Vehicle operation control methods, electronic equipment and vehicles

Abstract

This application provides a vehicle operation control method, electronic device, and vehicle, relating to the field of intelligent driving technology. The method includes: acquiring vehicle operation information, suspension operation information, and road noise information for a given road surface type; determining the corresponding initial tire pressure based on the vehicle operation information, suspension operation information, and road noise information; and determining a target tire pressure based on each of the initial tire pressures, thereby controlling vehicle operation based on the target tire pressure. This application, by integrating vehicle operation information, suspension operation information, and road noise information, determines three types of initial tire pressures oriented towards handling, comfort, and quietness, breaking through the limitations of traditional single-dimensional tire pressure control that only focuses on energy consumption or safety, and achieving dynamic collaborative optimization of multi-objective performance.

Description

Technical Field

[0001] This application relates to the field of intelligent driving technology, and in particular to a vehicle operation control method, electronic equipment, and vehicle. Background Technology

[0002] Existing tire pressure regulation technologies mostly rely on manual or preset mode switching, which is severely disconnected from the dynamic performance of the vehicle. They cannot automatically identify and finely coordinate control based on real-time changes in driving modes, road conditions, and vehicle dynamic needs. This results in tire condition not being dynamically matched with suspension, power, and NVH performance, making it difficult to simultaneously achieve multiple optimization goals such as high-speed stability, ride comfort, and noise suppression. This limits the improvement of the vehicle's intelligence level and requires improvement. Summary of the Invention

[0003] In view of this, the purpose of this application is to propose a vehicle operation control method, electronic equipment and vehicle to solve the problem of serious disconnect between tire pressure regulation and vehicle dynamic performance in related technologies.

[0004] To achieve the above objectives, this application provides a vehicle operation control method, the method comprising: Obtain vehicle operation information, suspension operation information, and road noise information for a given road surface type; The initial tire pressure is determined based on the vehicle operation information, suspension operation information, and road noise information, respectively. A target tire pressure is determined based on each of the initial tire pressures, and the vehicle operation is controlled based on the target tire pressure.

[0005] Furthermore, the vehicle operation information includes the vehicle driving mode and vehicle speed; the initial tire pressure corresponding to the vehicle operation information is the first tire pressure; Determining the first tire pressure based on the vehicle operating information includes: Determine the performance weighting coefficients corresponding to the vehicle driving mode and road surface type; The first tire pressure is determined based on the vehicle speed and performance weighting coefficient.

[0006] Furthermore, the suspension operation information includes the current suspension travel, standard suspension travel, and suspension action force change rate, and the initial tire pressure corresponding to the suspension operation information is the second tire pressure; Determining the second tire pressure based on the suspension operating information includes: The suspension travel deviation is determined based on the current suspension travel and the standard suspension travel; The suspension tire pressure coupling factor is determined based on the suspension travel deviation and the suspension dynamic change rate. The second tire pressure is obtained by compensating the first tire pressure based on the suspension tire pressure coupling factor.

[0007] Furthermore, the initial tire pressure corresponding to the suspension operation information is the third tire pressure; Determining the third tire pressure based on the road noise information includes: The road noise information is preprocessed to obtain initial frequency domain features; Based on the road surface type, the target frequency domain features are determined from the initial frequency domain features; In response to determining that the amplitude of the target frequency domain feature is greater than a preset threshold, the frequency domain tire pressure corresponding to the target frequency domain feature is determined, and this frequency domain tire pressure is determined as the third tire pressure; The preset threshold is determined based on the road surface type.

[0008] Furthermore, determining the target tire pressure based on each of the initial tire pressures includes: The first tire pressure, the second tire pressure, and the third tire pressure are weighted and calculated based on the performance weighting coefficients to obtain the target tire pressure.

[0009] Further, the first tire pressure, the second tire pressure, and the third tire pressure are weighted and calculated based on the performance weighting coefficients to obtain the target tire pressure, including: The first tire pressure, the second tire pressure, and the third tire pressure are weighted based on the performance weighting coefficients to obtain the initial fusion tire pressure; The initial fusion tire pressure is checked for a safe threshold range, and the initial fusion tire pressure that passes the check is determined as the target tire pressure; The safety threshold range is determined based on the driving mode.

[0010] Furthermore, controlling vehicle operation based on the target tire pressure includes: Get the current tire pressure; In response to determining that the deviation of the current tire pressure from the target tire pressure is greater than a preset threshold, the deviation tire pressure is divided into multiple deviation sub-ticket pressures; The tire pressure of each deviation sub-tire is executed sequentially according to a preset frequency until the target tire pressure is reached; or until the amplitude of the target frequency domain feature in the road noise information is less than or equal to a preset threshold. The magnitudes of the multiple deviation tire pressures conform to a normal distribution.

[0011] Furthermore, the method also includes: In response to the determination of an abnormality in the air pump connected to the wheel or an abnormality in the tire pressure of the wheel, the wheel inflation / deflation solenoid valve is locked, and the suspension damping coefficient is determined based on the vehicle speed and performance weighting coefficient. The suspension operation is controlled based on the aforementioned suspension damping coefficient.

[0012] Based on the same inventive concept, this disclosure also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement any of the methods described above.

[0013] Based on the same inventive concept, this disclosure also provides a vehicle including the above-mentioned electronic devices.

[0014] As can be seen from the above, the vehicle operation control method, electronic device, and vehicle provided in this application include: acquiring vehicle operation information, suspension operation information, and road noise information for a given road surface type; determining the corresponding initial tire pressure based on the vehicle operation information, suspension operation information, and road noise information; and determining a target tire pressure based on each of the initial tire pressures, thereby controlling vehicle operation based on the target tire pressure. This application, by integrating vehicle operation information, suspension operation information, and road noise information, determines three types of initial tire pressures oriented towards handling, comfort, and quietness, breaking through the limitations of traditional single-dimensional tire pressure control that only focuses on energy consumption or safety, and achieving dynamic collaborative optimization of multi-objective performance. Specifically, handling-oriented tire pressure based on vehicle operating information (such as vehicle speed and driving mode) ensures steering response and stability, comfort-oriented tire pressure based on suspension operating information (such as suspension travel and actuator force change rate) effectively attenuates road impacts, and quietness-oriented tire pressure based on road noise information precisely suppresses tire noise transmission. After the three are integrated through adaptive weighting of driving modes, they can intelligently balance handling precision, ride smoothness and cabin quietness in different driving scenarios to improve the overall driving quality and driving safety. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic flowchart of the vehicle operation control method according to an embodiment of this application; Figure 2 This is a schematic diagram of a vehicle operation control device according to an embodiment of this application; Figure 3 This is a schematic diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0018] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0019] In related technologies, current vehicle tire pressure regulation technologies are mainly divided into two categories: passive monitoring and active regulation. Passive tire pressure monitoring systems (TPMS) can only identify abnormal tire pressure and issue warnings. Drivers need to manually add air when the vehicle is parked. The tire pressure parameters remain basically static between two manual interventions and cannot respond to dynamic changes in driving conditions. To overcome this limitation, some vehicle models have introduced a central inflation / deflation system as an active regulation method. This system consists of an onboard air pump, an air storage device, wheel-end solenoid valve assemblies, and control switches. Based on experience, drivers can trigger the system by pressing preset mode buttons (such as sand, mud, and highway modes) when the vehicle is stationary or traveling at low speeds. This activates or deactivates the corresponding air circuits to achieve unified inflation / deflation operations, adapting the tire pressure to the specific road conditions required for traction.

[0020] Specifically, the central tire inflation / deflation system typically activates when the driver determines that changes in tire traction or driving stability are needed. For example, when transitioning from paved roads to unpaved surfaces like sand, mud, or rocks, the tire pressure needs to be reduced to increase the contact patch, improve grip, and enhance cushioning. Conversely, when returning from off-road terrain to paved roads, the standard tire pressure needs to be restored to ensure handling safety and fuel economy. For instance, by observing the tire pressure monitoring data on the instrument panel or relying on driving experience, the driver presses a preset mode button (such as sand mode) on the control panel when the vehicle is stationary or traveling at low speed. The system then performs inflation or deflation according to a fixed procedure. This system typically consists of an engine-driven high-pressure air pump, a central air tank, four independent air circuit control valve assemblies for each wheel, a rotary sealed air circuit connecting the wheel hubs, and control switches in the driver's cabin. When the driver issues a command, the air pump draws air from the atmosphere or the air tank and inflates the tires through the intake solenoid valve and piping. To deflate, the exhaust solenoid valve opens, allowing the tire's internal pressure to release gas back to the atmosphere or air tank.

[0021] However, the aforementioned active adjustment technologies still have significant drawbacks. First, the control logic is rigid and relies on manual intervention. The system only responds to discrete commands from the driver and cannot make continuous, adaptive, and refined adjustments based on real-time driving modes (such as Eco, Comfort, Sport, Off-road, Cruise, etc.), vehicle speed changes, and road surface types (such as dry asphalt, wet and slippery roads, snow-covered roads, gravel roads, or pothole roads, etc.). This leads to a disconnect between tire pressure and the dynamic performance requirements of the vehicle. Second, the control architecture is isolated. The central inflation / deflation system is completely disconnected from the fully active suspension system. It neither receives dynamic feedback such as suspension travel and actuator forces (such as the output force of shock absorbers) nor outputs coordinated commands to the suspension system. The two core ground-contact components, the tires and the suspension, operate independently and cannot work together to simultaneously optimize comfort and handling. Third, the NVH (Noise, Vibration, and Harshness) control methods are limited. Related technologies only suppress road noise through passive sound insulation or suspension adjustments, failing to utilize the active adjustment of tire pressure changes on the shape and stiffness of the contact patch to attenuate noise frequencies generated by specific road surfaces at their source. Therefore, the improvement in quietness is limited. Fourth, the safety redundancy mechanism is weak. In case of air pump failure or pipeline leakage, the system can only provide a simple alarm, lacking functional degradation strategies and cross-system backup capabilities, posing potential safety hazards.

[0022] The root cause of the above problems lies in the technical barriers between the various subsystems of tire pressure management, suspension control, driving mode selection and NVH management in the traditional vehicle control architecture, and the lack of a top-level intelligent collaborative unit to integrate and make decisions based on multi-source information.

[0023] The applicant discovered that by deeply integrating vehicle operating information (such as driving mode and vehicle speed), suspension operating information (such as current suspension travel, standard travel, and actuator force change rate), and road noise information (such as noise frequency and amplitude) with the vehicle controller, a tire pressure correlation with different road surface types can be established. This enables closed-loop linkage between the suspension and tires, active NVH suppression, and safety redundancy control, thereby overcoming the performance bottlenecks of existing technologies.

[0024] The following is in conjunction with the appendix Figures 1-3 The present application will be described in conjunction with the embodiments.

[0025] In some embodiments, a vehicle operation control method is provided, which is executed by a vehicle controller or by another controller independent of the vehicle controller. For the convenience of subsequent description, unless otherwise specified, the method is described using the vehicle controller as an example.

[0026] In some embodiments, the vehicle operation control method refers to Figure 1 ,include: S101. Obtain vehicle operation information, suspension operation information, and road noise information for a given road surface type.

[0027] In this step, the vehicle controller integrates camera visual features (identifying road surface color, texture, reflectivity, and water reflection), millimeter-wave radar (detecting signal scattering intensity caused by road surface roughness), wheel speed and acceleration sensors (analyzing wheel slip ratio and vertical vibration spectrum), and microphone array (collecting tire noise frequency features). Through Kalman filtering or deep learning classifiers, it performs spatiotemporal alignment and weight arbitration of multimodal data to infer the current road surface type in real time. This includes, but is not limited to, dry asphalt roads (high texture frequency, low slip ratio), wet roads (specular reflection, low-frequency attenuation of tire noise), snow-covered roads (low adhesion, high slip ratio, bright white areas), gravel roads (wideband vibration, high-frequency noise surge), or pothole roads (significant impact pulses, sudden changes in suspension travel), providing high-confidence operating condition feedforward for subsequent coordinated control of tire pressure and suspension.

[0028] For different road surface types, the system simultaneously collects three types of key data: First, vehicle operation information, such as reading the driver's selected driving mode signal (e.g., Eco, Sport, Comfort, or Off-road mode) through the body domain controller, and obtaining real-time vehicle speed by combining wheel speed sensors and powertrain CAN signals; second, suspension operation information, such as using suspension travel sensors to obtain the current suspension travel of each wheel (i.e., the real-time relative displacement of sprung and unsprung mass), while calling a pre-set standard travel mapping table in the ECU (which is calibrated based on vehicle load and attitude), and simultaneously collecting the change rate of actuator force of the active suspension or shock absorber (obtained through force sensors or current estimation models, the change value of damping force per unit time) to quantify road impact intensity; third, road noise information, which collects noise signals generated by tire-road contact through microphone arrays deployed in the vehicle chassis and cabin, and performs spectral analysis and feature extraction to identify road texture, roughness, and abnormal impacts. All raw data, after filtering and other preprocessing, are stored in a cache along with road surface type labels, providing multi-dimensional input for subsequent tire pressure decisions.

[0029] S102. Determine the corresponding initial tire pressure based on the vehicle operation information, suspension operation information, and road noise information, respectively.

[0030] This step establishes three types of parallel decision-making submodules to generate initial tire pressure recommendations for the specific parameters. For example, a lookup table mapping can be used based on driving mode and vehicle speed information: in Sport mode with a speed > 100 km / h, the initial tire pressure is increased to 2.6 bar to reduce sidewall deformation; in Comfort mode with low to medium speeds, 2.3 bar is used to balance rolling resistance and tire life. For example, the deviation ΔS between the current suspension travel and the standard travel can be calculated. When ΔS exceeds a threshold and the actuator force change rate fluctuates drastically at high frequencies, it is determined to be a large impact condition, and it is recommended to reduce the initial tire pressure to improve tire flexibility and cushioning. If the travel deviation is small and the force change rate is stable, the baseline tire pressure is maintained. For example, in off-road mode, when ΔS > 50 mm and the force change rate > 500 N / s, the initial tire pressure can be reduced to 1.8 bar; as another example, in cruise mode, noise reduction is prioritized, and the tire pressure is appropriately reduced by 0.1-0.2 bar. Based on road noise information, noise frequency and amplitude are used as proxy variables for road roughness. For example, high-frequency (>1kHz) high-amplitude noise indicates a rough or grooved road surface, and to avoid abnormal wear, it is recommended to reduce tire pressure by 0.05-0.1 bar; low-frequency (<500Hz) high-amplitude noise suggests a road surface with large undulations, requiring a larger reduction in tire pressure to improve shock absorption. The initial tire pressure values ​​P_veh, P_susp, and P_noise are output for the three types of information, respectively.

[0031] S103. Determine a target tire pressure based on each of the initial tire pressures, and control vehicle operation based on the target tire pressure.

[0032] This step constructs a multi-objective performance fusion and dynamic arbitration framework, mapping the three initial tire pressure values ​​output by S102 to specific driving performance dimensions. For example, P_veh represents the handling-oriented tire pressure (derived from vehicle speed and driving mode, prioritizing steering response, roll suppression, and braking stability), P_susp represents the comfort-oriented tire pressure (derived from suspension travel and actuator force change rate, aiming to maximize vibration damping and ride comfort), and P_noise represents the quietness-oriented tire pressure (derived from noise frequency and amplitude, focusing on reducing tire noise and road excitation noise). The system first looks up preset performance weight coefficients w1 (handling), w2 (comfort), and w3 (quietness) based on the current driving mode (economy / comfort / sport / off-road / cruise) and road surface type. This weight table is calibrated by the OEM through extensive subjective evaluation and objective testing. Then, the weighted fusion value P_comb = w1·P_veh + w2·P_susp + w3·P_noise is calculated.

[0033] The system then enters the safety constraint verification stage, which involves verifying P_comb against the tire's rated safety range [P_min, P_max]. Once the verification is passed, P_comb becomes the target tire pressure P_target. The determined target tire pressure P_target is then sent to the Active Tire Pressure Regulating System (ATMS). For example, ATMS uses a solenoid valve and a micro air pump to smoothly adjust the tire pressure to the target value at a rate of 0.05 bar / s, thus preventing sudden changes in tire pressure from causing vehicle vibration.

[0034] This embodiment integrates vehicle operation information, suspension operation information, and road noise information to determine three initial tire pressures oriented towards handling, comfort, and quietness, respectively. This overcomes the limitations of traditional single-dimensional tire pressure control, which only focuses on energy consumption or safety, and achieves dynamic and coordinated optimization of multi-objective performance. Specifically, handling-oriented tire pressure based on vehicle operation information (such as vehicle speed and driving mode) ensures steering response and stability; comfort-oriented tire pressure based on suspension operation information (such as suspension travel and actuator force change rate) effectively attenuates road impacts; and quietness-oriented tire pressure based on road noise information precisely suppresses tire noise transmission. After adaptive weighting and fusion based on driving mode, these three factors intelligently balance handling precision, ride comfort, and cabin quietness in different driving scenarios to improve overall vehicle ride quality and driving safety.

[0035] In some embodiments, the vehicle operating information includes the vehicle driving mode and vehicle speed; the initial tire pressure corresponding to the vehicle operating information is a first tire pressure. Determining the first tire pressure based on the vehicle operating information in S102 includes: S201. Determine the performance weighting coefficients corresponding to the vehicle driving mode and road surface type.

[0036] The performance weighting coefficient is used to characterize the degree of emphasis on comfort, handling and quietness in the vehicle driving mode.

[0037] In this step, the system analyzes the driver's selected driving mode signal (such as Eco, Sport, Comfort, Off-road, or Cruise) and combines it with the real-time identified road surface type (including dry asphalt, wet and slippery, snow and ice, gravel, potholes, etc.). It then retrieves the corresponding performance weight coefficients w1 (handling), w2 (comfort), and w3 (quietness) from a two-dimensional relationship mapping table pre-installed in the ECU's flash memory. This mapping table essentially couples and quantifies the qualitative intent of the driving mode with the objective conditions of the road surface type, mapping it to the emphasis ratio of the three core performance indicators: comfort, handling, and quietness. Its calibration process integrates subjective driving evaluation and objective testing: a professional evaluation team subjectively scores steering response sensitivity, suspension vibration filtering efficiency, and cabin quietness under different mode and road surface combinations, and combines this with objective performance curves obtained during hardware simulation. Finally, a multi-objective optimization algorithm fits the weight allocation for each mode-road surface combination.

[0038] For example, in Comfort mode on rough asphalt roads, the system might look up a table to obtain weights w1=0.2, w2=0.5, and w3=0.3, meaning it moderately sacrifices handling rigidity in exchange for significant vibration damping and noise reduction. In Sport mode on dry asphalt roads, the weights become w1=0.7, w2=0.2, and w3=0.1, meaning it moderately sacrifices comfort and quietness to improve handling. In Cruise mode on dry asphalt roads, w1=0.2, w2=0.3, and w3=0.5, significantly increasing the quietness weight to address the exponential increase in wind and tire noise with vehicle speed. These weighting coefficients serve as the normalization basis for subsequent multi-objective decision-making, accurately translating driver intent and road conditions into engineering parameters.

[0039] S202. Determine the first tire pressure based on the vehicle speed and performance weighting coefficient.

[0040] Specifically, this step can employ a weighted lookup table strategy, comparing the three performance weight coefficients w1, w2, and w3 determined in S201 to identify the performance dimension corresponding to the maximum value (e.g., the largest w1 indicates handling dominance, the largest w2 indicates comfort dominance, and the largest w3 indicates quietness dominance), and then calling the dedicated MAP table bound to that dimension. Specifically, the system presets three independently calibrated speed-tire pressure pulse maps: a handling MAP (emphasizing high-speed stability and steering precision, with tire pressure increasing at a positive slope with speed), a comfort MAP (emphasizing shock absorption and travel utilization, with tire pressure exhibiting a negative slope or plateau characteristics with speed), and a quietness MAP (emphasizing noise suppression, using a lower tire pressure plateau at mid-to-high speeds). Once the dominant MAP table is selected, the system uses the current vehicle speed as an index to retrieve the first tire pressure P_veh from that MAP. For example, if w3 has the highest weight in cruise mode, the quietness MAP is invoked, and P_veh = 2.15 bar is found at a vehicle speed of 120 km / h; if w1 has the highest weight in sport mode, the handling MAP is invoked, and P_veh = 2.45 bar is found at the same vehicle speed. This mechanism locks in the core performance target through weight arbitration, avoiding the computational complexity caused by multi-meter interpolation, while ensuring that the first tire pressure accurately responds to the primary needs of driving scenarios, thus balancing real-time performance and decision focus.

[0041] In this embodiment, by incorporating road surface type into the performance weight coefficient mapping logic, the weight allocation is made more closely aligned with actual working conditions, avoiding the problem of mismatch in performance of a single driving mode on different road surfaces. Furthermore, a weight-driven MAP lookup mechanism is adopted to simplify multi-objective optimization into single-objective priority decision-making, significantly reducing the computational load of the embedded system while improving real-time response. Thus, tire pressure control can reflect both the driver's subjective intentions and adapt to objective road conditions, ultimately systematically improving the overall vehicle ride quality and driving safety through a dynamic balance of handling, comfort, and quietness.

[0042] In some embodiments, the suspension operating information includes the current suspension travel, standard suspension travel, and suspension action force change rate, and the initial tire pressure corresponding to the suspension operating information is the second tire pressure; Determining the second tire pressure based on the suspension operating information in S102 includes: S301, Based on the current suspension travel S current and standard suspension travel S std Determine the suspension travel deviation ΔS.

[0043] For example, this step can determine the suspension travel deviation ΔS using the following formula: ΔS = S current - S std Specifically, the vehicle controller collects the current suspension travel S of each wheel in real time through linear displacement sensors or height sensors installed in the suspension system. current This value characterizes the instantaneous relative position of the sprung and unsprung masses of the suspension in the vertical direction. Simultaneously, the system calls the standard suspension travel S preset in the ECU. std This baseline value is determined based on the current vehicle load (estimated via air spring pressure or acceleration sensor readings) within a pre-defined data mapping table, reflecting the proper balance height of the suspension under that load. The calculated travel deviation ΔS is distinguished by positive and negative signs: a negative value indicates the suspension is in compression (i.e., the wheel is close to the vehicle body, commonly seen when driving over bumps or under heavy loads), while a positive value indicates the suspension is in extension (i.e., the wheel is away from the vehicle body, commonly seen when driving over potholes or when the vehicle body is lifted). The absolute value of ΔS quantifies the degree to which the suspension deviates from its steady state, providing a fundamental input for subsequent assessments of road impact intensity and tire contact requirements. This deviation is updated at a millisecond refresh rate after filtering, ensuring dynamic response capability to continuously uneven road surfaces.

[0044] S302. Determine the suspension tire pressure coupling factor α based on the suspension travel deviation and the suspension action force change rate.

[0045] Specifically, the suspension actuation force refers to the force output by the suspension actuator. The suspension actuator is an execution mechanism installed between the sprung mass (or unsprung mass, generally referring to the vehicle body) and the unsprung mass (or unsprung mass, generally referring to the wheels) of a vehicle, capable of actively generating control force. For example, the suspension actuator is a shock absorber.

[0046] For example, this step can determine the suspension tire pressure coupling factor α using the following formula:

[0047] Where α is the coupling factor (dimensionless), a positive α usually indicates that tire pressure needs to be increased to improve support and response; a negative α indicates that tire pressure needs to be decreased to enhance vibration damping and contact patch. ΔS is the deviation between the current suspension travel and the standard travel (Standard travel S). std The standard suspension travel, the determination process of which has already been explained in S301, will not be repeated here; sign(ΔS) is the sign function, taking the positive or negative sign of ΔS. |ΔS| / S std This is a relative amount of travel deviation, normalized to eliminate the influence of dimensions between different vehicle models, representing the degree to which the suspension deviates from its equilibrium position. d(F) act ) / dt: Suspension as power source F act The derivative with respect to time (unit: N / s) represents the severity or rate of change of road impact, and is a key indicator for judging the severity of road conditions. The faster the suspension dynamics change, the more uneven the road surface.std β is the reference force (in N) of the suspension actuator under standard conditions, used to normalize the rate of change of suspension action force; β is a weighting coefficient (dimensionless). It is used to adjust the contribution ratio of the two factors, "travel deviation" and "rate of change of suspension action force", in the coupling factor. This coefficient is calibrated through a large number of real vehicle tests, for example, β=0.5.

[0048] Specifically, for example, the current suspension travel S current = 192mm, standard stroke S std = 200mm, stroke deviation ΔS = S current - S std = -8mm, suspension actuator force change rate d(F) act ) / dt = 15000 N / s, reference force F std = 5000N, weighting coefficient β = 0.5 (calibrated value), then the suspension tire pressure coupling factor α = -1.54 is obtained.

[0049] This step aims to correlate the travel deviation ΔS obtained from S301 with the suspension's dynamic change rate d(F). act The system performs a fusion calculation of ) / dt to generate a dimensionless suspension-titer pressure coupling factor α, which directly indicates the direction and intensity of real-time tire pressure compensation based on suspension conditions. Specifically, the system obtains the current actuation force F through a force sensor built into the actuator or an estimation model based on motor current / solenoid valve pressure. act And calculate its rate of change d(F) per unit time. act The differential component |ΔS| / dt represents the severity of the road impact—the greater the rate of change, the steeper the road surface undulation and the more concentrated the impact energy. sign(ΔS) determines the compensation direction (compression stroke requires pressure reduction to absorb the impact, tension stroke requires pressure increase to maintain support), and the first term |ΔS| / S std The second term, β × (|d(F), reflects the static degree to which the suspension deviates from its equilibrium position. act ) / dt| / F std The dynamic intensity of the impact is reflected by β, which is the calibration weighting coefficient used to balance the contribution ratio of the static and dynamic components. This coupling factor integrates geometric deviation and transient mechanical response into a single decision variable, realizing a leap from "deformation perception" to "force response quantification" of road surface excitation, and providing a theoretical basis for fine tire pressure compensation.

[0050] S303. Based on the suspension tire pressure coupling factor, the first tire pressure is compensated to obtain the second tire pressure P_susp.

[0051] For example, this step can determine the second tire pressure P_susp using the following formula: P_susp = P_veh + k × α; This step applies the suspension tire pressure coupling factor α generated in S302 to the first tire pressure P_veh obtained in S202, and calculates the second tire pressure using a linear compensation formula, where k is the compensation gain coefficient (unit: bar, calibrated by bench testing, typical value: 0.05-0.15 bar; exemplarily, k=0.1). This compensation logic ensures the accuracy of the tire pressure correction based on the suspension state and has scenario adaptability. For example, when the wheel passes over a bump at high speed, ΔS is negative and |d(F act When |dt| is maximized and α is significantly negative, the system rapidly reduces tire pressure to enhance the tire's "soft connection" cushioning effect, protecting the suspension and cabin from severe impacts. Conversely, when the wheel is stuck in a deep ditch and in its extension stroke, α is positive, and the system moderately increases pressure to prevent tire drag and sidewall wrinkling. This mechanism directly incorporates suspension feedback into the tire pressure decision-making closed loop, achieving coordinated control of the tire and suspension, effectively balancing safety, comfort, and durability.

[0052] Specifically, for example, with the first tire pressure P_veh = 2.3 bar, the compensation gain coefficient k = 0.1 bar, and the suspension tire pressure coupling factor α = -1.54, the second tire pressure P_susp = 2.3 + 0.1 × (-1.54) = 2.146 bar. That is, by reducing the pressure by 0.15 bar, the road impact is effectively absorbed, while avoiding excessive pressure reduction that would affect handling stability.

[0053] This embodiment constructs a dynamic coupling factor by integrating suspension travel deviation and dynamic force change rate, achieving complete quantification of road impact from geometric deformation to mechanical response. This enables tire pressure compensation decisions to possess both static position perception and dynamic intensity prediction capabilities. Through sign function and normalization design, the complex coupling relationship of multiple physical quantities is decoupled into dimensionless indices with clear direction and adjustable amplitude. Furthermore, a linear compensation mechanism directly incorporates suspension feedback into the tire pressure closed-loop control, making the tire and suspension no longer independent actuators but a coupled and optimized collaborative system, significantly enhancing the adaptive capability to complex road surfaces. This solution overcomes the limitations of traditional open-loop tire pressure control that relies solely on vehicle speed and load, significantly improving the vehicle's adaptability to complex road surfaces, ride comfort, and driving safety.

[0054] In some embodiments, the initial tire pressure corresponding to the suspension operation information is the third tire pressure; Determining the third tire pressure based on the road noise information in S102 includes: S401. Preprocess the road noise information to obtain initial frequency domain features; In this step, the system uses microphone arrays located inside the wheel arches, chassis longitudinal beams, and cabin floor to collect noise signals generated by tire-road contact excitation in real time. This signal is a time-domain sound pressure level sequence, with frequency components including tread block impacts, rubber vibrations, cavity resonance, and chassis structure-transmitted noise. To extract features related to tire pressure regulation, the vehicle controller performs a Fast Fourier Transform (FFT) on the original noise signal using a 100ms sliding window, converting the time-domain waveform into a spectral distribution to obtain an initial frequency domain feature vector. For example, this vector covers the key frequency band from 20Hz to 2kHz, where the 20-200Hz low-frequency band mainly reflects the overall tire rigidity and suspension resonance characteristics, the 200-800Hz mid-frequency band corresponds to the periodic impacts of the tread blocks and sidewall bending vibrations, and the 800-2000Hz high-frequency band characterizes localized rubber friction and micro-texture excitation. The system synchronously calculates the amplitude (characterized by dB(A) or power spectral density) and dominant frequency distribution at each frequency point, forming structured data containing frequency-amplitude pairs, which provides quantitative input for subsequent feature screening related to road surface type.

[0055] S402. Based on the road surface type, determine the target frequency domain features from the initial frequency domain features.

[0056] This step aims to filter and focus the full-band frequency domain features based on the real-time identified road surface type. Since the spectral characteristics of excitation from different road surfaces vary significantly, indiscriminate global analysis will introduce noise interference. Specifically, the system has a built-in road surface-frequency band mapping table: when the road surface is identified as dry asphalt, the target frequency domain features are locked in the mid-to-high frequency band of 500-1200Hz, because smooth asphalt mainly excites high-frequency vibrations in the tire tread pattern; when the road surface is rough asphalt or cement, the target frequency domain shifts down to 300-800Hz to capture the mid-frequency impact caused by macroscopic textures; when the road surface is gravel, the frequency domain is further expanded to 200-600Hz and the low-frequency components are enhanced, because loose particles cause overall tire shaking; when the road surface is icy or snowy, the focus is on monitoring the low-frequency band of 200-500Hz, because tire slippage and tread self-excited vibration energy are concentrated in the low frequency range under low-adhesion surfaces. This screening mechanism is implemented through bandpass filters or frequency domain masks. It extracts the frequency band amplitude envelope that is most strongly coupled with the current road surface physical characteristics as the target frequency domain feature, thereby focusing computing resources and decision weights on the most representative noise source and improving the targeting and signal-to-noise ratio of tire pressure regulation.

[0057] S403. In response to determining that the amplitude of the target frequency domain feature is greater than a preset threshold, the frequency domain tire pressure corresponding to the target frequency domain feature is determined (for example, determined in preset mapping relationship data), and this frequency domain tire pressure is determined as the third tire pressure; in response to determining that the amplitude of the target frequency domain feature is less than or equal to a preset threshold, the first tire pressure is determined as the third tire pressure; wherein, the preset threshold is determined based on the road surface type.

[0058] This step establishes a closed-loop decision-making logic for noise and tire pressure. For the target frequency band determined in S402, the system calculates its weighted amplitude A_target and compares it with a preset threshold A_th dynamically adjusted based on road surface type: if A_target ≤ A_th, it indicates that the current tire noise is at an acceptable level, and the third tire pressure P_noise remains unchanged compared to the first tire pressure P_veh; if A_target > A_th, the tire pressure compensation mechanism is triggered. The preset threshold A_th is obtained through calibration; for example, in cruise mode where quietness requirements are stringent, A_th is 3-5 dB lower than in comfort mode. If the limit is exceeded, the system uses the center frequency and amplitude of the target frequency band as an index to query a preset frequency domain-tire pressure MAP. This MAP is established through NVH bench testing and records the optimal tire pressure adjustment amount (usually a pressure reduction) required when energy exceeds the limit in different frequency bands. For example, if the amplitude exceeds the limit by 5 dB at 800 Hz, the MAP indicates that the tire pressure needs to be reduced by 0.08 bar to weaken tread resonance; if the energy exceeds the limit in lower frequency bands, a larger reduction may be needed to suppress overall tire vibration. The compensation amount ΔP obtained from the lookup table is superimposed on P_veh to finally obtain the third tire pressure P_noise. This mechanism quantifies subjective auditory perception into objective spectral indicators and maps them to engineering control parameters, realizing active closed-loop management of NVH performance.

[0059] This embodiment introduces frequency domain analysis of road noise, transforming the traditionally passively received acoustic roughness into an actively controlled input signal. This significantly expands the performance dimensions of tire pressure optimization, extending quietness improvement from a single approach of suspension tuning to a systematic solution involving tire and suspension collaboration. Specifically, a dynamic frequency band filtering mechanism based on road type accurately captures the main noise sources under different operating conditions, avoiding redundancy and interference from full-band analysis and improving decision-making efficiency and signal-to-noise ratio. Meanwhile, the spectrum amplitude threshold over-limit triggering and MAP lookup table compensation strategy decouple the complex NVH optimization problem into real-time executable engineering logic, achieving rapid noise suppression response. Ultimately, through a closed-loop noise feedback system and refined tire pressure adjustment, this solution significantly reduces cabin sound pressure level and sharpness while maintaining a balance between handling and comfort, systematically improving NVH quality and ride comfort during cruising and on rough roads.

[0060] In some embodiments, determining the target tire pressure based on each of the initial tire pressures includes: The first tire pressure, the second tire pressure, and the third tire pressure are weighted and calculated based on the performance weighting coefficients to obtain the target tire pressure.

[0061] Furthermore, this step can also be described as follows: weighting the first tire pressure, the second tire pressure, and the third tire pressure based on the performance weighting coefficient to obtain an initial merged tire pressure; verifying the initial merged tire pressure within a safe threshold range, and determining the initial merged tire pressure that passes the verification as the target tire pressure; wherein, the safe threshold range is determined based on the driving mode (e.g., determining the safe threshold range of tire pressure corresponding to the driving mode based on a preset data mapping table).

[0062] This step constructs a multi-performance-dimensional dynamic weighted fusion framework, aiming to integrate the first tire pressure P_veh (handling-oriented) generated in S202, the second tire pressure P_susp (comfort-oriented) generated in S303, and the third tire pressure P_noise (quietness-oriented) generated in S403 into a single target tire pressure P_target. The system first retrieves the corresponding performance weight coefficient vector (w1, w2, w3) from a preset weight mapping table based on the current driving mode and road surface type. This vector, determined through extensive subjective and objective calibration experiments, represents the user's emphasis on handling, comfort, and quietness. Then, the system performs a weighted calculation P_comb = w1·P_veh + w2·P_susp + w3·P_noise to obtain a preliminary fusion value. This weighted preliminary fusion value then undergoes a safety verification, followed by a safety constraint verification, which compares P_comb with the tire's rated safety range [P_min, P_max]. If the verification passes, P_comb becomes the target tire pressure P_target. This mechanism achieves a controllable trade-off between multiple objectives through dynamic weight allocation, which avoids the one-sidedness of optimizing a single index and reduces the complexity of online computation through table lookup and linear weighting, thus balancing the scientific nature of decision-making with the real-time requirements of embedded systems.

[0063] For example, assuming the vehicle is in cruise mode driving on a rough asphalt road, S102 calculates three initial tire pressure values: the first tire pressure P_veh = 2.35 bar (emphasizing handling stability, the tire pressure is too high at a speed of 120 km / h), the second tire pressure P_susp = 2.12 bar (suspension feedback indicates slight bumps, it is recommended to reduce the pressure to improve comfort), and the third tire pressure P_noise = 2.08 bar (the 800Hz frequency band noise amplitude exceeds the standard, it is necessary to reduce tire noise by reducing the pressure). The system queries the mapping table to determine the weighting coefficients for cruise mode + rough road surface as w1=0.25 (handling), w2=0.30 (comfort), and w3=0.45 (quietness). Weighted calculation: P_comb = 0.25×2.35 + 0.30×2.12 + 0.45×2.08 = 0.5875 + 0.636 + 0.936 = 2.16 bar. In subsequent safety verification, the safe tire pressure threshold range [2.0, 2.8] bar corresponding to the cruise mode was first determined. 2.16 bar satisfies the cruise lower limit of 2.0 bar, therefore the final target tire pressure P_target is determined to be 2.16 bar. This result is approximately 0.19 bar lower than the first tire pressure, significantly sacrificing some handling stiffness, but effectively suppressing tire noise under the dominance of quietness weight; at the same time, it moderately increases by 0.08 bar compared to the third tire pressure, avoiding excessive pressure reduction leading to a sharp increase in rolling resistance and insufficient lateral stiffness, reflecting an intelligent balance across multiple performance dimensions.

[0064] This embodiment uses performance weighting coefficients to dynamically weight and fuse three types of initial tire pressure, establishing an explicit mapping from multi-source sensor information to a single control objective. This achieves a scenario-based intelligent trade-off between handling, comfort, and quietness, breaking through the limitations of traditional tire pressure control's single-objective optimization. The mode-road adaptive lookup table mechanism of the weighting coefficients enables the system to accurately respond to both driver intentions and objective road conditions, enhancing the personalization of the driving experience and road condition adaptability. The combination of linear weighted calculation and safety verification ensures the real-time performance of the embedded system while balancing the freedom of performance optimization and driving safety through the dual guarantees of hard boundary constraints and soft weight adjustment. Ultimately, this solution upgrades tire pressure regulation from open-loop preset to closed-loop collaborative control, systematically improving the vehicle's NVH quality, driving smoothness, and comprehensive performance under multiple operating conditions.

[0065] In some embodiments, controlling vehicle operation based on the target tire pressure in S103 includes: S501, Get the current tire pressure.

[0066] In this step, the system uses the vehicle's built-in Tire Pressure Monitoring System (TPMS) to obtain the actual tire pressure values ​​of all four wheels in real time as the current tire pressure. Specifically, each tire's valve stem integrates a piezoresistive pressure sensor and a temperature sensor, transmitting data to the vehicle's receiver every second via radio frequency signal with an accuracy of ±0.01 bar. The system performs temperature compensation and rolling average filtering (typically using a 5-second sliding window) on the received raw data to eliminate noise caused by tire rotation centrifugal force and instantaneous temperature fluctuations. The difference between the current tire pressure and the target tire pressure is calculated to obtain the deviation tire pressure ΔP = current tire pressure - target tire pressure. If |ΔP| ≤ 0.05 bar (preset threshold), the system is considered to be in the target state, and the graded adjustment in S502 is not triggered, meaning direct adjustment is sufficient. If the deviation exceeds the threshold, the graded adjustment process is initiated to avoid frequent actuator operation due to small fluctuations, thus extending the lifespan of the actuators and tires.

[0067] S502. In response to determining that the deviation tire pressure between the current tire pressure and the target tire pressure is greater than a preset threshold, the deviation tire pressure is divided into multiple deviation sub-ticket pressures; wherein the magnitudes of the multiple deviation sub-ticket pressures conform to a normal distribution.

[0068] When the system determines that the absolute value of the deviation tire pressure ΔP is greater than the preset threshold of 0.05 bar, in order to avoid sudden pitch changes and driving discomfort caused by a large one-time inflation or deflation, the total deviation needs to be broken down into deviation sub-tilt pressures ΔP that conform to a normal distribution. i The process is executed sequentially. Specifically, using the target tire pressure as the mean μ, the adjustment interval [0, ΔP] from the current tire pressure to the target tire pressure is mapped to a range of 3 times the standard deviation (3σ). This interval is then divided into 5 sub-regions with equal probability using the probability density function of a Gaussian distribution. At both ends of the adjustment process (i.e., the initial segment near the current tire pressure and the final segment near the target tire pressure), the sub-deviation is relatively small (approximately 10%-15% of the total deviation, i.e., 0.04-0.06 bar), achieving a "soft start" and "soft landing" to reduce the risk of initial shock and over-adjustment. In the middle of the adjustment process (i.e., the region close to the target tire pressure), the sub-deviation is relatively large (approximately 30%-35% of the total deviation, i.e., 0.12-0.14 bar), to accelerate the convergence speed and reduce the number of adjustment stages. For example, if the current tire pressure is 2.5 bar and the target tire pressure is 2.1 bar (the total deviation ΔP = 0.4 bar requires pressure reduction), then the five sub-stages are ΔP1 = 0.04 bar, ΔP2 = 0.09 bar, ΔP3 = 0.14 bar, ΔP4 = 0.09 bar, and ΔP5 = 0.04 bar, respectively. This approach follows the probability distribution characteristics of the normal curve while also considering execution efficiency and stability.

[0069] S503. Execute each deviation sub-tire pressure sequentially according to the preset frequency until the target tire pressure is reached; or until the amplitude of the target frequency domain feature in the road noise information is less than or equal to the preset threshold.

[0070] The vehicle controller executes each deviation tire pressure ΔP sequentially at a preset frequency (e.g., 0.5Hz, meaning one sub-stage is executed every 0.5 seconds). i The system uses an ATMS solenoid valve and a micro air pump to perform phased inflation and deflation. After each sub-deviation, the actuator pauses for approximately 200ms to allow the tire pressure to fully equalize and the vehicle's attitude to stabilize. Simultaneously, it collects updated current tire pressure and road noise frequency characteristics, forming a small closed-loop feedback. This process continues until one of two termination conditions is met: first, after all sub-deviations have been executed, the current tire pressure deviation from the target tire pressure is less than 0.05 bar, indicating that the target has been achieved; second, when the performance weight coefficient representing quietness guidance is the largest among the performance weight coefficients, the target frequency characteristic amplitude A_target in the road noise information drops below the preset threshold A_th after a certain sub-stage execution, indicating that the tire pressure adjustment has effectively improved tire noise, and subsequent sub-stages are terminated early to avoid over-adjustment. For example, in noise-reduction oriented cruise mode, after the second sub-deviation is executed, the 800Hz frequency band noise has decreased from exceeding the standard by 5dB to within the threshold. Even if the tire pressure has not yet fully reached the target tire pressure, the system will stop further pressure reduction.

[0071] This embodiment transforms abrupt tire pressure adjustments into gradual, multi-stage optimization through tiered adjustment, significantly suppressing vehicle pitch fluctuations and transient shocks, thus improving ride smoothness and comfort. The preset frequency execution and inter-stage pause mechanism provide a time window for online performance evaluation, enabling the system to dynamically terminate adjustments based on noise feedback, avoiding over-optimization and ineffective actuator work, and improving energy efficiency and responsiveness. At the same time, this strategy protects the ATMS air pump and solenoid valve from transient high-flow shocks, extending hardware life and reliability, ultimately achieving a multi-dimensional synergistic improvement in safety, comfort, NVH quality, and system durability.

[0072] In some embodiments, the method further includes: In response to the determination of an abnormality in the air pump connected to the wheel or an abnormality in the tire pressure of the wheel, the wheel inflation / deflation solenoid valve is locked, and the suspension damping coefficient is determined based on the vehicle speed and performance weighting coefficient; the suspension operation is controlled based on the suspension damping coefficient.

[0073] This embodiment constructs a degradation control and performance compensation mechanism for tire pressure regulation system failures or abnormal tire conditions. When the controller detects actuator failures such as pump stall, current overload, or air leakage, or when the TPMS continuously reports abnormal tire signals such as sudden tire pressure changes, rapid temperature rises, or slow air leaks, the system immediately locks the corresponding wheel's inflation / deflation solenoid valve to its current position, cutting off the active tire pressure regulation function to prevent the fault from escalating or abnormal inflation / deflation from causing loss of control. Simultaneously, based on the real-time vehicle speed and the performance weight coefficient determined by S201, the system queries the preset suspension damping MAP for compensatory damping coefficients. By increasing the current of the shock absorber solenoid valve (increasing damping) to suppress the transmission of vibrations and vehicle pitch under abnormal tire conditions, or by reducing damping (reducing current) to compensate for the loss of ride comfort due to the inability to adjust tire pressure, the dynamic performance optimization that should have been achieved through tire pressure adjustment is transferred to the suspension system. This forms a two-level control strategy of "tire pressure failure, suspension compensation," ensuring that the vehicle can still maintain acceptable handling stability, comfort, and safety when there is a partial failure in the system. This significantly improves the system's fault tolerance and functional availability, and avoids the overall deterioration of vehicle performance or functional unavailability due to a single point of failure.

[0074] It should be noted that the method in this embodiment can be executed by a single device, such as a computer or server. The method can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.

[0075] It should be noted that the above description describes some embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0076] Based on the same inventive concept, corresponding to any of the above embodiments, this application also provides a vehicle operation control device.

[0077] refer to Figure 2 The vehicle operation control device includes: The acquisition module 201 is configured to acquire vehicle operation information, suspension operation information, and road noise information for a given road surface type. The determining module 202 is configured to determine the corresponding initial tire pressure based on the vehicle operation information, suspension operation information, and road noise information, respectively. The execution module 203 determines a target tire pressure based on each of the initial tire pressures, and controls the vehicle operation based on the target tire pressure.

[0078] Furthermore, the vehicle operation information includes the vehicle driving mode and vehicle speed; the initial tire pressure corresponding to the vehicle operation information is the first tire pressure; The determining module 202 is configured as follows: Determine the performance weighting coefficients corresponding to the vehicle driving mode and road surface type; The first tire pressure is determined based on the vehicle speed, road surface type, and performance weighting coefficient.

[0079] Furthermore, the suspension operation information includes the current suspension travel, standard suspension travel, and suspension action force change rate, and the initial tire pressure corresponding to the suspension operation information is the second tire pressure; The determining module 202 is configured as follows: The suspension travel deviation is determined based on the current suspension travel and the standard suspension travel; The suspension tire pressure coupling factor is determined based on the suspension travel deviation and the suspension dynamic change rate. The second tire pressure is obtained by compensating the first tire pressure based on the suspension tire pressure coupling factor.

[0080] Furthermore, the initial tire pressure corresponding to the suspension operation information is the third tire pressure; The determining module 202 is configured as follows: The road noise information is preprocessed to obtain initial frequency domain features; Based on the road surface type, the target frequency domain features are determined from the initial frequency domain features; In response to determining that the amplitude of the target frequency domain feature is greater than a preset threshold, the frequency domain tire pressure corresponding to the target frequency domain feature is determined, and this frequency domain tire pressure is determined as the third tire pressure; The preset threshold is determined based on the road surface type.

[0081] Furthermore, the execution module 203 is configured as follows: The first tire pressure, the second tire pressure, and the third tire pressure are weighted and calculated based on the performance weighting coefficients to obtain the target tire pressure.

[0082] Furthermore, the execution module 203 is configured as follows: The first tire pressure, the second tire pressure, and the third tire pressure are weighted based on the performance weighting coefficients to obtain the initial fusion tire pressure; The initial fusion tire pressure is checked for a safe threshold range, and the initial fusion tire pressure that passes the check is determined as the target tire pressure; The safety threshold range is determined based on the driving mode.

[0083] Furthermore, the execution module 203 is configured as follows: Get the current tire pressure; In response to determining that the deviation of the current tire pressure from the target tire pressure is greater than a preset threshold, the deviation tire pressure is divided into multiple deviation sub-ticket pressures; The tire pressure of each deviation sub-tire is executed sequentially according to a preset frequency until the target tire pressure is reached; or until the amplitude of the target frequency domain feature in the road noise information is less than or equal to a preset threshold. The magnitudes of the multiple deviation tire pressures conform to a normal distribution.

[0084] Furthermore, the determining module 202 is also configured to: In response to the determination of an abnormality in the air pump connected to the wheel or an abnormality in the tire pressure of the wheel, the wheel inflation / deflation solenoid valve is locked, and the suspension damping coefficient is determined based on the vehicle speed and performance weighting coefficient. The suspension operation is controlled based on the aforementioned suspension damping coefficient.

[0085] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle operation control method described in any of the above embodiments.

[0086] Figure 3 This embodiment illustrates a more specific hardware structure of an electronic device. The device may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0087] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0088] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0089] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.

[0090] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WFI, Bluetooth, etc.).

[0091] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0092] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0093] The electronic devices described above are used to implement the corresponding vehicle operation control methods in any of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0094] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a vehicle, including an electronic device, which is used to execute the vehicle operation control method described in any of the above embodiments.

[0095] The vehicles described in the above embodiments are used to implement the corresponding vehicle operation control methods in any of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0096] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium that stores computer instructions for causing the computer to execute the vehicle operation control method as described in any of the above embodiments.

[0097] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0098] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the vehicle operation control method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0099] It is understood that before using the technical solutions of the various embodiments in this disclosure, users will be informed of the type, scope of use, and usage scenarios of the personal information involved in an appropriate manner, and user authorization will be obtained.

[0100] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose, based on the prompt message, whether to provide personal information to the software or hardware such as electronic devices, applications, servers, or storage media performing the operations of this disclosed technical solution.

[0101] As an optional but not limited implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0102] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0103] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

[0104] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this application, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0105] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0106] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.

Claims

1. A vehicle operation control method, characterized in that, include: Obtain vehicle operation information, suspension operation information, and road noise information for a given road surface type; The initial tire pressure is determined based on the vehicle operation information, suspension operation information, and road noise information, respectively. A target tire pressure is determined based on each of the initial tire pressures, and vehicle operation is controlled based on the target tire pressure. The vehicle operation information includes the vehicle driving mode and vehicle speed; the initial tire pressure corresponding to the vehicle operation information is the first tire pressure. Determining the first tire pressure based on the vehicle operating information includes: Determine the performance weighting coefficients corresponding to the vehicle driving mode and road surface type; The first tire pressure is determined based on the vehicle speed and performance weighting coefficient. The suspension operation information includes the current suspension travel, standard suspension travel, and suspension action force change rate, and the initial tire pressure corresponding to the suspension operation information is the second tire pressure; Determining the second tire pressure based on the suspension operating information includes: The suspension travel deviation is determined based on the current suspension travel and the standard suspension travel; The suspension tire pressure coupling factor is determined based on the suspension travel deviation and the suspension dynamic change rate. The second tire pressure is obtained by compensating the first tire pressure based on the suspension tire pressure coupling factor. The initial tire pressure corresponding to the road noise information is the third tire pressure; Determining the third tire pressure based on the road noise information includes: The road noise information is preprocessed to obtain initial frequency domain features; Based on the road surface type, the target frequency domain features are determined from the initial frequency domain features; In response to determining that the amplitude of the target frequency domain feature is greater than a preset threshold, the frequency domain tire pressure corresponding to the target frequency domain feature is determined, and this frequency domain tire pressure is determined as the third tire pressure; The preset threshold is determined based on the road surface type.

2. The method according to claim 1, characterized in that, Determining the target tire pressure based on each of the initial tire pressures includes: The first tire pressure, the second tire pressure, and the third tire pressure are weighted and calculated based on the performance weighting coefficients to obtain the target tire pressure.

3. The method according to claim 2, characterized in that, The target tire pressure is obtained by weighting the first tire pressure, the second tire pressure, and the third tire pressure based on the performance weighting coefficient, including: The first tire pressure, the second tire pressure, and the third tire pressure are weighted based on the performance weighting coefficients to obtain the initial fusion tire pressure; The initial fusion tire pressure is checked for a safe threshold range, and the initial fusion tire pressure that passes the check is determined as the target tire pressure; The safety threshold range is determined based on the driving mode.

4. The method according to claim 1, characterized in that, The method of controlling vehicle operation based on the target tire pressure includes: Get the current tire pressure; In response to determining that the deviation of the current tire pressure from the target tire pressure is greater than a preset threshold, the deviation tire pressure is divided into multiple deviation sub-ticket pressures; The tire pressure of each deviation sub-tire is executed sequentially according to a preset frequency until the target tire pressure is reached; or until the amplitude of the target frequency domain feature in the road noise information is less than or equal to a preset threshold. The magnitudes of the multiple deviation tire pressures conform to a normal distribution.

5. The method according to claim 1, characterized in that, The method further includes: In response to the determination of an abnormality in the air pump connected to the wheel or an abnormality in the tire pressure of the wheel, the wheel inflation / deflation solenoid valve is locked, and the suspension damping coefficient is determined based on the vehicle speed and performance weighting coefficient. The suspension operation is controlled based on the aforementioned suspension damping coefficient.

6. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor, when executing the program, implements the method as claimed in any one of claims 1 to 5.

7. A vehicle, characterized in that, Includes the electronic device as described in claim 6.

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