New energy vehicle remote regulation and control method and device based on environment perception

Abstract

The invention discloses a new energy vehicle remote regulation and control method and device based on environment perception, and relates to the technical field of vehicle regulation and control, and the method comprises the following steps: monitoring and obtaining in-vehicle environment data information, and constructing a vehicle environment data set; on the basis of the vehicle environment data set, in-vehicle environment optimization setting information corresponding to different pieces of in-vehicle environment data information is obtained in combination with a historical vehicle environment data set; based on the in-vehicle environment optimization setting information, in combination with a preset in-vehicle environment influence factor weight, obtaining in-vehicle environment regulation and control parameters; and the target vehicle is regulated and controlled based on the in-vehicle environment regulation and control parameters. According to the method, the in-vehicle environment is monitored, and based on the in-vehicle environment and the in-vehicle environment influence factor weight, the in-vehicle environment is adjusted to a suitable internal environment state, so that the use comfort of the vehicle is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile control, and in particular to a method and device for remotely controlling a new energy vehicle based on environmental perception. Background Art

[0002] In current automotive technology, especially in the field of new energy vehicles, remote control and environmental pre-conditioning systems are increasingly becoming important technologies to enhance user experience. Traditional vehicle remote start systems are mainly limited to starting the engine or pre-adjusting basic temperature settings in the car, such as simple heating or cooling. Although these systems provide certain conveniences for car owners, they still have many limitations in actual operation.

[0003] First, most traditional systems lack the ability to fully perceive the external and internal environment of the vehicle. Without detailed environmental data support, these systems cannot accurately adjust the interior environment to adapt to external weather changes. For example, in extremely high or low temperature weather conditions, the pre-conditioning of the interior of the vehicle often cannot achieve the ideal comfort state. In addition, relying solely on preset temperature adjustment, it is impossible to take into account a variety of environmental factors such as humidity, light and air quality, which may cause the interior environment of the vehicle to still feel uncomfortable to the human body in some cases.

[0004] Secondly, energy efficiency management is an issue that new energy vehicles need to pay special attention to. Traditional remote control systems often cause unnecessary energy waste during the startup, preheating or precooling process. This ineffective or excessive energy consumption not only affects the vehicle's endurance, but may also have a negative impact on battery life. For example, if the vehicle runs the heater or air conditioner for a long time before the necessary internal temperature is reached, more electricity will be consumed, which is a significant disadvantage for electric vehicles.

[0005] Therefore, in order to meet actual needs, a new energy vehicle remote control technology based on environmental perception is provided. Summary of the invention

[0006] In view of the defects existing in the prior art, the purpose of the present invention is to provide a remote control method and device for new energy vehicles based on environmental perception, which monitors the interior environment of the vehicle, and adjusts the internal environment to a more suitable state based on the interior environment and the weights of factors affecting the interior environment, thereby improving the comfort of vehicle use.

[0007] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0008] In a first aspect, the present application provides a method for remotely controlling a new energy vehicle based on environmental perception, the method comprising the following steps:

[0009] Monitor and obtain in-vehicle environment data information and build a vehicle environment data set;

[0010] Based on the vehicle environment data set, combined with the historical vehicle environment data set, obtaining in-vehicle environment optimization setting information corresponding to different in-vehicle environment data information;

[0011] Based on the in-vehicle environment optimization setting information and in combination with preset in-vehicle environment influencing factor weights, obtaining in-vehicle environment control parameters;

[0012] The target vehicle is regulated based on the in-vehicle environment regulation parameters.

[0013] On the basis of the above technical solution, before the monitoring obtains the in-vehicle environment data information and constructs the vehicle environment data set, the method further includes the following steps:

[0014] Arrange the in-vehicle environment monitoring components at the preset positions in the target vehicle;

[0015] The in-vehicle environment monitoring components include: temperature sensors, humidity sensors, light sensors, PM2.5 concentration sensors, PM10 concentration sensors, and nitrogen dioxide and ozone level sensors;

[0016] The in-vehicle environmental data information includes in-vehicle temperature information, in-vehicle humidity information, in-vehicle light intensity, PM2.5 concentration information, PM10 concentration information, nitrogen dioxide level information and ozone level information.

[0017] Based on the above technical solution, the in-vehicle temperature information, in-vehicle humidity information, in-vehicle light intensity, PM2.5 concentration information, PM10 concentration information, nitrogen dioxide level information and ozone level information in the vehicle environment data set are configured with corresponding collection time points.

[0018] Based on the above technical solution, the monitoring obtains the in-vehicle environment data information and constructs the vehicle environment data set, including the following steps:

[0019] The vehicle environment data set is constructed according to a time series mode based on each in-vehicle environment data information and the corresponding time.

[0020] Based on the above technical solution, the monitoring and obtaining of vehicle interior environment data information and constructing a vehicle environment data set also include the following steps:

[0021] Based on the standard deviation theory, data outliers in the vehicle environment data set are removed.

[0022] On the basis of the above technical solution, the in-vehicle environment optimization setting information is combined with the preset in-vehicle environment influencing factor weights to obtain the in-vehicle environment control parameters, including the following steps:

[0023] Obtaining the in-vehicle temperature, air quality, seat heating or cooling status, and steering wheel heating or cooling status in the in-vehicle environment optimization setting information;

[0024] Calculate the weight of environmental factors affecting the optimization of the in-vehicle environment by each parameter in the in-vehicle environment optimization setting information;

[0025] Based on the in-vehicle temperature, the air quality, the seat heating or cooling state, and the steering wheel heating or cooling state, combined with corresponding environmental factor weights, the in-vehicle environment control parameters are obtained.

[0026] On the basis of the above technical solution, the control of the target vehicle based on the in-vehicle environment control parameters includes the following steps:

[0027] Based on the in-vehicle environment control parameters, an electric compressor, a blower, a seat heating device, a seat ventilation device and a steering wheel heating device of the target vehicle are controlled.

[0028] In a second aspect, the present application provides a remote control device for new energy vehicles based on environmental perception, wherein:

[0029] The environment monitoring module is used to monitor and obtain the in-vehicle environment data information and build a vehicle environment data set;

[0030] A data set arrangement module, which is used to obtain in-vehicle environment optimization setting information corresponding to different in-vehicle environment data information based on the vehicle environment data set and in combination with a historical vehicle environment data set;

[0031] A control parameter acquisition module, which is used to obtain the in-vehicle environment control parameters based on the in-vehicle environment optimization setting information and in combination with preset in-vehicle environment influencing factor weights;

[0032] The vehicle control module is used to control the target vehicle based on the in-vehicle environment control parameters.

[0033] On the basis of the above technical solution, the environment monitoring module is also used to control the in-vehicle environment monitoring component arranged at a preset position in the target vehicle to monitor and obtain the in-vehicle environment data information; wherein,

[0034] The in-vehicle environment monitoring components include: temperature sensors, humidity sensors, light sensors, PM2.5 concentration sensors, PM10 concentration sensors, and nitrogen dioxide and ozone level sensors;

[0035] The in-vehicle environmental data information includes in-vehicle temperature information, in-vehicle humidity information, in-vehicle light intensity, PM2.5 concentration information, PM10 concentration information, nitrogen dioxide level information and ozone level information.

[0036] On the basis of the above technical solution, the environment monitoring module is also used to construct the vehicle environment data set in a time series mode based on the in-vehicle environment data information and the corresponding time.

[0037] Based on the above technical solution, the in-vehicle temperature information, in-vehicle humidity information, in-vehicle light intensity, PM2.5 concentration information, PM10 concentration information, nitrogen dioxide level information and ozone level information in the vehicle environment data set are configured with corresponding collection time points.

[0038] On the basis of the above technical solution, the data set sorting module is also used to eliminate data outliers in the vehicle environment data set based on standard deviation theory.

[0039] On the basis of the above technical solution, the control parameter acquisition module is also used to obtain the in-vehicle temperature, air quality, seat heating or cooling status and steering wheel heating or cooling status in the in-vehicle environment optimization setting information;

[0040] The control parameter acquisition module is also used to calculate the weight of environmental factors that affect the optimization of the in-vehicle environment of each parameter in the in-vehicle environment optimization setting information;

[0041] The control parameter acquisition module is also used to obtain the in-vehicle environment control parameters based on the in-vehicle temperature, the air quality, the seat heating or cooling status, and the steering wheel heating or cooling status, combined with the corresponding environmental factor weights.

[0042] On the basis of the above technical solution, the vehicle control module is also used to control the electric compressor, blower, seat heating device, seat ventilation device and steering wheel heating device of the target vehicle based on the in-vehicle environment control parameters.

[0043] Compared with the prior art, the advantages of the present invention are:

[0044] The present invention monitors the in-vehicle environment and adjusts the internal environment to a more suitable state based on the in-vehicle environment and the weights of factors affecting the in-vehicle environment, thereby improving the comfort of vehicle use. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0046] Figure 1A flowchart of the steps of a remote control method for new energy vehicles based on environment perception according to an embodiment of the present invention;

[0047] Figure 2 This is a principle flow chart of a method for remotely controlling a new energy vehicle based on environmental perception according to an embodiment of the present invention;

[0048] Figure 3 This is a structural block diagram of a remote control device for new energy vehicles based on environment perception according to an embodiment of the present invention;

[0049] Figure 4 This is a principle block diagram of a remote control device for new energy vehicles based on environmental perception according to an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0051] The embodiments of the present invention are further described in detail below with reference to the accompanying drawings.

[0052] The embodiments of the present application provide a method and device for remote control of new energy vehicles based on environmental perception, which monitors the interior environment of the vehicle and adjusts the internal environment to a more suitable state based on the interior environment and the weights of factors affecting the interior environment, thereby improving the comfort of vehicle use.

[0053] In order to achieve the above technical effects, the overall idea of ​​this application is as follows:

[0054] A remote control method for a new energy vehicle based on environmental perception, the method comprising the following steps:

[0055] A1. Monitor and obtain in-vehicle environment data information and build a vehicle environment data set;

[0056] A2. Based on the vehicle environment data set and in combination with the historical vehicle environment data set, obtain the in-vehicle environment optimization setting information corresponding to different in-vehicle environment data information;

[0057] A3. Based on the in-vehicle environment optimization setting information and the preset in-vehicle environment influencing factor weights, the in-vehicle environment control parameters are obtained;

[0058] A4. Based on the in-vehicle environment control parameters, the target vehicle is controlled.

[0059] The embodiments of the present application are further described in detail below in conjunction with the accompanying drawings.

[0060] First, see Figures 1-2 As shown, the embodiment of the present application provides a new energy vehicle remote control method based on environmental perception, the method comprising the following steps:

[0061] A1. Monitor and obtain in-vehicle environment data information and build a vehicle environment data set;

[0062] A2. Based on the vehicle environment data set and in combination with the historical vehicle environment data set, obtain the in-vehicle environment optimization setting information corresponding to different in-vehicle environment data information;

[0063] A3. Based on the in-vehicle environment optimization setting information and the preset in-vehicle environment influencing factor weights, the in-vehicle environment control parameters are obtained;

[0064] A4. Based on the in-vehicle environment control parameters, the target vehicle is controlled.

[0065] In an embodiment of the present application, the interior environment of the vehicle is monitored, and based on the interior environment and the weights of factors affecting the interior environment, the internal environment is adjusted to a more suitable state to improve the comfort of vehicle use.

[0066] Furthermore, before the monitoring obtains the in-vehicle environment data information and constructs the vehicle environment data set, the method further includes the following steps:

[0067] Arrange the in-vehicle environment monitoring components at the preset positions in the target vehicle;

[0068] The in-vehicle environment monitoring components include: temperature sensors, humidity sensors, light sensors, PM2.5 concentration sensors, PM10 concentration sensors, and nitrogen dioxide and ozone level sensors;

[0069] The in-vehicle environmental data information includes in-vehicle temperature information, in-vehicle humidity information, in-vehicle light intensity, PM2.5 concentration information, PM10 concentration information, nitrogen dioxide level information and ozone level information.

[0070] Furthermore, the in-vehicle temperature information, the in-vehicle humidity information, the in-vehicle light intensity, the PM2.5 concentration information, the PM10 concentration information, the nitrogen dioxide level information and the ozone level information in the vehicle environment data set are configured with corresponding collection time points.

[0071] Furthermore, the monitoring obtains in-vehicle environment data information and constructs a vehicle environment data set, including the following steps:

[0072] The vehicle environment data set is constructed according to a time series mode based on each in-vehicle environment data information and the corresponding time.

[0073] Furthermore, the monitoring and obtaining of in-vehicle environment data information and constructing a vehicle environment data set further includes the following steps:

[0074] Based on the standard deviation theory, data outliers in the vehicle environment data set are removed.

[0075] Furthermore, the obtaining of the in-vehicle environment control parameters based on the in-vehicle environment optimization setting information and in combination with the preset in-vehicle environment influencing factor weights includes the following steps:

[0076] Obtaining the in-vehicle temperature, air quality, seat heating or cooling status, and steering wheel heating or cooling status in the in-vehicle environment optimization setting information;

[0077] Calculate the weight of environmental factors affecting the optimization of the in-vehicle environment by each parameter in the in-vehicle environment optimization setting information;

[0078] Based on the in-vehicle temperature, the air quality, the seat heating or cooling state, and the steering wheel heating or cooling state, combined with corresponding environmental factor weights, the in-vehicle environment control parameters are obtained.

[0079] Furthermore, the control of the target vehicle based on the in-vehicle environment control parameters includes the following steps:

[0080] Based on the in-vehicle environment control parameters, an electric compressor, a blower, a seat heating device, a seat ventilation device and a steering wheel heating device of the target vehicle are controlled.

[0081] Based on the technical solution of the embodiment of the present application, the specific implementation is as follows:

[0082] S1. Collect data about the vehicle's environment through environmental sensors installed inside and outside the vehicle, including but not limited to temperature, humidity, light, atmospheric pressure, particulate matter (PM2.5 and PM10) concentration, nitrogen dioxide and ozone levels, and build a vehicle environment dataset;

[0083] S2, transmitting the collected vehicle environment data set to a central processing unit of the vehicle;

[0084] S3, the central processing unit uses a machine learning-based environment adaptation algorithm trained based on historical and real-time vehicle environment data sets to predict optimized settings for the in-vehicle environment under specific environmental conditions based on the received vehicle environment data set;

[0085] S4, environmental adaptation algorithm automatically determines the most suitable adjustment method for in-vehicle temperature, air quality and other environmental parameters through weight adjustment and pattern recognition of environmental factors;

[0086] S5. According to the judgment result of step S4, the central processing unit automatically adjusts the vehicle interior environment settings, including the vehicle interior temperature, air quality, and the heating or cooling status of the seats and steering wheel;

[0087] S6, remotely starting the vehicle and adjusting the internal environment of the vehicle to the optimal state determined in step S5;

[0088] S7, through the communication module installed in the vehicle, the vehicle startup and environment adjustment status information is fed back to the user's remote control device in real time;

[0089] S8. The user receives vehicle status information through the remote control device and can remotely adjust the in-vehicle environment settings in step S5.

[0090] Specifically, step S1 includes the following steps:

[0091] S11. Setting sensor locations and types, including installing temperature sensors (T), humidity sensors (H), light sensors (L), atmospheric pressure sensors (P), PM2.5 and PM10 concentration sensors (PM), and nitrogen dioxide and ozone level sensors (G) at the front, rear, sides and roof of the vehicle, but not limited to the above types of sensors; at least one set of sensors is installed in each part to form an all-round perception of the vehicle's surrounding environment.

[0092] S12. Each sensor is set to automatically collect environmental data once every minute. The collected data includes the current temperature T i , humidity H i , light L i , atmospheric pressure P i , PM2.5 and PM10 concentrations PM i , nitrogen dioxide and ozone levels G i , where i represents a different sensor position number.

[0093] S13, formatting the data collected by each sensor into time series data points to form an environmental data set, expressed as:

[0094] D i (t)={t,x ti ,x hi ,x li ,x pi ,x pmi ,x gi};

[0095] Among them, t represents the specific time point of data collection.

[0096] Optionally, for the data collection methods of various sensors, the improved combination of actual physical principles and mathematical models makes the data collection not only accurate but also creative:

[0097] The temperature is measured using a temperature-dependent thermistor. The measuring principle is based on the nonlinear relationship between temperature and resistance, which is expressed by the Steinhardt equation:

[0098]

[0099] in, is the resistance of the thermistor, and a, b, c are constants specific to the sensor.

[0100] The response of a capacitive humidity sensor is described by the following equation, which takes into account the nonlinear relationship between capacitance and humidity and adds a temperature adjustment factor:

[0101] H i =α+β·(C meas -C dry ) / (C wet -C dry )·f(T i );

[0102] Among them, C meas is the measured capacitance, C dry and C wet are the calibration capacitances under extreme dry and wet conditions, β is the calibration coefficient, and f(T i ) is a temperature compensation function that adjusts the accuracy of humidity readings at different temperatures.

[0103] The response of a photoresistor is usually inversely proportional to the intensity of the incident light and can be expressed by the following formula:

[0104]

[0105] Where I0 is the reference light intensity during calibration, is the currently measured light intensity, K L is the sensitivity coefficient of the photoresistor. This logarithmic model helps improve the dynamic range of the response, allowing the sensor to more accurately reflect changes in lighting conditions.

[0106] The response of a piezoresistive sensor can be described by the equation that includes the temperature dependence:

[0107]

[0108] Among them, P stdis the standard atmospheric pressure, M is the molar mass of air, g is the acceleration due to gravity, R is the ideal gas constant, is the resistance read from the sensor and temperature T i A calculated altitude change function provides the pressure change as a function of altitude and temperature.

[0109] The model expression of the laser scattering sensor measuring particle concentration is:

[0110]

[0111] Among them, I scatter is the measured scattered light intensity, K PM is the conversion factor, μ scatter It is the average value of scattered light intensity. The innovative Gaussian model helps describe the relationship between particle concentration and scattered light intensity.

[0112] The response of the electrochemical sensor uses the following model:

[0113]

[0114] Among them, N A is Avogadro's constant, I electro is the sensor current, V cell is the voltage of the battery, n is the number of electrons transferred, F is the Faraday constant, A is the area of ​​the electrode, and t is the measurement time. The concentration of the gas is calculated based on the principle of electrochemical reaction, ensuring high accuracy and reproducibility.

[0115] Specifically, step S2 includes the following steps:

[0116] S21. Transmitting the data of each sensor to the vehicle central processing unit in real time through the vehicle's internal network, with each transmission including the latest collected data of all sensors.

[0117] S22. The central processing unit performs preliminary processing on the received data. In order to form an environmental data set in a unified format, an innovative mathematical formula can be used to process and standardize the data collected from each sensor, involving outlier processing, data interpolation, normalization processing, and weight allocation to ensure that the data set can be effectively used in the decision support system for environmental pre-conditioning:

[0118] An improved standard deviation-based filtering method is used to identify and remove outliers:

[0119]

[0120] Among them, x (k) is the kth data point.

[0121] For data points that become null values ​​due to outlier processing, an improved linear interpolation method is used to fill them:

[0122]

[0123] Among them, t k It's a point in time.

[0124] The data is scaled using a modified max-min normalization method to fit the input requirements of the central processing unit:

[0125]

[0126] Different weights are assigned to sensors based on their location and importance to optimize the representativeness of environmental data:

[0127]

[0128] Among them, w i is the weight of the ith sensor, n is the total number of sensors, is the normalized data of the ith sensor at time point k.

[0129] Environmental datasets in a unified format D total It is expressed as:

[0130]

[0131] Where m is the total number of data points in the dataset, providing reliable input for the vehicle central processing unit.

[0132] Specifically, step S3 includes the following steps:

[0133] S31, receiving and generating a unified format environment data set D total , innovatively introduces the use of historical environmental data sets and real-time updated data sets to build training data sets for machine learning models. The historical data sets are composed of D total The real-time data set is composed of the data collected during the current vehicle operation:

[0134]

[0135] in,

[0136] D train is the dataset used to train the random forest model, combining historical data and real-time data, y (k) Indicates the actual in-vehicle environment settings at the corresponding time point.

[0137] S32. Select a machine learning model suitable for environmental adaptation analysis, such as random forest, support vector machine or deep neural network. Here, random forest is selected to better fit the topic.

[0138] RF(θ)={θ i |θ i =(N trees ,d max ,F random )};

[0139] Among them, N trees represents the number of decision trees, d max is the maximum depth of the tree, F random is the number of features considered in each split and Θ represents the overall set of parameters of the model.

[0140] S33. Train the random forest model using the formula:

[0141]

[0142] Among them, L represents the loss function of the overall model, which measures the difference between the predicted value of each tree and the actual in-vehicle environment setting, and l is the loss function of a single tree.

[0143] S34. Use the trained random forest model to analyze the real-time environmental data D train Make predictions and output the optimal settings for the interior environment, including the predicted interior temperature, air quality, and heating or cooling status of the seats and steering wheel, using the prediction function:

[0144]

[0145] in, is the in-vehicle environment setting predicted by the average of all decision trees, and f is the prediction function of a single decision tree.

[0146] Specifically, step S4 includes the following steps:

[0147] S41, receiving the prediction model The output predicts the in-car environment settings, including in-car temperature, air quality, and heating or cooling status of seats and steering wheels.

[0148] S42. Define an environmental factor weight adjustment formula to calculate the weight of each environmental factor (temperature, humidity, light) on the optimization of the in-vehicle environment. In order to improve the adaptability of the environmental factor weight, a dynamic adjustment coefficient γ(t) can be introduced. This is a time function used to dynamically adjust the value of β according to the vehicle usage time and changes in external conditions:

[0149]

[0150] Among them, x e represents the measured value of the environmental factor, E is the set of all environmental factors, and w e is the calculated weight of the environmental factor, and γ(t) is the adjustment factor according to time changes. It can be set based on factors such as external temperature or daily cycle so that the weight reflects the dynamic impact of daily or seasonal changes.

[0151] S43. Use pattern recognition technology to analyze the relationship between real-time environmental data and the in-vehicle environment, determine the most suitable adjustment method, and introduce a complex linear regression model containing interaction terms and nonlinear transformations, taking into account the nonlinear relationship between environmental factors and in-vehicle settings:

[0152]

[0153] Among them, α e,e′ It represents the interaction effect coefficient between environmental factors e and e'. The model takes into account the interaction between environmental factors and their nonlinear effects.

[0154] Specifically, step S8 includes the following steps:

[0155] S81. Setting an in-vehicle communication module to transmit the current environmental status of the vehicle and the in-vehicle environmental settings preset by the user in real time.

[0156] S82. The user receives data sent by the vehicle central processing unit through the communication module through a remote control device, such as a smart phone or tablet computer. The data is formatted as:

[0157] I status ={t,y temp ,y air ,y heat ,y cool};

[0158] Where t represents the sending time, y temp ,y air ,y heat ,y cool They respectively indicate the current in-car temperature, air quality, seat heating and steering wheel cooling status.

[0159] S83. Provide input options on the user interface to allow the user to adjust the in-vehicle environment settings according to their own needs. The input format is:

[0160]

[0161] in, They respectively represent the new temperature, new air quality, new seat heating and new steering wheel cooling status that the user wishes to adjust.

[0162] S84. After the user confirms and sends the adjustment instruction, the remote control device sends the U set Sent back to the vehicle's central processing unit via the cloud.

[0163] S85. The vehicle central processing unit receives the user's adjustment instructions and adjusts the parameters of the vehicle's environmental control system (electric compressor, blower, seat heating / ventilation device, steering wheel heating device, etc.) accordingly to ensure that the vehicle's interior environment is updated according to the user's settings.

[0164] S86. The vehicle communication module feeds back the adjusted status to the user, and the updated status information is formatted as shown in step S82, ensuring that the user can view the adjustment effect in real time.

[0165] In summary, the technical solution of the embodiment of the present application can collect and analyze environmental data in real time, such as temperature, humidity, light, atmospheric pressure, etc., through various sensors installed inside and outside the vehicle. The above data is used to intelligently adjust the temperature, air quality and other comfort settings in the car, such as the heating or cooling status of the seats and steering wheel. Therefore, no matter how the external environment changes, the vehicle can automatically adjust to the most suitable internal environment state, greatly increasing the comfort of driving and riding.

[0166] Furthermore, using advanced machine learning algorithms, the vehicle can not only adjust internal settings based on current environmental data, but also learn user preferences and behavior patterns to further optimize energy use, help reduce energy waste without sacrificing comfort, extend battery life, and improve the overall energy efficiency of the vehicle.

[0167] Second, see Figures 3-4 As shown, an embodiment of the present application provides a remote control device for new energy vehicles based on environment perception, the device comprising:

[0168] The environment monitoring module is used to monitor and obtain the in-vehicle environment data information and build a vehicle environment data set;

[0169] A data set arrangement module, which is used to obtain in-vehicle environment optimization setting information corresponding to different in-vehicle environment data information based on the vehicle environment data set and in combination with a historical vehicle environment data set;

[0170] A control parameter acquisition module, which is used to obtain the in-vehicle environment control parameters based on the in-vehicle environment optimization setting information and in combination with preset in-vehicle environment influencing factor weights;

[0171] The vehicle control module is used to control the target vehicle based on the in-vehicle environment control parameters.

[0172] In an embodiment of the present application, the interior environment of the vehicle is monitored, and based on the interior environment and the weights of factors affecting the interior environment, the internal environment is adjusted to a more suitable state to improve the comfort of vehicle use.

[0173] Furthermore, the environment monitoring module is also used to control the in-vehicle environment monitoring components arranged at preset positions in the target vehicle to monitor and obtain the in-vehicle environment data information; wherein,

[0174] The in-vehicle environment monitoring components include: temperature sensors, humidity sensors, light sensors, PM2.5 concentration sensors, PM10 concentration sensors, and nitrogen dioxide and ozone level sensors;

[0175] The in-vehicle environmental data information includes in-vehicle temperature information, in-vehicle humidity information, in-vehicle light intensity, PM2.5 concentration information, PM10 concentration information, nitrogen dioxide level information and ozone level information.

[0176] Furthermore, the environment monitoring module is also used to construct the vehicle environment data set in a time series mode based on the in-vehicle environment data information and the corresponding time.

[0177] Furthermore, the in-vehicle temperature information, the in-vehicle humidity information, the in-vehicle light intensity, the PM2.5 concentration information, the PM10 concentration information, the nitrogen dioxide level information and the ozone level information in the vehicle environment data set are configured with corresponding collection time points.

[0178] Furthermore, the data set sorting module is also used to remove data outliers in the vehicle environment data set based on standard deviation theory.

[0179] Furthermore, the control parameter acquisition module is also used to obtain the in-vehicle temperature, air quality, seat heating or cooling status, and steering wheel heating or cooling status in the in-vehicle environment optimization setting information;

[0180] The control parameter acquisition module is also used to calculate the weight of environmental factors that affect the optimization of the in-vehicle environment of each parameter in the in-vehicle environment optimization setting information;

[0181] The control parameter acquisition module is also used to obtain the in-vehicle environment control parameters based on the in-vehicle temperature, the air quality, the seat heating or cooling status, and the steering wheel heating or cooling status, combined with the corresponding environmental factor weights.

[0182] Furthermore, the vehicle control module is also used to control the electric compressor, blower, seat heating device, seat ventilation device and steering wheel heating device of the target vehicle based on the in-vehicle environment control parameters.

[0183] It should be noted that the remote control device for new energy vehicles based on environmental perception mentioned in the second aspect is similar to the technical principles of the remote control method for new energy vehicles based on environmental perception mentioned in the first aspect in terms of technical issues, technical means and technical effects, and will not be elaborated here.

[0184] In the description of the present application, it should be noted that the terms "upper", "lower", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. Unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0185] It should be noted that, in this application, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0186] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest range consistent with the principles and novel features applied for herein.

Claims

1. A remote control method for new energy vehicles based on environmental perception, characterized in that: The method comprises the following steps: Monitor and obtain in-vehicle environment data information and build a vehicle environment data set; Based on the vehicle environment data set, combined with the historical vehicle environment data set, obtaining in-vehicle environment optimization setting information corresponding to different in-vehicle environment data information; Based on the in-vehicle environment optimization setting information and in combination with preset in-vehicle environment influencing factor weights, obtaining in-vehicle environment control parameters; The target vehicle is regulated based on the in-vehicle environment regulation parameters.

2. The remote control method for new energy vehicles based on environmental perception as claimed in claim 1, characterized in that: Before the monitoring and obtaining of in-vehicle environment data information and constructing a vehicle environment data set, the method further includes the following steps: Arrange the in-vehicle environment monitoring components at the preset positions in the target vehicle; The in-vehicle environment monitoring components include: temperature sensors, humidity sensors, light sensors, PM2.5 concentration sensors, PM10 concentration sensors, and nitrogen dioxide and ozone level sensors; The in-vehicle environmental data information includes in-vehicle temperature information, in-vehicle humidity information, in-vehicle light intensity, PM2.5 concentration information, PM10 concentration information, nitrogen dioxide level information and ozone level information.

3. The remote control method for new energy vehicles based on environmental perception as claimed in claim 2 is characterized in that: The in-vehicle temperature information, in-vehicle humidity information, in-vehicle light intensity, PM2.5 concentration information, PM10 concentration information, nitrogen dioxide level information and ozone level information in the vehicle environment data set are configured with corresponding collection time points.

4. The remote control method for new energy vehicles based on environmental perception as claimed in claim 1, characterized in that: The monitoring obtains the in-vehicle environment data information and constructs the vehicle environment data set, including the following steps: The vehicle environment data set is constructed according to a time series mode based on each in-vehicle environment data information and the corresponding time.

5. The remote control method for new energy vehicles based on environment perception as claimed in claim 1, characterized in that: The monitoring and obtaining of vehicle interior environment data information and constructing a vehicle environment data set further include the following steps: Based on the standard deviation theory, data outliers in the vehicle environment data set are removed.

6. The remote control method for new energy vehicles based on environment perception as claimed in claim 1, characterized in that: The step of obtaining the in-vehicle environment control parameters based on the in-vehicle environment optimization setting information and combining the preset in-vehicle environment influencing factor weights includes the following steps: Obtaining the in-vehicle temperature, air quality, seat heating or cooling status, and steering wheel heating or cooling status in the in-vehicle environment optimization setting information; Calculate the weight of environmental factors affecting the optimization of the in-vehicle environment by each parameter in the in-vehicle environment optimization setting information; Based on the in-vehicle temperature, the air quality, the seat heating or cooling state, and the steering wheel heating or cooling state, combined with corresponding environmental factor weights, the in-vehicle environment control parameters are obtained.

7. The remote control method for new energy vehicles based on environment perception as claimed in claim 1, characterized in that: The step of regulating the target vehicle based on the in-vehicle environment regulation parameters includes the following steps: Based on the in-vehicle environment control parameters, an electric compressor, a blower, a seat heating device, a seat ventilation device and a steering wheel heating device of the target vehicle are controlled.

8. A remote control device for new energy vehicles based on environmental perception, characterized in that: The device: The environment monitoring module is used to monitor and obtain the in-vehicle environment data information and build a vehicle environment data set; A data set arrangement module, which is used to obtain in-vehicle environment optimization setting information corresponding to different in-vehicle environment data information based on the vehicle environment data set and in combination with a historical vehicle environment data set; A control parameter acquisition module, which is used to obtain the in-vehicle environment control parameters based on the in-vehicle environment optimization setting information and in combination with preset in-vehicle environment influencing factor weights; The vehicle control module is used to control the target vehicle based on the in-vehicle environment control parameters.

9. The remote control device for new energy vehicles based on environment perception as claimed in claim 8, characterized in that: The environment monitoring module is also used to control the in-vehicle environment monitoring components arranged at a preset position in the target vehicle to monitor and obtain the in-vehicle environment data information; wherein, The in-vehicle environment monitoring components include: temperature sensors, humidity sensors, light sensors, PM2.5 concentration sensors, PM10 concentration sensors, and nitrogen dioxide and ozone level sensors; The in-vehicle environmental data information includes in-vehicle temperature information, in-vehicle humidity information, in-vehicle light intensity, PM2.5 concentration information, PM10 concentration information, nitrogen dioxide level information and ozone level information.

10. The remote control device for new energy vehicles based on environment perception as claimed in claim 8, characterized in that: The environment monitoring module is also used to construct the vehicle environment data set according to a time series mode based on each in-vehicle environment data information and the corresponding time.

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