Vehicle control method and vehicle

Abstract

This disclosure relates to a vehicle control method and a vehicle, applied in the field of smart cockpit technology. The method includes: acquiring the occupant status of each seat and the current vehicle speed; generating at least one candidate window opening scheme based on the occupant status and current speed; determining the estimated wind noise value at the driver's seat under each candidate window opening scheme; selecting a recommended window opening scheme from the at least one candidate scheme based on the estimated wind noise value; and controlling each window and sunroof to adjust to the target opening degree corresponding to the recommended window opening scheme. Thus, by acquiring the occupant status and vehicle speed, generating candidate window opening schemes, selecting a recommended scheme based on the estimated wind noise at the driver's seat, and executing it with a single click, automated low-noise window opening control is achieved. This solves the problem of users finding the optimal combination manually, prioritizes a low-noise environment for the driver, and improves driving safety.

Description

Technical Field

[0001] This disclosure relates to the field of intelligent cockpit technology, and more particularly to a vehicle control method and a vehicle. Background Technology

[0002] When a user opens the side windows or sunroof for ventilation while the vehicle is in motion, the airflow interacts with the window gaps, rearview mirrors, and vehicle pillars, generating wind noise. The intensity of wind noise increases non-linearly with vehicle speed.

[0003] Existing vehicles only offer manual control of windows and sunroofs, or have basic functions such as one-touch up and down, but cannot intelligently adjust the opening and closing combinations of windows and sunroofs. In particular, it is difficult to ensure a low-noise environment on the driver's side, making it difficult for users to balance ventilation needs and ride comfort. Moreover, excessive wind noise on the driver's side can directly interfere with the driver's attention and affect driving safety. Summary of the Invention

[0004] To address the aforementioned technical problems, this disclosure provides a vehicle control method and a vehicle.

[0005] A first aspect of this disclosure provides a vehicle control method, including: Obtain the occupancy status of each seat in the vehicle and the current vehicle speed; Based on the passenger seating status and the current vehicle speed, at least one candidate window opening scheme is generated, and each candidate window opening scheme includes the target opening degree of each window and the sunroof. Determine the estimated wind noise value at the driver's seat under each candidate window opening scheme, and select a recommended window opening scheme from the at least one candidate window opening scheme based on the estimated wind noise value; Control each window and the sunroof to adjust to the target opening degree corresponding to the recommended window opening scheme.

[0006] In some embodiments of this disclosure, generating at least one candidate window opening scheme based on the passenger seating status and the current vehicle speed includes: Multiple initial window opening schemes were determined; The multiple initial window opening schemes are filtered based on the passenger seating status to obtain the filtered window opening schemes; A search algorithm is used to generate at least one candidate windowing scheme from the filtered windowing schemes.

[0007] In some embodiments of this disclosure, the search algorithm is a genetic algorithm; the step of generating at least one candidate windowing scheme by using the search algorithm on the screened windowing schemes includes: Using real-number encoding, the opening degree of each window and sunroof is used as an individual vector, and the fitness function is constructed with the goal of minimizing the estimated wind noise value at the driver's seat. The windowing scheme is iteratively optimized through selection, crossover, and mutation operations until the termination condition is met, and at least one individual vector with the highest fitness in the windowing scheme is selected as a candidate windowing scheme.

[0008] In some embodiments of this disclosure, determining the estimated wind noise value at the driver's seat under each candidate window opening scheme includes: Construct a wind noise mapping model based on real vehicle wind tunnel test data or simulation data; The opening degree of each window and sunroof corresponding to each candidate window opening scheme and the current vehicle speed are input into the wind noise mapping model, and the estimated wind noise value at each seat is output through the wind noise mapping model.

[0009] In some embodiments of this disclosure, selecting a recommended window opening scheme from the at least one candidate window opening schemes based on the estimated wind noise value includes: The at least one candidate window opening scheme is ranked based on the estimated wind noise value; The recommended window opening scheme is determined based on the number of candidate window opening schemes with the lowest estimated wind noise value.

[0010] In some embodiments of this disclosure, determining the recommended window opening scheme based on the first preset number of candidate window opening schemes with the lowest estimated wind noise value includes: The optimal window opening scheme is determined from the preset number of candidate window opening schemes with the lowest estimated wind noise value; The optimal window opening scheme is determined as the recommended window opening scheme.

[0011] In some embodiments of this disclosure, determining the optimal window opening scheme from the preset number of candidate window opening schemes with the smallest estimated wind noise value includes: When the difference between the estimated wind noise values ​​at the driver's seat of each candidate window opening scheme is less than a preset threshold, the total wind noise value of the non-driver's seat in each candidate window opening scheme or the total opening degree value in each candidate window opening scheme is determined. The optimal window opening scheme is determined by the scheme with the lowest total wind noise or the highest total opening degree among all candidate window opening schemes.

[0012] In some embodiments of this disclosure, the method further includes: During operation, the vehicle speed and the seating status of passengers in each seat are continuously monitored. When the change in vehicle speed exceeds a preset threshold or the passenger seating status changes, the steps of obtaining the passenger seating status and current vehicle speed, generating candidate window opening schemes, selecting a recommended window opening scheme are re-executed, and the user is prompted to update the window opening scheme.

[0013] In some embodiments of this disclosure, obtaining the occupancy status of each seat in the vehicle includes: The system identifies the occupant status of the driver's seat, front passenger seat, and rear seats using at least one of the following methods: seat pressure sensor, seatbelt buckle sensor, or in-vehicle camera.

[0014] In some embodiments of this disclosure, controlling the adjustment of each vehicle window and the sunroof to the target opening degree corresponding to the recommended window opening scheme includes: The central control display screen shows a confirmation control for the recommended window opening scheme, or the user is prompted by voice to confirm the execution. In response to the user's confirmation command, control commands are sent to the drive motors of each window and the sunroof, and based on the control commands, each window and the sunroof are adjusted to the target opening degree corresponding to the recommended window opening scheme.

[0015] A second aspect of this disclosure provides a vehicle control device, including: The acquisition module is used to acquire the occupancy status of each seat in the vehicle and the current vehicle speed; The generation module is used to generate at least one candidate window opening scheme based on the passenger riding status and the current vehicle speed. Each candidate window opening scheme includes the target opening degree of each window and the sunroof. The determination module is used to determine the estimated wind noise value at the driver's seat under each candidate window opening scheme, and select a recommended window opening scheme from the at least one candidate window opening scheme based on the estimated wind noise value; The control module is used to control the adjustment of each window and the sunroof to the target opening degree corresponding to the recommended window opening scheme.

[0016] In some embodiments of this disclosure, when the generation module generates at least one candidate window opening scheme based on the passenger seating status and the current vehicle speed, it is specifically used for: Multiple initial window opening schemes were determined; The multiple initial window opening schemes are filtered based on the passenger seating status to obtain the filtered window opening schemes; A search algorithm is used to generate at least one candidate windowing scheme from the filtered windowing schemes.

[0017] In some embodiments of this disclosure, the search algorithm is a genetic algorithm; when the generation module uses the search algorithm to generate at least one candidate windowing scheme from the filtered windowing schemes, it is specifically used for: Using real-number encoding, the opening degree of each window and sunroof is used as an individual vector, and the fitness function is constructed with the goal of minimizing the estimated wind noise value at the driver's seat. The windowing scheme is iteratively optimized through selection, crossover, and mutation operations until the termination condition is met, and at least one individual vector with the highest fitness in the windowing scheme is selected as a candidate windowing scheme.

[0018] In some embodiments of this disclosure, when the determining module determines the estimated wind noise value at the driver's seat under each candidate window opening scheme, it is specifically used for: Construct a wind noise mapping model based on real vehicle wind tunnel test data or simulation data; The opening degree of each window and sunroof corresponding to each candidate window opening scheme and the current vehicle speed are input into the wind noise mapping model, and the estimated wind noise value at each seat is output through the wind noise mapping model.

[0019] In some embodiments of this disclosure, when the determining module selects a recommended window opening scheme from the at least one candidate window opening schemes based on the estimated wind noise value, it is specifically used for: The at least one candidate window opening scheme is ranked based on the estimated wind noise value; The recommended window opening scheme is determined based on the number of candidate window opening schemes with the lowest estimated wind noise value.

[0020] In some embodiments of this disclosure, when the determining module determines the recommended window opening scheme based on the top preset number of candidate window opening schemes with the smallest estimated wind noise value, it is specifically used for: The optimal window opening scheme is determined from the preset number of candidate window opening schemes with the lowest estimated wind noise value; The optimal window opening scheme is determined as the recommended window opening scheme.

[0021] In some embodiments of this disclosure, when the determining module determines the optimal window opening scheme from the preset number of candidate window opening schemes with the smallest estimated wind noise value, it is specifically used for: When the difference between the estimated wind noise values ​​at the driver's seat of each candidate window opening scheme is less than a preset threshold, the total wind noise value of the non-driver's seat in each candidate window opening scheme or the total opening degree value in each candidate window opening scheme is determined. The optimal window opening scheme is determined by the scheme with the lowest total wind noise or the highest total opening degree among all candidate window opening schemes.

[0022] In some embodiments of this disclosure, the device further includes a monitoring module and an updating module: The monitoring module is used to continuously monitor changes in vehicle speed and the occupancy status of each seat during operation. The update module is used to re-execute the steps of obtaining the seat occupants' seating status and current vehicle speed, generating candidate window opening schemes, selecting recommended window opening schemes, and prompting the user to update the window opening scheme when the change in vehicle speed exceeds a preset change threshold or the occupants' seating status changes.

[0023] In some embodiments of this disclosure, when the acquisition module acquires the occupancy status of each seat in the vehicle, it is specifically used for: The system identifies the occupant status of the driver's seat, front passenger seat, and rear seats using at least one of the following methods: seat pressure sensor, seatbelt buckle sensor, or in-vehicle camera.

[0024] In some embodiments of this disclosure, when the control module controls the adjustment of each window and the sunroof to the target opening degree corresponding to the recommended window opening scheme, it is specifically used for: The central control display screen shows a confirmation control for the recommended window opening scheme, or the user is prompted by voice to confirm the execution. In response to the user's confirmation command, control commands are sent to the drive motors of each window and the sunroof, and based on the control commands, each window and the sunroof are adjusted to the target opening degree corresponding to the recommended window opening scheme.

[0025] A third aspect of this disclosure provides an electronic device, including: processor; Memory, used to store executable instructions; The processor is used to read executable instructions from memory and execute the executable instructions to implement the vehicle control method provided in the first aspect above.

[0026] A fourth aspect of this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to implement the vehicle control method provided in the first aspect.

[0027] A fifth aspect of this disclosure provides a computer program product comprising a computer program or instructions that, when executed by a processor, implement the vehicle control method of the first aspect described above.

[0028] A sixth aspect of this disclosure provides a vehicle that includes electronic equipment provided in the third aspect.

[0029] The technical solution provided in this disclosure has the following advantages: The vehicle control method and vehicle provided in this disclosure can acquire the occupant status of each seat and the current vehicle speed. Based on the occupant status and the current vehicle speed, at least one candidate window opening scheme is generated. Further, the estimated wind noise value at the driver's seat under each candidate window opening scheme is determined, and a recommended window opening scheme is selected from the at least one candidate window opening scheme based on the estimated wind noise value. Then, the windows and sunroof are controlled to adjust to the target opening degree corresponding to the recommended window opening scheme. Thus, by acquiring the occupant status and vehicle speed of each seat, generating candidate window opening schemes, selecting a recommended scheme based on the estimated wind noise at the driver's seat, and executing it with one click, automated low-noise window opening control is achieved. This solves the problem that users find it difficult to manually find the optimal combination, prioritizes a low-noise environment for the driver, and improves driving safety. Attached Figure Description

[0030] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0031] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a flowchart of a vehicle control method provided in an embodiment of this disclosure; Figure 2 This is a flowchart of another vehicle control method provided in this disclosure embodiment; Figure 3 This is a flowchart of yet another vehicle control method provided in this disclosure embodiment; Figure 4 This is a schematic diagram of the structure of a vehicle control device provided in an embodiment of this disclosure; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0033] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0034] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0035] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0036] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0037] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0038] When a user opens the side windows or sunroof for ventilation while the vehicle is in motion, the airflow interacts with the window gaps, rearview mirrors, and vehicle pillars, generating wind noise. The intensity of wind noise increases non-linearly with vehicle speed.

[0039] Existing vehicles only offer manual control of windows and sunroofs, or basic functions such as one-touch up / down, but cannot intelligently adjust the opening and closing combinations of windows and sunroofs. This makes it particularly difficult to ensure a low-noise environment on the driver's side, resulting in a difficulty in balancing ventilation needs with ride comfort. Furthermore, excessive wind noise on the driver's side can directly interfere with the driver's attention and affect driving safety. Therefore, this disclosure provides a vehicle control method, which will be described below with reference to specific embodiments.

[0040] Figure 1This is a flowchart of a vehicle control method provided in an embodiment of the present disclosure. The method can be executed by a vehicle control device, which can be implemented in software and / or hardware. The vehicle control device can be configured in an electronic device, such as a server or terminal, wherein the terminal specifically includes an in-vehicle terminal, a computer, or a tablet computer, etc.

[0041] like Figure 1 As shown, the vehicle control method provided in this disclosure can be applied to the field of smart cockpit technology. For example, it can be used to control vehicle windows. The vehicle control method may include the following steps: S110: Obtain the occupancy status of each seat in the vehicle and the current vehicle speed.

[0042] In this embodiment, seat pressure sensors can be used to detect whether anyone is seated in each seat. For example, if the driver's seat pressure sensor detects a pressure value exceeding a preset threshold, it indicates that someone is in the driver's seat; if the passenger seat pressure sensor does not detect a valid pressure signal, it indicates that no one is in the passenger seat; if the rear left and rear right pressure sensors detect signals respectively, it indicates that someone is in both the rear left and rear right seats. Simultaneously, the current vehicle speed signal is read in real time via the CAN bus, for example, if the current vehicle speed is 80 km / h.

[0043] In some embodiments, obtaining the occupancy status of each seat in the vehicle includes: identifying the occupancy status of the driver's seat, the front passenger seat, and each rear seat by means of at least one of a seat pressure sensor, a seatbelt buckle sensor, or an in-vehicle camera.

[0044] In this step, at least one of the following methods is used to identify whether the driver's seat, front passenger seat, and rear seats are occupied: seat pressure sensors, seatbelt buckle sensors, or in-vehicle cameras. For example, if the driver's seat pressure sensor detects a pressure value greater than a preset threshold and the seatbelt buckle is locked, it is determined that the driver's seat is occupied; if the front passenger seat pressure sensor shows no effective pressure, it is determined that the front passenger seat is unoccupied; if the rear left seat camera detects a human silhouette, it is determined that the rear left seat is occupied. This step provides the basis for subsequently eliminating unreasonable window opening schemes.

[0045] The embodiments disclosed herein identify seat occupancy through multiple methods such as pressure sensors, seat belt sensors, or cameras, thereby improving the reliability and redundancy of detection and avoiding misjudgments due to the failure of a single sensor.

[0046] S120. Based on the passenger riding status and the current vehicle speed, generate at least one candidate window opening scheme, wherein each candidate window opening scheme includes the target opening degree of each window and the sunroof.

[0047] In this embodiment of the disclosure, at least one candidate window opening scheme is generated based on the passenger seating status and the current vehicle speed. For example, windows need to be opened in occupied seats and not in unoccupied seats, and the window opening range is determined based on the vehicle speed. Alternatively, which windows to open can be determined based on the user's window opening habits.

[0048] Optionally, the set of adjustable windows can be determined based on the occupant status. Since the front passenger seat is unoccupied, the front passenger side window is forcibly set to fully closed (0% opening / closing) and will not participate in subsequent optimization. The rear left, rear right, and driver's side windows can participate in optimization if someone is present. The sunroof can always participate in optimization. Based on the combination of opening / closing degrees of each window, candidate window opening schemes are obtained.

[0049] S130. Determine the estimated wind noise value at the driver's seat under each candidate window opening scheme, and select a recommended window opening scheme from the at least one candidate window opening scheme based on the estimated wind noise value.

[0050] In this embodiment of the disclosure, after obtaining at least one candidate window opening scheme, the estimated wind noise value at the driver's seat under each candidate window opening scheme can be determined. Optionally, the estimated wind noise value at each seat can be calculated based on a wind noise prediction algorithm to obtain the estimated wind noise value at the driver's seat. Further, a recommended window opening scheme is selected from the at least one candidate window opening scheme based on the estimated wind noise value. For example, a candidate window opening scheme with an estimated wind noise value lower than a first threshold is selected as the recommended window opening scheme.

[0051] S140. Control each window and the sunroof to adjust to the target opening degree corresponding to the recommended window opening scheme.

[0052] In this embodiment of the disclosure, the user can select and confirm a recommended window opening scheme. In response to the user's confirmation of the recommended window opening scheme, the system controls the adjustment of each window and the sunroof to the target opening degree corresponding to the recommended window opening scheme. For example, the target opening degree corresponding to the recommended window opening scheme is: driver's side window opening degree 20%, passenger side window opening degree 0%, rear left window opening degree 10%, rear right window opening degree 8%, and sunroof opening degree 40%.

[0053] In some embodiments, the final opening / closing combinations of the user's past N (e.g., 50) manual window opening operations, along with the corresponding vehicle speed and seat occupancy status, can be recorded to form a personalized preference vector. For example, statistics may show that users tend not to open the driver's side window in most cases (the average opening degree of the driver's side window is only 8%), but are more willing to open the sunroof. Therefore, when generating candidate solutions, a tighter upper limit constraint (e.g., not exceeding 15%) can be imposed on the opening degree of the driver's side window, or a higher weight can be given to the sunroof opening degree.

[0054] Specifically, a personalized reward is added to the fitness function. If the driver's side window opening of a candidate window opening scheme is close to the user's historical average opening, a small fitness reward is added; if the sunroof opening is close to the user's preference, a reward is also given. This makes the final recommended scheme more in line with user habits. Through personalized learning, it can adapt to the habits of different drivers, further improving user satisfaction.

[0055] Therefore, in this embodiment, the occupant status of each seat in the vehicle and the current vehicle speed can be obtained. Based on the occupant status and the current vehicle speed, at least one candidate window opening scheme is generated. Further, the estimated wind noise value at the driver's seat under each candidate window opening scheme is determined, and a recommended window opening scheme is selected from the at least one candidate window opening scheme based on the estimated wind noise value. Then, the windows and the sunroof are controlled to adjust to the target opening degree corresponding to the recommended window opening scheme. Thus, by obtaining the occupant status and vehicle speed of each seat, generating candidate window opening schemes, selecting a recommended scheme based on the estimated wind noise at the driver's seat, and executing it with one click, automated low-noise window opening control is achieved. This solves the problem that users find it difficult to manually find the optimal combination, prioritizes a low-noise environment for the driver, and improves driving safety.

[0056] Optionally, S130 determines the estimated wind noise value at the driver's seat under each candidate window opening scheme, which may specifically include S1301 and S1302: S1301. Construct a wind noise mapping model based on real vehicle wind tunnel test data or simulation data; In this step, the wind noise mapping model can employ a surrogate model based on neural network regression. The model can be trained offline or online, without limitation. Specifically, approximately 5000 sets of data can be generated using Latin hypercube sampling, covering vehicle speeds from 20 to 120 km / h and combinations of seat opening degrees from 0 to 1. The sound pressure level (SPL) for the driver, front passenger, left rear seat, and right rear seat in each data set is obtained through CFD simulation or real-vehicle wind tunnel experiments as labels. The network structure of the wind noise mapping model is as follows: input layer (vehicle speed + 5 seat opening degrees, 6 neurons in total), two hidden layers each with 32 neurons (ReLU activation), and output layer with 4 neurons (SPL for each seat, linear output). After training, the model size is only a few KB.

[0057] In some embodiments, the training process of the wind noise mapping model may include the following steps: 1) Data Acquisition: In the wind tunnel laboratory, tests were conducted on different vehicle models (based on this vehicle). Vehicle speed gradients were set: 20, 40, 60, 80, 100, and 120 km / h; each window opening combination was sampled using Latin hypercube sampling, generating a total of 5000 combinations. For each combination, the wind noise pressure level (SPL) was measured at four positions: driver's seat, passenger's seat, left rear, and right rear.

[0058] 2) Data preprocessing: The input (vehicle speed normalized to [0,1], opening degree directly used [0,1]) and output (SPL value, in dB) are standardized.

[0059] 3) Network Training: Using the Adam optimizer and mean squared error loss function, train for 100 epochs. The training set to validation set ratio is 8:2. After training, the model parameters are stored in the ECU's ROM as floating-point numbers.

[0060] 4) Online Inference: While the vehicle is running, the current vehicle speed and opening / closing degree are input into the model, and the output is calculated by a lightweight inference engine (such as TFLite Micro). The entire inference process takes no more than 1ms, meeting real-time requirements.

[0061] Compared to the lookup table method, the wind noise mapping model has a smaller memory footprint and stronger generalization ability.

[0062] S1302. Input the opening degree of each window and sunroof corresponding to each candidate window opening scheme and the current vehicle speed into the wind noise mapping model, and output the estimated wind noise value at each seat through the wind noise mapping model.

[0063] In this step, the current vehicle speed (e.g., 72 km / h) and the opening / closing vector of the candidate scheme (e.g., [0.15,0,0.08,0,0.2]) can be input into the model to calculate the driver's SPL = 58 dB, the passenger's SPL = 52 dB, the rear left SPL = 55 dB, and the rear right SPL = 60 dB. The inference time is less than 1 ms.

[0064] Therefore, in this embodiment of the present disclosure, by constructing a wind noise mapping model, the seat wind noise value under different combinations of vehicle speed and opening degree can be accurately predicted, providing a reliable evaluation basis for optimization, and the online inference speed is fast, making it suitable for in-vehicle embedded environments.

[0065] Figure 2 This is a flowchart of another vehicle control method provided in this embodiment.

[0066] like Figure 2 As shown, the vehicle control method may include the following steps: S310: Obtain the occupancy status of each seat in the vehicle and the current vehicle speed.

[0067] Specifically, the implementation process and principle of S310 and S110 are the same, and will not be repeated here.

[0068] S320. Determine multiple initial window opening schemes.

[0069] The initial window opening scheme space is determined based on the number of adjustable windows. For example, for a configuration with four windows plus a sunroof, without considering any constraints, the window opening scheme space includes all possible continuous combinations of opening degrees. In some embodiments, the initial window opening scheme can also be determined based on the user's window opening habits. For example, the user's preferred window opening combination could be the driver's side + right rear window, or the driver's side + passenger side window; or different window opening combinations could be used in different driving scenarios, such as highway scenarios and city scenarios, with the driver's side slightly open and the sunroof mainly open at high speeds, and the driver's side + passenger side window open in city scenarios; or different window opening combinations could be used in different speed ranges, etc.

[0070] S330. Based on the passenger seating status, the multiple initial window opening schemes are filtered to obtain the filtered window opening schemes.

[0071] In some embodiments, the filtering rules differ depending on the seat usage. For example, when a seat is unoccupied, the filtering rules include selecting window opening schemes where the opening degree of the window corresponding to the unoccupied seat is zero; or, if the driver needs ventilation, selecting window opening schemes where the opening degree of the window corresponding to the driver is greater than or equal to a preset opening degree threshold.

[0072] Optionally, the filtering rules may include selecting window opening schemes where the window opening degree is zero for seats where the occupant status indicates no occupant. In some embodiments, the filtering rules may include selecting window opening schemes where the window opening degree for the driver's seat is greater than or equal to a preset opening degree threshold. In other embodiments, the filtering rules may include selecting window opening schemes where the window opening degree is zero for seats where the occupant status indicates no occupant, and selecting window opening schemes where the window opening degree for the driver's seat is greater than or equal to a preset opening degree threshold. In still other embodiments, other filtering rules may also be included, which are not specifically limited here. For example, the occupant status is: occupant in the driver's seat, occupant in the front passenger seat, occupant in the left rear seat, and occupant in the right rear seat. According to the filtering rules, the scheme where the front passenger window opening degree is zero for occupant is retained, and the remaining schemes are discarded. For another example, if the current vehicle only has occupants in the driver's seat and the right rear seat, then in the filtered schemes, the front passenger window and the left rear window will both have an opening degree of 0. Optionally, a preset opening threshold of 5% is set to ensure that the driver's side window is opened at least 5% to guarantee basic ventilation on the driver's side. During the screening process, the opening degree of the driver's side window must be greater than or equal to the preset opening threshold, meaning that the value of the driver's side window is limited to the range of [0.05, 1].

[0073] S340. Use a search algorithm to generate at least one candidate windowing scheme from the filtered windowing schemes.

[0074] In this step, a search algorithm is used to generate multiple possible window opening combinations. Each combination includes the opening degree (0%~100% continuous value) of the left front window, right front window, left rear window, right rear window, and sunroof. For example, five candidate schemes are generated: Scheme A (driver's side 15%, passenger side 0%, left rear 8%, right rear 0%, sunroof 20%), Scheme B (driver's side 10%, passenger side 5%, left rear 0%, right rear 0%, sunroof 15%), etc.

[0075] This embodiment determines multiple initial window opening schemes, filters out schemes with zero window opening for unoccupied seats and driver's side window opening not lower than a threshold based on passenger seating status, and then uses a search algorithm to generate candidate schemes, effectively reducing the search space, eliminating unreasonable schemes, and improving optimization efficiency and scheme feasibility.

[0076] In some embodiments, the search algorithm is a genetic algorithm; S340 includes S3401 and S3402: S3401. Using real number encoding, the opening degree of each window and sunroof is used as an individual vector, and the fitness function is constructed with the goal of minimizing the estimated wind noise value at the driver's seat.

[0077] In this step, each window opening scheme is represented as an individual vector [x1, x2, x3, x4, x5], corresponding to the opening degree of the front left, front right, rear left, rear right, and sunroof, respectively, with values ​​ranging from [0,1]. For example, individual A = [0.15, 0, 0.08, 0,0.2]. A fitness function is constructed with the optimization objective of minimizing the estimated wind noise value at the driver's seat. The fitness function can be expressed as F(x) = -SPL_driver(x, v), where SPL_driver is the estimated wind noise value at the driver's seat, x represents any window opening scheme, and v represents the vehicle speed. Since the objective is to minimize the wind noise at the driver's seat, the fitness function takes a negative value; a larger fitness value indicates lower wind noise.

[0078] S3402. Iteratively optimize the windowing scheme through selection, crossover and mutation operations until the termination condition is met, and select at least one individual vector with the highest fitness in the windowing scheme as a candidate windowing scheme.

[0079] Specifically, the following iterative steps are performed: 1) Initialization: Randomly generate 100 individuals, ensuring that the component corresponding to the unmanned seat is forced to be 0, and the driver component is ≥0.05.

[0080] 2) Selection: Tournament selection, three individuals are randomly selected each time, and the one with the highest fitness is taken as the parent.

[0081] 3) Crossover: Simulate binary crossover (SBX), with a crossover probability of 0.9.

[0082] 4) Mutation: Polynomial mutation (PM), with a mutation probability of 1 / 5 = 0.2.

[0083] 5) Elite retention: The two best individuals from each generation are retained and directly enter the next generation.

[0084] 6) Termination condition: After 50 iterations, or after 10 consecutive iterations, the change in optimal fitness is less than 0.1dB.

[0085] 7) Output: Select the top 5 individuals with the highest fitness in the final population as candidate windowing schemes.

[0086] This embodiment uses a genetic algorithm with the goal of minimizing real number encoding and driver wind noise. Through iterative optimization using selection, crossover, mutation, and elite retention operations, it can efficiently handle nonlinear optimization problems with multi-degree-of-freedom continuous variables, overcome the drawback of excessive computational cost of full enumeration, and ensure real-time performance.

[0087] S350. Determine the estimated wind noise value at the driver's seat under each candidate window opening scheme.

[0088] In this step, the estimated wind noise level at the driver's seat for each candidate window opening scheme can be determined based on the vehicle speed and the combination of opening and closing degrees for each scheme. For example, scheme A estimates the driver's seat wind noise at 58 dB, while scheme B estimates it at 62 dB.

[0089] S360. Sort the at least one candidate window opening scheme based on the estimated wind noise value.

[0090] For example, five candidate schemes were generated, with estimated wind noise levels for the driver's seat as follows: Scheme A = 58dB, Scheme B = 62dB, Scheme C = 57dB, Scheme D = 59dB, and Scheme E = 61dB. These schemes are sorted from smallest to largest wind noise value as follows: C(57), A(58), D(59), E(61), B(62). Alternatively, they can be sorted from largest to smallest wind noise value as follows: B(62), E(61), D(59), A(58), C(57), without restriction.

[0091] S370. Determine the recommended window opening scheme based on the preset number of candidate window opening schemes with the lowest estimated wind noise value.

[0092] For example, if the preset number is 3, the three options with the lowest estimated wind noise values, namely C, A, and D, will be selected as recommended window opening options and displayed on the central control screen for the user to choose from. The user can see a brief description of each option (such as "Option C: Driver's side window open 12%, sunroof tilted up, estimated wind noise 57dB").

[0093] This embodiment sorts the options according to the estimated wind noise value and selects a preset number of options, ensuring that the wind noise of the driver's side of the recommended option is at the optimal level. The selection method is simple and efficient, while avoiding the confusion of giving users too many choices.

[0094] S380. Display the confirmation control for the recommended window opening scheme on the central control display screen, or prompt the user to confirm the execution via voice broadcast.

[0095] In this step, a card pops up on the vehicle's central control screen, displaying a diagram of the recommended window opening scheme and the estimated wind noise level, with a "One-Click Execution" confirmation button below. The user clicks the button to send a confirmation command. Alternatively, the system can announce through the car's audio system, "A minimum wind noise window opening scheme has been generated for you. Execute?" The user answers "Confirm" or "Yes," and the voice recognition module receives the command.

[0096] S390. In response to the user's confirmation command, a control command is sent to the drive motors of each window and the sunroof, and the windows and the sunroof are adjusted to the target opening degree corresponding to the recommended window opening scheme based on the control command.

[0097] In this step, after user confirmation, the target position command (e.g., the number of pulses corresponding to a 15% opening for the left front window) is sent to each window motor and sunroof motor via the LIN bus or CAN bus. The motor drives the window regulator or sunroof sunshade to the designated position, and the actual position is fed back through Hall sensors, forming a closed-loop control.

[0098] This embodiment provides an intuitive and convenient human-computer interaction method by receiving confirmation commands through a central control screen or voice prompts. Users can decide whether to execute the commands, thus balancing automation and user control.

[0099] This embodiment of the disclosure acquires the occupant seating status and current vehicle speed of each seat inside the vehicle. Then, multiple initial window opening schemes are determined, and these schemes are filtered based on the occupant seating status to obtain filtered window opening schemes. A search algorithm is then used to generate at least one candidate window opening scheme from the filtered schemes. Further, the estimated wind noise value at the driver's seat for each candidate window opening scheme is determined, and the at least one candidate window opening scheme is sorted based on the estimated wind noise value. A recommended window opening scheme is determined based on the top preset number of candidate window opening schemes with the lowest estimated wind noise values. A confirmation control for the recommended window opening scheme is displayed on the central control screen, or a voice prompt is given to the user to confirm execution. In response to the user's confirmation command, control commands are sent to the drive motors of each window and the sunroof, adjusting each window and the sunroof to the target opening degree corresponding to the recommended window opening scheme based on the control commands. Therefore, by determining multiple initial window opening schemes, the schemes with zero window opening for unoccupied seats and driver's side window opening not lower than a threshold are selected based on the passenger seating status. Then, a search algorithm is used to generate candidate schemes, which effectively reduces the search space, eliminates unreasonable schemes, improves optimization efficiency and scheme feasibility, and sorts the schemes according to the estimated wind noise value and selects the first preset number of schemes to ensure that the recommended scheme has the optimal wind noise level for the driver's side. The selection method is simple and efficient, while avoiding overwhelming users with too many choices.

[0100] Figure 3 This is a flowchart of another vehicle control method provided in the embodiments of this disclosure.

[0101] like Figure 3 As shown, the vehicle control method may include the following steps: S410: Obtain the occupancy status of each seat in the vehicle and the current vehicle speed.

[0102] Specifically, the implementation process and principle of S410 and S110 are the same, and will not be repeated here.

[0103] S420. Based on the passenger seating status and the current vehicle speed, generate at least one candidate window opening scheme.

[0104] Specifically, the implementation process and principle of S420 and S120 are the same, and will not be repeated here.

[0105] S430. Determine the estimated wind noise value at the driver's seat under each candidate window opening scheme, and select a recommended window opening scheme from the at least one candidate window opening scheme based on the estimated wind noise value.

[0106] Specifically, the implementation process and principle of S430 and S130 are the same, and will not be repeated here.

[0107] S440. Determine the optimal window opening scheme from the preset number of candidate window opening schemes with the smallest estimated wind noise value.

[0108] In this step, the optimal window opening scheme will be determined from a preset number of candidate schemes. For example, there are three candidate schemes: C (driver's side 57dB), A (58dB), and D (59dB). Users may not care about a difference of 1-2dB, but they would prefer lower wind noise or greater ventilation in the rear seats.

[0109] In this embodiment of the disclosure, when there are multiple candidate windowing schemes, the optimal windowing scheme is further determined, and then the optimal windowing scheme is determined as the recommended scheme, which avoids the user's decision-making confusion when faced with multiple options and improves the convenience of interaction.

[0110] In some embodiments, S440 includes S4401 and S4402: S4401. When the difference between the estimated wind noise values ​​at the driver's seat of each candidate window opening scheme is less than a preset threshold, determine the total wind noise value of the non-driver's seat in each candidate window opening scheme or the total opening degree value in each candidate window opening scheme. In this step, for example, there are three recommended window opening options: C (driver's seat 57dB), A (58dB), and D (59dB), with a preset threshold of 2dB. When the difference in the estimated wind noise value at the driver's seat for each candidate window opening option is less than the preset threshold, the total wind noise of the passenger seat and rear seats is further compared, or the total opening degree of all windows is compared (ventilation volume).

[0111] S4402. The scheme with the smallest total wind noise or the largest total opening degree among the candidate window opening schemes is determined as the optimal window opening scheme.

[0112] For example, the total wind noise in option C (non-driver's side) is 65dB, option A is 70dB, and option D is 68dB. Option C has the lowest total wind noise, so C is selected as the optimal window opening option. Optionally, the optimal option can be automatically selected based on the user's preset preferences (e.g., selecting "prefer quiet" or "prefer ventilation" in vehicle settings). If the user prefers ventilation, the option with the highest total opening degree among the candidate window opening options is determined as the optimal window opening option. The total opening degree is calculated as follows: Option C = 0.12 + 0 + 0.05 + 0 + 0.18 = 0.35, Option A = 0.15 + 0 + 0.08 + 0 + 0.2 = 0.43, and Option D = 0.1 + 0.05 + 0 + 0 + 0.25 = 0.4. Therefore, Option A is selected as the optimal option. If the user prefers quiet, the option with the lowest total wind noise among the candidate window opening options is determined as the optimal window opening option. Ultimately, only one optimal solution is displayed for user confirmation, simplifying the user's decision-making process.

[0113] In this embodiment, when the difference in wind noise between the driver and passengers is less than a threshold, secondary optimization is performed by minimizing the total wind noise of the non-driver area or maximizing the total opening and closing value. This achieves a multi-objective balance under the premise of prioritizing the driver's seat, taking into account the comfort or ventilation needs of the entire vehicle.

[0114] S450. The optimal window opening scheme is determined as the recommended window opening scheme.

[0115] In this step, after obtaining the optimal windowing scheme, the optimal windowing scheme is determined as the recommended windowing scheme.

[0116] S460, Control each window and the sunroof to adjust to the target opening degree corresponding to the recommended window opening scheme.

[0117] Specifically, the implementation process and principle of S460 and S140 are the same, and will not be repeated here.

[0118] S470 continuously monitors changes in vehicle speed and the occupancy status of each seat during operation.

[0119] In this step, for example, the vehicle speed and seat occupancy status are read at a frequency of 1Hz.

[0120] S480. When the change in vehicle speed exceeds a preset change threshold or the passenger seating status changes, the steps of obtaining the passenger seating status and current vehicle speed, generating candidate window opening schemes, selecting recommended window opening schemes are re-executed, and the user is prompted to update the window opening scheme.

[0121] In this step, for example, the preset change threshold is ±5 km / h. For instance, if the current vehicle speed is 72 km / h, the recommended window opening scheme is generated based on 72 km / h. When the vehicle speed increases to 80 km / h (a change of 8 km / h > 5), the entire process will be rerun to generate a new window opening scheme suitable for 80 km / h. For example, if the front passenger gets out of the vehicle midway, the seat pressure sensor detects the pressure disappearing, so the scheme is recalculated, forcibly setting the front passenger window to 0. After the new scheme is generated, the central control screen will display a prompt: "Vehicle speed / seat position has changed; the window opening scheme has been updated for you. Execute?" The user can choose to confirm or ignore. If the user ignores, the current window status remains unchanged; if the user confirms, the window opening is controlled based on the new window opening scheme.

[0122] This embodiment of the disclosure acquires the occupant seating status of each seat in the vehicle and the current vehicle speed. Based on the occupant seating status and the current vehicle speed, at least one candidate window opening scheme is generated. Further, the estimated wind noise value at the driver's seat under each candidate window opening scheme is determined. Based on the estimated wind noise value, a recommended window opening scheme is selected from the at least one candidate window opening scheme. From the top preset number of candidate window opening schemes with the smallest estimated wind noise value, the optimal window opening scheme is determined and designated as the recommended window opening scheme. Then, the windows and the sunroof are controlled to adjust to the target opening degree corresponding to the recommended window opening scheme. Furthermore, during driving, changes in vehicle speed and occupant seating status are continuously monitored. When the change in vehicle speed exceeds a preset change threshold or the occupant seating status changes, the steps of acquiring the occupant seating status and current vehicle speed, generating candidate window opening schemes, and selecting a recommended window opening scheme are re-executed, and the user is prompted to update the window opening scheme. Therefore, by continuously monitoring changes in vehicle speed and seat status and automatically updating the window opening scheme, the system can dynamically adapt to changes in driving conditions and occupants, always maintaining the optimal state and enhancing environmental adaptability.

[0123] Figure 4 This is a schematic diagram of the structure of a vehicle control device provided in an embodiment of this disclosure.

[0124] In this embodiment, the vehicle control device can be housed within an electronic device and is understood as a functional module within the aforementioned electronic device. Specifically, the electronic device can be a server or a terminal, wherein the terminal specifically includes an in-vehicle terminal, a computer, or a tablet computer, etc., without limitation.

[0125] like Figure 4 As shown, the vehicle control device 700 may include an acquisition module 710, a generation module 720, a determination module 730, and a control module 740.

[0126] The acquisition module 710 is used to acquire the occupancy status of each seat in the vehicle and the current vehicle speed; The generation module 720 is used to generate at least one candidate window opening scheme based on the passenger riding status and the current vehicle speed. Each candidate window opening scheme includes the target opening degree of each window and the sunroof. The determining module 730 is used to determine the estimated wind noise value at the driver's seat under each candidate window opening scheme, and select a recommended window opening scheme from the at least one candidate window opening scheme based on the estimated wind noise value; The control module 740 is used to control the adjustment of each window and the sunroof to the target opening degree corresponding to the recommended window opening scheme.

[0127] In some embodiments of this disclosure, when the generation module 720 generates at least one candidate window opening scheme based on the passenger seating status and the current vehicle speed, it is specifically used for: Multiple initial window opening schemes were determined; The multiple initial window opening schemes are filtered based on the passenger seating status to obtain the filtered window opening schemes; A search algorithm is used to generate at least one candidate windowing scheme from the filtered windowing schemes.

[0128] In some embodiments of this disclosure, the search algorithm is a genetic algorithm; when the generation module 720 uses the search algorithm to generate at least one candidate windowing scheme from the filtered windowing schemes, it is specifically used for: Using real-number encoding, the opening degree of each window and sunroof is used as an individual vector, and the fitness function is constructed with the goal of minimizing the estimated wind noise value at the driver's seat. The windowing scheme is iteratively optimized through selection, crossover, and mutation operations until the termination condition is met, and at least one individual vector with the highest fitness in the windowing scheme is selected as a candidate windowing scheme.

[0129] In some embodiments of this disclosure, when the determining module 730 determines the estimated wind noise value at the driver's seat under each candidate window opening scheme, it is specifically used for: Construct a wind noise mapping model based on real vehicle wind tunnel test data or simulation data; The opening degree of each window and sunroof corresponding to each candidate window opening scheme and the current vehicle speed are input into the wind noise mapping model, and the estimated wind noise value at each seat is output through the wind noise mapping model.

[0130] In some embodiments of this disclosure, when the determining module 730 selects a recommended window opening scheme from the at least one candidate window opening scheme based on the estimated wind noise value, it is specifically used for: The at least one candidate window opening scheme is ranked based on the estimated wind noise value; The recommended window opening scheme is determined based on the number of candidate window opening schemes with the lowest estimated wind noise value.

[0131] In some embodiments of this disclosure, when the determining module 730 determines the recommended window opening scheme based on the first preset number of candidate window opening schemes with the smallest estimated wind noise value, it is specifically used for: The optimal window opening scheme is determined from the preset number of candidate window opening schemes with the lowest estimated wind noise value; The optimal window opening scheme is determined as the recommended window opening scheme.

[0132] In some embodiments of this disclosure, when the determining module 730 determines the optimal window opening scheme from the preset number of candidate window opening schemes with the smallest estimated wind noise value, it is specifically used for: When the difference between the estimated wind noise values ​​at the driver's seat of each candidate window opening scheme is less than a preset threshold, the total wind noise value of the non-driver's seat in each candidate window opening scheme or the total opening degree value in each candidate window opening scheme is determined. The optimal window opening scheme is determined by the scheme with the lowest total wind noise or the highest total opening degree among all candidate window opening schemes.

[0133] In some embodiments of this disclosure, the device further includes a monitoring module 750 and an updating module 760; The monitoring module 750 is used to continuously monitor changes in vehicle speed and changes in the seating status of passengers in each seat during driving. The update module 760 is used to re-execute the steps of obtaining the seat occupants' seating status and current vehicle speed, generating candidate window opening schemes, selecting recommended window opening schemes, and prompting the user to update the window opening scheme when the change in vehicle speed exceeds a preset change threshold or the occupants' seating status changes.

[0134] In some embodiments of this disclosure, when the control module 740 controls the adjustment of each window and the sunroof to the target opening degree corresponding to the recommended window opening scheme, it is specifically used for: The central control display screen shows a confirmation control for the recommended window opening scheme, or the user is prompted by voice to confirm the execution. In response to the user's confirmation command, control commands are sent to the drive motors of each window and the sunroof, and based on the control commands, each window and the sunroof are adjusted to the target opening degree corresponding to the recommended window opening scheme.

[0135] It should be noted that, Figure 4 The vehicle control device 700 shown can execute the various steps in the above method embodiments and realize the various processes and effects in the above method embodiments, which will not be elaborated here.

[0136] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure.

[0137] In this embodiment of the disclosure, Figure 5 The electronic device shown can be a server or a terminal. Specifically, the terminal includes in-vehicle terminals, computers, or tablets, etc., without limitation.

[0138] like Figure 5 As shown, the electronic device may include a processor 810 and a memory 820 storing computer program instructions.

[0139] Specifically, the processor 810 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this disclosure.

[0140] Memory 820 may include mass storage for information or instructions. For example, and not limitingly, memory 820 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 820 may include removable or non-removable (or fixed) media. Where appropriate, memory 820 may be internal or external to the integrated gateway device. In a particular embodiment, memory 820 is non-volatile solid-state memory. In a particular embodiment, memory 820 includes read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (Electrically Programmable ROM, EPROM), an electrically erasable PROM (EEPROM), an electrically alterable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0141] The processor 810 reads and executes computer program instructions stored in the memory 820 to perform the steps of the vehicle control method provided in the embodiments of this disclosure.

[0142] In one example, the electronic device may also include a transceiver 830 and a bus 840. Wherein, as... Figure 5 As shown, the processor 810, memory 820 and transceiver 830 are connected via bus 840 and communicate with each other.

[0143] Bus 840 may include hardware, software, or both. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industrial Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 840 may include one or more buses.

[0144] This disclosure also provides a computer-readable storage medium that can store a computer program that, when executed by a processor, enables the processor to implement the vehicle control method provided in this disclosure.

[0145] When the computer program is executed by the processor, it can perform the following steps: acquire the occupant status of each seat in the vehicle and the current vehicle speed; based on the occupant status and the current vehicle speed, generate at least one candidate window opening scheme, each of the at least one candidate window opening scheme including the target opening degree of each window and the sunroof; determine the estimated wind noise value at the driver's seat under each candidate window opening scheme, and select a recommended window opening scheme from the at least one candidate window opening scheme according to the estimated wind noise value; control each window and the sunroof to adjust to the target opening degree corresponding to the recommended window opening scheme.

[0146] The aforementioned storage medium may, for example, include a memory 820 containing computer program instructions, which can be executed by a processor 810 of an electronic device to perform the vehicle control method provided in the embodiments of this disclosure. Optionally, the storage medium may be a non-transitory computer-readable storage medium, such as a read-only memory (ROM), random access memory (RAM), external cache memory, compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, flash memory, and optical data storage device. By way of illustration and not limitation, RAM is available in various forms, such as static random access memory (SRAM) and dynamic random access memory (DRAM).

[0147] This disclosure also provides a vehicle that includes electronic devices that can implement the various processes and effects described in the above embodiments of this disclosure, which will not be elaborated here.

[0148] This disclosure also provides a computer program product, which includes a computer program or instructions. When the computer program or instructions are executed by a processor, they implement the vehicle control method provided in this disclosure and can achieve the various processes and effects in the above embodiments of this disclosure, which will not be elaborated here.

[0149] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A vehicle control method, characterized in that, The method includes: Obtain the occupancy status of each seat in the vehicle and the current vehicle speed; Based on the passenger seating status and the current vehicle speed, at least one candidate window opening scheme is generated, and each candidate window opening scheme includes the target opening degree of each window and the sunroof. Determine the estimated wind noise value at the driver's seat under each candidate window opening scheme, and select a recommended window opening scheme from the at least one candidate window opening scheme based on the estimated wind noise value; Control each window and the sunroof to adjust to the target opening degree corresponding to the recommended window opening scheme.

2. The method according to claim 1, characterized in that, The step of generating at least one candidate window opening scheme based on the passenger seating status and the current vehicle speed includes: Multiple initial window opening schemes were determined; The multiple initial window opening schemes are filtered based on the passenger seating status to obtain the filtered window opening schemes; A search algorithm is used to generate at least one candidate windowing scheme from the filtered windowing schemes.

3. The method according to claim 2, characterized in that, The search algorithm is a genetic algorithm; the step of generating at least one candidate windowing scheme using the search algorithm on the screened windowing schemes includes: Using real-number encoding, the opening degree of each window and sunroof is used as an individual vector, and the fitness function is constructed with the goal of minimizing the estimated wind noise value at the driver's seat. The windowing scheme is iteratively optimized through selection, crossover, and mutation operations until the termination condition is met, and at least one individual vector with the highest fitness in the windowing scheme is selected as a candidate windowing scheme.

4. The method according to claim 1, characterized in that, Determining the estimated wind noise value at the driver's seat under each candidate window opening scheme includes: Construct a wind noise mapping model based on real vehicle wind tunnel test data or simulation data; The opening degree of each window and sunroof corresponding to each candidate window opening scheme and the current vehicle speed are input into the wind noise mapping model, and the estimated wind noise value at each seat is output through the wind noise mapping model.

5. The method according to claim 1, characterized in that, The step of selecting a recommended window opening scheme from the at least one candidate window opening schemes based on the estimated wind noise value includes: The at least one candidate window opening scheme is ranked based on the estimated wind noise value; The recommended window opening scheme is determined based on the number of candidate window opening schemes with the lowest estimated wind noise value.

6. The method according to claim 1, characterized in that, The step of determining the recommended window opening scheme based on the first preset number of candidate window opening schemes with the lowest estimated wind noise value includes: The optimal window opening scheme is determined from the preset number of candidate window opening schemes with the lowest estimated wind noise value; The optimal window opening scheme is determined as the recommended window opening scheme.

7. The method according to claim 6, characterized in that, The step of determining the optimal window opening scheme from the preset number of candidate window opening schemes with the lowest estimated wind noise value includes: When the difference between the estimated wind noise values ​​at the driver's seat of each candidate window opening scheme is less than a preset threshold, the total wind noise value of the non-driver's seat in each candidate window opening scheme or the total opening degree value in each candidate window opening scheme is determined. The optimal window opening scheme is determined by the scheme with the lowest total wind noise or the highest total opening degree among all candidate window opening schemes.

8. The method according to claim 1, characterized in that, The method further includes: During operation, the vehicle speed and the seating status of passengers in each seat are continuously monitored. When the change in vehicle speed exceeds a preset threshold or the passenger seating status changes, the steps of obtaining the passenger seating status and current vehicle speed, generating candidate window opening schemes, selecting a recommended window opening scheme are re-executed, and the user is prompted to update the window opening scheme.

9. The method according to claim 1, characterized in that, The control of adjusting each window and the sunroof to the target opening degree corresponding to the recommended window opening scheme includes: The central control display screen shows a confirmation control for the recommended window opening scheme, or the user is prompted by voice to confirm the execution. In response to the user's confirmation command, control commands are sent to the drive motors of each window and the sunroof, and based on the control commands, each window and the sunroof are adjusted to the target opening degree corresponding to the recommended window opening scheme.

10. A vehicle, characterized in that, include: Memory; processor; as well as Computer programs; The computer program is stored in the memory and configured to be executed by the processor to implement the method as described in any one of claims 1-9.

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