operating scenarios within a short preset time period, dynamically switch target control strategies, and optimize resource utilization.

[0160] On the basis of the above embodiment, another embodiment of the present application further provides a vehicle control method of vehicle-cloud collaboration, which is applied to the vehicle controller of the target vehicle. Figure 8Another embodiment of the present application provides a process of a vehicle control method for vehicle-cloud collaboration, such as Figure 8 As shown, the method includes:

[0161] Step 801: Upload the historical operating data of the target vehicle within a preset unit historical time period collected by the on-board equipment of the target vehicle to the cloud device.

[0162] The vehicle-mounted equipment includes positioning equipment, a power take-off controller, a pressure sensor, and other equipment, which are not limited in the present embodiment. The historical operation data includes: positioning data of historical trajectory points, power take-off enabling time, parking time, and air pump enabling time.

[0163] Optionally, the target vehicle's onboard device collects the target vehicle's location data of track points, power take-off enable time, parking time, and air pump enable time within a preset unit historical time period and uploads it to the cloud device. The preset unit historical time period may be 1 second.

[0164] Step 802: Receive the target control strategy sent by the cloud device. The target control strategy is a control strategy determined by the cloud device according to the vehicle control method of vehicle-cloud collaboration.

[0165] Step 803: Control the energy distribution of the power battery and the fuel cell on the target vehicle according to the target control strategy.

[0166] In an embodiment of the present application, historical operating data of a target vehicle is uploaded to a cloud device, a target control strategy is received from the cloud, and energy distribution between the power battery and fuel cell on the target vehicle is controlled according to the target control strategy. This application can optimize the target vehicle's energy distribution, improve its energy consumption, and more efficiently utilize limited energy, thereby extending the vehicle's range.

[0167] Based on the above embodiments, this application also provides a process for controlling energy distribution in a vehicle control method of vehicle-cloud collaboration. Figure 9 A schematic diagram of a process for controlling energy distribution in a vehicle control method for vehicle-cloud collaboration provided in an embodiment of the present application is shown in FIG. Figure 9 As shown, in the above step 803, according to the target control strategy, the energy distribution of the power battery and the fuel cell on the target vehicle is controlled, including:

[0168] Step 901: If the target control strategy is a long-distance control strategy, obtain the current driving state of the target vehicle.

[0169] The driving state of the target vehicle may include: constant speed driving, accelerating driving, climbing driving and braking state.

[0170] Optionally, if the target control strategy is a control strategy for long-distance operation, a speed sensor, an acceleration sensor, and a positioning device on the target vehicle are obtained to determine the current driving state of the target vehicle.

[0171] Step 902: If the current driving state is constant speed driving, control the fuel cell to output energy based on a preset rated power.

[0172] The preset rated power can be 80%. When the total power of the fuel cell is 120 kilowatts, the preset rated power can be 96 kilowatts. The specific preset rated power is determined based on the fuel cell of the target vehicle and the parameters of the target vehicle, and is not limited in this embodiment of the present application. Constant speed driving can include: low-speed constant speed driving and high-speed constant speed driving.

[0173] Optionally, if the current driving state is uniform speed driving, it means that the target vehicle has no need to accelerate or decelerate, and the fuel cell is controlled to output energy based on a preset rated power.

[0174] Optionally, if the current driving state is uniform speed, it means that the target vehicle has no need to accelerate or decelerate. The power requirement of the target vehicle at this speed is determined based on the degree of accelerator pedal opening by the driver at this speed. The power requirement of the target vehicle at this speed is used as the preset rated power, and the fuel cell is controlled to output energy based on the preset rated power.

[0175] Step 903: If the current driving state is accelerating or climbing, the fuel cell is controlled to output energy based on the preset rated power, and the power battery is controlled to supplement power.

[0176] Optionally, if the current driving state is accelerating or climbing, it means that the target vehicle is only powered by the fuel cell, which may not be able to meet the power requirements of the target vehicle. The fuel cell is controlled to output energy based on the preset rated power, and the power battery is controlled to supplement power, so that the target vehicle can still drive stably when the current driving state is accelerating or climbing.

[0177] Step 904: If the current driving state is a braking state, control the power battery to recover energy so that the state of charge of the power battery is within a preset range; if the state of charge after energy recovery is still not within the preset range, control the fuel cell to charge the power battery so that the state of charge of the power battery is within the preset range.

[0178] Among them, the preset range can be 30%-70%.

[0179] Optionally, if the current driving state is braking, the power battery is controlled to perform energy recovery so that the power battery's state of charge is within a preset range. If the energy recovery state of charge is still not within the preset range, the fuel cell is controlled to supply energy to the target vehicle while charging the power battery so that the power battery's state of charge is within the preset range.

[0180] In an embodiment of the present application, the control strategy for the fuel cell and the power battery is determined based on the vehicle control strategy and the driving status of the target vehicle, which can improve the energy utilization rate of the fuel cell and the power battery, extend the vehicle's cruising range and the life of the fuel cell and the power battery, and improve the performance of the vehicle.

[0181] Based on the above embodiment, this application also provides another process for controlling energy distribution in a vehicle control method of vehicle-cloud collaboration. Figure 10 A schematic diagram of a process for controlling energy distribution in another vehicle-cloud collaborative vehicle control method provided in an embodiment of the present application is shown in FIG. Figure 10 As shown, in the above step 803, according to the target control strategy, the energy distribution of the power battery and the fuel cell on the target vehicle is controlled, including:

[0182] Step 1001: If the target control strategy is a short-distance operating condition control strategy, obtain the current state of charge of the power battery.

[0183] The current state of charge parameters of the power battery are determined by the battery management system in the power battery.

[0184] Optionally, if the target control strategy is a control strategy for a short-distance operating condition, the current state of charge of the power battery is obtained through the battery management system of the power battery.

[0185] Step 1002: If the current state of charge is within the first charge interval, control the power battery to output energy at the full required power of the target vehicle, and control the fuel cell to enter a standby state.

[0186] The first charge interval is an interval in which the state of charge parameter is greater than 90%.

[0187] Optionally, if the current state of charge is within the first charge interval, it means that the power battery can meet the power supply demand of the target vehicle, then the power battery is controlled to output energy at the full required power of the target vehicle, and the fuel cell is controlled to enter the standby state, at which time the fuel cell does not work.

[0188] Step 1003: If the current state of charge is not within the first charge interval but within the second charge interval, control the power battery to output a first proportion of the required power for energy output, control the fuel cell to start and maintain a second proportion of the rated power for energy output, and use the redundant power of the fuel cell to charge the power battery.

[0189] The second charge range is the range where the state of charge parameter is greater than 75% and less than 90%. The first ratio of required power is between 70% and 90% of the target vehicle system requirement, and the second ratio of rated power can be between 10% and 30%, which is not limited in this embodiment of the application.

[0190] Alternatively, if the current state of charge is not within the first charge range but within the second charge range, the power battery is controlled to output a first proportion of the required power for energy output. If the power battery may not be able to meet the system requirements of the target vehicle at this time, the fuel cell is controlled to start and maintain a second proportion of the rated power for energy output, and the power battery is charged using the fuel cell's redundant power. Specifically, when the fuel cell's output power meets the system requirements of the target vehicle, the fuel cell's redundant power is used to charge the power battery.

[0191] Step 1004: If the current state of charge is not within the second charge interval but within the third charge interval, control the fuel cell to output energy at a third ratio of the rated power, control the power battery to output energy at a fourth ratio of the required power, and use the redundant power of the fuel cell to charge the power battery.

[0192] The third ratio may be 40%, which is greater than the second ratio, and the fourth ratio may be 80%, which is less than the first ratio. The third charge interval is an interval in which the state of charge parameter is less than 75%, which is not limited in the present embodiment.

[0193] Optionally, if the current state of charge is not within the second charge interval but within the third charge interval, and the power battery cannot meet the power supply requirements of the system, the fuel cell is controlled to output energy at a third proportion of the rated power, and the power battery is controlled to output energy at a fourth proportion of the required power, and the redundant power of the fuel cell is used to charge the power battery.

[0194] Based on the same inventive concept, the embodiment of the present application also provides a vehicle-cloud collaborative vehicle control device corresponding to a vehicle-cloud collaborative vehicle control method, which is applied to cloud devices. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the above-mentioned vehicle-cloud collaborative vehicle control method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0195] Figure 11 A schematic diagram of a vehicle control device for vehicle-cloud collaboration provided in an embodiment of the present application is shown as follows: Figure 11 As shown, the device includes:

[0196] An acquisition module 1101 is used to acquire historical operation data of a target vehicle within a preset unit historical time period;

[0197] Identification module 1102, for identifying operating condition characteristics of historical operating data, and determining historical operating condition characteristics of the target vehicle in a preset unit historical time period;

[0198] The determination module 1103 is configured to determine the historical operating scenario operating condition of the target vehicle in a preset unit historical time period based on the historical operating condition characteristics of the target vehicle and using a preset operating condition characteristic threshold;

[0199] A determination module 1103 is configured to determine a target control strategy based on historical operating scenario conditions, wherein the target operating scenario condition is a control strategy for a long-distance operating condition or a control strategy for a short-distance operating condition;

[0200] The sending module 1104 is used to send the target control strategy to the vehicle controller of the target vehicle, so that the vehicle controller controls the energy distribution of the power battery and the fuel cell on the target vehicle according to the target control strategy.

[0201] Optionally, the historical operation data includes: positioning data of multiple historical trajectory points, the enabling time of the power take-off, the parking time, and the enabling time of the air pump; the identification module 1102 is specifically used to: calculate the maximum running distance of the target vehicle within a preset unit historical time period based on the positioning data of the multiple historical trajectory points;

[0202] Calculate the interval between two consecutive power take-off activations within a preset unit historical time period based on the positioning data of multiple historical trajectory points and the power take-off activation time;

[0203] Calculate the number of unit distance stops within a preset unit historical time period based on the positioning data and parking time of multiple historical trajectory points;

[0204] Calculate the number of times the air pump is enabled per unit distance within a preset unit historical time period based on the positioning data of multiple historical trajectory points and the air pump enabling time;

[0205] Among them, the historical operating condition characteristics include: the longest running distance, the power take-off enabling interval distance, the number of stops per unit distance, and the number of air pump enabling times per unit distance.

[0206] Optionally, the preset operating condition characteristic thresholds include: a preset operating distance threshold, a preset power take-off enabling interval distance threshold, a preset parking number threshold, and a preset pumping enabling number threshold; the identification module 1102 is specifically configured to: normalize the longest operating distance according to the preset operating distance threshold to obtain a first evaluation parameter;

[0207] Normalizing the power take-off enabling interval distance according to a preset power take-off enabling interval distance threshold to obtain a second evaluation parameter;

[0208] Normalizing the number of stops per unit distance according to a preset stop number threshold to obtain a third evaluation parameter;

[0209] The fourth evaluation parameter is determined by normalizing the number of times the air pump is enabled per unit distance according to a preset threshold value of the number of times the air pump is enabled;

[0210] The historical operating scenario conditions are determined based on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter.

[0211] Optionally, the identification module 1102 is specifically configured to: perform a weighted sum operation on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter to obtain a target evaluation parameter;

[0212] If the target evaluation parameter is greater than or equal to the preset threshold, the historical operating scenario condition is determined to be a long-distance condition;

[0213] If the target evaluation parameter is less than the preset threshold, the historical operating scenario condition is determined to be a short-distance condition.

[0214] Optionally, the identification module 1102 is specifically configured to: perform a weighted sum operation on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter according to the first preset weight, the second preset weight, the third preset weight, and the fourth preset weight to obtain a target evaluation parameter;

[0215] The sum of the first preset weight, the second preset weight, the third preset weight and the fourth preset weight is 1, and the first preset weight and the second preset weight are both greater than the third preset weight and the fourth preset weight.

[0216] Optionally, the determination module 1103 is specifically configured to: determine whether there is a change in operating conditions in a preset unit historical time period based on historical operating scenario operating conditions;

[0217] If there is no change in the working condition, the preset control strategy corresponding to the working condition of the historical operation scenario is determined as the target control strategy;

[0218] If there is a change in the operating condition, and the latest operating scenario operating condition is maintained within a preset number of unit historical time periods, the preset control strategy corresponding to the latest operating scenario operating condition is determined as the target control strategy.

[0219] For descriptions of the processing flow of each module in the device and the interaction flow between each module, reference can be made to the relevant descriptions in the above method embodiment, which will not be described in detail here.

[0220] Based on the same inventive concept, another embodiment of the present application also provides a vehicle-cloud collaborative vehicle control device corresponding to a vehicle-cloud collaborative vehicle control method, which is applied to a vehicle controller. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the above-mentioned vehicle-cloud collaborative vehicle control method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0221] Figure 12 A schematic diagram of a vehicle control device for vehicle-cloud collaboration provided in another embodiment of the present application is shown as follows: Figure 12 As shown, the device includes:

[0222] The collection module 1201 is used to upload the historical operation data of the target vehicle collected by the on-board equipment of the target vehicle within a preset unit historical time period to the cloud device;

[0223] A receiving module 1202 is configured to receive a target control strategy issued by a cloud device, where the target control strategy is a control strategy determined by the cloud device according to a vehicle control method for vehicle-cloud collaboration;

[0224] The control module 1203 is used to control the energy distribution of the power battery and the fuel cell on the target vehicle according to the target control strategy.

[0225] Optionally, the control module 1203 is specifically configured to: if the target control strategy is a long-distance driving condition control strategy, obtain the current driving state of the target vehicle;

[0226] If the current driving state is constant speed, the fuel cell is controlled to output energy based on the preset rated power;

[0227] If the current driving state is accelerating or climbing, the fuel cell is controlled to output energy based on the preset rated power, and the power battery is controlled to supplement power;

[0228] If the current driving state is a braking state, the power battery is controlled to recover energy so that the state of charge of the power battery is within a preset range; if the state of charge after energy recovery is still not within the preset range, the fuel cell is controlled to charge the power battery so that the state of charge of the power battery is within the preset range.

[0229] Optionally, the control module 1203 is specifically configured to: if the target control strategy is a short-distance operating condition control strategy, obtain the current state of charge of the power battery;

[0230] If the current state of charge is within the first charge interval, the power battery is controlled to output energy at the full required power of the target vehicle, and the fuel cell is controlled to enter a standby state;

[0231] If the current state of charge is not within the first charge range but within the second charge range, the power battery is controlled to output a first proportion of the required power for energy output, the fuel cell is controlled to start and maintain a second proportion of the rated power for energy output, and the redundant power of the fuel cell is used to charge the power battery;

[0232] If the current state of charge is not within the second charge interval but within the third charge interval, the fuel cell is controlled to output energy at a third ratio of the rated power, and the power battery is controlled to output energy at a fourth ratio of the required power, and the redundant power of the fuel cell is used to charge the power battery; wherein the third ratio is greater than the second ratio, and the fourth ratio is less than the first ratio.

[0233] The embodiment of the present application also provides a cloud device, Figure 13 A schematic diagram of the structure of a cloud device provided in an embodiment of the present application includes: a first processor 1301, a first memory 1302, and optionally, a first bus 1303. The first memory 1302 stores machine-readable instructions executable by the first processor 1301. When the cloud device 200 is running, the first processor 1301 communicates with the first memory 1302 via the first bus 1303, and the machine-readable instructions are executed by the first processor 1301 to perform the steps of the vehicle control method for vehicle-cloud collaboration described above.

[0234] The embodiment of the present application also provides a vehicle controller, Figure 14 This is a schematic diagram of the structure of a vehicle controller provided in another embodiment of the present application, comprising: a second processor 1401, a second memory 1402, and optionally, a second bus 1403. The second memory 1402 stores machine-readable instructions executable by the second processor 1401. When the vehicle controller 100 is running, the second processor 1401 communicates with the second memory 1402 via the second bus 1403, and the machine-readable instructions are executed by the second processor 1401 to perform the steps of the vehicle control method for vehicle-cloud collaboration described above.

[0235] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the above-mentioned vehicle control method for vehicle-cloud collaboration are executed.

[0236] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and device described above can refer to the corresponding process in the method embodiment, and will not be repeated in this application. In the several embodiments provided in this application, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0237] In addition, the functional units in the various embodiments of the present application can be integrated into a single processing unit, each unit can exist physically separately, or two or more units can be integrated into a single unit. If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0238] The above is only a specific implementation method of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the protection scope of the present application.

Claims

1. A vehicle control method based on vehicle-cloud collaboration, characterized in that: Applied to a cloud device, the method includes: Obtain historical operating data of the target vehicle within a preset unit historical time period; wherein the historical operating data includes: positioning data of multiple historical trajectory points, power take-off enabling time, parking time, and air pump enabling time; Calculating the maximum running distance of the target vehicle within the preset unit historical time period based on the positioning data of the multiple historical trajectory points; Calculating the interval between two adjacent power take-off activations within the preset unit historical time period based on the positioning data of the multiple historical trajectory points and the activation time of the power take-off; Calculating the number of unit distance stops within the preset unit historical time period based on the positioning data of the multiple historical trajectory points and the parking time; Calculate the number of times the air pump is enabled per unit distance within the preset unit historical time period based on the positioning data of the multiple historical trajectory points and the air pump enabling time; Normalizing the longest running distance according to a preset running distance threshold to obtain a first evaluation parameter; Normalizing the power take-off enabling interval distance according to a preset power take-off enabling interval distance threshold to obtain a second evaluation parameter; Normalizing the number of stops per unit distance according to a preset stop number threshold to obtain a third evaluation parameter; Normalizing the number of times the air pump is enabled per unit distance according to a preset threshold value of the number of times the air pump is enabled to determine a fourth evaluation parameter; performing a weighted sum operation on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter to obtain a target evaluation parameter; If the target evaluation parameter is greater than or equal to a preset threshold, the historical operating scenario operating condition is determined to be a long-distance operating condition; If the target evaluation parameter is less than the preset threshold, determining that the historical operating scenario operating condition is a short-distance operating condition; Determining a target control strategy based on the historical operating scenario conditions, wherein the target control strategy is a control strategy for the long-distance operating condition or a control strategy for the short-distance operating condition; The target control strategy is issued to a vehicle controller of the target vehicle, so that the vehicle controller controls energy distribution of a power battery and a fuel cell on the target vehicle according to the target control strategy.

2. The method according to claim 1, characterized in that The performing a weighted sum operation on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter to obtain a target evaluation parameter includes: performing a weighted sum operation on the first evaluation parameter, the second evaluation parameter, the third evaluation parameter, and the fourth evaluation parameter according to the first preset weight, the second preset weight, the third preset weight, and the fourth preset weight to obtain the target evaluation parameter; The sum of the first preset weight, the second preset weight, the third preset weight and the fourth preset weight is 1, and the first preset weight and the second preset weight are both greater than the third preset weight and the fourth preset weight.

3. The method according to claim 1, characterized in that Determining the target control strategy based on the historical operating scenario conditions includes: Determine, based on the historical operating scenario operating conditions, whether there is an operating condition change in the preset unit historical time period; If there is no change in the operating condition, determining the preset control strategy corresponding to the historical operating scenario operating condition as the target control strategy; If there is a change in the operating condition, and the latest operating scenario operating condition is maintained within a preset number of unit historical time periods, the preset control strategy corresponding to the latest operating scenario operating condition is determined to be the target control strategy.

4. A vehicle control method based on vehicle-cloud collaboration, characterized in that: Applied to a vehicle controller of a target vehicle, the method comprises: Uploading the historical operating data of the target vehicle collected by the on-board device of the target vehicle within a preset unit historical time period to the cloud device; Receive a target control strategy issued by the cloud device, where the target control strategy is a control strategy determined by the cloud device according to the vehicle control method for vehicle-cloud collaboration according to claim 1; According to the target control strategy, the energy distribution of the power battery and the fuel cell on the target vehicle is controlled.

5. The method according to claim 4, characterized in that The controlling the energy distribution of the power battery and the fuel cell on the target vehicle according to the target control strategy includes: If the target control strategy is a long-distance control strategy, obtaining the current driving state of the target vehicle; If the current driving state is constant speed driving, controlling the fuel cell to output energy based on a preset rated power; If the current driving state is accelerating or climbing, controlling the fuel cell to output energy based on the preset rated power, and controlling the power battery to supplement power; If the current driving state is a braking state, the power battery is controlled to recover energy so that the state of charge of the power battery is within a preset range; if the state of charge after energy recovery is still not within the preset range, the fuel cell is controlled to charge the power battery so that the state of charge of the power battery is within the preset range.

6. The method according to claim 4, characterized in that The controlling the energy distribution of the power battery and the fuel cell on the target vehicle according to the target control strategy includes: If the target control strategy is a short-distance operating condition control strategy, obtaining the current state of charge of the power battery; If the current state of charge is within the first charge interval, controlling the power battery to output energy at the full required power of the target vehicle, and controlling the fuel cell to enter a standby state; If the current state of charge is not within the first charge range but within the second charge range, controlling the power battery to output a first proportion of the required power for energy output, controlling the fuel cell to start and maintain a second proportion of the rated power for energy output, and using the redundant power of the fuel cell to charge the power battery; If the current state of charge is not within the second charge interval but within the third charge interval, the fuel cell is controlled to output energy at a third ratio of the rated power, and the power battery is controlled to output energy at a fourth ratio of the required power, and the power battery is charged using the redundant power of the fuel cell; wherein the third ratio is greater than the second ratio, and the fourth ratio is less than the first ratio.

7. A computer-readable storage medium, characterized in that The storage medium stores a computer program, which, when executed by a processor, executes the steps of the vehicle control method for vehicle-cloud collaboration according to any one of claims 1 to 6.

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