Vehicle control method, computer readable storage medium, computer program product, electronic device and vehicle

Abstract

The invention relates to a vehicle control method, a computer readable storage medium, a computer program product, electronic equipment and a vehicle, and the method comprises the steps: generating or outputting a control instruction for controlling a preset function of the vehicle according to a control strategy outputted by a cloud control strategy model; wherein the cloud control strategy model is a computer model constructed based on digital twinning. According to the vehicle control method, through the control strategy output by the cloud control strategy model based on the digital twinborn model, according to twinborn contrast calibration of the entity model and the simulation model, when the cloud control strategy model is updated each time, the vehicle obtains a more accurate control strategy.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and more particularly to a vehicle control method, a computer-readable storage medium, a computer program product, an electronic device, and a vehicle. Background Technology

[0002] In related technologies, vehicle control strategies typically originate from local controllers or cloud servers. When the control strategy originates locally, it can only control according to preset logic and parameters, and cannot be dynamically adjusted based on the actual situation of the vehicle. While cloud-based control strategies can update the control strategy model based on big data, the control strategy is highly dependent on the training data of the cloud model, which can easily lead to problems of mismatch with the actual situation of the vehicle. Summary of the Invention

[0003] This application provides a vehicle control method, a computer-readable storage medium, a computer program product, an electronic device, and a vehicle to at least partially solve the above-mentioned technical problems.

[0004] To achieve the above objectives, according to a first aspect of this application, a vehicle control method is provided, comprising: generating or outputting control commands for controlling preset functions of a vehicle based on a control strategy output by a cloud-based control strategy model; wherein the cloud-based control strategy model is a computer model constructed based on a digital twin.

[0005] Optionally, in some embodiments of this application, the cloud control strategy model includes: a neural network model.

[0006] Optionally, in some embodiments of this application, the input data of the cloud control strategy model includes: vehicle status data.

[0007] Optionally, in some embodiments of this application, the control strategy includes: a correspondence between target parameters and control parameters and / or a combination of multiple control parameters with a corresponding relationship.

[0008] Optionally, in some embodiments of this application, the control instructions include: thermal management control instructions for controlling the vehicle's thermal management system.

[0009] Optionally, in some embodiments of this application, the thermal management control command includes: a cabin heating control command for controlling the vehicle's cabin heating device.

[0010] Optionally, in some embodiments of this application, the vehicle control method further includes: uploading the control command and the corresponding vehicle status data to the cloud control strategy model.

[0011] Optionally, in some embodiments of this application, the vehicle control method further includes:

[0012] The uploaded vehicle status data is input into the cloud control strategy model so that the cloud control strategy model outputs corresponding control commands;

[0013] Perform entity calibration on the uploaded vehicle status data and / or corresponding control commands;

[0014] When the entity calibration meets the accuracy requirements, the cloud control strategy model is updated.

[0015] Optionally, in some embodiments of this application, the vehicle control method further includes: generating or outputting control instructions for controlling preset functions of the vehicle based on a control strategy output by a local control strategy model; wherein the local control strategy model is stored in the vehicle's controller.

[0016] Optionally, in some embodiments of this application, the step of generating or outputting control commands for controlling preset functions of the vehicle based on a control strategy output by a local control strategy model includes:

[0017] When the user selects local mode, vehicle status data is collected and sent to the controller;

[0018] The controller outputs a control strategy based on the local control strategy model stored in the controller.

[0019] When the control strategy output by the local control strategy model differs from the currently executed control strategy, the vehicle's preset functions are controlled according to the control parameters in the control strategy.

[0020] Optionally, in some embodiments of this application, the vehicle control method further includes: receiving a control strategy matched to the user indicated by the user tag data, based on the correspondence between user tag data and the cloud control strategy model.

[0021] Optionally, in some embodiments of this application, receiving a control policy matching the user indicated by the user tag data based on the correspondence between user tag data and the cloud control policy model includes:

[0022] When the user chooses to manually input commands, a control strategy is generated based on the user's input commands and uploaded to the cloud control strategy model.

[0023] When a user selects a voice input command, a control strategy is generated based on the user's voice input command and uploaded to the cloud control strategy model.

[0024] Based on user tag data identified or queried from the user's voiceprint data, a user recommendation control strategy is provided to the user based on the user tag data.

[0025] Optionally, in some embodiments of this application, the digital twin model includes: a one-dimensional simulation model of vehicle dynamics, a one-dimensional simulation model of the engine, a one-dimensional simulation model of the thermal management system, and a three-dimensional CFD simulation model of the passenger compartment.

[0026] Optionally, in some embodiments of this application, the method for constructing the digital twin model includes:

[0027] At least a one-dimensional simulation model of the vehicle's dynamics should be constructed based on the road conditions and vehicle speed.

[0028] At least based on the engine speed, torque and vehicle gear position output by the one-dimensional simulation model of the vehicle dynamics, a one-dimensional simulation model of the engine is constructed.

[0029] At least based on the heat output of the one-dimensional simulation model of the engine, a one-dimensional simulation model of the thermal management system is constructed.

[0030] At least a three-dimensional CFD simulation model of the passenger cabin should be constructed based on the environmental conditions.

[0031] According to a second aspect of this application, a non-transitory computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the vehicle control method described above.

[0032] According to a third aspect of this application, a computer program product is also provided, comprising a computer program that, when executed by a processor, implements the steps of the vehicle control method described above.

[0033] According to a fourth aspect of this application, an electronic device is provided, comprising: a memory storing a computer program; and a processor for executing the computer program in the memory to implement the steps of the method described above.

[0034] According to a fifth aspect of this application, a vehicle is also provided, including the aforementioned electronic equipment.

[0035] The vehicle control method of this application outputs a control strategy based on a cloud-based control strategy model using a digital twin model. This control strategy can be calibrated by comparing the physical model with the simulation model, thereby enabling the vehicle to obtain a more accurate control strategy each time the cloud-based control strategy model is updated.

[0036] Other features and advantages of this application will be described in detail in the following detailed description section. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] To gain a more complete understanding of this application and its beneficial effects, the following description will be provided in conjunction with the accompanying drawings, wherein the same reference numerals in the following description denote the same parts.

[0039] Figure 1 This is a schematic diagram of the main steps of a vehicle control method provided in one embodiment of this application;

[0040] Figure 2 This is a schematic diagram of the architecture of a digital twin model provided in one embodiment of this application;

[0041] Figure 3 This is a schematic diagram illustrating the construction process of a digital twin model provided in one embodiment of this application;

[0042] Figure 4 This is a schematic diagram of a portion of the training process of a digital twin model provided in one embodiment of this application;

[0043] Figure 5 This is a schematic diagram of a portion of the training process of a digital twin model provided in one embodiment of this application;

[0044] Figure 6 This is a schematic diagram of the input and output of a digital twin model provided in one embodiment of this application;

[0045] Figure 7 This is a schematic diagram of a heating control process provided in one embodiment of this application;

[0046] Figure 8 This is a three-dimensional structural schematic diagram of a foot heating system provided in one embodiment of this application;

[0047] Figure 9 This is a schematic diagram of the piping structure of the first vehicle heat exchange system provided in one embodiment of this application;

[0048] Figure 10 This is a schematic diagram of the piping structure of a second vehicle heat exchange system provided in one embodiment of this application;

[0049] Figure 11 This is a schematic diagram of the piping structure of a third vehicle heat exchange system provided in one embodiment of this application;

[0050] Figure 12This is a schematic diagram of the piping structure of a fourth vehicle heat exchange system provided in one embodiment of this application;

[0051] Figure 13 This is a schematic diagram of the control flow of a user-defined mode provided in one embodiment of this application;

[0052] Figure 14 This is a schematic diagram of the structure of an electronic device provided in one embodiment of this application. Detailed Implementation

[0053] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the protection scope of this application.

[0054] Reference Figure 1 As shown, as a first aspect of this application, this application provides a vehicle control method, which includes the following steps:

[0055] S100: Generates or outputs control commands for controlling preset functions of the vehicle based on the control strategy output by a cloud-based control strategy model.

[0056] Among them, the cloud control strategy model is a computer model built based on digital twins.

[0057] A computer model built on digital twins refers to a digital real-time simulation model that corresponds to a physical entity model, established through technologies such as virtual simulation, big data, and machine learning. This model can achieve the same output results as the physical model under the same working conditions for specific functional requirements. In addition, the real-time data connection between the digital twin model and the physical model established based on Internet of Things technology can input the optimal control parameters obtained after optimization calculation by the twin model into the physical entity, realizing the dynamic adjustment of the control strategy.

[0058] The vehicle control method of this application outputs a control strategy based on a cloud-based control strategy model using a digital twin model. This strategy can be calibrated by comparing the physical model with the simulation model, thereby enabling the vehicle to acquire a more precise control strategy each time the cloud-based control strategy model is updated. In other words, the vehicle control method of this application, based on the obtained vehicle information, can apply this information to the control of some vehicle functions.

[0059] For example, regarding the heating or cooling function of the vehicle compartment, when applying the vehicle control method of this application, the temperature information inside the compartment can be obtained during the cooling or heating process. Based on the comparison between the temperature inside the compartment and the target temperature, the heating or cooling capacity can be adjusted to ultimately bring the temperature inside the compartment to the target temperature. Simultaneously, the obtained vehicle information can be uploaded to a cloud-based control strategy model. The required cooling or heating capacity information can be obtained through cloud-based calculations, and a digital twin model can be used to simulate the operating parameters of components used for heating or cooling, such as water pumps and throttling expansion valves. This information is then transmitted back to the vehicle to control the operating status of the water pumps and throttling expansion valves, thereby outputting an appropriate cooling capacity to the vehicle.

[0060] Compared to solutions employing local vehicle control strategies, which are limited by space constraints on the vehicles themselves, resulting in a limited number of storage devices and processing capacity, and thus insufficient actual computing power, cloud-based control strategy models based on digital twins are less constrained by the space available for installing equipment within the vehicle. This allows for the configuration of higher computing power and more diverse model storage and processing devices, enabling rapid adjustment of the vehicle's interior temperature to the target temperature without compromising the performance or responsiveness of other devices controlled by the vehicle's local processor. Furthermore, compared to other cloud-based data models, cloud-based control strategy models based on digital twin technology can output more accurate data, improving the precision of vehicle status control.

[0061] In some embodiments of this application, the cloud control strategy model includes a neural network model, such as a convolutional neural network model. The convolutional neural network can be iteratively updated by feeding in data information, enabling the cloud control strategy model, after training, to output control commands that more closely approximate actual needs based on vehicle information, thereby improving the accuracy of the generated control commands.

[0062] In some embodiments of this application, the input data for the cloud-based control strategy model includes vehicle status data. This vehicle status data may include: vehicle tilt angle, environmental data, passenger compartment temperature, and vehicle speed.

[0063] In some embodiments of this application, the control strategy includes: a correspondence between target parameters and control parameters, and / or a combination of multiple control parameters with a corresponding relationship. Here, the target parameter refers to the desired intuitive parameter, while the control parameter is the parameter used to control the corresponding device to achieve the target parameter. For example, if the target parameter is the passenger compartment temperature, the control parameter could be the water pump power of the vehicle's air conditioning system, etc. One target parameter can correspond to multiple control parameters. For instance, when the control method of this application and the corresponding cloud-based control strategy model are applied to the passenger compartment cooling or heating process of vehicle thermal management, the water pump power, refrigerant flow rate in the pipeline, etc., can be used as control parameters. By calibrating these control parameters, the target parameter of the passenger compartment temperature can be controlled. In the vehicle control method provided in this application, control parameters are obtained through processing by the cloud-based control strategy model, thereby achieving control of the target parameter.

[0064] As a specific solution, the control commands include: thermal management control commands. These commands are used to control the vehicle's thermal management system. Furthermore, since cabin heating is a function that consumes a significant amount of vehicle electricity, more refined control is needed to achieve energy savings. Similarly, cabin heating has a noticeable impact on user comfort, thus requiring the application of personalized control strategies.

[0065] Based on this, the thermal management control commands include: passenger compartment heating control commands. These commands are used to control the vehicle's passenger compartment heating system. In a specific implementation, the passenger compartment heating system mentioned in this application can be components such as water pumps, electronic expansion valves, or throttle valves used to achieve passenger compartment cooling and heating functions, as well as electronic components such as vehicle controllers electrically connected to these components and controlling their operating status. That is, by outputting passenger compartment heating control commands to the electronic components, control is achieved over parameters such as water pump power, valve opening, and refrigerant flow rate in the pipeline.

[0066] Of course, the cloud-based control strategy model can also be used to implement other functions, such as driver assistance functions. This application only uses the implementation of cabin heating control as an example to illustrate the inventive concept of this application.

[0067] In some embodiments of this application, the vehicle control method further includes uploading control commands and corresponding vehicle state data to a cloud-based control strategy model. This process can be performed when the vehicle is not running, thereby facilitating upgrades to the cloud-based control strategy model.

[0068] In some embodiments of this application, the vehicle control method further includes: inputting uploaded vehicle status data into a cloud-based control strategy model to enable the cloud-based control strategy model to output corresponding control commands; performing entity calibration on the uploaded vehicle status data and / or the corresponding control commands; and updating the cloud-based control strategy model when the entity calibration meets the accuracy requirements. This process can be a specific implementation where uploading is performed when the vehicle is not running, thus helping to upgrade the cloud-based control strategy model.

[0069] In some embodiments of this application, the vehicle control method further includes: generating or outputting control commands for controlling preset functions of the vehicle based on a control strategy output by a local control strategy model; wherein the local control strategy model is stored in the vehicle's controller. Even without a network or user operation, the vehicle can still rely on the local control strategy model for control to meet the vehicle's usage needs in different network environments.

[0070] In some embodiments of this application, control commands for controlling preset vehicle functions are generated or output based on a control strategy output by a local control strategy model. This includes: when the user selects a local mode, collecting vehicle status data and sending it to the controller; outputting a control strategy based on the local control strategy model stored in the controller; and controlling the vehicle's preset functions according to the control parameters in the control strategy when the control strategy output by the local control strategy model differs from the currently executed control strategy. This solution specifically enables vehicle control using a local control strategy when the network environment is poor or the user does not choose to use a cloud-based control strategy.

[0071] In some embodiments of this application, the vehicle control method further includes: receiving a control strategy matched to the user indicated by the user tag data, based on the correspondence between user tag data and a cloud-based control strategy model. That is, a personalized cloud-based control strategy model can be trained based on tag data such as user ID or voiceprint, thereby obtaining a more personalized control strategy.

[0072] In some embodiments of this application, based on the correspondence between user tag data and a cloud-based control strategy model, a control strategy matching the user indicated by the user tag data is received. This includes: when the user selects manual input, generating a control strategy based on the user's input and uploading the control strategy to the cloud-based control strategy model; when the user selects voice input, generating a control strategy based on the user's voice input and uploading the control strategy to the cloud-based control strategy model; and providing the user with a user-recommended control strategy based on the user tag data identified or queried from the user's voiceprint data. Thus, after matching user tag data such as the user's voiceprint, specific control strategies can be recommended or provided to the user to improve the user experience.

[0073] In some embodiments of this application, the digital twin model includes: a one-dimensional simulation model of vehicle dynamics, a one-dimensional simulation model of the engine, a one-dimensional simulation model of the thermal management system, and a three-dimensional CFD simulation model of the passenger compartment.

[0074] In some embodiments of this application, the method for constructing a digital twin model includes: constructing a one-dimensional simulation model of vehicle dynamics based at least on the road conditions and vehicle speed; constructing a one-dimensional simulation model of the engine based at least on the engine speed, torque, and vehicle gear output by the one-dimensional simulation model of vehicle dynamics; constructing a one-dimensional simulation model of the thermal management system based at least on the heat output by the one-dimensional simulation model of the engine; and constructing a three-dimensional CFD simulation model of the passenger compartment based at least on the environmental conditions.

[0075] The following combination Figures 2 to 13 The specific implementation methods of this application will be described.

[0076] Reference Figures 2 to 6 The illustration shows a specific exemplary model building process for a digital twin model applied to vehicle heating control in this application embodiment. In this exemplary embodiment, the digital twin model for vehicle heating control is used for vehicle heating control, and the vehicle's heating system includes heated floor mats.

[0077] Reference Figure 8 As shown, the heated foot mat includes a foot mat installed inside the vehicle compartment. When a user sits inside the compartment, their feet can rest on the foot mat. Specifically, the foot mat can be a liquid heat exchange plate 1, on which a pipe is fixedly installed for the refrigerant or water, etc., to pass through. The pipe is equipped with corresponding valves to control the flow of the heat exchange medium in the pipe. Alternatively, the type of valve can be further selected to control the flow rate of the heat exchange medium in the pipe; for example, an expansion valve or a throttle valve can be used. By controlling the opening of these valves, the temperature and flow rate of the heat exchange medium can be adjusted. The following description uses a throttle valve 2 as an example to illustrate the inventive concept of this application.

[0078] When the heat exchange medium flows through the pipeline, it exchanges heat with the liquid heat exchange plate 1, thereby cooling or heating the liquid heat exchange plate 1 to achieve cooling or heating of the interior environment of the carriage and the users' feet. Depending on the number of seats in the carriage, multiple liquid heat exchange plates 1 can be installed to provide cooling or heating to users sitting in the driver's seat, front passenger seat, and rear seats respectively, as shown in the reference. Figure 8 and Figure 9 As shown, for different areas of the liquid heat exchanger plate 1, corresponding branch pipes 3 and corresponding valves can be set to control the temperature of each area of ​​the liquid heat exchanger plate separately. The digital twin model of this application for vehicle heating control can be set up to control the temperature of each area of ​​the liquid heat exchanger plate.

[0079] Reference Figure 9As shown, some vehicles can be equipped with a driver's side liquid heat exchanger plate, a passenger side liquid heat exchanger plate, a rear left liquid heat exchanger plate, a rear center liquid heat exchanger plate, and a rear right liquid heat exchanger plate, each with corresponding branch pipes 3 to deliver the heat exchange medium and exchange heat with each liquid heat exchanger plate 1. Each branch pipe 3 can be integrated into a single working medium pipe 4, which delivers the heat exchange medium to each branch pipe 3. This working medium pipe 4 is also connected to the vehicle's engine 5, water pump 6, and on-board heat exchangers 7 (such as condensers, evaporators, etc.) to form a circulation path for the heat exchange medium and to supply the heat exchange medium to the branch pipes 3. A three-way valve 8 can be installed on the working medium pipe 4 to control the flow of the heat exchange medium from the working medium pipe to at least some of the branch pipes.

[0080] Before using the digital twin model for vehicle heating control provided in this application to control vehicle heating, it is necessary to build the digital twin model. The model building process of the digital twin model for vehicle heating control provided in some embodiments of this application is mainly divided into five steps.

[0081] Step 1: Building a multiphysics co-simulation model: Refer to Figure 2 As shown, since this heating solution involves multiple functional systems on the vehicle, such as the power system, thermal management system and passenger compartment, it is necessary to establish virtual simulation models for the above systems, including a one-dimensional simulation model of the vehicle dynamics, a one-dimensional simulation model of the engine, a one-dimensional simulation model of the thermal management system, a three-dimensional CFD simulation model of the passenger compartment, and a model of the control strategy.

[0082] Among them, the one-dimensional simulation model of vehicle dynamics calculates the operating parameters of the power system based on road slope and vehicle speed, such as engine speed, torque and vehicle gear; the one-dimensional simulation model of the engine calculates the engine's heat output based on the engine speed, torque and vehicle gear information input from the former; the one-dimensional simulation model of the thermal management system calculates the input temperature and flow rate of the liquid heat plate 1 based on the engine's heat output, water pump speed, the opening of the three-way valve 8 and the opening of the throttle valve 2 at the branch pipe 3 of each liquid heat plate 1; the three-dimensional CFD simulation model of the passenger compartment calculates the temperature data of the user's feet at different times based on environmental conditions (such as the external temperature of the vehicle), the initial temperature of the passenger compartment and the output results of the one-dimensional simulation model of the thermal management system.

[0083] Step 2: Simulation Model Calibration: To improve the accuracy of model calculations, parameter calibration of the model is required before generating the digital twin model. Refer to... Figure 3As shown, based on the same operating conditions, the calculation results output by the virtual simulation model and the experimental results output by the physical entity are obtained respectively. By analyzing and calibrating the two results, the relevant parameter settings of the simulation model are adjusted and optimized until the accuracy meets the requirements. The simulation model to be calibrated here includes the simulation sub-models in step one, namely the one-dimensional simulation model of vehicle dynamics, the one-dimensional simulation model of the engine, the one-dimensional simulation model of the thermal management system, and the three-dimensional CFD simulation model of the passenger compartment.

[0084] Step 3: Generate training samples: Refer to Figure 4 As shown, multiple sets of simulation calculation conditions are created using the Design of Experiment (DOE) method, and the corresponding simulation calculation results are obtained based on each high-precision simulation sub-model calibrated in step 2.

[0085] Step 4: Model Training: Refer to Figure 5 As shown, while the simulation model achieves high accuracy in its calculations, its slow computation speed, stemming from its complex physical model and finite element / finite volume solution method, fails to meet the demands of rapid decision-making and deployment of control strategies in actual vehicle use. To address this issue, a "model reduction" approach can be adopted. Based on the computational samples generated in step three, a real-time simulation model capable of millisecond-level computational efficiency can be trained, meaning it can complete calculations and output results within milliseconds after receiving data input. The models requiring model reduction mainly include the simulation sub-models from step one: the one-dimensional simulation model of vehicle dynamics, the one-dimensional simulation model of the engine, the one-dimensional simulation model of thermal management, and the three-dimensional CFD simulation model of the passenger compartment. Model training can be achieved by separating training and validation samples according to a certain ratio of the computational samples.

[0086] Step 5: Model Deployment and Application: Referring to Figure 6, by setting the data input and output interfaces of each digital twin sub-model in Step 4, the connection between models is completed, and a complete digital twin model of the heating system is generated. Based on the data information collected by various sensors during the actual operation of the vehicle, the data is input into the digital twin model, which can calculate and output the parameters required to adjust the control strategy in a very short time. In a specific scheme, the data information collected by the sensors may include, for example, road slope, ambient temperature, environmental conditions, solar radiation intensity, as well as the initial temperature of the user's feet, the target heating temperature, and the target vehicle speed. After being input into the corresponding simulation sub-models in the digital twin model, the digital twin model outputs control parameters such as foot temperature, water pump speed, three-way valve opening, and throttle valve opening.

[0087] By following the steps above, a digital twin model can be built, which can then be used for vehicle heating control.

[0088] After completing the construction of the digital twin model applied to vehicle heating control, refer to Figure 7 As shown, the specific application process is as follows: The vehicle's current status is detected. If the vehicle is running, the system selects whether to use the twin drive mode for the heating system. The twin drive mode is usually set to on by default. It is only recommended to turn it off if the vehicle's network data transmission function is abnormal or the network signal is poor, resulting in limited data transmission rates. Alternatively, the user can be prompted to select whether to enable the twin drive mode through human-machine interaction methods, such as in-vehicle display devices and their accompanying touchscreens, or control buttons. If the twin drive mode is enabled, the vehicle's sensors first upload the collected data signals to a server in the cloud that stores the digital twin model. The digital twin model on the server then optimizes and calculates the best control strategy parameters and transmits them to the vehicle to adjust the strategy. The sensors detect vehicle data information at regular intervals. This interval can be pre-configured in the vehicle's electronic control system's control program or configured by the user in the vehicle's electronic control system. If the user keeps the vehicle heating function on, the next round of mode selection and strategy dynamic adjustment will proceed. Understandably, if the user's network connection is good, the twin drive mode can remain on without the user having to manually select it frequently.

[0089] If the user turns off the heating function, the heating will end.

[0090] If the twin drive mode is turned off, the vehicle-side sensors collect data information during vehicle operation and transmit it to the vehicle's own controller. The controller then outputs control strategy parameters based on its stored vehicle-side control strategy, which are used to control components of the vehicle's heating system, such as the water pump 6 and the throttle valve 2. The sensors detect vehicle data information at regular intervals. If the user keeps the vehicle's heating function on, the system will proceed with the next round of mode selection and dynamic strategy adjustment. The user can control the activation of the twin drive mode or, based on factors such as network status, choose whether to enable it.

[0091] If the vehicle is not currently running, the server-side digital twin model will automatically calibrate and improve its accuracy based on the most recent vehicle operating data before the engine was shut down, and upgrade the model version for use in the customer's subsequent digital twin drive mode. Specifically, during the most recent vehicle operation, the vehicle data signal transmitted to the cloud is input into the digital twin model as a sample for model parameter calibration. If the accuracy requirements are met after calibration, the model is updated to optimize and upgrade the digital twin model.

[0092] Reference Figure 8 and Figure 9As shown, the control method of this application can be used to control Figure 8 and Figure 9 The heat exchange system shown in this scheme uses an independent combination of "liquid heat plate 1 + valve 2" to regulate the temperature for different occupant positions. At the same time, the temperature control range can be further improved by controlling the opening of the three-way valve 8.

[0093] Reference Figure 10 As shown, in an optional implementation, in addition to controlling the liquid heat exchanger 1 in the heating system, control of the foot warmer can also be added. Figure 10 The difference between the proposed solution and the aforementioned technology lies in the need to control the flow rate of each heating core 12 that determines the foot-blowing temperature. This function can be achieved by adding corresponding control parameters to the thermal management system simulation model. At the same time, the structural design of the foot-blowing heating core 12 can be added to the 3D CFD simulation model of the passenger cabin, such as installing fans that blow air towards the feet in the passenger compartment. The flow rate of the heating core 12 is used as the target parameter, and the fan speed, which is the specific structure of the heating core 12, is used as the control parameter. The output of fan speed information is added to the 3D CFD simulation model of the passenger cabin. The rest of the construction process and ideas are the same as those described above.

[0094] Reference Figures 11 to 12 As shown, Figure 11 and Figure 12 The proposed solution, in addition to adding control over the temperature of the foot-blowing air, can also add control over different heating sources, such as... Figure 11 The scheme shown uses the heat generated by the PTC electric heater 9 during operation as an additional heating source. Figure 12 The schemes shown are respectively using PTC electric heater 9 and the heat from the engine exhaust waste heat recovery section as additional heating heat sources. At this time, valves such as three-way valve 10 and three-way valve 11 are also installed on the working fluid pipeline 4 to control the on / off supply of the heat exchange working fluid heated by PTC electric heater 9 or engine exhaust waste heat to the branch pipeline.

[0095] Reference Figure 12 As shown, Figure 12 The difference between the proposed solution and the basic solution described above lies in the additional control required for the heating power of the PTC electric heater 9, the opening degree of the three-way valve 10, and the opening degree of the three-way valve 11. This function can be achieved by adding corresponding control parameters to the one-dimensional simulation model of the thermal management system. The rest of the setup process and approach remain the same as described above. Furthermore, the electric heating control mode can either indirectly heat the feet by heating the heat exchange medium, or directly heat the vehicle floor by using an electric heating film laid on the floor supporting the user inside the cabin.

[0096] In some embodiments, refer to Figure 13 As shown, further voice recognition and user profiling of passengers can be used to learn different passengers' heating preferences and control methods, thereby achieving differentiated heating control modes for different users. The specific implementation process is as follows: When the vehicle is running, by recognizing the user's voice commands, a dedicated behavior database is established for that user. User operation data (manual or voice commands) is recorded and stored throughout the vehicle's operation and uploaded to the server. When the vehicle is not running, the server storing the digital twin model learns the user's behavioral habits based on the most recent user operation data, identifies key parameters in the control strategy such as the user's target temperature and airflow speed, and establishes corresponding control strategies (e.g., the relationship between the user's target temperature and airflow speed under different foot temperatures, in-vehicle air temperatures, and outside ambient temperatures), generating a strategy model based on the specific user. This allows the user to directly adopt a personalized heating strategy that suits their preferences when the heating mode is activated next time. In specific implementation plans, for example, when the heating mode is turned on again, user tags can be determined through user voiceprint recognition, and then the aforementioned user-specific strategy model can be recommended to the user through human-computer interaction, or when the twin-driven mode is turned on, the user-specific strategy model generated by the twin-driven model can be used automatically.

[0097] According to a second aspect of this application, embodiments of this application also provide a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the vehicle control method described above. This non-transitory computer-readable storage medium possesses all the beneficial effects of the vehicle control method described above, which will not be elaborated further here.

[0098] According to a third aspect of this application, embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the above-described vehicle control method and has all the beneficial effects of the above-described vehicle control method, which will not be elaborated further here.

[0099] According to a fourth aspect of this application, embodiments of this application also provide an electronic device, including: a memory and a processor, wherein a computer program is stored in the memory; the processor is configured to execute the computer program in the memory to implement the steps of the vehicle control method described above. This electronic device possesses all the beneficial effects of the vehicle control method described above, which will not be elaborated upon further herein.

[0100] Please refer to Figure 14The electronic device 600 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 into a random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the electronic device 600. The processing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0101] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic device 600 to communicate wirelessly or wiredly with other devices to exchange data. Although... Figure 14 An electronic device 600 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 14 Each box shown can represent a device or multiple devices as needed.

[0102] In particular, according to some embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 609, or installed from storage device 608, or installed from ROM 602. When the computer program is executed by processing device 601, it performs the functions defined above in the methods of some embodiments of this application.

[0103] It should be noted that the computer-readable medium in some embodiments of this application may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. The computer-readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof, and this application does not specifically limit its use. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0104] In some embodiments of this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In some embodiments of this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0105] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol, such as HTTP (Hypertext Transfer Protocol), and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (LANs), wide area networks (WANs), the internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0106] The aforementioned computer-readable medium may be included in the aforementioned electronic device, or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: generate or output control instructions for controlling preset functions of the vehicle, based on a control strategy output by a cloud-based control strategy model.

[0107] Computer program code for performing operations of some embodiments of this application can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0108] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function.

[0109] It should also be noted that in some alternative implementations, the functions marked in the box may occur in a different order than those marked in the attached figures.

[0110] For example, two consecutively represented blocks can actually be executed in substantially parallel order, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, as well as combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified functions or operations, or using a combination of dedicated hardware and computer instructions.

[0111] The units described in some embodiments of this application can be implemented in software or in hardware.

[0112] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0113] According to a fourth aspect of this application, embodiments of this application also provide a vehicle including the aforementioned electronic device, which can be used to execute the aforementioned vehicle control method. This vehicle possesses all the beneficial effects of the aforementioned electronic device, which will not be elaborated upon here.

[0114] The vehicle may be a gasoline-powered vehicle, a plug-in hybrid electric vehicle, or a new energy vehicle, etc., and this application does not make any specific restrictions.

[0115] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0116] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0117] The embodiments, implementation methods, and related technical features of this application can be combined and substituted for each other without conflict.

[0118] The above are merely preferred embodiments of this application and are not intended to limit this application in any way. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of this application without departing from the scope of the technical solution of this application shall still fall within the scope of the technical solution of this application.

Claims

1. A vehicle control method, comprising: generating or outputting a control instruction for controlling a preset function of a vehicle according to a control strategy output by a cloud control strategy model; wherein the cloud control strategy model is a computer model constructed based on digital twinning. 2.The vehicle control method of claim 1, wherein: the cloud control strategy model comprises a neural network model. 3.The vehicle control method of claim 1, wherein: input data of the cloud control strategy model comprises vehicle state data. 4.The vehicle control method of claim 1, wherein: the control strategy comprises a corresponding relationship between a target parameter and a control parameter and / or a combination of a plurality of control parameters having a corresponding relationship. 5.The vehicle control method of claim 1, wherein: the control instruction comprises: a thermal management control instruction for controlling a thermal management system of the vehicle. 6.The vehicle control method of claim 5, wherein: the thermal management control instruction comprises: a cabin heating control instruction for controlling a cabin heating device of the vehicle. 7.The vehicle control method of any one of claims 1 to 6, wherein: the vehicle control method further comprises: uploading the control instruction and corresponding vehicle state data to the cloud control strategy model. 8.The vehicle control method of claim 7, wherein: the vehicle control method further comprises: inputting the uploaded vehicle state data to the cloud control strategy model to cause the cloud control strategy model to output a corresponding control instruction; performing physical calibration on the uploaded vehicle state data and / or the corresponding control instruction; updating the cloud control strategy model when the physical calibration meets accuracy requirements. 9.The vehicle control method of claim 1, wherein: the vehicle control method further comprises: generating or outputting a control instruction for controlling a preset function of a vehicle according to a control strategy output by a local control strategy model; wherein the local control strategy model is stored in a controller of the vehicle.

10. The vehicle control method according to claim 9, wherein: the generating or outputting a control instruction for controlling a preset function of a vehicle according to a control strategy output by a local control strategy model comprises: when a user selects a local mode, collecting vehicle state data to the controller; outputting a control strategy according to the local control strategy model stored in the controller; controlling the preset function of the vehicle according to a control parameter in the control strategy when the control strategy output by the local control strategy model is different from a currently executed control strategy. 11.The vehicle control method of any one of claims 1 to 6, wherein: the vehicle control method further comprises: receiving a control strategy matching a user pointed by user label data according to a corresponding relationship between the user label data and the cloud control strategy model.

12. The vehicle control method according to claim 11, wherein: the receiving a control strategy matching a user pointed by user label data according to a corresponding relationship between the user label data and the cloud control strategy model comprises: When the user selects a manual input instruction, a control strategy is generated according to the user input instruction and uploaded to a cloud control strategy model; When the user selects a voice input instruction, a control strategy is generated according to the user voice input instruction and uploaded to a cloud control strategy model; According to the user tag data identified or queried by the voiceprint data of the user, a user recommended control strategy based on the user tag data is provided to the user.

13. The vehicle control method according to any one of claims 1 to 6, characterized in that: The digital twin model comprises: A vehicle dynamics one-dimensional simulation model, an engine one-dimensional simulation model, a thermal management system one-dimensional simulation model, and a passenger cabin three-dimensional CFD simulation model.

14. The vehicle control method according to claim 13, characterized in that: The construction method of the digital twin model comprises: Constructing a vehicle dynamics one-dimensional simulation model according to at least the road conditions and vehicle speed of the vehicle; Constructing an engine one-dimensional simulation model according to at least the engine speed, torque, and vehicle operating gear of the vehicle output by the vehicle dynamics one-dimensional simulation model; Constructing a thermal management system one-dimensional simulation model according to at least the heat generation power output by the engine one-dimensional simulation model; Constructing a passenger cabin three-dimensional CFD simulation model according to at least the environmental conditions.

15. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: The computer program is executed by a processor to implement the steps of the vehicle control method according to any one of claims 1 to 14.

16. A computer program product comprising a computer program, characterized in that: The computer program is executed by a processor to implement the steps of the vehicle control method according to any one of claims 1 to 14.

17. An electronic device, characterized in that: The electronic device comprises: A memory storing a computer program; A processor for executing the computer program in the memory to implement the steps of the method according to any one of claims 1 to 14.

18. A vehicle, characterized in that: The vehicle comprises the electronic device according to claim 17.

Images