A method for transmitting tire pressure information data

Abstract

This application relates to a method for transmitting tire pressure information data, comprising the following steps: S1. A relay receiver receives tire pressure data transmitted by multiple tire pressure sensors via a wireless channel during a receiving period; S2. The relay receiver transmits the integrated tire pressure information to a tire pressure host via a wired data connection line during a sending period; S3. The tire pressure host selects either a precise display mode or a fuzzy feedback mode to output the tire pressure information based on the vehicle's status; wherein: in the precise display mode, the precise pressure value and temperature data of each tire are displayed via a pre-installed onboard display screen; in the fuzzy feedback mode, tire pressure status information is transmitted via a pre-installed tactile feedback device and LED indicator light combination on the vehicle. This application can significantly improve the anti-interference performance and timeliness of tire pressure data transmission.

Description

Technical Field

[0001] The present application relates to the field of tire pressure data processing, and in particular to a method for transmitting tire pressure information data. Background Art

[0002] With the rapid development of automotive electronics, tire pressure monitoring systems (TPMS) have become a standard safety feature in modern vehicles. However, existing technologies still have the following prominent problems in practical applications:

[0003] 1. Electromagnetic interference: The traditional 315 / 433MHz transmission frequency band is susceptible to electromagnetic interference from vehicle-mounted equipment such as the ignition system (generating transient interference with a peak value of 200V / m) and the electric power steering (generating 20-100kHz harmonic interference). Actual measurement data shows that at the moment of engine startup, the bit error rate of the traditional system can reach 10 -2 Magnitude.

[0004] 2. Transmission conflict: When relay devices transmit and receive signals in the same frequency band, they can cause co-frequency interference. Experiments have shown that when the transmit power exceeds 10dBm, the receiving sensitivity decreases by over 30%.

[0005] 3. Insufficient feedback effectiveness: Existing systems mostly use a single visual alarm, with a recognition rate of less than 60% in strong lighting environments, and cannot meet the multimodal interaction requirements of L3 and above autonomous driving systems.

[0006] 4. Data integrity risk: The traditional CRC check has a missed detection rate of up to 0.1% in sudden interference scenarios, and the packet loss rate in complex electromagnetic environments can reach 5%-8%.

[0007] A Chinese patent with announcement number CN115091901B discloses a tire pressure information transmission method, system and device. The method includes the following steps: wirelessly monitoring the tire pressure signal radiated by any one of a plurality of tire pressure sensors, and entering a batch processing state after receiving the first tire pressure signal; continuing to monitor and receive the tire pressure signals radiated by the plurality of tire pressure sensors in the batch processing state; after obtaining the tire pressure signals of all the plurality of tire pressure sensors, or after the batch processing state is terminated, repackaging the tire pressure information in each received tire pressure signal into comprehensive tire pressure information; and transmitting the comprehensive tire pressure information to a tire pressure host for displaying the comprehensive tire pressure information via a data connection line. This method only avoids interference of wired communication on wireless signals through time-segmented non-overlapping transmission, but does not solve the anti-interference problem of wireless transmission itself and cannot cope with complex electromagnetic environments. In particular, it relies on a batch processing mechanism and needs to wait for a preset period of time or for all sensor data to be received before sending comprehensive information, resulting in significant response delays in emergency scenarios. In addition, the fixed time window design makes the tire pressure transmission timing unstable, which easily leads to incomplete tire pressure data and data update lags at high vehicle speeds.

[0008] With respect to the above-mentioned related technologies, the inventors believe that the existing tire pressure information transmission methods have problems such as poor anti-interference ability, insufficient real-time performance and single user interaction. Summary of the Invention

[0009] In order to solve the above problems, the present application provides a method for transmitting tire pressure information data.

[0010] In a first aspect, the present application provides a method for transmitting tire pressure information data, which adopts the following technical solutions:

[0011] A method for transmitting tire pressure information data comprises the following steps:

[0012] S1. The relay receiver receives tire pressure data sent by multiple tire pressure sensors through a wireless channel during a receiving period;

[0013] S2. The relay receiver transmits the comprehensive tire pressure information to the tire pressure host via the wired data connection line during a sending period, wherein the sending period and the receiving period do not overlap in time and are separated by a guard interval of at least 1 ms;

[0014] S3. The tire pressure host selects the precise display mode or the fuzzy feedback mode to output tire pressure information according to the vehicle status; wherein:

[0015] In the precise display mode, the precise pressure and temperature data of each tire are displayed on the pre-set on-board display screen of the vehicle;

[0016] In fuzzy feedback mode, tire pressure status information is transmitted through the interactive device pre-installed on the vehicle.

[0017] Preferably, the receiving period adopts a frequency hopping mechanism to perform dynamic frequency switching in the 902-928 MHz frequency band.

[0018] Preferably, the receiving period in step S1 adopts a three-dimensional time division multiplexing control mechanism, specifically including:

[0019] A1. Time dimension division: The front and rear wheel sensors use staggered time window transmission, and the time window length is dynamically adjusted according to vehicle speed;

[0020] A2. Spatial dimension control: Each tire sensor is assigned a different initial transmission time slot based on its installation location;

[0021] A3. Frequency dimension coordination: Adjacent tire sensors within the same time window use different communication frequencies.

[0022] Preferably, the specific method of dynamically adjusting the time window length according to the vehicle speed includes:

[0023] B1. When the vehicle speed is less than 30 km / h, the receiving window length is 200±50ms;

[0024] B2. When 30 km / h ≤ vehicle speed < 80 km / h, the receiving window length is dynamically set using a preset receiving window calculation formula. The receiving window calculation formula is specifically: T = 200 - 1.75V, where T is the receiving window length in milliseconds; V is the vehicle speed value;

[0025] B3. When the vehicle speed is ≥80km / h, the fixed receiving window is 50ms.

[0026] Preferably, the data transmission in step S1 adopts a PPM-FSK hybrid modulation mode, specifically:

[0027] When the tire pressure fluctuation amplitude is less than 5kPa, FSK modulation is used;

[0028] When the tire pressure fluctuation amplitude is ≥5kPa, switch to PPM modulation mode.

[0029] Preferably, the fuzzy feedback mode can be pre-set according to the application vehicle, specifically comprising the following steps:

[0030] Collect configuration information of vehicles sold on the market to establish a vehicle database;

[0031] Obtain the VIN code of the application vehicle and search the vehicle database to obtain its configuration information; the configuration information includes vehicle hardware configuration information and hardware control logic configuration information;

[0032] A fuzzy feedback rule for the application vehicle is generated based on a preset matching strategy model according to the configuration information of the application vehicle. The fuzzy feedback mode is pre-set by loading the matched fuzzy feedback rule into the application vehicle. The fuzzy feedback rule includes the vehicle's tactile feedback hardware, sound feedback hardware and / or visual feedback hardware, hardware fixed trigger logic parameters, and hardware dynamic adjustment strategy. The matching strategy model is a deep neural network model obtained through deep learning training of historical data, and the historical data includes vehicle configuration information, optimal feedback rules set by experts, strategy effect feedback data, and industry prior rule data.

[0033] Preferably, the generating of the fuzzy feedback rules of the application vehicle according to the matching strategy model preset based on the configuration information of the application vehicle specifically includes the following steps:

[0034] The matching strategy model determines the feedback hardware that can be enabled for the vehicle and the optimal trigger logic parameters according to the vehicle hardware configuration information of the application vehicle; the enabled feedback hardware includes priority feedback hardware and second priority feedback hardware;

[0035] The matching strategy model determines whether the optimal trigger logic parameters of the priority feedback hardware are occupied by other functions of the application vehicle based on the hardware control logic configuration information of the application vehicle;

[0036] If it is not occupied, the priority feedback hardware is selected and its optimal trigger logic parameters are used as the hardware fixed trigger logic parameters. The hardware dynamic adjustment strategy of the selected hardware is generated through matching strategy model matching, and the fuzzy feedback rules of the application vehicle are packaged and output;

[0037] If occupied, determine whether there is a second priority feedback hardware of the same type based on the feedback type of the occupied priority feedback hardware;

[0038] If it exists, the second-priority feedback hardware of the same type as the occupied priority feedback hardware and other unoccupied priority feedback hardware are selected, and their optimal trigger logic parameters are used as the hardware fixed trigger logic parameters. The hardware dynamic adjustment strategy of the selected hardware is generated through matching strategy model matching, and the fuzzy feedback rules of the application vehicle are packaged and output;

[0039] If it does not exist, the idle feedback mode of the occupied priority feedback hardware is selected according to the hardware control logic configuration information through the matching strategy model, and the decision is made to generate its current optimal trigger logic parameters;

[0040] The current optimal trigger logic parameters of the occupied priority feedback hardware and the optimal trigger logic parameters of other unoccupied priority feedback hardware are selected as the hardware fixed trigger logic parameters. The hardware dynamic adjustment strategy of the selected hardware is generated through matching strategy model matching, and the fuzzy feedback rules of the application vehicle are packaged and output.

[0041] Preferably, steps S1 and S2 employ a double check mechanism during data transmission, specifically including:

[0042] First check: CRC-8 check is used when transmitting data over wireless channels;

[0043] Second check: BCH (15,7) coding check is used when transmitting data on the wired data connection line.

[0044] Preferably, it also includes building a multi-vehicle collaborative tire pressure warning network to realize tire pressure information warning, which specifically includes the following steps:

[0045] Build a tire pressure information sharing network between vehicles, and broadcast the tire pressure status data packet of the application vehicle in real time through the pre-configured V2X communication module. The tire pressure status data packet includes vehicle location information, tire pressure status information and digital signature information;

[0046] Receive tire pressure status data packets from surrounding vehicles in the inter-vehicle tire pressure information sharing network in real time, and calculate the warning risk value R using a preset risk calculation formula. The risk calculation formula is specifically:

[0047] ;

[0048] in, is the absolute value of the tire pressure deviation of the surrounding abnormal vehicles, in kPa; D is the real-time distance between the application vehicle and the abnormal vehicle; a is the tire pressure abnormality weight coefficient, and b is the vehicle distance weight coefficient, both of which are set by the management personnel, and a>b;

[0049] When the warning risk value R>0.8, it is judged that there is a risk of abnormal tire pressure, and a heat map of the warning area is projected on the vehicle HUD.

[0050] Preferably, the tire pressure data sent by the tire pressure sensor is transmitted in a data compression manner, which specifically includes the following steps:

[0051] A lightweight tire pressure prediction model with a size of less than 50KB runs on the tire pressure sensor. It inputs a pressure / temperature sequence of 10 historical tire pressure sampling points and outputs a predicted value for the next cycle. The lightweight tire pressure prediction model is a lightweight LSTM model trained using historical tire pressure data.

[0052] Using the improved CAPS protocol for data transmission, the system determines whether the pressure deviation ΔP or temperature deviation ΔT between the tire pressure sensor's measured and predicted values ​​exceeds a preset prediction threshold. The prediction thresholds include tire pressure error thresholds and temperature error thresholds, both set by management personnel.

[0053] If it exceeds, it is determined to be an abnormal state, and the complete 4-byte differential data is transmitted to the relay receiver, along with a timestamp;

[0054] If it does not exceed, it is determined to be in normal state and a 1-byte status code is transmitted to the relay receiver. This status code includes a prediction deviation flag, which is used to indicate the deviation level between the measured data and the predicted data.

[0055] In summary, this application includes at least one of the following beneficial technical effects:

[0056] 1. Wireless reception and wired transmission are performed in a time-sharing manner through a relay receiver. The reception period and the transmission period do not overlap, effectively avoiding electromagnetic interference of wired transmission on the wireless signal and significantly reducing the bit error rate. Different feedback display modes are provided according to the user's vehicle status. When the user's vehicle is parked or driving at low speeds (less than 5km / h), the precise display mode is activated to provide the user with the precise pressure value and temperature data of each tire. When the user's vehicle is at medium or high speeds, the user is often distracted and cannot frequently check the tire pressure data. In this case, the fuzzy feedback mode uses tactile / optical signals to transmit information, allowing the driver to understand tire pressure anomalies in real time, greatly shortening the driver's response time, helping to ensure driver safety, and greatly improving the anti-interference performance and timeliness of tire pressure data transmission.

[0057] 2. A three-dimensional time-division multiplexing control mechanism is used. Time-division division prevents interference between sensors of the same type, spatial-dimension control enables the relay receiver to accurately identify the data sent by each sensor, and frequency-dimension coordination further reduces data transmission conflicts at the frequency level. The coordinated optimization across time, space, and frequency dimensions comprehensively improves the reliability, efficiency, and anti-interference capabilities of tire pressure sensor data transmission, providing strong support for safe and stable vehicle operation.

[0058] 3. It can significantly improve the adaptability and effectiveness of tire pressure information data transmission methods and different vehicles. It can generate personalized fuzzy feedback rules through matching strategy models based on the actual configuration of the vehicle, and can meet the differences in hardware configuration and control logic of vehicles of different brands and models. Whether it is the complex electronic system of high-end luxury cars or the relatively simple configuration of economy vehicles, it can achieve good adaptation and accurately generate fuzzy feedback rules that conform to the actual situation of the application vehicle. This accuracy ensures that tire pressure abnormality feedback can be presented to the driver in the most appropriate way on different vehicles, improving the driver's perception efficiency of tire pressure abnormalities. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a system block diagram of the tire pressure information data transmission system in Example 1 of the present application;

[0060] Figure 2 This is a flow chart of a method for transmitting tire pressure information data in Example 1 of the present application;

[0061] Figure 3 This is a flow chart of a method for generating a frequency sequence of a frequency hopping mechanism in Example 1 of the present application;

[0062] Figure 4 This is a three-dimensional time division multiplexing timing diagram in Example 1 of the present application;

[0063] Figure 5 This is a flow chart of a method for presetting the fuzzy feedback mode according to the application vehicle in Example 1 of the present application;

[0064] Figure 6 is a flow chart of a method for generating fuzzy feedback rules for applying vehicle matching in Example 1 of the present application;

[0065] Figure 7 This is a flow chart of a method for constructing a multi-vehicle collaborative tire pressure warning network to implement tire pressure information warning in Example 2 of the present application;

[0066] Figure 8 This is a flow chart of a method for transmitting tire pressure data sent by the tire pressure sensor in Example 3 of the present application using data compression. DETAILED DESCRIPTION

[0067] The following is combined with Figure 1-8 This application is described in further detail.

[0068] Example 1

[0069] The embodiment of the present application discloses a method for transmitting tire pressure information data. Figure 1 and Figure 2 A method for transmitting tire pressure information data comprises the following steps:

[0070] S1. The relay receiver receives tire pressure data transmitted by multiple tire pressure sensors via a wireless channel during a receiving period. The relay receiver receives tire pressure data transmitted by multiple tire pressure sensors via a wireless channel during a predefined receiving period. Each tire pressure sensor is installed inside a vehicle tire and periodically collects tire pressure values ​​(unit: kPa) and temperature values ​​(unit: °C) and transmits them to the relay receiver via wireless signals.

[0071] S2. The relay receiver transmits the comprehensive tire pressure information to the tire pressure host through the wired data connection line during the sending period. The sending period and the receiving period do not overlap in time dimension and are separated by a protection interval of at least 1ms. The protection interval can effectively suppress co-frequency interference. The applicant's experimental data shows that when the protection interval is 1ms, the bit error rate of the relay receiver is reduced to 10 -5 the following;

[0072] S3. The tire pressure host selects the precise display mode or the fuzzy feedback mode to output tire pressure information according to the vehicle status; wherein:

[0073] In the precise display mode, the vehicle's pre-set onboard display screen displays the precise pressure and temperature data of each tire; it is suitable for scenarios where the vehicle is stationary or driving at low speeds.

[0074] In fuzzy feedback mode, tire pressure status information is transmitted via pre-configured interactive devices on the vehicle. These interactive devices include the vehicle's haptic, audio, and visual feedback hardware. This mode is suitable for medium- and high-speed driving scenarios, minimizing driver distraction. A relay receiver performs wireless reception and wired transmission in a time-sharing manner, with the reception and transmission periods non-overlapping. This effectively prevents electromagnetic interference from wired transmission on wireless signals, significantly reducing bit error rates. Different feedback display modes are provided based on the user's vehicle status. When the vehicle is parked or driving at low speeds (less than 5 km / h), the precise display mode is activated, providing the user with precise pressure and temperature data for each tire. However, when the vehicle is driving at medium and high speeds, where the user is often distracted and unable to check tire pressure data, fuzzy feedback mode uses tactile / optical signals to transmit information, allowing the driver to understand tire pressure anomalies in real time. This significantly reduces driver response time, helps ensure safe driving, and significantly improves the interference resistance and timeliness of tire pressure data transmission. In addition, the fuzzy feedback mode uses multi-modal feedback (touch + vision) compared to traditional visual feedback, which can greatly shorten the driver's response time, seize the golden reaction time of abnormal tire pressure, and ensure the safety of people on the vehicle.

[0075] In this embodiment, the receiving period in step S1 uses a frequency hopping mechanism to perform dynamic frequency switching in the 902-928MHz frequency band. The frequency hopping mechanism dynamically switches the frequency point to avoid interference in the fixed frequency band. The frequency hopping mechanism dynamically switches the frequency point in 1MHz steps, and the frequency hopping sequence is generated by a Hash algorithm. Figure 3 The specific process is as follows:

[0076] S11, VIN code input: Generate an initial seed value based on the vehicle's unique identifier (such as the VIN code);

[0077] S12, Hash value calculation: Input the seed value into the hash function (such as SHA-256) and output the hash value;

[0078] S13. Output frequency hopping sequence: The last 16 bits of the hash value are truncated, converted to a decimal number, and then modulo-calculated to obtain the frequency hopping sequence. Following this process ensures the randomness and unpredictability of the frequency hopping sequence, effectively avoiding external interference sources (such as 200V / m transient interference from the ignition system), and significantly improving the tire pressure sensor's data transmission success rate. Furthermore, the hash-generated frequency hopping sequence is unpredictable, preventing malicious signal blocking attacks and enhancing tire pressure data security.

[0079] To reduce multi-sensor data transmission conflicts, the receiving period in step S1 adopts a three-dimensional time division multiplexing control mechanism, specifically including:

[0080] A1. Time dimension division: The front and rear wheel sensors use staggered time window transmission, and the time window length is dynamically adjusted according to vehicle speed;

[0081] A2. Spatial dimension control: Each tire sensor is assigned a different initial transmission time slot based on its installation location (front left, front right, rear left, rear right);

[0082] A3. Frequency dimension coordination: Adjacent tire sensors in the same time window use different communication frequencies. Figure 4 , which shows an example of a 3D time-division multiplexing timing diagram. Using a 3D time-division multiplexing control mechanism, time-division division prevents interference between sensors of the same type. Spatial-dimension control facilitates accurate identification of data from each sensor by the relay receiver. Frequency coordination further reduces data transmission conflicts at the frequency level. This collaborative optimization across time, space, and frequency dimensions comprehensively improves the reliability, efficiency, and anti-interference capabilities of tire pressure sensor data transmission, providing strong support for safe and stable vehicle operation.

[0083] The specific method of dynamically adjusting the time window length according to the vehicle speed includes:

[0084] B1. When the vehicle speed is less than 30 km / h, the receiving window length is 200 ± 50 ms. Specifically, when the vehicle speed is less than 30 km / h, the Doppler shift caused by vehicle movement is small. The specific setting value of the receiving window length can be adjusted differently according to the specific vehicle configuration and antenna model, but the value range is 200 ± 50 ms. At the same time, adaptive adjustment can be made based on road conditions. When the vehicle speed is less than 30 km / h, the road condition is determined by the vehicle acceleration rate. When the acceleration rate is greater than 0.5 m / s² (such as in urban roads with frequent starts and stops), the window length is capped at 250 ms to increase the data reception fault tolerance rate. When the acceleration rate is ≤ 0.5 m / s² (such as on slow-moving highways), the window length is capped at 150 ms to increase the data update frequency.

[0085] B2. When 30 km / h ≤ vehicle speed < 80 km / h, the receiving window length is dynamically set using a preset receiving window calculation formula. The receiving window calculation formula is specifically: T = 200 - 1.75V, where T is the receiving window length in milliseconds; V is the vehicle speed value;

[0086] B3. When the vehicle speed is ≥80 km / h, the fixed receiving window is 50ms. The receiving window is dynamically adjusted so that the data update frequency increases with vehicle speed. At low vehicle speeds, the risk of abnormal tire pressure is low, and the driver has ample time to react. Extending the window improves the weak signal reception rate and ensures stable data reception. At high speeds, the risk of abnormal tire pressure is relatively high, and the driver's reaction time is greatly shortened. Shortening the window ensures data timeliness. Combined with the fuzzy feedback mode, it ensures that the driver can respond to abnormal tire pressure immediately and react efficiently, greatly improving vehicle driving safety.

[0087] In addition, the data transmission in step S1 adopts the PPM-FSK hybrid modulation method, specifically:

[0088] When the tire pressure fluctuation amplitude is less than 5kPa, FSK modulation is used;

[0089] When the tire pressure fluctuation is ≥5kPa, it switches to PPM modulation. When the tire pressure fluctuation is small, FSK modulation is used, and its low power consumption is suitable for stable transmission. When the tire pressure fluctuation is ≥5kPa, it switches to PPM modulation, increasing the transmission rate and range (FSK is only 30m, PPM is 50m) to cope with emergency situations. This hybrid modulation method can significantly reduce the energy consumption of the tire pressure monitoring system.

[0090] Reference Figure 5 The fuzzy feedback mode can be preset according to the application vehicle, specifically including the following steps:

[0091] C1. Establish vehicle database: collect configuration information of vehicles sold on the market to establish a vehicle database;

[0092] C2. Obtain vehicle configuration information: Obtain the VIN code of the application vehicle and search the vehicle database to obtain its configuration information; the configuration information includes vehicle hardware configuration information and hardware control logic configuration information;

[0093] C3. Generate and load fuzzy feedback rules: Generate fuzzy feedback rules for the application vehicle based on the preset matching strategy model of the application vehicle's configuration information. Loading the matched fuzzy feedback rules into the application vehicle completes the pre-setting of the fuzzy feedback mode. The fuzzy feedback rules include the vehicle's tactile feedback hardware, sound feedback hardware, and / or visual feedback hardware, hardware fixed trigger logic parameters, and hardware dynamic adjustment strategy. The matching strategy model is a deep neural network model obtained through deep learning training of historical data. The historical data includes vehicle configuration information, optimal feedback rules set by experts, strategy effect feedback data, and industry prior rule data. It should be noted that the specific training steps of the deep neural network model are existing technologies and will not be repeated here. Through the above steps, the adaptability and effectiveness of the tire pressure information data transmission method to different vehicles can be greatly improved. The personalized fuzzy feedback rules can be generated through the matching strategy model according to the actual configuration of the vehicle. The differences in hardware configuration and control logic of vehicles of different brands and models can be met. Whether it is the complex electronic system of a high-end luxury car or the relatively simple configuration of an economy vehicle, good adaptation can be achieved, and fuzzy feedback rules that meet the actual situation of the application vehicle can be accurately generated. This accuracy ensures that on different vehicles, tire pressure abnormality feedback can be presented to the driver in the most appropriate manner, thereby improving the driver's perception efficiency of tire pressure abnormalities.

[0094] For example, after a fuzzy feedback rule is loaded on an application vehicle, when the pressure is insufficient: the driver's left seat produces 2Hz intermittent vibration and the amber indicator light flashes;

[0095] When the pressure is too high: the steering wheel area will vibrate continuously at 3Hz and the red indicator light will be on;

[0096] When the temperature is abnormal: the accelerator pedal generates tactile pulse feedback and the two-color indicator light flashes alternately.

[0097] At the same time, it also sets the hardware dynamic adjustment strategy, including:

[0098] Strong light environment: Enhance LED brightness (brightness increased by 50% when >1000 lux);

[0099] High noise environment (>75dB): tactile feedback intensity automatically increases by 1 level;

[0100] Supports night mode (LED brightness automatically drops to 30nits) to avoid dazzling the driver.

[0101] Reference Figure 6 The method of generating the fuzzy feedback rules of the application vehicle based on the preset matching strategy model of the application vehicle configuration information specifically includes the following steps:

[0102] D1. Determining Enabled Feedback Hardware and Optimal Triggering Logic Parameters for the Vehicle: The matching strategy model determines enabled feedback hardware and optimal triggering logic parameters for the vehicle based on the vehicle hardware configuration information of the application vehicle; the enabled feedback hardware includes priority feedback hardware and sub-priority feedback hardware;

[0103] D2. Determine whether the priority feedback hardware is occupied: The matching strategy model determines whether the optimal trigger logic parameters of the priority feedback hardware are occupied by other functions of the application vehicle based on the hardware control logic configuration information of the application vehicle;

[0104] D3. Select priority feedback hardware and output fuzzy feedback rules: If it is not occupied, select the priority feedback hardware and use its optimal trigger logic parameters as the hardware's fixed trigger logic parameters. Generate a hardware dynamic adjustment strategy for the selected hardware through matching strategy model matching and package and output the fuzzy feedback rules for the applicable vehicle.

[0105] D4. Determine whether there is the same type of second-priority feedback hardware: If occupied, determine whether there is the same type of second-priority feedback hardware based on the feedback type of the occupied priority feedback hardware;

[0106] D5. Select the next-highest priority feedback hardware and other unoccupied priority feedback hardware and output the fuzzy feedback rules. If any exist, select the next-highest priority feedback hardware of the same type as the occupied priority feedback hardware and other unoccupied priority feedback hardware, use their optimal trigger logic parameters as the hardware fixed trigger logic parameters, generate the hardware dynamic adjustment strategy for the selected hardware through matching strategy model matching, and package and output the fuzzy feedback rules for the applicable vehicle.

[0107] D6. Decision-making to generate the currently optimal trigger logic parameters for the occupied priority feedback hardware: If none exists, then select the idle feedback mode of the occupied priority feedback hardware based on the hardware control logic configuration information through the matching strategy model, and decide to generate its currently optimal trigger logic parameters;

[0108] D7. Generate hardware dynamic adjustment strategy and output fuzzy feedback rules: Select the current optimal trigger logic parameters of the occupied priority feedback hardware and the optimal trigger logic parameters of other unoccupied priority feedback hardware as the hardware fixed trigger logic parameters. Generate a hardware dynamic adjustment strategy for the selected hardware through matching strategy model matching, and package and output the fuzzy feedback rules for the vehicle in which it is applied. Through these steps, not only can the fuzzy feedback rules be accurately adapted to the vehicle hardware, fully utilizing hardware performance and improving feedback effectiveness, but they can also effectively address hardware conflicts, avoiding feedback function failures caused by hardware conflicts, and ensuring that tire pressure feedback can continue to operate normally and efficiently even in complex vehicle hardware usage environments. In addition, based on the selected hardware, a hardware dynamic adjustment strategy is generated with the help of a matching strategy model. This can dynamically optimize the fuzzy feedback rules based on the vehicle's real-time status and hardware usage, providing the driver with the most appropriate and timely tire pressure anomaly feedback, improving driving safety and user experience.

[0109] The above steps S1 and S2 use a double check mechanism during data transmission, specifically including:

[0110] First check: CRC-8 check is used when transmitting data over wireless channels;

[0111] Secondary checksum: BCH (15,7) coded checksum is used when transmitting data over wired data lines. CRC-8 checksums can quickly detect common errors caused by noise interference, signal attenuation, and other factors during wireless channel transmission. BCH (15,7) coded checksums offer strong error correction capabilities, enabling them to not only detect but also correct a certain number of errors during wired data transmission. This dual checksum significantly reduces missed detection rates, providing multi-level assurance of data accuracy and reliability.

[0112] Example 2

[0113] The difference between this embodiment and embodiment 1 is that, referring to Figure 7 A method for transmitting tire pressure information data also includes building a multi-vehicle collaborative tire pressure warning network to implement tire pressure information warning, specifically including the following steps:

[0114] E1. Establishing a tire pressure information sharing network among vehicles, broadcasting tire pressure status data packets of the application vehicles in real time through a pre-configured V2X communication module. The tire pressure status data packets include vehicle location information, tire pressure status information, and digital signature information;

[0115] E2. Receive tire pressure status data packets from surrounding vehicles in the inter-vehicle tire pressure information sharing network in real time, and calculate the warning risk value R using a preset risk calculation formula. The risk calculation formula is specifically:

[0116] ;

[0117] in, is the absolute value of the tire pressure deviation of the surrounding abnormal vehicles, in kPa; D is the real-time distance between the application vehicle and the abnormal vehicle; a is the tire pressure abnormality weight coefficient, and b is the vehicle distance weight coefficient, both of which are set by the management personnel, and a>b;

[0118] E3. When the warning risk value R > 0.8, the risk of abnormal tire pressure is determined to exist, and a heat map of the warning area is projected on the vehicle's HUD. Through the above steps, by building a tire pressure information sharing network between vehicles, the application vehicle can obtain tire pressure status data packets from surrounding vehicles in real time. When the tire pressure of surrounding vehicles is abnormal, the application vehicle can calculate the warning risk value using the risk calculation formula. Once the warning risk value R > 0.8, the risk of abnormal tire pressure is immediately determined to exist, and a heat map of the warning area is projected on the vehicle's HUD. This allows drivers to be aware of potential risk areas in advance, giving them ample time to take preventive measures such as slowing down and changing lanes in complex road conditions, especially on highways, to avoid accidents caused by abnormal tire pressure of surrounding vehicles, greatly improving driving safety.

[0119] A heat map of the warning area is projected onto the vehicle's HUD, visually displaying the risk areas of abnormal tire pressure in surrounding vehicles. Compared to simple text or audio prompts, the heat map allows drivers to more quickly and clearly understand the location and scope of the risk, enabling them to make more informed decisions while driving.

[0120] Example 3

[0121] The difference between this embodiment and embodiment 2 is that, referring to Figure 8 The tire pressure data sent by the tire pressure sensor is transmitted in a data compression manner, which specifically includes the following steps:

[0122] F1. Predicting the tire pressure sensor's detection value: A lightweight tire pressure prediction model, less than 50 KB in size, runs on the tire pressure sensor. It inputs a pressure / temperature sequence of 10 historical tire pressure sampling points and outputs the predicted value for the next cycle. This lightweight tire pressure prediction model is a lightweight LSTM model trained using historical tire pressure data. It should be noted that lightweight LSTM models, less than 50 KB in size, are state-of-the-art, and the specific training steps for lightweight LSTM models are not detailed here.

[0123] F2. Using the improved CAPS protocol for data transmission, determine whether the pressure deviation ΔP or temperature deviation ΔT between the tire pressure sensor's measured and predicted values ​​exceeds a preset prediction threshold. The prediction thresholds include a tire pressure error threshold and a temperature error threshold, both set by management. In this embodiment, the prediction thresholds are preferably ΔP > 2 kPa and ΔT > 1°C.

[0124] F3. If it exceeds, it is determined to be an abnormal state and the complete 4-byte differential data is transmitted to the relay receiver with a timestamp;

[0125] F4. If it does not exceed the threshold, the system determines the status as normal and transmits a 1-byte status code to the relay receiver. This status code includes a prediction deviation flag, which indicates the degree of deviation between the measured and predicted data. A lightweight LSTM model is used to predict the tire pressure value for the next cycle. The full 4-byte differential data is transmitted only when the pressure deviation ΔP or temperature deviation ΔT between the measured and predicted values ​​exceeds a preset threshold (e.g., ΔP > 2 kPa and ΔT > 1°C). Under most normal circumstances, only a 1-byte status code is transmitted, significantly reducing data transmission volume. Tire pressure data is typically relatively stable during vehicle operation. This mechanism avoids the transmission of large amounts of duplicate and redundant data, effectively conserving wireless channel resources, improving data transmission efficiency, and reducing transmission latency. The dynamic strategy better adapts to varying tire pressure conditions, ensuring efficient data transmission without compromising data accuracy, and ensuring timely and stable transmission of tire pressure information to the relay receiver.

[0126] Furthermore, if the deviation exceeds the threshold in the above steps, the complete differential data and timestamp are immediately transmitted, providing detailed abnormality information to the relay receiver. This enables the vehicle's tire pressure monitoring system to promptly detect potential safety hazards, such as tire leakage and blowout risks caused by excessive temperatures, buying time for the driver to take appropriate measures and improving driving safety.

[0127] It should be noted that this embodiment 3 can be preferably applied to ordinary passenger cars, family cars, etc. according to actual needs to increase sensor endurance and reduce transmission load. For high-performance vehicles such as racing cars, the data compression method of this embodiment is not recommended.

[0128] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the scope of protection of the invention. Obviously, the embodiments described are only some embodiments of the present invention, rather than all embodiments. Based on these embodiments, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in this field can still combine, add, delete or make other adjustments to the features in the various embodiments of the present invention according to the circumstances without conflict, without making creative work, so as to obtain different other technical solutions that do not deviate from the concept of the present invention in essence, and these technical solutions also fall within the scope of protection of the present invention.

Claims

1. A method for transmitting tire pressure information data, characterized in that: The following steps are involved: S1. The relay receiver receives tire pressure data sent by multiple tire pressure sensors through a wireless channel during a receiving period; S2. The relay receiver transmits the comprehensive tire pressure information to the tire pressure host via the wired data connection line during a sending period, wherein the sending period and the receiving period do not overlap in time and are separated by a guard interval of at least 1 ms; S3. The tire pressure host selects the precise display mode or the fuzzy feedback mode to output tire pressure information according to the vehicle status; wherein: In the precise display mode, the precise pressure and temperature data of each tire are displayed on the pre-set on-board display screen of the vehicle; In fuzzy feedback mode, tire pressure status information is transmitted through the interactive device pre-set on the vehicle; The data transmission in step S1 adopts PPM-FSK hybrid modulation mode, specifically: When the tire pressure fluctuation amplitude is less than 5kPa, FSK modulation is used; When the tire pressure fluctuation amplitude is ≥5kPa, switch to PPM modulation mode; The receiving period in step S1 adopts a three-dimensional time division multiplexing control mechanism, specifically including: A1. Time dimension division: The front and rear wheel sensors use staggered time window transmission, and the time window length is dynamically adjusted according to vehicle speed; A2. Spatial dimension control: Each tire sensor is assigned a different initial transmission time slot based on its installation location; A3. Frequency dimension coordination: Adjacent tire sensors within the same time window use different communication frequencies; The specific method of dynamically adjusting the time window length according to the vehicle speed includes: B1. When the vehicle speed is less than 30 km / h, the receiving window length is 200±50ms; B2. When 30 km / h ≤ vehicle speed < 80 km / h, the receiving window length is dynamically set using a preset receiving window calculation formula. The receiving window calculation formula is specifically: T = 200 - 1.75V, where T is the receiving window length in milliseconds; V is the vehicle speed value; B3. When the vehicle speed is ≥80km / h, the fixed receiving window is 50ms.

2. The tire pressure information data transmission method according to claim 1, characterized in that: The receiving period uses a frequency hopping mechanism to perform dynamic frequency switching in the 902-928 MHz frequency band.

3. The tire pressure information data transmission method according to claim 1, characterized in that: The fuzzy feedback mode can be preset according to the application vehicle and specifically includes the following steps: Collect configuration information of vehicles sold on the market to establish a vehicle database; Obtain the VIN code of the application vehicle and search the vehicle database to obtain its configuration information; the configuration information includes vehicle hardware configuration information and hardware control logic configuration information; A fuzzy feedback rule for the application vehicle is generated based on a preset matching strategy model according to the configuration information of the application vehicle. The fuzzy feedback mode is pre-set by loading the matched fuzzy feedback rule into the application vehicle. The fuzzy feedback rule includes the vehicle's tactile feedback hardware, sound feedback hardware and / or visual feedback hardware, hardware fixed trigger logic parameters, and hardware dynamic adjustment strategy. The matching strategy model is a deep neural network model obtained through deep learning training of historical data, and the historical data includes vehicle configuration information, optimal feedback rules set by experts, strategy effect feedback data, and industry prior rule data.

4. The tire pressure information data transmission method according to claim 3, characterized in that: The generating of the fuzzy feedback rules for the application vehicle based on the matching strategy model preset according to the configuration information of the application vehicle specifically includes the following steps: The matching strategy model determines the feedback hardware that can be enabled for the vehicle and the optimal trigger logic parameters according to the vehicle hardware configuration information of the application vehicle; the enabled feedback hardware includes priority feedback hardware and second priority feedback hardware; The matching strategy model determines whether the optimal trigger logic parameters of the priority feedback hardware are occupied by other functions of the application vehicle based on the hardware control logic configuration information of the application vehicle; If it is not occupied, the priority feedback hardware is selected and its optimal trigger logic parameters are used as the hardware fixed trigger logic parameters. The hardware dynamic adjustment strategy of the selected hardware is generated through matching strategy model matching, and the fuzzy feedback rules of the application vehicle are packaged and output; If occupied, determine whether there is a second priority feedback hardware of the same type based on the feedback type of the occupied priority feedback hardware; If it exists, the second-priority feedback hardware of the same type as the occupied priority feedback hardware and other unoccupied priority feedback hardware are selected, and their optimal trigger logic parameters are used as the hardware fixed trigger logic parameters. The hardware dynamic adjustment strategy of the selected hardware is generated through matching strategy model matching, and the fuzzy feedback rules of the application vehicle are packaged and output; If it does not exist, the idle feedback mode of the occupied priority feedback hardware is selected according to the hardware control logic configuration information through the matching strategy model, and the decision is made to generate its current optimal trigger logic parameters; The current optimal trigger logic parameters of the occupied priority feedback hardware and the optimal trigger logic parameters of other unoccupied priority feedback hardware are selected as the hardware fixed trigger logic parameters. The hardware dynamic adjustment strategy of the selected hardware is generated through matching strategy model matching, and the fuzzy feedback rules of the application vehicle are packaged and output.

5. The tire pressure information data transmission method according to claim 1, characterized in that: Steps S1 and S2 employ a double check mechanism during data transmission, specifically including: First check: CRC-8 check is used when transmitting data over wireless channels; Second check: BCH (15,7) coding check is used when transmitting data on the wired data connection line.

6. The tire pressure information data transmission method according to claim 1, characterized in that: It also includes building a multi-vehicle collaborative tire pressure warning network to implement tire pressure information warning, which specifically includes the following steps: Build a tire pressure information sharing network between vehicles, and broadcast the tire pressure status data packet of the application vehicle in real time through the pre-configured V2X communication module. The tire pressure status data packet includes vehicle location information, tire pressure status information and digital signature information; Receive tire pressure status data packets from surrounding vehicles in the inter-vehicle tire pressure information sharing network in real time, and calculate the warning risk value R using a preset risk calculation formula. The risk calculation formula is specifically: ； in, is the absolute value of the tire pressure deviation of the surrounding abnormal vehicles, in kPa; D is the real-time distance between the application vehicle and the abnormal vehicle; a is the tire pressure abnormality weight coefficient, and b is the vehicle distance weight coefficient, both of which are set by the management personnel, and a>b; When the warning risk value R>0.8, it is judged that there is a risk of abnormal tire pressure, and a heat map of the warning area is projected on the vehicle's HUD.

7. The tire pressure information data transmission method according to claim 1, characterized in that: The tire pressure data sent by the tire pressure sensor is transmitted in a data compression manner, specifically including the following steps: A lightweight tire pressure prediction model with a size of less than 50KB runs on the tire pressure sensor. It inputs a pressure / temperature sequence of 10 historical tire pressure sampling points and outputs a predicted value for the next cycle. The lightweight tire pressure prediction model is a lightweight LSTM model trained using historical tire pressure data. Determine whether the pressure deviation ΔP or temperature deviation ΔT between the actual and predicted values ​​of the tire pressure sensor exceeds a preset prediction threshold; the prediction threshold includes a tire pressure error threshold and a temperature error threshold, both of which are set by the management personnel; If it exceeds, it is determined to be an abnormal state, and the complete 4-byte differential data is transmitted to the relay receiver, along with a timestamp; If it does not exceed, it is determined to be in normal state and a 1-byte status code is transmitted to the relay receiver. This status code includes a prediction deviation flag, which is used to indicate the deviation level between the measured data and the predicted data.

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