Commercial vehicle tire pressure monitoring method and device based on vehicle type configuration adaptation

Abstract

The present application relates to a kind of commercial vehicle tire pressure monitoring method and device based on vehicle type configuration self-adaption, the method includes: obtaining the configuration information of vehicle, parsing drive axle number and axle position function attribute;Collect the real-time running parameter and tire state data of vehicle;Based on the axle position function attribute and the running parameter, dynamically determine the different alarm threshold of each axle position tire;Judge the relationship between the tire state data and the different alarm threshold of corresponding axle position, execute corresponding tire pressure monitoring alarm strategy based on the result of judging.The present application can realize the accurate tire pressure monitoring and early warning of new energy commercial vehicle complex axle position configuration, effectively solve the technical problems that traditional tire pressure monitoring system cannot adapt to multi-axle position difference and complex working condition, significantly improve the driving safety and operation efficiency of new energy commercial vehicle.

Description

Technical Field

[0001] This invention relates to the field of safety monitoring technology for energy commercial vehicles, and in particular to a method and device for tire pressure monitoring of commercial vehicles based on vehicle configuration adaptation. Background Technology

[0002] With the rapid development of new energy commercial vehicles and the popularization of intelligent driving technology, the safety and intelligence requirements of tire pressure monitoring systems (TPMS) are becoming increasingly prominent. Under the trends of electrification, connectivity, and intelligence, TPMS is not only a traditional safety feature but also a key data node in intelligent driving systems. However, the TPMS currently equipped in new energy commercial vehicles have significant shortcomings.

[0003] First, traditional TPMS has poor adaptability. Due to the different number of drive axles in commercial vehicles (such as 6×4 three-axle, 4×2 two-axle, 8×4 four-axle, etc.), traditional systems need to be adapted to different vehicle models through hardware jumpers or software flashing. This is not only complicated and error-prone, but also increases maintenance costs and time. Compared with passenger car TPMS, which usually only needs to match 4 tires, commercial vehicles need to support 6 to 22 tires (including trailers), which greatly increases the complexity. Existing solutions still rely on manual input of vehicle model codes and fail to achieve fully automatic recognition.

[0004] Secondly, the traditional TPMS instrument display interface is fixed and cannot be automatically adjusted according to the actual number and position of tires on the vehicle. This leads to display redundancy issues. For example, if the instrument panel of a 6×4 vehicle is designed with maximum capacity, a large number of invalid areas will be left blank on a 4×2 vehicle, interfering with the driver's attention. At the same time, the display layout often does not conform to the actual tire topology and fails to distinguish between drive shafts, steering shafts, and load-bearing shafts. Furthermore, for temporarily attached trailers, their tire data cannot be automatically integrated into the main vehicle's instrument panel, requiring switching to a secondary menu to view, which increases operational risks.

[0005] Third, the alarm threshold is singular and does not consider the differentiated needs of different axle positions. Traditional systems use a uniform alarm threshold for all tires, but the functions of tires on different axles of commercial vehicles differ significantly. For example, drive axles are subjected to greater torque, resulting in more frequent tire pressure fluctuations and requiring higher alarm sensitivity; while load-bearing axles mainly bear the load, resulting in slower tire pressure changes, but low pressure poses a greater risk and requires stricter low-pressure alarm standards. Furthermore, existing systems do not fully consider the impact of load and temperature factors on tire pressure. For instance, the ideal tire pressure difference between unloaded and fully loaded load-bearing axles can reach 30%, and the temperature rise of the drive axle during long downhill driving conditions may cause the system to misjudge abnormal tire pressure.

[0006] Therefore, there is an urgent need for a tire pressure monitoring system for new energy commercial vehicles that can adapt to different drive shaft configurations, realize automatic vehicle model recognition, dynamic interface adjustment, and differentiated alarm strategies based on axle characteristics, so as to improve the system's applicability and accuracy, while reducing maintenance costs. Summary of the Invention

[0007] This invention discloses a method, device, and self-powered system for tire pressure monitoring of commercial vehicles based on vehicle configuration adaptation, aiming to solve the technical problems existing in the prior art. The invention adopts the following technical solution:

[0008] On one hand, embodiments of the present invention provide a tire pressure monitoring method for commercial vehicles based on vehicle configuration adaptation, including:

[0009] Obtain vehicle configuration information and parse the number of drive shafts and axle position functional attributes;

[0010] Collect real-time operating parameters and tire status data of the vehicle;

[0011] Based on the axle position functional attributes and the operating parameters, dynamically determine the differentiated alarm thresholds for tires in each axle position;

[0012] Determine the relationship between the tire status data and the differential alarm threshold of the corresponding axle position, and execute the corresponding tire pressure monitoring alarm strategy based on the determination result.

[0013] Secondly, embodiments of the present invention provide a vehicle static tire pressure monitoring device, comprising:

[0014] The vehicle configuration acquisition module is used to acquire vehicle configuration information and parse the number of drive shafts and axle position functional attributes.

[0015] The data acquisition module is used to collect real-time operating parameters and tire status data of the vehicle.

[0016] The threshold determination module is used to dynamically determine the differentiated alarm threshold of each axle tire based on the axle position functional attributes and the operating parameters.

[0017] The monitoring and alarm module is used to determine the relationship between the tire status data and the differential alarm threshold of the corresponding axle position, and to execute the corresponding tire pressure monitoring and alarm strategy based on the determination result.

[0018] Thirdly, embodiments of the present invention provide a computer-readable storage medium storing at least one instruction, which is loaded by a processor and executed to implement the vehicle configuration-adaptive commercial vehicle tire pressure monitoring method described above.

[0019] Fourthly, embodiments of the present invention provide an electronic device, the electronic device including a processor and a memory, the memory storing at least one instruction, the instruction being loaded and executed by the processor to implement the vehicle configuration-adaptive commercial vehicle tire pressure monitoring method described above.

[0020] One embodiment of the above invention has the following advantages or beneficial effects:

[0021] The present invention provides a commercial vehicle tire pressure monitoring method and device based on vehicle configuration adaptation. By identifying vehicle configuration information and analyzing the number of drive shafts and axle position functional attributes, it achieves automatic adaptation to different vehicle models. Compared with the traditional tire pressure monitoring system that requires manual configuration or software flashing, this solution greatly improves the system's compatibility, enabling the same tire pressure monitoring controller to be adapted to different vehicle models, significantly reducing the overall vehicle BOM cost (by more than 30%) and maintenance complexity.

[0022] This invention employs a differentiated alarm strategy based on axle position. Vehicle tires are categorized into steering axles, drive axles, and load-bearing follow-up axles according to their functional attributes. The tire pressure alarm thresholds for each axle position are dynamically adjusted based on real-time vehicle operating parameters such as load status, speed, and road gradient. This differentiated processing mechanism effectively solves the problem of false alarms or missed alarms caused by the uniform alarm thresholds used in traditional systems, significantly improving alarm accuracy to 99.2%. Simultaneously, a temperature compensation mechanism avoids false alarms caused by thermal expansion.

[0023] This invention also enables adaptive adjustment of the user interface, automatically optimizing the display layout according to vehicle configuration, and automatically adjusting UI elements for different vehicle models (such as 6×4 three-axle vehicles and 4×2 two-axle vehicles). It also supports automatic expansion of the display area when trailers are connected. This dynamic interface solution not only reduces manual inspection time but also improves information recognition efficiency and effectively reduces driver distraction, providing a strong guarantee for the safe operation of commercial vehicles.

[0024] In addition, the present invention also has predictive alarm capabilities. By analyzing the historical trend of tire condition data, it can predict future tire pressure changes in advance and issue early warning signals before abnormal conditions occur, providing drivers and fleet managers with sufficient response time and effectively preventing potential safety hazards and operational interruptions.

[0025] In summary, this invention has significant advantages in improving the safety of commercial vehicles, extending tire life, reducing operating costs, and supporting intelligent driving data fusion. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below, forming part of the present invention. The illustrative embodiments of the present invention and their descriptions explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0027] Figure 1 This is a flowchart of a commercial vehicle tire pressure monitoring method based on vehicle configuration adaptation, disclosed in one embodiment of the present invention.

[0028] Figure 2 A flowchart of a commercial vehicle tire pressure monitoring method based on vehicle configuration adaptation disclosed in a preferred embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram of the user interface layout in a 6×4 axis mode disclosed in one embodiment of the present invention;

[0030] Figure 4 This is a structural block diagram of a vehicle static tire pressure monitoring device disclosed in one embodiment of the present invention. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. In the description of this invention, it should be noted that the term "or" is generally used to include the meaning of "and / or," unless otherwise expressly indicated.

[0032] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. Furthermore, in the description of this application, the terms "first," "second," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0033] Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0034] To address the technical problems existing in the prior art, the present invention provides, in a preferred embodiment, a method for tire pressure monitoring of commercial vehicles based on vehicle configuration adaptation, such as... Figure 1 The method preferably includes steps S110 to S140, as follows:

[0035] Step S110: Obtain the vehicle's configuration information and parse the number of drive shafts and their functional attributes.

[0036] Preferably, the vehicle described in this embodiment is a new energy tractor, and the specific specifications of the vehicle are not limited.

[0037] Preferably, step S110 specifically includes: obtaining the vehicle identification code and electronic control unit configuration parameters through the vehicle communication bus; extracting the vehicle drive type identifier from the configuration parameters; determining the number of drive shafts of the vehicle based on the drive type identifier; and determining the functional type of each axle position according to the number of drive shafts, including drive shaft, steering shaft and load-bearing follower shaft.

[0038] The preferred vehicle communication bus is the CAN bus, through which the system collects the vehicle's VIN code and vehicle configuration identifier from the ECU configuration parameters in real time. In one specific implementation, when the fifth byte of the vehicle configuration identifier is detected to be 0x1, it is automatically identified as a 6×4 vehicle model; when the byte value is 0x2, it is automatically identified as a 4×2 vehicle model. Using a pre-set vehicle model-tire mapping database, the number and distribution of tires under different drive configurations can be quickly determined.

[0039] Preferably, the preset vehicle model-tire mapping database is a dynamic topology model, including various drive configurations (such as 8×4, 6×4, and 4×2) for different vehicle models on different platforms (e.g., mass-produced vehicles, intelligent driving vehicles). In practical implementation, the system can automatically determine the number of tire sensors and communication protocols to be activated based on the configuration requirements of a specific vehicle model. For example, when a 4×2 drive configuration is detected, the system will only load the communication protocols for the front axle steering wheels (2 tires) and the rear drive axle (4 tires), effectively saving processor resources and improving system response speed. This dynamic topology model can automatically adapt to changes in vehicle configuration (such as axle number adjustments or sensor replacements) without manual intervention, significantly improving the system's scalability and versatility.

[0040] Preferably, step S110 further includes: setting the vehicle's form parameters, energy form parameters, and tire pressure monitoring system configuration status through an on-board configuration tool; encrypting the form parameters and energy form parameters to generate a vehicle configuration identifier; and writing the vehicle configuration identifier into the on-board control unit through a diagnostic interface; wherein the vehicle configuration identifier is used to verify the validity of the drive form identifier during system initialization.

[0041] In practice, a dedicated configuration tool can be used to set the configuration information of the vehicle upon production, including parameters such as vehicle type, energy type, drive type, and whether a tire pressure monitoring system is equipped. The system uses a hash algorithm to encrypt and store the configuration parameters, generating a corresponding configuration identifier, which is then written to the on-board unit (OIN) via the vehicle diagnostic system. This configuration identifier is read each time the system starts to verify the correctness of the vehicle's drive type and prevent malfunctions of the tire pressure monitoring system due to incorrect configuration information.

[0042] Step S120: Collect real-time operating parameters and tire status data of the vehicle.

[0043] Preferably, step S120 specifically includes: receiving tire status data from tire sensors, including tire pressure and tire temperature values, wherein the tire status data corresponds one-to-one with the physical tire positions of the vehicle according to a preset axle position coding rule; acquiring the vehicle's current load status, driving speed, and road slope information; and monitoring the working status and temperature distribution of the vehicle's braking system.

[0044] Specifically, the system uses an axle-position coding rule to identify tire positions. This rule uses the high four bits to represent axle information and the low four bits to represent the specific position within the same axle. For example, 0x00 represents the left outer tire of the first axle, 0x03 represents the right outer tire of the first axle, and 0x11 represents the left inner tire of the second axle, etc. The system collects tire status data in real time through an onboard sensor network, with temperature data covering a range of -40℃ to 215℃ and an accuracy of 1℃. Simultaneously, the system obtains vehicle load information, driving speed, and road gradient information calculated based on vehicle attitude sensors through the onboard ECU. For braking system monitoring, the system collects real-time temperature information and braking pressure data from each wheel brake, providing basic data support for subsequent calculation of differentiated alarm thresholds.

[0045] Preferably, step S120 further includes: detecting the trailer connection status; when trailer connection is detected, automatically acquiring trailer tire sensor data and integrating it into the tire status data set of the master vehicle; and dynamically expanding the tire monitoring range according to the acquired trailer configuration information.

[0046] Specifically, the system detects the access status of the trailer TPMS node via the J1939-92 protocol. When it receives a specific message ID (such as 0x18FEF100) from the trailer node, it identifies the trailer connection status. After identifying the trailer connection, the system automatically establishes a communication link with the trailer TPMS system, collects the status data of each tire of the trailer, and integrates it into the master vehicle's data set according to a unified data structure. For different types of trailers, the system can determine the number of axles and tires based on the received trailer configuration information, and then dynamically adjust the monitoring range.

[0047] Preferably, during data processing, the system uses a unified timestamp to mark the tire status data of the tractor and trailer, ensuring the consistency of data sequence and providing a reliable data foundation for subsequent abnormal state analysis. When the trailer is disconnected, the system can automatically detect the change in connection status and adjust the monitoring range and display interface accordingly.

[0048] Step S130: Based on the axle position functional attributes and operating parameters, dynamically determine the differentiated alarm thresholds for each axle tire.

[0049] Preferably, step S130 specifically includes: classifying vehicle tires into steering axle tires, drive axle tires, and load-bearing follow-up axle tires according to axle position functional attributes; obtaining the reference tire pressure limit values ​​for each type of axle tire; for steering axle tires, correcting their reference tire pressure limit values ​​based on driving speed and correction coefficients to obtain differentiated alarm thresholds for steering axle tires; for drive axle tires, correcting their reference tire pressure limit values ​​based on load status, road slope information, and correction coefficients to obtain differentiated alarm thresholds for drive axle tires; for load-bearing follow-up axle tires, correcting their reference tire pressure limit values ​​based on load status and correction coefficients to obtain differentiated alarm thresholds for load-bearing follow-up axle tires; wherein different correction coefficients are used for different axle types.

[0050] Specifically, for steering axle tires, the formula for calculating the differentiated alarm threshold is as follows:

[0051] Steering axle tire pressure threshold = Baseline threshold + Vehicle speed coefficient × Driving speed

[0052] The steering axle reference threshold is set at 800 kPa, the vehicle speed coefficient is 0.5 kPa / (km / h), and the maximum tire pressure threshold is 900 kPa. For example, when the vehicle speed is 60 km / h, the steering axle tire pressure threshold is: 800 kPa + 0.5 kPa / (km / h) × 60 km / h = 830 kPa.

[0053] Specifically, for the drive axle tires, the formula for calculating the differentiated alarm threshold is as follows:

[0054] Drive axle tire pressure threshold = Baseline threshold + Load factor × Load weight + Gradient factor × Road slope angle

[0055] The drive axle reference threshold is set at 850 kPa, the load factor is 1.2 kPa / ton, the gradient factor is 2 kPa / °, and the maximum tire pressure threshold is 950 kPa. For example, when the load is 15 tons and the road incline is 3°, the drive axle tire pressure threshold is: 850 kPa + 1.2 kPa / ton × 15 tons + 2 kPa / ° × 3° = 874 kPa.

[0056] Specifically, for load-bearing follow-up axle tires, the formula for calculating the differentiated alarm threshold is as follows:

[0057] Load-bearing follow-up axle tire pressure threshold = reference threshold + load factor × load weight

[0058] The load-bearing follower axle reference threshold is set at 780 kPa, the load factor is 2.0 kPa / ton, and the maximum tire pressure threshold is 880 kPa. For example, when the load is 20 tons, the load-bearing follower axle tire pressure threshold is: 780 kPa + 2.0 kPa / ton × 20ton = 820 kPa.

[0059] Preferably, the system adopts a real-time calculation model to continuously update the differentiated alarm thresholds for each axle tire based on the vehicle's current driving status, ensuring that the alarm strategy always meets the requirements of the current driving conditions.

[0060] Preferably, step S130 further includes: monitoring the working status of the braking system; when a long downhill condition is detected, acquiring tire temperature data for each axle; for drive axle tires, when the tire temperature exceeds a preset temperature threshold, automatically reducing the corresponding differentiated tire pressure alarm threshold; for non-drive axle tires, keeping the original differentiated tire pressure alarm threshold unchanged; wherein, the reduction ratio of the differentiated tire pressure alarm threshold is positively correlated with the tire temperature, used to prevent false alarms caused by thermal expansion.

[0061] Preferably, the system acquires braking system status information through the onboard brake control unit (BCU) and detects road gradient changes through a gradient sensor. When the system continuously monitors that the vehicle is in a continuous downhill state and the braking system is continuously operating, it automatically enters the long downhill condition monitoring mode. In the long downhill condition mode, the system prioritizes the temperature changes of the drive axle tires. This is because during long downhill braking of commercial vehicles, the drive axle tires often bear the main engine braking function, and their temperature rise is more significant. When the temperature of the drive axle tire exceeds the preset temperature threshold of 85°C, the system dynamically adjusts the tire pressure alarm threshold for that axle tire based on the actual temperature value. Specifically, after exceeding the preset temperature threshold of 85°C, the differential tire pressure alarm threshold can be directly reduced by 10%.

[0062] For the steering axle and load-bearing follow-up axle tires, since their temperature rise is not as significant as that of the drive axle in long downhill conditions, the system preferably keeps their original differentiated tire pressure alarm threshold unchanged to avoid unnecessary threshold fluctuations.

[0063] Step S140: Determine the relationship between tire status data and the differential alarm threshold of the corresponding axle position, and execute the corresponding tire pressure monitoring alarm strategy based on the determination result.

[0064] Preferably, step S140 specifically includes: acquiring tire status data for each axle in real time; comparing the acquired tire status data with the differential alarm threshold for the corresponding axle; and triggering an alarm signal when the tire status data exceeds the corresponding differential alarm threshold.

[0065] Compared to existing monitoring schemes that use a uniform threshold, using differentiated alarm thresholds can reduce the false alarm rate by 76%.

[0066] Preferably, step S140 further includes: calculating the tire pressure change trend within a future preset time period based on the historical change trend of tire condition data using a prediction algorithm; triggering a pre-alarm signal when the predicted tire pressure value exceeds the corresponding differentiated alarm threshold; wherein, the prediction algorithm calculates the change trend of tire condition parameters based on historical data sequences.

[0067] Specifically, this embodiment of the invention employs a tire pressure prediction model based on Kalman filtering to predict the tire pressure change trend within the next 5 minutes. This prediction model first establishes a time series of tire condition data. The system collects complete tire condition data every 10 seconds and uses historical data from the most recent 30 minutes as the basis for prediction, forming a sliding time window mechanism.

[0068] The predictive model uses a Kalman filter algorithm to process historical data. This algorithm alternates between state estimation and observation update stages to effectively filter out random fluctuations and measurement noise in the data, extracting the true trend of tire pressure changes. Based on the processed data, the tire pressure change trend for the next 5 minutes is calculated recursively, and the prediction result is compared with the differentiated alarm threshold corresponding to the current axle position. When the prediction indicates that the tire pressure of a certain tire will exceed the alarm threshold within the next 5 minutes, the system triggers a pre-alarm signal, informing the driver of the potential risk through the instrument display interface and voice prompts, providing sufficient warning time.

[0069] Preferably, the prediction algorithm designs differentiated early warning strategies for different abnormal modes: for slow deflation (e.g., tire pressure drop rate less than 5 kPa / minute), the system calculates the estimated time for complete deflation and provides an early warning of the corresponding level; for sudden tire pressure abnormalities, the system immediately triggers a high-level early warning and advises the driver to take emergency measures.

[0070] like Figure 2 In a preferred embodiment, the above method further includes steps S210 to S230, and these three steps are preferably performed after step S120.

[0071] Step S210: Based on the vehicle's configuration information, the user interface layout is adaptively adjusted. The user interface layout is dynamically adjusted on different display devices based on an adaptive algorithm.

[0072] Specifically, the system employs an adaptive UI algorithm to automatically optimize the interface layout based on the size and resolution of the vehicle's instrument panel display. (Reference) Figure 3The system displays a 6x4 axle user interface layout, designed using the QT framework for scalable, component-based design. It dynamically generates the most suitable display layout based on vehicle configuration information (such as the number of axles and tires) and precisely maps tire position information by defining axle position locator controls. An adaptive algorithm considers the characteristics of different display devices; when the system detects displays of different sizes, it automatically adjusts the size and arrangement of UI elements to ensure optimal visual effects and user experience on various in-vehicle display devices.

[0073] Specifically, the adaptive algorithm can be a rule-based layout algorithm, a responsive layout algorithm, a fluid layout algorithm, a grid layout algorithm, or a machine learning-assisted layout optimization algorithm, etc. In this embodiment, there is no limitation on which adaptive algorithm is used, as long as it can achieve the purpose of dynamically adjusting the interface layout according to different display devices and vehicle configuration information.

[0074] For example, in 4×2 axis mode, the system adjusts the brightness of the compressed display area to 40% to hide the third axis control, while simultaneously enlarging the font size of the tire pressure value on the drive axis by 20% to highlight its importance.

[0075] Step S220: Based on the axis position function attributes, use different visual identifiers to distinguish axes with different functions in the user interface.

[0076] Preferably, the system adopts a categorized visual design scheme, using a differentiated display strategy for axes with different functions. (Reference) Figure 3 For the 6×4 axle mode, the three-axis data is distributed in a vertical matrix. The drive axle icons are bordered in red to visually highlight their crucial role in vehicle operation. Furthermore, the interface design must consider the spatial layout characteristics of different axle positions to ensure the interface display is consistent with the actual vehicle structure, facilitating quick driver identification of the corresponding positions.

[0077] Step S230: Based on the tire status data, dynamically display the temperature and tire pressure information of the tires on each axle.

[0078] Preferably, the tire temperature data is displayed using a color gradient, with a blue-to-red gradient from low to high temperature to visually reflect the temperature change.

[0079] Preferably, after receiving real-time tire status data collected by sensors, the system updates the interface display according to a preset refresh frequency, allowing the driver to intuitively understand the current status of each tire. When a tire status parameter approaches a warning threshold, the corresponding value area will change color to alert the driver; when it exceeds the alarm threshold, the driver will be further alerted through color flashing and icon changes.

[0080] Preferably, the method further includes step S240, which automatically expands the user interface display area to accommodate the increased tire monitoring points when a trailer connection signal is received.

[0081] Specifically, by detecting the TPMS node access status of the trailer using the J1939-92 protocol, the system can automatically identify the trailer connection status. When a trailer connection signal is detected, the interface will automatically enter the trailer plug-and-play display mode, dynamically expanding the tire monitoring display area and integrating the trailer tire status information into a unified interface.

[0082] refer to Figure 3 Based on the existing layout, the system will adaptively add a trailer tire status display area below or to the side of the original main vehicle display area, depending on the available screen space, and clearly distinguish the main vehicle and trailer sections with a visual dividing line. For different vehicle models and trailer configurations, the system can intelligently identify and adjust the displayed content to ensure a reasonable and intuitive information layout, improving information recognition efficiency by approximately 70%. It also supports adaptive tire pressure display systems that can be attached to the current vehicle and trailer as needed.

[0083] It should be noted that the main body executing the commercial vehicle tire pressure monitoring method based on vehicle configuration adaptation in this embodiment is the tire pressure monitoring system. The "system" mentioned in the method of this invention refers to this system, which interacts with other electronic control units of the vehicle through the CAN bus, receives tire sensor data, processes and analyzes it according to a preset algorithm, and connects to the instrument display unit through the standard vehicle protocol to present the processed data to the driver in a visual form, and triggers an alarm mechanism when necessary.

[0084] like Figure 4 In one embodiment of the present invention, a commercial vehicle tire pressure monitoring device 300 based on vehicle configuration adaptation is also provided. This device includes a vehicle configuration acquisition module 310, a data acquisition module 320, a threshold determination module 330, and a monitoring and alarm module 340. The vehicle configuration acquisition module 310 acquires vehicle configuration information and parses the number of drive axles and axle position functional attributes. The data acquisition module 320 acquires real-time operating parameters and tire status data of the vehicle. The threshold determination module 330 dynamically determines differentiated alarm thresholds for tires at each axle position based on the axle position functional attributes and the operating parameters. The monitoring and alarm module 340 determines the relationship between the tire status data and the differentiated alarm thresholds for the corresponding axle position, and executes corresponding tire pressure monitoring and alarm strategies based on the determination result.

[0085] Specifically, the commercial vehicle tire pressure monitoring device 300 based on vehicle configuration adaptation provided in this embodiment of the invention and the aforementioned commercial vehicle tire pressure monitoring method based on vehicle configuration adaptation originate from the same inventive concept and are the hardware implementation of the method. Each functional module in the device corresponds one-to-one with each step in the method. The specific functions, implementation methods, technical features, and preferred implementation methods of each module are consistent with the descriptions of the corresponding steps in the aforementioned method, and will not be repeated here.

[0086] In one embodiment of the present invention, a vehicle is also provided, which is equipped with the above-described commercial vehicle tire pressure monitoring device based on vehicle model configuration and is capable of executing the above-described commercial vehicle tire pressure monitoring method based on vehicle model configuration. Preferably, the vehicle in this embodiment is a pure electric commercial vehicle, specifically a pure electric tractor.

[0087] This invention also provides an electronic device including a memory and a processor. The memory stores a computer program executed by the processor. When the computer program is run by the processor, it causes the processor to execute the aforementioned vehicle model configuration-based adaptive tire pressure monitoring method for commercial vehicles. The memory may also store various application programs and various data, such as various data used and / or generated by the application programs. The processor may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other processing units with data processing capabilities and / or instruction execution capabilities.

[0088] This invention also provides a computer-readable storage medium storing a computer program executed by a processor. When the computer program is executed by the processor, it causes the processor to perform the vehicle configuration-based adaptive tire pressure monitoring method for commercial vehicles as described above. Exemplarily, the computer storage medium may include a memory card of a smartphone, a storage component of a tablet computer, a hard disk of a personal computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disc read-only memory (CD-ROM), a USB memory, or any combination of the above storage media. The computer-readable storage medium may be any combination of one or more computer-readable storage media.

[0089] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of this application. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of this application. All such changes and modifications are intended to be included within the scope of this application as claimed in the appended claims.

[0090] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0091] Similarly, it should be understood that, in order to streamline this application and aid in understanding one or more of the various inventive aspects, features of this application may sometimes be grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of this application. However, this approach should not be construed as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, its inventive point lies in solving the corresponding technical problem with features fewer than all features of a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this application.

[0092] Those skilled in the art will understand that, apart from the mutual exclusion of features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or elements of any method or apparatus so disclosed can be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature serving the same, equivalent, or similar purpose.

[0093] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of the present invention.

Claims

1. A method for tire pressure monitoring in commercial vehicles based on vehicle configuration adaptation, characterized in that, include: Obtain vehicle configuration information and parse the number of drive axles and axle position functional attributes. Specifically, this includes: setting the vehicle's form parameters, energy form parameters, and tire pressure monitoring system configuration status through an on-board configuration tool; encrypting the form parameters and energy form parameters to generate a vehicle configuration identifier; and writing the vehicle configuration identifier into the on-board control unit through a diagnostic interface. The vehicle configuration identifier is used to verify the validity of the drive form identifier during system initialization. The system collects real-time operating parameters and tire status data of the vehicle, specifically including: receiving tire status data from tire sensors, including tire pressure and tire temperature values, wherein the tire status data corresponds one-to-one with the physical tire positions of the vehicle according to a preset axle position coding rule; acquiring the vehicle's current load status, driving speed, and road slope information; and monitoring the working status and temperature distribution of the vehicle's braking system. Based on the axle position functional attributes and the operating parameters, the differentiated alarm thresholds for tires in each axle position are dynamically determined, specifically including: classifying vehicle tires into steering axle tires, drive axle tires, and load-bearing follow-up axle tires according to the axle position functional attributes; obtaining the baseline tire pressure limit values ​​for each type of axle tire; for steering axle tires, correcting their baseline tire pressure limit values ​​based on the driving speed and correction coefficient to obtain the differentiated alarm thresholds for steering axle tires; for drive axle tires, correcting their baseline tire pressure limit values ​​based on the load state, road slope information, and correction coefficient to obtain the differentiated alarm thresholds for drive axle tires; for load-bearing follow-up axle tires... Based on the load state and correction coefficient, the reference tire pressure limit value is corrected to obtain the differentiated alarm threshold for the load-bearing follow-up axle tire; different correction coefficients are used for different axle types; and the working status of the braking system is monitored, and when a long downhill condition is detected, the tire temperature data of each axle is acquired; for drive axle tires, when the tire temperature exceeds a preset temperature threshold, the corresponding differentiated tire pressure alarm threshold is automatically reduced; for non-drive axle tires, the original differentiated tire pressure alarm threshold remains unchanged; wherein, the reduction ratio of the differentiated tire pressure alarm threshold is positively correlated with the tire temperature to prevent false alarms caused by thermal expansion; Determine the relationship between the tire status data and the differential alarm threshold of the corresponding axle position, and execute the corresponding tire pressure monitoring alarm strategy based on the determination result.

2. The commercial vehicle tire pressure monitoring method based on vehicle configuration adaptation according to claim 1, characterized in that, The steps of obtaining vehicle configuration information and parsing the number of drive axles and axle position functional attributes specifically include: The vehicle identification code and electronic control unit configuration parameters are obtained through the vehicle communication bus. Extract the driver type identifier from the configuration parameters; The number of drive shafts of the vehicle is determined based on the drive type identifier; Based on the number of drive shafts, determine the functional type of each shaft position, including drive shaft, steering shaft, and load-bearing follower shaft.

3. The commercial vehicle tire pressure monitoring method based on vehicle configuration adaptation according to claim 1, characterized in that, The steps of collecting real-time operating parameters and tire condition data of the vehicle also include: Check the trailer connection status; When a trailer connection is detected, the system automatically acquires data from the trailer's tire sensors and integrates it into the tire status data set of the main vehicle. Based on the obtained trailer configuration information, the tire monitoring range is dynamically expanded.

4. The commercial vehicle tire pressure monitoring method based on vehicle configuration adaptation according to claim 1, characterized in that, The step of determining the relationship between the tire condition data and the differential alarm threshold of the corresponding axle position, and executing the corresponding tire pressure monitoring alarm strategy based on the determination result, includes: Real-time acquisition of tire status data for each axle; The acquired tire status data is compared with the differential alarm threshold for the corresponding axle position; An alarm signal is triggered when the tire status data exceeds the corresponding differentiated alarm threshold.

5. The commercial vehicle tire pressure monitoring method based on vehicle configuration adaptation according to claim 4, characterized in that, The step of determining the relationship between the tire condition data and the differential alarm threshold of the corresponding axle position, and executing the corresponding tire pressure monitoring alarm strategy based on the determination result, further includes: Based on the historical trends of tire condition data, a predictive algorithm is used to calculate the tire pressure change trend within a preset time period in the future. When the predicted tire pressure value exceeds the corresponding differential alarm threshold, a pre-alarm signal is triggered; The prediction algorithm calculates the changing trend of tire condition parameters based on historical data sequences.

6. The commercial vehicle tire pressure monitoring method based on vehicle configuration adaptation according to claim 1, characterized in that, Also includes: Based on the vehicle's configuration information, the user interface layout is adaptively adjusted, and the user interface layout is dynamically adjusted on different display devices based on an adaptive algorithm; Based on the axis position functional attributes, axes with different functions are distinguished by different visual identifiers in the user interface; Based on the tire condition data, the temperature and tire pressure information of each axle tire are dynamically displayed.

7. The commercial vehicle tire pressure monitoring method based on vehicle configuration adaptation according to claim 6, characterized in that, Also includes: When a trailer connection signal is received, the user interface display area is automatically expanded to accommodate the increased tire monitoring points.

8. A tire pressure monitoring device for commercial vehicles based on vehicle configuration adaptation, characterized in that, include: The vehicle configuration acquisition module is used to acquire vehicle configuration information and parse the number of drive shafts and axle position functional attributes. Specifically, it includes: setting the vehicle's form parameters, energy form parameters, and tire pressure monitoring system configuration status through an on-board configuration tool; encrypting the form parameters and energy form parameters to generate a vehicle configuration identifier; and writing the vehicle configuration identifier into the on-board control unit through a diagnostic interface. The vehicle configuration identifier is used to verify the validity of the drive form identifier during system initialization. The data acquisition module is used to collect real-time operating parameters and tire status data of the vehicle. Specifically, it includes: receiving the tire status data from the tire sensors, including tire pressure and tire temperature values, wherein the tire status data corresponds one-to-one with the physical tire positions of the vehicle according to a preset axle position coding rule; acquiring the vehicle's current load status, driving speed, and road slope information; and monitoring the working status and temperature distribution of the vehicle's braking system. The threshold determination module is used to dynamically determine the differentiated alarm thresholds for tires on each axle based on the axle position functional attributes and the operating parameters. Specifically, it includes: classifying vehicle tires into steering axle tires, drive axle tires, and load-bearing follow-up axle tires according to the axle position functional attributes; obtaining the baseline tire pressure limit values ​​for each type of axle tire; for steering axle tires, correcting their baseline tire pressure limit values ​​based on the driving speed and a correction coefficient to obtain the differentiated alarm thresholds for steering axle tires; for drive axle tires, correcting their baseline tire pressure limit values ​​based on the load status, road slope information, and a correction coefficient to obtain the differentiated alarm thresholds for drive axle tires; and for load-bearing follow-up axle tires... The following axle tire, based on the load state and correction coefficient, corrects its reference tire pressure limit value to obtain the differentiated alarm threshold for the load-bearing following axle tire; different correction coefficients are used for different axle types; and the working status of the braking system is monitored, and when a long downhill condition is detected, the tire temperature data of each axle is acquired; for drive axle tires, when the tire temperature exceeds a preset temperature threshold, the corresponding differentiated tire pressure alarm threshold is automatically reduced; for non-drive axle tires, the original differentiated tire pressure alarm threshold remains unchanged; wherein, the reduction ratio of the differentiated tire pressure alarm threshold is positively correlated with the tire temperature to prevent false alarms caused by thermal expansion; The monitoring and alarm module is used to determine the relationship between the tire status data and the differential alarm threshold of the corresponding axle position, and to execute the corresponding tire pressure monitoring and alarm strategy based on the determination result.

9. A computer-readable storage medium, characterized in that, The storage medium stores at least one instruction, which is loaded by a processor and executed to implement the commercial vehicle tire pressure monitoring method based on vehicle configuration adaptation as described in any one of claims 1-7.

10. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing at least one instruction, which is loaded and executed by the processor to implement the vehicle configuration-adaptive commercial vehicle tire pressure monitoring method as described in any one of claims 1-7.

Images