WO2023050850A1 - 用于控制驻车空调的方法、装置及驻车空调 - Google Patents

用于控制驻车空调的方法、装置及驻车空调 Download PDF

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Publication number
WO2023050850A1
WO2023050850A1 PCT/CN2022/096139 CN2022096139W WO2023050850A1 WO 2023050850 A1 WO2023050850 A1 WO 2023050850A1 CN 2022096139 W CN2022096139 W CN 2022096139W WO 2023050850 A1 WO2023050850 A1 WO 2023050850A1
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WIPO (PCT)
Prior art keywords
air conditioner
parking air
information
vehicle
prediction model
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PCT/CN2022/096139
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English (en)
French (fr)
Inventor
郭继宾
李艳春
李恒元
路炎
封荣杰
Original Assignee
青岛海尔空调器有限总公司
青岛海尔空调电子有限公司
海尔智家股份有限公司
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Application filed by 青岛海尔空调器有限总公司, 青岛海尔空调电子有限公司, 海尔智家股份有限公司 filed Critical 青岛海尔空调器有限总公司
Publication of WO2023050850A1 publication Critical patent/WO2023050850A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60H—ARRANGEMENTS OF HEATING, COOLING, VENTILATING OR OTHER AIR-TREATING DEVICES SPECIALLY ADAPTED FOR PASSENGER OR GOODS SPACES OF VEHICLES
    • B60H1/00—Heating, cooling or ventilating [HVAC] devices
    • B60H1/00642—Control systems or circuits; Control members or indication devices for heating, cooling or ventilating devices
    • B60H1/00735—Control systems or circuits characterised by their input, i.e. by the detection, measurement or calculation of particular conditions, e.g. signal treatment, dynamic models
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60H—ARRANGEMENTS OF HEATING, COOLING, VENTILATING OR OTHER AIR-TREATING DEVICES SPECIALLY ADAPTED FOR PASSENGER OR GOODS SPACES OF VEHICLES
    • B60H1/00—Heating, cooling or ventilating [HVAC] devices
    • B60H1/00357—Air-conditioning arrangements specially adapted for particular vehicles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60H—ARRANGEMENTS OF HEATING, COOLING, VENTILATING OR OTHER AIR-TREATING DEVICES SPECIALLY ADAPTED FOR PASSENGER OR GOODS SPACES OF VEHICLES
    • B60H1/00—Heating, cooling or ventilating [HVAC] devices
    • B60H1/00642—Control systems or circuits; Control members or indication devices for heating, cooling or ventilating devices
    • B60H1/00735—Control systems or circuits characterised by their input, i.e. by the detection, measurement or calculation of particular conditions, e.g. signal treatment, dynamic models
    • B60H1/00764—Control systems or circuits characterised by their input, i.e. by the detection, measurement or calculation of particular conditions, e.g. signal treatment, dynamic models the input being a vehicle driving condition, e.g. speed
    • B60H1/00771—Control systems or circuits characterised by their input, i.e. by the detection, measurement or calculation of particular conditions, e.g. signal treatment, dynamic models the input being a vehicle driving condition, e.g. speed the input being a vehicle position or surrounding, e.g. GPS-based position or tunnel

Definitions

  • the present application relates to the technical field of equipment control, for example, to a method, device and air conditioner for controlling a parking air conditioner.
  • the built-in automotive air conditioner in the logistics transport truck generally requires the engine to run before it can be used. This method will increase the load on the engine, and the identification will also lead to an increase in fuel consumption. For this reason, most car transport drivers will choose to install an additional parking air conditioner.
  • an air-conditioning control scheme which includes: acquiring the urban area where the vehicle equipment travels during driving; acquiring the weather temperature of the urban area where the vehicle equipment travels; Calculate the difference between the fixed temperature and the weather temperature of the urban area where the vehicle equipment travels, and adjust the target temperature of the air conditioner in combination with the result of the difference calculation. It can be seen that the prior art can only realize the adjustment of the target operation information of the air conditioner through the difference calculation results of multiple parameters, and the degree of intelligence of the air conditioner is not high.
  • Embodiments of the present disclosure provide a method and device for controlling a parking air conditioner, and the parking air conditioner, so as to provide a more intelligent control solution for the parking air conditioner.
  • the method includes: obtaining relevant information of the vehicle, the relevant information includes weather information at the location of the vehicle and time information at the location of the vehicle; inputting the weather information and time information into the A predictive model of operating information; control the parking air conditioner to operate under the target operating information output by the predictive model.
  • the method includes: obtaining samples for training the predictive model, and randomly dividing the samples into a training set and a test set, the samples including setting habits for adjusting the operating information of the parking air conditioner under different relevant information Information; Input different relevant information in the training set into the initial prediction model, and use the setting habit information corresponding to the different relevant information in the training set as the output of the initial prediction model to train the initial prediction model; verify the initial prediction model after training according to the test set The prediction model is used to obtain the verification result; if the verification result indicates that the prediction is accurate, the prediction model is obtained.
  • the method includes: if the prediction model is a decision tree model, determining the depth of the decision tree; and optimizing the decision tree model according to the depth of the decision tree.
  • the method includes: determining a target parking air conditioner when there are multiple parking air conditioners associated with the terminal device; controlling the target parking air conditioner to operate under the target operating information output by the prediction model.
  • the method includes: determining the parking air conditioner connected to the terminal device by default as the target parking air conditioner; or, among multiple parking air conditioners, determining the parking air conditioner that has received the connection request as the target parking air conditioner. car air conditioner.
  • the method includes: obtaining the current moving distance of the vehicle; when the moving distance is greater than a preset distance, determining the adjusted target operating information, and controlling the parking air conditioner to operate under the adjusted target operating information run.
  • the method includes: obtaining the interval time for the vehicle to move to the current location; if the interval time is greater than the preset time length, determining the adjusted target operation information, and controlling the parking air conditioner to set the adjusted target Run under the running information.
  • the method includes: inputting the weather information of the current location of the vehicle and the current time information into the prediction model; determining the target operation information output by the prediction model as the adjusted target operation information.
  • the device includes: a processor and a memory storing program instructions, and the processor is configured to execute the aforementioned method for controlling the parking air conditioner when executing the program instructions.
  • the parking air conditioner includes: the aforementioned device for controlling the parking air conditioner.
  • the prediction model for adjusting the operation information of the parking air conditioner By inputting the obtained weather information of the location of the vehicle and the time information of the vehicle at the location into the prediction model for adjusting the operation information of the parking air conditioner, it is possible to predict the target operation information of the parking air conditioner and control the parking air conditioner Run under the target running information output by the predictive model.
  • the target operating information of the parking air conditioner is reasonably predicted by effectively combining the weather information of the location of the parking air conditioner and the time information of the parking air conditioner at this location, which improves the low intelligence of the existing parking air conditioner control method.
  • the problem of improving the intelligent level of parking air conditioning control is described inputting the obtained weather information of the location of the vehicle and the time information of the vehicle at the location into the prediction model for adjusting the operation information of the parking air conditioner.
  • Fig. 1 is a schematic diagram of a method for controlling a parking air conditioner provided by an embodiment of the present disclosure
  • FIG. 2 is a schematic diagram of a method for obtaining a prediction model provided by an embodiment of the present disclosure
  • Fig. 3 is a schematic diagram of another method for controlling a parking air conditioner provided by an embodiment of the present disclosure
  • Fig. 4 is a schematic diagram of another method for controlling a parking air conditioner provided by an embodiment of the present disclosure
  • Fig. 5 is a schematic diagram of another method for controlling a parking air conditioner provided by an embodiment of the present disclosure
  • Fig. 6 is a schematic diagram of an apparatus for controlling a parking air conditioner provided by an embodiment of the present disclosure.
  • A/B means: A or B.
  • a and/or B means: A or B, or, A and B, these three relationships.
  • correspondence may refer to an association relationship or a binding relationship, and the correspondence between A and B means that there is an association relationship or a binding relationship between A and B.
  • the terminal device refers to an electronic device with a wireless connection function.
  • the terminal device can be connected to the parking air conditioner by connecting to the Internet, or directly communicate with the parking air conditioner through bluetooth, wifi, etc.
  • the terminal device is, for example, a mobile device, a computer, etc., or any combination thereof.
  • the mobile device may include, for example, a mobile phone, a smart home device, a wearable device, a smart mobile device, a virtual reality device, etc., or any combination thereof, wherein the wearable device includes, for example, a smart watch, a smart bracelet, a pedometer, and the like.
  • Fig. 1 is a schematic diagram of a method for controlling a parking air conditioner provided by an embodiment of the present disclosure; in combination with what is shown in Fig. 1 , an embodiment of the present disclosure provides a method for controlling a parking air conditioner, including:
  • the terminal device obtains relevant information of the vehicle, and the relevant information includes weather information at the location of the vehicle and time information at the location of the vehicle.
  • the terminal device inputs weather information and time information into a prediction model for adjusting the operation information of the parking air conditioner.
  • the terminal device controls the parking air conditioner to operate under the target operating information output by the predictive model.
  • the terminal device can obtain information about the vehicle.
  • the relevant information of the vehicle may be relevant information during the driving of the vehicle.
  • the relevant information of the vehicle includes weather information of the location of the vehicle and time information of the vehicle at the location.
  • the weather information of the location of the vehicle may include temperature, humidity, wind speed, wind direction, cloudy, rainy or cloudy, etc. of the location of the vehicle.
  • the time information of the vehicle at the position may be the date information of the vehicle at the position, or the time information of the vehicle at the position.
  • the terminal device can obtain the location of the vehicle through its configured positioning device. For example, if the terminal device is a mobile phone, the location of the vehicle can be obtained through its configured positioning chip.
  • the time information of the vehicle at the location is determined through the timing device configured on the terminal device.
  • the weather information of the vehicle's location is obtained through the weather platform of the cloud server associated with the terminal device. In this way, the weather information and time information of the location of the vehicle can be accurately acquired in real time.
  • the terminal device After the terminal device obtains the weather information and time information of the vehicle location, it can be input into the prediction model used to adjust the operating information of the parking air conditioner.
  • the prediction model is used to predict more reasonable operating information of the parking air conditioner.
  • the prediction model may be a standardized model, and may also be a model constructed based on the operating information of the parking air conditioner in the area and deployed on the terminal device.
  • the parking air conditioner connected to the terminal device can be controlled to operate under the target operating information.
  • the target operation information of the parking air conditioner includes the target mode, target set temperature, target set wind speed, target wind direction, etc. of the parking air conditioner. Introducing the machine learning algorithm into the intelligent control logic of the parking air conditioner will help the parking air conditioner to operate accurately and automatically under the predicted target operating information, freeing the user from the complicated operation method of manually setting the operating information of the parking air conditioner. Improved user experience.
  • the method for controlling the parking air conditioner provided by the embodiments of the present disclosure, by inputting the obtained weather information at the location of the vehicle and the time information of the vehicle at the location into the prediction model for adjusting the operation information of the parking air conditioner, it is possible
  • the target operating information of the parking air conditioner is predicted, and the parking air conditioner is controlled to operate under the target operating information output by the prediction model.
  • the target operating information of the parking air conditioner is reasonably predicted by effectively combining the weather information of the location of the parking air conditioner and the time information of the parking air conditioner at this location, which improves the low intelligence of the existing parking air conditioner control method.
  • the problem of improving the intelligent level of parking air conditioning control is described by inputting the obtained weather information at the location of the vehicle and the time information of the vehicle at the location into the prediction model for adjusting the operation information of the parking air conditioner.
  • Fig. 2 is a schematic diagram of a method for obtaining a prediction model provided by an embodiment of the present disclosure; in combination with what is shown in Fig. 2, optionally, the prediction model is obtained in the following manner, including:
  • the terminal device obtains samples for training the predictive model, and randomly divides the samples into a training set and a test set.
  • the samples include setting habit information for adjusting the operation information of the parking air conditioner under different relevant information.
  • the terminal device inputs different relevant information in the training set to the initial prediction model, and uses setting habit information corresponding to the different relevant information in the training set as an output of the initial prediction model, so as to train the initial prediction model.
  • the terminal device verifies the trained initial prediction model according to the test set, and obtains a verification result.
  • the terminal device obtains the prediction model when the verification result indicates that the prediction is accurate.
  • the initial prediction model may be a prediction model determined according to a machine learning algorithm, specifically an artificial neural network algorithm, a random forest algorithm, a decision tree algorithm, a support vector machine algorithm, and the like.
  • a machine learning algorithm specifically an artificial neural network algorithm, a random forest algorithm, a decision tree algorithm, a support vector machine algorithm, and the like.
  • SVM Small Vector Machine, Support Vector Machine
  • the sample is randomly divided into a training set and a test set, and different relevant information in the training set is used as the training input, and the setting habit information corresponding to the different related information is used as the training output.
  • the samples can also be randomly divided into training set, test set and validation set. In one example, 60% may be used as a training set, 20% as a test set, and 20% as a validation set.
  • different related information can be embodied as weather information corresponding to multiple vehicles at the same location under different time information.
  • the same location refers to a location with the same longitude and latitude.
  • the setting habit information used to adjust the operation information of the parking air conditioner under different related information may specifically include the customary setting operating temperature, setting operation mode, setting wind speed, and setting wind swing mode of multiple parking air conditioners.
  • the setting habit information may be obtained through various implementation manners, which are illustrated below with examples.
  • the operating information of the parking air conditioner settings under the different relevant information of multiple parking air conditioners at the same location can be collected respectively, so as to determine the setting habit information according to the collected data.
  • the preset duration may be 30 days to 90 days. It is preferably 90 days, so that the complete parking air conditioner operating information can be collected quarterly as much as possible, so as to accurately obtain the setting habit information according to the season.
  • the operating information of all the parking air conditioners at the same location under different related information can be extracted from the big data module of the associated cloud server by the terminal device, so as to extract The prestored data determine the setting habit information.
  • the effective acquisition of setting habit information can be realized in various ways.
  • the invalid data can include the setting habit information in the shutdown state, and can also include the setting habit information whose duration is within the preset time length.
  • the preset time length can be 1 minute.
  • the terminal device determines the depth of the decision tree; the terminal device may optimize the decision tree model according to the depth of the decision tree.
  • the prediction model is a decision tree model determined according to a decision tree algorithm
  • the terminal device needs to determine the depth of the decision tree. It is understandable that if the depth of the tree is set too high, the model will easily deviate from the real sinusoidal curve and easily form an over-fitting situation.
  • the decision tree model needs to be further optimized to effectively control the complexity of the decision tree model.
  • the maximum depth of the tree can be preset as 3, which can effectively optimize the decision tree model, so that the optimized decision tree model has higher prediction accuracy, thereby improving the intelligence of the air conditioner.
  • Fig. 3 is a schematic diagram of another method for controlling the parking air conditioner provided by an embodiment of the present disclosure; combined with what is shown in Fig. 3 , optionally, in S13, the terminal device controls the parking air conditioner to operate under the target operation information output by the prediction model, include:
  • the terminal device determines a target parking air conditioner.
  • the terminal device controls the target parking air conditioner to operate under the target operating information output by the predictive model.
  • the terminal device if the terminal device is associated with multiple parking air conditioners, it is necessary to determine the target parking air conditioner to be controlled among the multiple parking air conditioners. In order to realize the precise determination of the object to be controlled.
  • the terminal device activates the wireless connection function, and if there are multiple parking air conditioners in its scanning area, it is determined that the terminal device is associated with multiple parking air conditioners.
  • the wireless connection may be a Bluetooth connection or a WIFI connection.
  • the terminal device controls the target parking air conditioner to operate under the target operating information output by the predictive model. With this scheme, the target parking air conditioner is effectively controlled to operate under the target operation information output by the prediction model, and the intelligence level of the parking air conditioner control is improved.
  • the terminal device determines the target parking air conditioner, including:
  • the terminal device determines its default connected parking air conditioner as the target parking air conditioner; or,
  • the terminal device determines the parking air conditioner that has received the connection request as the target parking air conditioner.
  • the terminal device may determine the parking air conditioner that has been connected or is connected by default as the target parking air conditioner. In another case, if there is no parking air conditioner that has been connected to the terminal device among the multiple parking air conditioners, when the parking air conditioner receives a connection request manually input by the driver, it will receive the connection request. The air conditioner is determined as the target parking air conditioner.
  • Fig. 4 is a schematic diagram of another method for controlling a parking air conditioner provided by an embodiment of the present disclosure; in combination with what is shown in Fig. 4 , an embodiment of the present disclosure provides a method for controlling a parking air conditioner, including:
  • the terminal device obtains relevant information of the vehicle, and the relevant information includes weather information at the location of the vehicle and time information at the location of the vehicle.
  • the terminal device inputs the weather information and time information into the prediction model used to adjust the parking air conditioner operation information.
  • the terminal device controls the parking air conditioner to operate under the target operation information output by the predictive model.
  • the terminal device obtains the current moving distance of the vehicle.
  • the terminal device determines the adjusted target operating information, and controls the parking air conditioner to operate under the adjusted target operating information.
  • the preset value can be set in the terminal device in advance.
  • the preset distance may be determined according to the adjustment requirements of the driver's parking air conditioner operating information.
  • the preset distance may be 10 kilometers.
  • the current moving distance of the vehicle may be determined during the running of the vehicle, where the moving distance may be the distance between the initial vehicle location and the current vehicle location.
  • the initial vehicle location is the location of the vehicle when the vehicle-related information is obtained.
  • the adjusted target operating information of the parking air conditioner may be determined.
  • the moving distance of the vehicle exceeds the preset distance, combined with the adjusted target operating information predicted by the prediction model, the current target operating information of the parking air conditioner can be adjusted in real time, which improves the control process of the parking air conditioner. intelligence level.
  • Fig. 5 is a schematic diagram of another method for controlling a parking air conditioner provided by an embodiment of the present disclosure; in combination with what is shown in Fig. 5 , an embodiment of the present disclosure provides a method for controlling a parking air conditioner, including:
  • the terminal device obtains relevant information of the vehicle, and the relevant information includes weather information at the location of the vehicle and time information at the location of the vehicle.
  • the terminal device inputs weather information and time information into a prediction model for adjusting the operation information of the parking air conditioner.
  • the terminal device controls the parking air conditioner to operate under the target operation information output by the predictive model.
  • the terminal device obtains the interval time between the vehicle moving to the current position.
  • the terminal device determines the adjusted target operation information, and controls the parking air conditioner to operate under the adjusted target operation information.
  • the preset value can be set in the terminal device in advance.
  • Set duration can be determined according to the adjustment requirements of the driver's parking air-conditioning operation information.
  • the preset duration may be 30 minutes.
  • the interval time between the vehicle moving to the current position can be determined during the vehicle driving, and here, the interval time between the vehicle moving to the current position can be obtained through the timing device of the terminal device.
  • the adjusted target operating information of the parking air conditioner can be determined when the interval time between the vehicle moving to the current location is longer than the preset time period.
  • the current target operating information of the parking air conditioner can be adjusted in real time, improving the parking efficiency.
  • the intelligence level of the air conditioning control process is
  • the terminal device determines the adjusted target operation information, including:
  • the terminal device inputs the weather information of the vehicle's current location and the current time information into the prediction model; the terminal device determines the target operation information output by the prediction model as the adjusted target operation information.
  • the weather information of the current location of the vehicle and the current time information can be obtained through the terminal device.
  • the specific acquisition method is as above, and details are not repeated here.
  • the weather information of the current location of the vehicle acquired by the terminal device and the current time information can be input into the prediction model of the terminal device, and the target operation information output by the prediction model is determined as the adjusted target operation information.
  • the operating information of the parking air conditioner can be predicted again in combination with the current relevant information of the vehicle, providing an accurate data basis for the adjustment of the target operating information.
  • the terminal device may be a driver's mobile phone.
  • the driver's mobile phone may be used to acquire the weather information of the location of the driving vehicle and the time information of the vehicle at the location. And input the acquired weather information and time information into the prediction model for adjusting the operation information of the parking air conditioner, and obtain the target operation information of the parking air conditioner output by the prediction model.
  • the target parking air conditioner can be determined and connected through the mobile phone, and the connected target parking air conditioner can be controlled to operate under the target operation information output by the predictive model.
  • the target operating information of the parking air conditioner is reasonably predicted by effectively combining the weather information of the location of the parking air conditioner and the time information of the parking air conditioner at this location, which improves the low intelligence of the existing parking air conditioner control method.
  • the problem of improving the intelligent level of parking air conditioning control is reasonably predicted by effectively combining the weather information of the location of the parking air conditioner and the time information of the parking air conditioner at this location, which improves the low intelligence of the existing parking air conditioner control method.
  • An embodiment of the present disclosure provides a device for controlling a parking air conditioner, including an acquisition module, an input module and a control module.
  • the obtaining module is configured to obtain relevant information of the vehicle, and the relevant information includes weather information at the location of the vehicle and time information at the location of the vehicle;
  • the input module is configured to input the weather information and time information into the system for adjusting the parking air conditioner operation information A predictive model;
  • the control module is configured to control the parking air conditioner to operate under the target operating information output by the predictive model.
  • the device for controlling the parking air conditioner provided by the embodiment of the present disclosure, by inputting the obtained weather information of the location of the vehicle and the time information of the vehicle at the location into the prediction model used to adjust the operation information of the parking air conditioner, it can The target operating information of the parking air conditioner is predicted, and the parking air conditioner is controlled to operate under the target operating information output by the prediction model.
  • the target operating information of the parking air conditioner is reasonably predicted by effectively combining the weather information of the location of the parking air conditioner and the time information of the parking air conditioner at this location, which improves the low intelligence of the existing parking air conditioner control method.
  • the problem of improving the intelligent level of parking air conditioning control is described by inputting the obtained weather information of the location of the vehicle and the time information of the vehicle at the location into the prediction model used to adjust the operation information of the parking air conditioner.
  • FIG. 6 is a schematic diagram of a device for controlling a parking air conditioner provided by an embodiment of the present disclosure.
  • a device for controlling a parking air conditioner including a processor (processor) 100 and memory (memory) 101 .
  • the device may also include a communication interface (Communication Interface) 102 and a bus 103.
  • Communication interface 102 may be used for information transfer.
  • the processor 100 can call the logic instructions in the memory 101 to execute the method for controlling the parking air conditioner in the above embodiments.
  • the above logic instructions in the memory 101 may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as an independent product.
  • the memory 101 can be used to store software programs and computer-executable programs, such as program instructions/modules corresponding to the methods in the embodiments of the present disclosure.
  • the processor 100 executes the program instructions/modules stored in the memory 101 to execute functional applications and data processing, that is, to realize the method for controlling the parking air conditioner in the above-mentioned embodiments.
  • the memory 101 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application program required by at least one function; the data storage area may store data created according to the use of the terminal device, and the like.
  • the memory 101 may include a high-speed random access memory, and may also include a non-volatile memory.
  • An embodiment of the present disclosure provides a parking air conditioner, including the above-mentioned device for controlling the parking air conditioner.
  • An embodiment of the present disclosure provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are configured to execute the above-mentioned method for controlling a parking air conditioner.
  • An embodiment of the present disclosure provides a computer program product, the computer program product includes a computer program stored on a computer-readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer, the The computer executes the above method for controlling the parking air conditioner.
  • the above-mentioned computer-readable storage medium may be a transitory computer-readable storage medium, or a non-transitory computer-readable storage medium.
  • the technical solutions of the embodiments of the present disclosure can be embodied in the form of software products, which are stored in a storage medium and include one or more instructions to make a computer device (which can be a personal computer, a server, or a network equipment, etc.) to perform all or part of the steps of the method described in the embodiments of the present disclosure.
  • the aforementioned storage medium can be a non-transitory storage medium, including: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disc, etc.
  • the term “and/or” as used in this application is meant to include any and all possible combinations of one or more of the associated listed ones.
  • the term “comprise” and its variants “comprises” and/or comprising (comprising) etc. refer to stated features, integers, steps, operations, elements, and/or The presence of a component does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groupings of these.
  • an element defined by the statement “comprising a " does not exclude the presence of additional identical elements in the process, method or apparatus comprising said element.
  • the disclosed methods and products can be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units may only be a logical function division.
  • multiple units or components may be combined Or it can be integrated into another system, or some features can be ignored, or not implemented.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.
  • each functional unit in the embodiments of the present disclosure may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.
  • each block in a flowchart or block diagram may represent a module, program segment, or part of code that includes one or more Executable instructions.
  • the functions noted in the block may occur out of the order noted in the figures.
  • two blocks in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved.
  • the operations or steps corresponding to different blocks may also occur in a different order than that disclosed in the description, and sometimes there is no specific agreement between different operations or steps.
  • each block in the block diagrams and/or flowcharts, and combinations of blocks in the block diagrams and/or flowcharts can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by dedicated hardware implemented in combination with computer instructions.

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  • Physics & Mathematics (AREA)
  • Thermal Sciences (AREA)
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  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Air-Conditioning For Vehicles (AREA)
  • Air Conditioning Control Device (AREA)

Abstract

一种用于控制驻车空调的方法，包括：获得车辆的相关信息，相关信息包括车辆所在位置的天气信息及车辆所在位置的时间信息；将天气信息及时间信息输入至用于调节驻车空调运行信息的预测模型；控制驻车空调在预测模型输出的目标运行信息下运行。以此方案，有效地结合驻车空调所在位置的天气信息及驻车空调在该位置的时间信息对驻车空调的目标运行信息进行合理预测，改善了现有驻车空调控制方式智能性较低的问题，提高了驻车空调控制的智能化水平。还包括一种用于控制驻车空调的装置及一种驻车空调。

Description

用于控制驻车空调的方法、装置及驻车空调
本申请基于申请号为202111154682.8、申请日为2021年09月29日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本申请涉及设备控制技术领域，例如涉及一种用于控制驻车空调的方法、装置及空调。
背景技术
目前，物流运输卡车中自带的汽车空调一般是需要汽车发动机运行才能使用的，这种方式将导致发动机负荷增加，识别也会导致油耗增加。为此，大多数的汽车运输司机会选择另外安装一台驻车空调。
然而，现有的驻车空调功能太过单一，不能满足现有卡车司机的使用需求。目前，提供一种空调的控制方案，包括：在车辆设备行驶的过程中，获取车辆设备行驶到的城市区域；获取行驶到的城市区域的天气温度；将车辆设备的内部温度，空调当前的设定温度和车辆设备行驶到的城市区域的天气温度进行差值运算，并结合差值运算结果对空调的目标温度进行调整。由此可见，现有技术仅能通过多个参数的差值运算结果实现空调目标运行信息的调整，空调的智能化程度不高。
发明内容
为了对披露的实施例的一些方面有基本的理解，下面给出了简单的概括。所述概括不是泛泛评述，也不是要确定关键/重要组成元素或描绘这些实施例的保护范围，而是作为后面的详细说明的序言。
本公开实施例提供了一种用于控制驻车空调的方法、装置及驻车空调，以提供一种更加智能的驻车空调的控制方案。
在一些实施例中，所述方法包括：获得车辆的相关信息，相关信息包括车辆所在位置的天气信息及车辆在所述位置的时间信息；将天气信息及时间信息输入至用于调节驻车空调运行信息的预测模型；控制驻车空调在预测模型输出的目标运行信息下运行。
在一些实施例中，所述方法包括：获得用于训练预测模型的样本，并将样本随机分为训练集和测试集，样本包括不同相关信息下用于调节驻车空调运行信息的设定习惯信息； 将训练集中不同相关信息输入至初始预测模型，并将训练集中不同相关信息对应的设定习惯信息作为初始预测模型的输出，以对初始预测模型进行训练；根据测试集验证训练后的初始预测模型，得到验证结果；在验证结果表示预测准确的情况下，得到预测模型。
在一些实施例中，所述方法包括：在预测模型为决策树模型的情况下，确定决策树的深度；根据决策树的深度，优化决策树模型。
在一些实施例中，所述方法包括：在终端设备关联有多台驻车空调的情况下，确定目标驻车空调；控制目标驻车空调在预测模型输出的目标运行信息下运行。
在一些实施例中，所述方法包括：将终端设备默认连接的驻车空调确定为目标驻车空调；或，在多台驻车空调中，将接收到连接请求的驻车空调确定为目标驻车空调。
在一些实施例中，所述方法包括：获取车辆当前的移动距离；在移动距离大于预设距离的情况下，确定调整后的目标运行信息，并控制驻车空调在调整后的目标运行信息下运行。
在一些实施例中，所述方法包括：获取车辆移动至当前位置的间隔时长；在间隔时长大于预设时长的情况下，确定调整后的目标运行信息，并控制驻车空调在调整后的目标运行信息下运行。
在一些实施例中，所述方法包括：将车辆当前位置的天气信息及当前的时间信息输入至预测模型；将预测模型输出的目标运行信息，确定为调整后的目标运行信息。
在一些实施例中，所述装置包括：处理器和存储有程序指令的存储器，处理器被配置为在运行程序指令时，执行前述的用于控制驻车空调的方法。
在一些实施例中，所述驻车空调包括：前述的用于控制驻车空调的装置。
本公开实施例提供的用于控制驻车空调的方法、装置及驻车空调，可以实现以下技术效果：
通过将已获得的车辆所在位置的天气信息和车辆在该位置的时间信息输入至用于调节驻车空调运行信息的预测模型，能够对驻车空调的目标运行信息进行预测，并控制驻车空调在预测模型输出的目标运行信息下运行。以此方案，有效地结合驻车空调所在位置的天气信息及驻车空调在该位置的时间信息对驻车空调的目标运行信息进行合理预测，改善了现有驻车空调控制方式智能性较低的问题，提高了驻车空调控制的智能化水平。
以上的总体描述和下文中的描述仅是示例性和解释性的，不用于限制本申请。
附图说明
一个或多个实施例通过与之对应的附图进行示例性说明，这些示例性说明和附图并不 构成对实施例的限定，附图中具有相同参考数字标号的元件示为类似的元件，附图不构成比例限制，并且其中：
图1是本公开实施例提供的一个用于控制驻车空调的方法示意图；
图2是本公开实施例提供的获得预测模型的方法示意图；
图3是本公开实施例提供的另一个用于控制驻车空调的方法示意图；
图4是本公开实施例提供的另一个用于控制驻车空调的方法示意图；
图5是本公开实施例提供的另一个用于控制驻车空调的方法示意图；
图6是本公开实施例提供的一个用于控制驻车空调的装置示意图。
具体实施方式
为了能够更加详尽地了解本公开实施例的特点与技术内容，下面结合附图对本公开实施例的实现进行详细阐述，所附附图仅供参考说明之用，并非用来限定本公开实施例。在以下的技术描述中，为方便解释起见，通过多个细节以提供对所披露实施例的充分理解。然而，在没有这些细节的情况下，一个或多个实施例仍然可以实施。在其它情况下，为简化附图，熟知的结构和装置可以简化展示。
本公开实施例的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本公开实施例的实施例。此外，术语“包括”和“具有”以及他们的任何变形，意图在于覆盖不排他的包含。
除非另有说明，术语“多个”表示两个或两个以上。
本公开实施例中，字符“/”表示前后对象是一种“或”的关系。例如，A/B表示：A或B。
术语“和/或”是一种描述对象的关联关系，表示可以存在三种关系。例如，A和/或B，表示：A或B，或，A和B这三种关系。
术语“对应”可以指的是一种关联关系或绑定关系，A与B相对应指的是A与B之间是一种关联关系或绑定关系。
公开实施例中，终端设备是指具有无线连接功能的电子设备，终端设备可以通过连接互联网，与驻车空调相连接，也可以直接通过蓝牙、wifi等方式与驻车空调进行通信连接。在一些实施例中，终端设备例如为移动设备、电脑等，或其任意组合。移动设备例如可以包括手机、智能家居设备、可穿戴设备、智能移动设备、虚拟现实设备等，或其任意组合，其中，可穿戴设备例如包括：智能手表、智能手环、计步器等。
图1是本公开实施例提供的一个用于控制驻车空调的方法示意图；结合图1所示，本公开实施例提供一种用于控制驻车空调的方法，包括：
S11，终端设备获得车辆的相关信息，相关信息包括车辆所在位置的天气信息及车辆在该位置的时间信息。
S12，终端设备将天气信息及时间信息输入至用于调节驻车空调运行信息的预测模型。
S13，终端设备控制驻车空调在预测模型输出的目标运行信息下运行。
在本方案中，终端设备可以获得车辆的相关信息。这里，车辆的相关信息可以为车辆行驶过程中的相关信息。具体地，车辆的相关信息包括车辆所在位置的天气信息及车辆在该位置的时间信息。其中，车辆所在位置的天气信息可以包括车辆所在位置的温度、湿度、风速、风向、阴晴雨多云等。车辆在该位置的时间信息可以为车辆在该位置的日期信息，或车辆在该位置的时刻信息。在一种示例中，终端设备可以通过其配置的定位装置获得车辆所在位置。例如，若终端设备为手机，则可通过其配置的定位芯片获得车辆所在的位置。进一步地，在确定车辆所在位置后，通过终端设备上配置的计时装置确定车辆在该位置的时间信息。通过终端设备关联的云端服务器的气象平台获得车辆所在位置的天气信息。以此方式，可以实时对车辆所在位置的天气信息及时间信息进行精准获取。
进一步地，在终端设备获取车辆所在位置的天气信息和时间信息后，可以将其输入至用于调节驻车空调运行信息的预测模型。这里，预测模型用于预测较为合理的驻车空调的运行信息。具体地，预测模型可以为标准化模型，还可以为基于区域内驻车空调的运行信息进行构建并部署于终端设备的模型。进一步地，可以在预测模型输出目标运行信息后，控制终端设备连接的驻车空调在目标运行信息下运行。这里，驻车空调的目标运行信息为驻车空调的目标模式、目标设定温度、目标设定风速、目标风向等。将机器学习算法引入驻车空调的智能控制逻辑中，有助于驻车空调能够准确、自动地在已预测的目标运行信息下运行，使用户摆脱手动设置驻车空调运行信息的复杂操作方式，提高了用户的使用体验。
采用本公开实施例提供的用于控制驻车空调的方法，通过将已获得的车辆所在位置的天气信息和车辆在该位置的时间信息输入至用于调节驻车空调运行信息的预测模型，能够对驻车空调的目标运行信息进行预测，并控制驻车空调在预测模型输出的目标运行信息下运行。以此方案，有效地结合驻车空调所在位置的天气信息及驻车空调在该位置的时间信息对驻车空调的目标运行信息进行合理预测，改善了现有驻车空调控制方式智能性较低的问题，提高了驻车空调控制的智能化水平。
图2是本公开实施例提供的获得预测模型的方法示意图；结合图2所示，可选地，通过以下方式获得预测模型，包括：
S21，终端设备获得用于训练预测模型的样本，并将样本随机分为训练集和测试集，样本包括不同相关信息下用于调节驻车空调运行信息的设定习惯信息。
S22，终端设备将训练集中不同相关信息输入至初始预测模型，并将训练集中不同相关信息对应的设定习惯信息作为初始预测模型的输出，以对初始预测模型进行训。
S23，终端设备根据测试集验证训练后的初始预测模型，得到验证结果。
S24，终端设备在验证结果表示预测准确的情况下，得到预测模型。
其中，初始预测模型可以是根据机器学习算法确定的预测模型，具体可以是人工神经网络算法、随机森林算法、决策树算法、支持向量机算法等。以SVM(Support Vector Machine，支持向量机)算法为例，将样本随机分为训练集和测试集，以训练集中的不同相关信息作为训练输入，不同相关信息对应的设定习惯信息作为训练输出，调用svmtrain函数以训练初始预测模型；以测试集中的不同相关信息作为预测输入，调用svmprediect函数以输出不同相关信息下各自的预测设定习惯信息；将预测设定习惯信息和训练集中的设定习惯信息拟合成曲线，以验证训练后的初始预测模型，得到验证结果。这样根据SVM算法得到的模型，预测准确度较高，从而提高了空调的智能化。在一种优化的方案中，还可以将样本随机分为训练集、测试集和验证集。在一种示例中，可以将60％作为训练集、20％作为测试集、20％作为验证集。
此外，不同相关信息可以体现为同一位置多台车辆在不同时间信息下各自对应的天气信息。其中，同一位置是指同一经纬度所在位置。不同相关信息下用于调节驻车空调运行信息的设定习惯信息，具体可以包括多台驻车空调各自习惯的设定运行温度、设定运行模式、设定风速以及设定摆风方式等。
对应地，设定习惯信息可以通过多种实现方式获得，下面举例说明。
作为一种示例，可以在预设时长内，分别采集同一位置多台驻车空调不同相关信息下驻车空调设定的运行信息，以便根据采集到的数据确定设定习惯信息。具体地，预设时长可以为30天～90天。优选为90天，这样可以尽可能地按季度采集完整的驻车空调运行信息，以便按季节准确地获得设定习惯信息。
作为另一种示例，可以通过终端设备在其关联的云端服务器中的大数据模块中提取同一位置处所有驻车空调在不同相关信息下各自的设定的运行信息，以便根据大数据模块中提取的预存数据确定设定习惯信息。以此方案，能够通过多种方式实现对设定习惯信息的有效获取。
可选地，在将样本随机分为训练集和测试集前，可对样本中的无效数据进行数据清理，以获取更加准确地预测模型。这里，无效数据可以包括关机状态下的设定习惯信息，还可 以包括持续时间在预设时长内的设定习惯信息，这里，预设时长可以为1分钟。以此方式，在对样本进行分类前有效地对已获取的样本进行数据清洗，为预测模型的训练提供了准确地数据基础。
可选地，在预测模型为决策树模型的情况下，终端设备确定决策树的深度；终端设备可以根据决策树的深度，优化决策树模型。
在本方案中，若预测模型是根据决策树算法确定的决策树模型，则终端设备需要确定决策树的深度。可以理解地，若树的深度设置的过高，模型容易偏离真实的正弦曲线，容易形成过拟合的情形，此时需要对决策树模型进行进一步优化，以有效控制决策树模型的复杂程度。一般地，树的最大深度可以预设为3，这样能够对决策树模型进行有效优化，使优化后的决策树模型，预测准确度较高，从而提高了空调的智能化。
图3是本公开实施例提供的另一个用于控制驻车空调的方法示意图；结合图3所示，可选地，S13，终端设备控制驻车空调在预测模型输出的目标运行信息下运行，包括：
S31，在终端设备关联有多台驻车空调的情况下，终端设备确定目标驻车空调。
S32，终端设备控制目标驻车空调在预测模型输出的目标运行信息下运行。
在本方案中，若终端设备关联有多台驻车空调时，则需要在多台驻车空调中，确定待控制的目标驻车空调。以实现待控制对象的精准确定。在一种示例中，终端设备开启无线连接功能，若在其扫描区域中存在多台驻车空调，则确定终端设备关联有多台驻车空调。这里，无线连接可以为蓝牙连接或WIFI连接。进一步地，可以在确定目标驻车空调后，终端设备控制目标驻车空调在预测模型输出的目标运行信息下运行。以此方案，有效地控制目标驻车空调在预测模型输出的目标运行信息下运行，提高了驻车空调控制的智能化水平。
可选地，S31，终端设备确定目标驻车空调，包括：
终端设备将其默认连接的驻车空调确定为目标驻车空调；或，
在多台驻车空调中，终端设备将接收到连接请求的驻车空调确定为目标驻车空调。
在本方案中，在终端设备存在驻车空调的历史连接记录的情况下，终端设备可以将已连接过的或默认连接的驻车空调确定为目标驻车空调。在另外一种情况下，若多台驻车空调中并不存在终端设备已经连接过的驻车空调，则可以在驻车空调接收到驾驶者手动输入的连接请求时，将接收到连接请求的空调确定为目标驻车空调。以此方案，能够实现待控制对象的精准确定。
图4是本公开实施例提供的另一个用于控制驻车空调的方法示意图；结合图4所示，本公开实施例提供一种用于控制驻车空调的方法，包括：
S41，终端设备获得车辆的相关信息，相关信息包括车辆所在位置的天气信息及车辆在位置的时间信息。
S42，终端设备将天气信息及时间信息输入至用于调节驻车空调运行信息的预测模型。
S43，终端设备控制驻车空调在预测模型输出的目标运行信息下运行。
S44，终端设备获取车辆当前的移动距离。
S45，在移动距离大于预设距离的情况下，终端设备确定调整后的目标运行信息，并控制驻车空调在调整后的目标运行信息下运行。
在本方案中，在控制驻车空调在预测模型输出的目标运行信息下运行后，为了在车辆运行的过程中，对驻车空调的目标运行信息进行调整，则可以预先在终端设备中设置预设距离。这里，预设距离可以根据驾驶者的驻车空调运行信息的调整需求进行确定。例如，预设距离可以为10千米。进一步地，可以在车辆行驶过程中，确定车辆当前移动距离，这里，移动距离可以为初始车辆所在位置与当前车辆所在位置的距离。这里，初始车辆所在位置为获得车辆相关信息时车辆的所在位置。进一步地，可以在车辆的移动距离大于预设距离时，确定调整后的驻车空调的目标运行信息。以此方案，能够在车辆行驶的移动距离超过预设距离时，结合预测模型预测出的调整后的目标运行信息，实时对驻车空调当前的目标运行信息进行调整，提高了驻车空调控制过程的智能化水平。
图5是本公开实施例提供的另一个用于控制驻车空调的方法示意图；结合图5所示，本公开实施例提供一种用于控制驻车空调的方法，包括：
S51，终端设备获得车辆的相关信息，相关信息包括车辆所在位置的天气信息及车辆在位置的时间信息。
S52，终端设备将天气信息及时间信息输入至用于调节驻车空调运行信息的预测模型。
S53，终端设备控制驻车空调在预测模型输出的目标运行信息下运行。
S54，终端设备获取车辆移动至当前位置的间隔时长。
S55，在间隔时长大于预设时长的情况下，终端设备确定调整后的目标运行信息，并控制驻车空调在调整后的目标运行信息下运行。
在本方案中，在控制驻车空调在预测模型输出的目标运行信息下运行后，为了在车辆运行的过程中，对驻车空调的目标运行信息进行调整，则可以预先在终端设备中设置预设时长。这里，预设时长可以根据驾驶者的驻车空调运行信息的调整需求进行确定。例如，预设时长可以为30分钟。进一步地，可以在车辆行驶过程中，确定车辆移动至当前位置的间隔时长，这里，车辆移动至当前位置的间隔时长可以通过终端设备的计时装置获取。进一步地，可以在车辆移动至当前位置的间隔时长大于预设时长时，确定调整后的驻车空 调的目标运行信息。以此方案，能够在车辆移动至当前位置的间隔时长超过预设时长时，结合预测模型预测出的调整后的目标运行信息，实时对驻车空调当前的目标运行信息进行调整，提高了驻车空调控制过程的智能化水平。
可选地，终端设备确定调整后的目标运行信息，包括：
终端设备将车辆当前位置的天气信息及当前的时间信息输入至预测模型；终端设备将预测模型输出的目标运行信息，确定为调整后的目标运行信息。
在本方案中，为了实时对驻车空调的目标运行信息进行调整，可以通过终端设备获取车辆当前位置的天气信息及当前的时间信息。具体获取方式如上文，在此不做具体赘述。进一步地，可以将终端设备已获取的车辆当前位置的天气信息及当前的时间信息输入至终端设备的预测模型，并将预测模型输出的目标运行信息，确定为调整后的目标运行信息。以此方式，能够结合车辆当前的相关信息再次对驻车空调的运行信息进行预测，为目标运行信息的调整提供了准确地数据基础。
在实际应用中，终端设备可以为驾驶者的手机，具体地，可以通过驾驶者的手机获取行驶中的车辆的所在位置的天气信息及车辆在该位置的时间信息。并将已获取的天气信息及时间信息输入至用于调节驻车空调运行信息的预测模型，并获取预测模型输出的驻车空调的目标运行信息。进一步地，可以通过手机确定并连接目标驻车空调，并控制已连接的目标驻车空调在预测模型输出的目标运行信息下运行。以此方案，有效地结合驻车空调所在位置的天气信息及驻车空调在该位置的时间信息对驻车空调的目标运行信息进行合理预测，改善了现有驻车空调控制方式智能性较低的问题，提高了驻车空调控制的智能化水平。
本公开实施例提供一种用于控制驻车空调的装置，包括获得模块、输入模块和控制模块。获得模块被配置为获得车辆的相关信息，相关信息包括车辆所在位置的天气信息及车辆在位置的时间信息；输入模块被配置为将天气信息及时间信息输入至用于调节驻车空调运行信息的预测模型；控制模块被配置为控制驻车空调在预测模型输出的目标运行信息下运行。
采用本公开实施例提供的用于控制驻车空调的装置，通过将已获得的车辆所在位置的天气信息和车辆在该位置的时间信息输入至用于调节驻车空调运行信息的预测模型，能够对驻车空调的目标运行信息进行预测，并控制驻车空调在预测模型输出的目标运行信息下运行。以此方案，有效地结合驻车空调所在位置的天气信息及驻车空调在该位置的时间信息对驻车空调的目标运行信息进行合理预测，改善了现有驻车空调控制方式智能性较低的问题，提高了驻车空调控制的智能化水平。
图6是本公开实施例提供的一个用于控制驻车空调的装置示意图，结合图6所示，本公开实施例提供一种用于控制驻车空调的装置，包括处理器(processor)100和存储器(memory)101。可选地，该装置还可以包括通信接口(Communication Interface)102和总线103。其中，处理器100、通信接口102、存储器101可以通过总线103完成相互间的通信。通信接口102可以用于信息传输。处理器100可以调用存储器101中的逻辑指令，以执行上述实施例的用于控制驻车空调的方法。
此外，上述的存储器101中的逻辑指令可以通过软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。
存储器101作为一种计算机可读存储介质，可用于存储软件程序、计算机可执行程序，如本公开实施例中的方法对应的程序指令/模块。处理器100通过运行存储在存储器101中的程序指令/模块，从而执行功能应用以及数据处理，即实现上述实施例中用于控制驻车空调的方法。
存储器101可包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序；存储数据区可存储根据终端设备的使用所创建的数据等。此外，存储器101可以包括高速随机存取存储器，还可以包括非易失性存储器。
本公开实施例提供了一种驻车空调，包含上述的用于控制驻车空调的装置。
本公开实施例提供了一种计算机可读存储介质，存储有计算机可执行指令，所述计算机可执行指令设置为执行上述用于控制驻车空调的方法。
本公开实施例提供了一种计算机程序产品，所述计算机程序产品包括存储在计算机可读存储介质上的计算机程序，所述计算机程序包括程序指令，当所述程序指令被计算机执行时，使所述计算机执行上述用于控制驻车空调的方法。
上述的计算机可读存储介质可以是暂态计算机可读存储介质，也可以是非暂态计算机可读存储介质。
本公开实施例的技术方案可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括一个或多个指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本公开实施例所述方法的全部或部分步骤。而前述的存储介质可以是非暂态存储介质，包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等多种可以存储程序代码的介质，也可以是暂态存储介质。
以上描述和附图充分地示出了本公开的实施例，以使本领域的技术人员能够实践它们。其他实施例可以包括结构的、逻辑的、电气的、过程的以及其他的改变。实施例仅代 表可能的变化。除非明确要求，否则单独的部件和功能是可选的，并且操作的顺序可以变化。一些实施例的部分和特征可以被包括在或替换其他实施例的部分和特征。而且，本申请中使用的用词仅用于描述实施例并且不用于限制权利要求。如在实施例以及权利要求的描述中使用的，除非上下文清楚地表明，否则单数形式的“一个”(a)、“一个”(an)和“所述”(the)旨在同样包括复数形式。类似地，如在本申请中所使用的术语“和/或”是指包含一个或一个以上相关联的列出的任何以及所有可能的组合。另外，当用于本申请中时，术语“包括”(comprise)及其变型“包括”(comprises)和/或包括(comprising)等指陈述的特征、整体、步骤、操作、元素，和/或组件的存在，但不排除一个或一个以上其它特征、整体、步骤、操作、元素、组件和/或这些的分组的存在或添加。在没有更多限制的情况下，由语句“包括一个…”限定的要素，并不排除在包括所述要素的过程、方法或者设备中还存在另外的相同要素。本文中，每个实施例重点说明的可以是与其他实施例的不同之处，各个实施例之间相同相似部分可以互相参见。对于实施例公开的方法、产品等而言，如果其与实施例公开的方法部分相对应，那么相关之处可以参见方法部分的描述。
本领域技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，可以取决于技术方案的特定应用和设计约束条件。所述技术人员可以对每个特定的应用来使用不同方法以实现所描述的功能，但是这种实现不应认为超出本公开实施例的范围。所述技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
本文所披露的实施例中，所揭露的方法、产品(包括但不限于装置、设备等)，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，可以仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例。另外，在本公开实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。
附图中的流程图和框图显示了根据本公开实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段或代码的一部分，所述模块、程序段或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个连续的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这可以依所涉及的功能而定。在附图中的流程图和框图所对应的描述中，不同的方框所对应的操作或步骤也可以以不同于描述中所披露的顺序发生，有时不同的操作或步骤之间不存在特定的顺序。例如，两个连续的操作或步骤实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这可以依所涉及的功能而定。框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或动作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。

Claims (10)

  1. 一种用于控制驻车空调的方法，其特征在于，包括：
    获得车辆的相关信息，所述相关信息包括所述车辆所在位置的天气信息及所述车辆在所述位置的时间信息；
    将所述天气信息及所述时间信息输入至用于调节所述驻车空调运行信息的预测模型；
    控制所述驻车空调在所述预测模型输出的目标运行信息下运行。
  2. 根据权利要求1所述的方法，其特征在于，通过以下方式获得预测模型，包括：
    获得用于训练所述预测模型的样本，并将所述样本随机分为训练集和测试集，所述样本包括不同相关信息下用于调节所述驻车空调运行信息的设定习惯信息；
    将所述训练集中不同相关信息输入至初始预测模型，并将所述训练集中不同相关信息对应的设定习惯信息作为所述初始预测模型的输出，以对所述初始预测模型进行训练；
    根据所述测试集验证训练后的初始预测模型，得到验证结果；
    在所述验证结果表示预测准确的情况下，得到所述预测模型。
  3. 根据权利要求1所述的方法，其特征在于，包括：
    在所述预测模型为决策树模型的情况下，确定决策树的深度；
    根据所述决策树的深度，优化所述决策树模型。
  4. 根据权利要求1所述的方法，其特征在于，所述控制所述驻车空调在所述预测模型输出的目标运行信息下运行，包括：
    在终端设备关联有多台驻车空调的情况下，确定目标驻车空调；
    控制所述目标驻车空调在所述预测模型输出的目标运行信息下运行。
  5. 根据权利要求4所述的方法，其特征在于，所述确定目标驻车空调，包括：
    将所述终端设备默认连接的驻车空调确定为目标驻车空调；或，
    在所述多台驻车空调中，将接收到连接请求的驻车空调确定为目标驻车空调。
  6. 根据权利要求1所述的方法，其特征在于，在控制所述驻车空调在所述预测模型输出的目标运行信息下运行后，所述方法还包括：
    获取所述车辆当前的移动距离；
    在所述移动距离大于预设距离的情况下，确定调整后的目标运行信息，并控制所述驻车空调在所述调整后的目标运行信息下运行。
  7. 根据权利要求1所述的方法，其特征在于，在控制所述驻车空调在所述预测模 型输出的目标运行信息下运行后，所述方法还包括：
    获取所述车辆移动至当前位置的间隔时长；
    在所述间隔时长大于预设时长的情况下，确定调整后的目标运行信息，并控制所述驻车空调在所述调整后的目标运行信息下运行。
  8. 根据权利要求6或7任一项所述的方法，其特征在于，所述确定调整后的目标运行信息，包括：
    将所述车辆当前位置的天气信息及当前的时间信息输入至所述预测模型；
    将所述预测模型输出的目标运行信息，确定为调整后的目标运行信息。
  9. 一种用于控制驻车空调的装置，包括处理器和存储有程序指令的存储器，其特征在于，所述处理器被配置为在运行所述程序指令时，执行如权利要求1至8任一项所述的用于控制驻车空调的方法。
  10. 一种驻车空调，其特征在于，包括如权利要求9所述的用于控制驻车空调的装置。
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