Tire pressure data processing method and device, equipment and storage medium

Abstract

The invention relates to a tire pressure data processing method, device and equipment and a storage medium, and the method comprises the following steps: monitoring the current running speed data of a vehicle in real time, determining the current tire pressure sampling frequency of the vehicle based on the running speed data, the tire pressure sampling frequency is in one-to-one correspondence with each running speed interval; acquiring tire pressure change data of the vehicle based on the tire pressure sampling frequency, and correspondingly triggering a tire pressure abnormal event when the tire pressure change data exceeds a tire pressure change threshold value; an event abnormity level corresponding to the tire pressure abnormity event is determined, a corresponding vehicle alarm signal is sent to a vehicle gateway of the vehicle based on the event abnormity level, the event abnormity level comprises a plurality of event levels, and the vehicle alarm signal is transmitted based on a network priority and a signal retransmission strategy corresponding to the event level. According to the invention, through a multi-stage sampling frequency division and event grading processing mechanism, the tire pressure sampling power consumption is reduced, and the transmission efficiency of the tire pressure data is optimized.

Description

TECHNICAL FIELD

[0001] The present application relates to the monitoring technology field, in particular to a tire pressure data processing method and device, equipment and storage medium. BACKGROUND

[0002] The current vehicle tire pressure monitoring system generally adopts the design idea of fixed sampling frequency and single transmission mode, but in the real running environment where the vehicle speed continuously changes, the traditional scheme often sets the sampling period of the tire pressure sensor as a fixed value based on the highest expected risk, for example, whether the vehicle is in high-speed cruising, low-speed moving or long-time parking state, the tire pressure data is collected at a frequency of once per second or once per minute, and is continuously sent out through Bluetooth or radio frequency link. This kind of "one-size-fits-all" monitoring mechanism leads to high power consumption of the tire pressure monitoring system, and the battery life is greatly shortened. More importantly, when the vehicle really enters the high-speed driving stage, the tire pressure change rate significantly accelerates, and the fixed sampling interval is difficult to capture transient abnormalities in time; when the vehicle is stationary for a long time, the tire pressure is basically stable, and frequent sampling and continuous broadcasting cause a large amount of redundant data, further aggravating energy waste.

[0003] On the other hand, the response strategy of the prior art to abnormal events also lacks flexibility. The existing system usually only sets a single alarm threshold, and once the tire pressure or tire temperature exceeds the threshold, the alarm information is sent with a fixed broadcast intensity and a fixed retransmission number. Neither the severity of the abnormality is distinguished, nor the current channel occupancy and the vehicle operating state are considered. As a result, in the case of a tire blowout, the alarm data may compete with the regular data packets for the channel, resulting in a delay in responding to the emergency abnormal event; while in the case of a slight tire leak or temperature rise, the system still repeatedly sends data at the same high frequency, further wasting battery energy.

[0004] Therefore, the problem of high average power consumption of the tire pressure monitoring device in the prior art, and the transmission real-time and reliability of the key alarm signal are difficult to fully guarantee needs to be solved. SUMMARY

[0005] The purpose of the present application is to solve the above problems and provide a tire pressure data processing method and its corresponding device, equipment, non-volatile readable storage medium, and computer program product.

[0006] According to one aspect of the present application, a tire pressure data processing method is provided, comprising: monitoring the current driving speed data of the vehicle in real time, determining the current tire pressure sampling frequency of the vehicle based on the driving speed data, wherein the driving speed data is in a plurality of preset driving speed intervals, and the tire pressure sampling frequency corresponds to each driving speed interval one by one; acquire tire pressure change data of the vehicle based on the tire pressure sampling frequency, and trigger a tire pressure abnormal event when the tire pressure change data exceeds a preset tire pressure change threshold; determine an event abnormal level corresponding to the tire pressure abnormal event, and send a vehicle alarm signal corresponding to the tire pressure abnormal event to a vehicle gateway of the vehicle based on the event abnormal level, wherein the event abnormal level includes a plurality of event levels pre-divided, and the vehicle alarm signal is transmitted based on a network priority and a signal retransmission strategy corresponding to the event level.

[0007] According to another aspect of the present application, a tire pressure data processing device is provided, comprising: a frequency determination module configured to monitor current driving speed data of a vehicle in real time, and determine a current tire pressure sampling frequency of the vehicle based on the driving speed data, wherein the driving speed data is in a plurality of preset driving speed intervals, and the tire pressure sampling frequency corresponds to each driving speed interval one by one; a tire pressure monitoring module configured to acquire tire pressure change data of the vehicle based on the tire pressure sampling frequency, and trigger a tire pressure abnormal event when the tire pressure change data exceeds a preset tire pressure change threshold; an abnormal alarm module configured to determine an event abnormal level corresponding to the tire pressure abnormal event, and send a vehicle alarm signal corresponding to the tire pressure abnormal event to a vehicle gateway of the vehicle based on the event abnormal level, wherein the event abnormal level includes a plurality of event levels pre-divided, and the vehicle alarm signal is transmitted based on a network priority and a signal retransmission strategy corresponding to the event level.

[0008] According to another aspect of the present application, a tire pressure data processing device is provided, comprising a tire pressure sensor, a vehicle speed sensor, a tire temperature sensor, a microprocessor, a wireless transceiver module, a vehicle gateway and a battery management module. The tire pressure sensor is arranged in a tire and is used to collect tire pressure data in real time according to a sampling frequency given by the microprocessor. The vehicle speed sensor is used to read vehicle speed from a vehicle bus or a GPS module and output to the microprocessor. The tire temperature sensor is used to measure the current temperature of the vehicle tire. The microprocessor is used to set the sampling frequency of the tire pressure sensor according to the vehicle speed interval, and generate a tire pressure abnormal event and a corresponding event level when the tire pressure change exceeds a set threshold. The wireless transceiver module is connected with the microprocessor, and is used to send a vehicle alarm signal to the vehicle gateway according to a network priority and a retransmission strategy corresponding to the event level. The vehicle gateway is arranged in a driver's cabin, and is used to receive and forward the alarm signal to a vehicle-mounted display terminal or a mobile terminal. The battery management module is electrically connected with the tire pressure sensor, the microprocessor and the wireless transceiver module, and is used to switch between at least two power consumption modes according to the event level and the vehicle operating state.

[0009] According to another aspect of the present application, a non-volatile readable storage medium is provided, which stores a computer program realized according to the tire pressure data processing method in the form of computer readable instructions, and the computer program is invoked and run by a computer to execute the steps included in the method.

[0010] According to another aspect of the present application, a computer program product is provided, which includes computer program / instructions, and the computer program / instructions are executed by a processor to realize the steps of the method.

[0011] The present application aims at the long-standing defects of fixed sampling frequency and single alarm mode of traditional tire pressure monitoring, and proposes a tire pressure data processing method which adjusts sampling according to speed intervals and responds according to danger levels. The speed of the vehicle is read in real time, and the speed interval is mapped to different tire pressure sampling frequencies. When the vehicle speed is in the high speed interval, the sampling frequency is increased, and when the vehicle speed is in the low speed and parking interval, the corresponding sampling frequency is relatively reduced. Thus, while ensuring the accuracy of abnormal capture, the energy consumption caused by redundant sampling is minimized, and the problem of rapid battery depletion caused by fixed sampling period is directly solved.

[0012] Further, the present application compares the tire pressure change obtained by each sampling with the set threshold value. Once the threshold value is exceeded, an abnormal event is triggered, and the corresponding danger level of the event is obtained. The higher the danger level, the higher the network priority of the abnormal alarm signal, and the more the retransmission times. For slight abnormalities, the network priority of the signal transmission does not need to be improved, and the retransmission times are relatively reduced. Thus, the emergency alarm event corresponding to the abnormal event such as tire burst can be sent to the vehicle gateway as soon as possible and accurately through channel monopoly and multiple retransmissions, and the waste caused by repeated occupation of the channel by the abnormal event of slight air leakage is avoided, thereby eliminating the contradiction that the emergency signal appears delayed while the ordinary signal occupies the signal transmission resources, which may occur in the traditional single alarm strategy.

[0013] Therefore, through the cooperation of speed-driven sampling adjustment and danger level-driven transmission strategy, the present application reduces the overall power consumption while significantly improving the real-time performance and reliability of key alarms, prolongs the service life of the tire pressure monitoring device, and more effectively ensures the safety of vehicle operation. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 FIG. 1 is a flowchart of an embodiment of the tire pressure data processing method of the present application; Figure 2 FIG. 2 is a principle block diagram of the tire pressure data processing device of the present application; Figure 3 FIG. 3 is a structure diagram of another tire pressure data processing device used in the present application. DETAILED DESCRIPTION

[0015] The application can realize data monitoring processing of vehicle tire pressure through a tire pressure data processing device. The tire pressure data processing device mainly includes key components such as a tire pressure sensor, a vehicle speed sensor, a tire temperature sensor, a microprocessor, a wireless transceiver module, a vehicle gateway, and a battery management module, which can cooperate with each other through data transmission to jointly complete the tire pressure data processing task.

[0016] The tire pressure sensor is installed inside the tire and is used to sense the change of tire pressure and collect tire pressure data in real time. The vehicle speed sensor is responsible for obtaining the driving speed information of the vehicle, providing a basis for the subsequent dynamic adjustment of the tire pressure sampling frequency. The tire temperature sensor can obtain the current tire temperature of the vehicle. The microprocessor, as the core processing unit, can be used to receive data from the tire pressure sensor, the vehicle speed sensor, and the tire temperature sensor, calculate the current tire pressure sampling frequency according to the preset speed interval and sampling frequency mapping relationship, and judge whether the tire pressure change exceeds the safety threshold to trigger the corresponding abnormal event.

[0017] The wireless transceiver module is deployed in the tire pressure monitoring node and is responsible for converting the tire pressure data and abnormal alarm signals processed by the microprocessor into wireless signals. It forms a low-power and high-reliability Bluetooth Mesh network with the vehicle gateway, ensuring that the alarm signal can be quickly and stably transmitted to the vehicle gateway.

[0018] The vehicle gateway, as the core hub of the system, is embedded with a central processor, a memory, and a communication interface. The central processor undertakes data processing and system control tasks, analyzes data from each tire pressure monitoring node in real time, and runs event response logic. The memory stores system software, configuration parameters, and historical tire pressure data. The communication interface is connected to the Bluetooth Mesh network of the tire pressure monitoring node, and is also connected to the vehicle display terminal and the mobile terminal, realizing seamless transmission of tire pressure information.

[0019] The battery management module is built into the tire pressure monitoring node and is responsible for fine control of the power consumption mode switching of the node. It can smoothly switch between full power operation, dynamic sampling, light hibernation, and deep hibernation modes according to the running state of the vehicle and the requirements of the tire pressure monitoring task, thereby greatly prolonging the service life of the tire pressure monitoring node.

[0020] Therefore, through the close cooperation of each module in the tire pressure data processing device, the application realizes the full-process automation and intelligentization of tire pressure monitoring based on the tire pressure monitoring method of different sampling frequency grading and abnormal event grading, not only improves the accuracy and reliability of tire pressure monitoring, but also effectively reduces power consumption and prolongs the service life of the device, thereby further providing strong protection for the driving safety of the vehicle.

[0021] Please refer to Figure 1According to the tire pressure data processing method provided in the application, the computer program product can be installed in a tire pressure data processing device and run. In some embodiments, the method comprises the following steps: In step S1001, the current driving speed data of the vehicle is monitored in real time, and the current tire pressure sampling frequency of the vehicle is determined based on the driving speed data. The driving speed data is in a plurality of preset driving speed intervals, and the tire pressure sampling frequency corresponds to each driving speed interval.

[0022] No matter whether the vehicle is in a long-time off state, a slow start-stop state, or the vehicle is driving at a high speed, the real-time condition of the tire pressure needs to be monitored correspondingly, otherwise the tire pressure is too high, which can easily cause a tire burst and further cause a potential dangerous condition. The tire pressure is too low, which corresponds to the tire leakage condition, and when the truck is loaded with many goods, it can also cause the vehicle to be unstable and other conditions, which also has a safety hazard. Therefore, determining the tire pressure stability is very important for vehicle safety.

[0023] In the embodiment, in order to monitor the tire pressure of the vehicle, a tire pressure sensor, a tire temperature sensor, a microprocessor, a wireless transceiver module, and a battery management module are pre-installed in each tire of each vehicle. These components collectively constitute a tire pressure monitoring node, which can also be referred to as a trailer node, and are paired with a vehicle gateway in the cockpit through a low-power Bluetooth Mesh network. The vehicle gateway can also be called a master node. After the vehicle is powered on and starts to move, all tire pressure monitoring nodes are awakened. The tire pressure monitoring nodes collect tire pressure according to the corresponding tire pressure sampling frequency according to the real-time vehicle speed falling into the high-speed, medium-speed, low-speed, or parking interval. When the tire pressure change exceeds the threshold, the tire pressure monitoring node classifies the abnormal event and sends an alarm signal directly to the vehicle gateway through the Mesh network. The vehicle gateway drives the instrument warning light and the mobile terminal, thereby completing the deployment of the tire pressure monitoring framework and starting continuous monitoring at the moment the vehicle is powered on.

[0024] In an embodiment, the version of the tire pressure sensor and the tire pressure display terminal can be upgraded adaptively. For example, the version of the tire pressure sensor and the tire pressure display terminal is upgraded to BLE5.1 or above to ensure the stability and safety of signal transmission. The tire pressure sensor and the corresponding tire position of the vehicle have been pre-matched. During installation, only the corresponding position needs to be installed. When replacing or adding a tire pressure sensor, the corresponding matching process can be completed through the tire pressure display terminal.

[0025] In an embodiment, the Mesh network adopts a decentralized architecture design, and a full interconnection topology is established between each network node to realize a multi-path data transmission function. When an individual node fails, the system can ensure reliable data transmission through a redundant path, thereby significantly improving the reliability and scalability of the network. In a specific implementation, a Bluetooth tire pressure monitoring sensor is deployed inside each tire of the vehicle, and a Bluetooth tire pressure display terminal is installed in the center console of the vehicle. Both the terminal and each sensor support the Bluetooth Mesh networking protocol and can autonomously build a Mesh self-organizing network. The network architecture has a data relay function, can support large-scale deployment of tire pressure sensor clusters, and has an automatic network information storage capability, thereby not only realizing high-reliability connection of the tire pressure monitoring system but also significantly expanding the network coverage range to ensure that remote sensor nodes can still maintain stable connection and maximize the integrity and transmission reliability of tire pressure monitoring data.

[0026] In the tire pressure data processing method of the present application, the current driving speed data of the vehicle needs to be monitored in real time, and the current tire pressure sampling frequency of the vehicle is determined based on this data. This process can be realized by a vehicle speed sensor. The vehicle speed sensor can continuously obtain the driving speed information of the vehicle at a preset time interval, and the driving speed information is then transmitted to a microprocessor. The microprocessor has pre-stored multiple driving speed intervals, each of which corresponds to a specific tire pressure sampling frequency.

[0027] In an embodiment, the driving speed interval is pre-set according to the possible driving state of the vehicle. For example, the speed interval can be divided into a high-speed interval (≥80 km / h), a medium-speed interval (30 km / h≤speed<80 km / h), and a low-speed interval (speed<30 km / h), each of which corresponds to a tire pressure sampling frequency. For example, the high-speed interval corresponds to sampling once every 10 seconds, the medium-speed interval corresponds to sampling once every 30 seconds, and the low-speed interval corresponds to sampling once every 60 seconds. The specific interval division method can be adjusted according to the actual driving needs of the vehicle to ensure effective monitoring of tire pressure changes under different driving states. After the microprocessor receives the data from the vehicle speed sensor, it calculates the current tire pressure sampling frequency according to the pre-set speed interval and sampling frequency mapping relationship. For example, when the vehicle driving speed is 90 km / h, the microprocessor will determine that the vehicle is in the high-speed interval and set the tire pressure sampling frequency to once every 10 seconds; when the vehicle driving speed is 40 km / h, the microprocessor will determine that the vehicle is in the medium-speed interval and set the tire pressure sampling frequency to once every 30 seconds; and when the vehicle driving speed is 20 km / h, the microprocessor will determine that the vehicle is in the low-speed interval and set the tire pressure sampling frequency to once every 60 seconds.

[0028] In addition, the microprocessor also dynamically adjusts the tire pressure sampling frequency of the tire pressure sensor according to the real-time vehicle speed, to ensure that the tire pressure changes can be captured in time under different driving conditions. For example, when the vehicle changes from high-speed driving to low-speed driving or parking, the microprocessor will immediately detect the speed change and accordingly reduce the tire pressure sampling frequency. This process is not only applicable to the high-speed and low-speed intervals in the above example, but can also be extended to other preset speed intervals, such as parking (speed = 0), which can be set to sample once per hour to further reduce power consumption.

[0029] Step S1002, based on the tire pressure sampling frequency, obtaining tire pressure change data of the vehicle, and triggering a tire pressure abnormal event when the tire pressure change data exceeds a preset tire pressure change threshold.

[0030] In the process of obtaining tire pressure change data of the vehicle based on the tire pressure sampling frequency, the tire pressure sensor continuously monitors the pressure change in the vehicle tire according to the current tire pressure sampling frequency. The tire pressure sensor accurately measures the current tire pressure value in each sampling period and compares it with the tire pressure measurement value of the previous sampling period. The difference between the two is the tire pressure change data, which reflects the dynamic change of the tire pressure between the two sampling periods.

[0031] When the absolute value of the tire pressure change data exceeds the preset tire pressure change threshold in the microprocessor, the event is determined as a tire pressure abnormal event. For example, assuming that the preset tire pressure change threshold is 5% of the tire pressure change rate, if the monitored tire pressure change reaches 6% in a certain sampling period, the corresponding tire pressure abnormal event will be triggered. It can be seen that the setting of the tire pressure change threshold considers factors such as the specifications of the tire, the load of the vehicle, and the driving conditions, to ensure that the alarm can be issued in time when the tire pressure changes significantly.

[0032] If the tire pressure abnormal event is triggered, it will be processed according to the emergency level of the event. For example, a first-level event may correspond to a situation where the tire pressure drops sharply, indicating a risk of tire blowout. In this case, the system will immediately trigger an audible and visual alarm to remind the driver to take action as soon as possible. A second-level event may correspond to a situation where the tire pressure leaks slowly, affecting the stability of the vehicle. In this case, the system may only display a warning message, suggesting that the driver check the vehicle at the nearest safe opportunity. Such a hierarchical processing mechanism enables the system to provide appropriate and timely feedback according to different abnormal situations, to ensure driving safety.

[0033] Step S1003, determining an event abnormality level corresponding to the tire pressure abnormal event, and sending a vehicle alarm signal corresponding to the vehicle to a vehicle gateway of the vehicle based on the event abnormality level, wherein the event abnormality level includes a plurality of event levels pre-divided, and the vehicle alarm signal is transmitted based on the network priority and signal retransmission strategy corresponding to the event level.

[0034] After triggering the tire pressure abnormal event, it is necessary to further determine the event abnormal level corresponding to the tire pressure abnormal event, and send the corresponding vehicle alarm signal to the vehicle gateway of the vehicle based on the event abnormal level. When the microprocessor determines that the tire pressure abnormal event occurs, it will evaluate the emergency degree and severity of the current tire pressure abnormal event according to the preset event classification standard, so as to determine the event abnormal level. The event abnormal level usually includes multiple levels, such as a first-level event, a second-level event, a third-level event, etc., and each level corresponds to different tire pressure change conditions and potential risks.

[0035] In this embodiment, taking the common three-level event classification as an example, the first-level event may correspond to the case of rapid tire pressure drop, which usually indicates the potential risk of tire burst and poses a serious threat to driving safety. At this time, the system will give the alarm signal the highest network priority to ensure that the alarm signal can be quickly and unobstructed transmitted through the network. At the same time, in order to ensure the reliable delivery of the alarm signal, the system will also start multiple retransmission strategies, continuously sending the alarm signal multiple times within a preset time interval, for example, retransmitting once every two seconds, a total of three times. The second-level event may correspond to the case of slow tire pressure leakage, in which case the vehicle handling stability may be affected, but the danger level is relatively lower than the first-level event. At this time, the alarm signal will be given a medium priority, transmitted through the regular network channel, and the number of retransmissions will also be reduced accordingly, such as only retransmitting once. The third-level event may be some slight tire pressure fluctuations, although it is out of the normal range, but the threat to driving safety is small, and the alarm signal of this kind of event will be given a lower priority, which may only be transmitted when the network load is low, and usually will not start the retransmission strategy.

[0036] After determining the event abnormal level, the microprocessor will generate a vehicle alarm signal containing event level information, which will be sent to the vehicle gateway through the wireless transceiver module using the Bluetooth Mesh network. During transmission, the alarm signal will follow the preset network priority and signal retransmission strategy to ensure that critical alarm information can be timely and reliably delivered to the vehicle gateway. After receiving the alarm signal, the vehicle gateway will take appropriate measures according to the event level, for example, the first-level event will immediately trigger an audible and visual alarm to remind the driver to take immediate action; the second-level event may display warning information to suggest the driver to arrange for inspection as soon as possible; the third-level event may only be recorded for future maintenance reference. Such a mechanism ensures that tire pressure abnormal events of different emergency degrees can be properly and timely handled, effectively improving driving safety.

[0037] It is not difficult to understand from the above embodiments that the present application has achieved significant beneficial effects compared to traditional tire pressure data processing methods, including but not limited to: The tire pressure data processing method provided in the application realizes intelligent and dynamic monitoring and management of vehicle tire pressure, determines a tire pressure sampling frequency according to real-time monitoring of vehicle driving speed, ensures efficient and energy-saving monitoring of tire pressure changes in different driving states, further acquires tire pressure change data based on the tire pressure sampling frequency, triggers a tire pressure abnormal event when a preset tire pressure threshold is exceeded, effectively captures potential tire pressure abnormal risks, and ensures timely and reliable transmission of key alarm information by determining the level of the abnormal event and sending an alarm signal with corresponding network priority and retransmission strategy to a vehicle gateway. The steps of the above embodiments are closely connected and cooperate with each other, intelligently match tire pressure monitoring requirements of different driving speed intervals of the vehicle through innovative multi-level tire pressure sampling frequency, and realize accurate identification and hierarchical response of tire pressure abnormalities in combination with a mechanism of multiple tire pressure abnormal event levels finely divided, thereby significantly optimizing system power consumption and resource utilization efficiency while ensuring driving safety, improving the timeliness and accuracy of tire pressure monitoring, prolonging the service life of the monitoring system through reasonable resource allocation and energy consumption management, and providing a solid guarantee for safe operation of the vehicle.

[0038] On the basis of any embodiment of the method of the application, real-time monitoring of current driving speed data of the vehicle is performed, and the current tire pressure sampling frequency of the vehicle is determined based on the driving speed data, comprising: Step S2001, acquiring the driving speed data, matching the driving speed data with the driving speed intervals, and determining the driving speed interval in which the vehicle is currently located.

[0039] In this embodiment, in order to determine the driving speed interval in which the vehicle is currently located, the driving speed data of the vehicle needs to be acquired in real time through a vehicle speed sensor first. The acquisition of the driving speed data can be completed by the vehicle speed sensor, which is installed near the wheel hub of the vehicle, detects wheel speed pulses through a Hall element or an optical encoder, and converts the pulse frequency into a vehicle speed value; the vehicle speed signal output by a wheel speed module can also be directly read through the CAN bus of the vehicle, or the ground speed information provided by a GPS module can be used. The vehicle speed sensor measures the current speed of the vehicle at a fixed time interval, for example, once per second, and transmits these data to a microprocessor. The microprocessor has multiple driving speed intervals pre-stored therein, and each interval corresponds to a specific tire pressure sampling frequency.

[0040] The driving speed interval can be preset according to the possible driving state of the vehicle, and common division methods include: a parking state (speed = 0), a low-speed interval (for example, speed < 30 km / h), a medium-speed interval (30 km / h ≤ speed < 80 km / h), and a high-speed interval (speed ≥ 80 km / h). After receiving the data of the vehicle speed sensor, the microprocessor compares the real-time driving speed with the preset intervals to determine the driving speed interval in which the vehicle is currently located. For example, if the current speed of the vehicle is 90 km / h, the microprocessor determines that the vehicle is in the high-speed interval; if the speed is 40 km / h, it is determined to be in the medium-speed interval; if the speed is 15 km / h, it is in the low-speed interval; and if the speed is 0, it is in the parking state. This determination process ensures that the system can dynamically adjust the sampling frequency of the tire pressure monitoring according to the actual driving state of the vehicle, thereby optimizing the power consumption of the system while ensuring the monitoring accuracy.

[0041] In an embodiment, the microprocessor internally stores a driving speed interval mapping table which discretizes the continuous vehicle speed range into four intervals of parking, low speed, medium speed, and high speed. The parking interval is defined as a vehicle speed equal to 0 km / h; the low-speed interval is defined as 0 km / h < vehicle speed < 30 km / h; the medium-speed interval is defined as 30 km / h ≤ vehicle speed < 80 km / h; and the high-speed interval is defined as vehicle speed ≥ 80 km / h. When new driving speed data arrives, the microprocessor compares the value with the boundary values in the mapping table one by one. If the vehicle speed is equal to 0 km / h, it is directly marked as the parking interval; if the vehicle speed is greater than 0 and less than 30 km / h, it is marked as the low-speed interval; if the vehicle speed is greater than or equal to 30 and less than 80 km / h, it is marked as the medium-speed interval; and if the vehicle speed is greater than or equal to 80 km / h, it is marked as the high-speed interval. The matching result is written in the register of the microprocessor in the form of interval identifier for subsequent tire pressure sampling frequency calling logic.

[0042] Step S2002, calling a corresponding tire pressure sampling frequency based on the driving speed interval in which the vehicle is currently located, outputting the tire pressure sampling frequency to the tire pressure collection unit, so that the tire pressure collection unit collects the tire pressure change data based on the tire pressure sampling frequency.

[0043] The microprocessor reads the tire pressure sampling frequency value bound with the current driving speed interval in the internal mapping table immediately after confirming the current driving speed interval, and outputs the tire pressure sampling frequency value in the form of a digital instruction to the tire pressure acquisition unit through the internal bus. The tire pressure acquisition unit can be a tire pressure sensor, a tire temperature sensor, and their attached sampling circuit collectively, which reloads the internal timer as the period register value corresponding to the frequency after receiving the tire pressure sampling frequency instruction, and then starts a pressure and temperature sampling once every period, and caches the measured data to the data register, waiting for subsequent comparison and reporting. For example, when the driving speed interval is marked as a high speed interval, the tire pressure sampling frequency is once every 10 seconds, and the tire pressure acquisition unit triggers a complete pressure measurement once every 10 seconds; if the driving speed interval becomes a medium speed interval, the tire pressure sampling frequency is adjusted to once every 30 seconds, and the tire pressure acquisition unit automatically extends the sampling interval to 30 seconds; the low speed interval corresponds to once every 60 seconds; and the parking interval is further reduced to once every hour.

[0044] During the entire tire pressure sampling process, the tire pressure sampling frequency can be updated synchronously with the real-time switching of the driving speed interval without external intervention, ensuring that the tire pressure change data is captured in time and energy waste caused by redundant sampling is avoided.

[0045] The embodiment acquires driving speed data in real time through the vehicle speed sensor, and accurately matches the driving speed data with the preset driving speed interval to dynamically determine the driving speed interval in which the vehicle is currently located; then the microprocessor retrieves the corresponding tire pressure sampling frequency from the pre-stored mapping relationship according to the interval, and outputs the tire pressure sampling frequency to the tire pressure acquisition unit, realizing automatic and intelligent adjustment of the tire pressure monitoring frequency, ensuring that the tire pressure change can be captured in time at a high frequency during high-speed driving, and the monitoring accuracy and energy consumption are balanced at a moderate frequency during medium and low speed driving, and the power consumption is further reduced at a very low frequency in the parking state. By accurately matching the vehicle driving state and monitoring demand, the embodiment not only improves the timeliness and accuracy of tire pressure monitoring, but also significantly optimizes the energy efficiency of the system, prolongs the service life of the monitoring equipment, and provides reliable protection for the safe operation of the vehicle.

[0046] On the basis of any embodiment of the method of the application, the tire pressure change data of the vehicle is obtained based on the tire pressure sampling frequency, and a tire pressure abnormal event is triggered when the tire pressure change data exceeds a preset tire pressure change threshold, including: Step S3001, collecting the current tire pressure data and tire temperature data of the vehicle based on the tire pressure sampling frequency, and calculating the tire pressure change rate of the vehicle according to the current tire pressure data of the vehicle and the tire pressure data obtained last time.

[0047] In this embodiment, the tire pressure monitoring node performs data collection tasks according to the tire pressure sampling frequency set by the microprocessor, and the tire pressure sensor and the tire temperature sensor synchronously collect the pressure value and the temperature value in the current tire at this frequency. For example, when the tire pressure sampling frequency is set to once every 10 seconds, the tire pressure sensor accurately measures the current tire pressure value at each sampling period, and the tire temperature sensor collects the corresponding tire temperature data. The current tire pressure data collected and the tire pressure data of the last sampling period are used by the microprocessor to calculate the tire pressure change rate. The microprocessor subtracts the current tire pressure value from the tire pressure value collected last time, obtains the tire pressure change amount, and then divides it by the sampling time interval, thereby obtaining the tire pressure change rate, which reflects the dynamic change trend of the tire pressure in two sampling periods. For example, if the current tire pressure value is 2.5 bar, the tire pressure value collected last time is 2.4 bar, and the sampling time interval is 10 seconds, then the tire pressure change rate is 0.01 bar / s.

[0048] In an embodiment, a moving average algorithm can also be used to smooth the tire pressure change rate to reduce the impact of short-term fluctuations on the result. For example, the average value of the tire pressure change amount of the last three sampling periods is calculated, and then divided by the sampling interval to obtain the smoothed tire pressure change rate. Alternatively, a Kalman filter algorithm can be used to filter the tire pressure data, predict and correct the tire pressure change rate, to improve the accuracy and reliability of the data. The method described in this embodiment can be used in different application scenarios, and the appropriate algorithm can be selected according to actual needs to ensure the accuracy and stability of tire pressure monitoring.

[0049] Step S3002, when the tire pressure data is less than the preset tire pressure threshold, or the tire temperature data is higher than the preset tire temperature threshold, or the tire pressure change rate is greater than the tire pressure change threshold, the tire pressure abnormal event is generated based on the tire pressure data, the tire temperature data and the tire pressure change rate.

[0050] When the tire pressure data, the tire temperature data or the tire pressure change rate exceeds the preset threshold, a tire pressure abnormal event is generated accordingly. The current tire pressure data collected by the tire pressure sensor is compared with the preset tire pressure threshold, which can be set according to the tire specifications, vehicle load and driving conditions. For example, for a fully loaded truck tire, the preset tire pressure threshold can be set to no less than 2.0 bar. If the current tire pressure data is lower than this tire pressure threshold, it indicates that the tire may have a leak, and a tire pressure abnormal event is generated accordingly.

[0051] Meanwhile, the current tire temperature data collected by the tire temperature sensor is compared with a preset tire temperature threshold. The tire temperature threshold can be determined according to the tire material tolerance limit and the vehicle driving environment temperature range. For example, in a high-temperature summer scenario, the preset tire temperature threshold can be set to be not higher than 90°C. If the current tire temperature data exceeds this threshold, it can mean that the tire is overheated, and the vehicle is at risk of tire burst, which can also have a significant impact on the tire pressure. In this case, the tire temperature being too high can also be regarded as a tire pressure anomaly, and a tire pressure anomaly event will be triggered accordingly.

[0052] The tire pressure change rate calculated by the microprocessor is also compared with a preset tire pressure change threshold, which reflects the maximum allowed change rate of the tire pressure per unit time. For example, if the preset tire pressure change threshold is 0.05 bar / s, and the current calculated tire pressure change rate is 0.06 bar / s, it means that the tire pressure changes rapidly in a short time, which exceeds the preset warning threshold. This means that it may be an emergency caused by vehicle tire burst or rapid air leakage, and a tire pressure anomaly event can be generated accordingly.

[0053] After triggering the tire pressure anomaly event, the microprocessor integrates the current tire pressure data, tire temperature data and tire pressure change rate to generate an event data packet containing detailed anomaly information. Then, the event data packet is sent to the vehicle gateway through the wireless transceiver module according to the network priority and retransmission strategy corresponding to the event level via the Bluetooth Mesh network. After receiving the tire pressure anomaly event data packet, the vehicle gateway will take appropriate measures according to the emergency level of the event, such as triggering sound and light alarm for a first-level event to prompt the driver to stop and check immediately; displaying warning information for a second-level event to suggest the driver to arrange maintenance as soon as possible; and recording abnormal data for a third-level event for subsequent maintenance analysis.

[0054] As can be seen from the present embodiment, the tire pressure monitoring node collects current tire pressure data and tire temperature data according to the tire pressure sampling frequency, and calculates the tire pressure change rate, thereby achieving comprehensive monitoring of the tire state of the vehicle. When the tire pressure data is below the preset threshold, the tire temperature data is above the preset threshold, or the tire pressure change rate exceeds the threshold, the present embodiment can generate a tire pressure anomaly event in time, which not only can quickly capture potential tire pressure anomalies, but also can improve the accuracy and reliability of anomaly judgment by comprehensively analyzing data in multiple dimensions of tire pressure, tire temperature and tire pressure change rate. By generating an anomaly event in time, the present embodiment can also quickly remind the driver to take appropriate measures, thereby effectively improving driving safety, optimizing the performance of the tire pressure monitoring system, and ensuring stable and efficient operation of the system under various driving conditions.

[0055] On the basis of any embodiment of the method of the present application, when the tire pressure data does not exceed the tire pressure change threshold, the method comprises: Step S4001, difference operation is performed on the current tire pressure data and the last valid tire pressure data to obtain tire pressure difference data.

[0056] In the tire pressure monitoring process, the microprocessor is responsible for processing the current tire pressure data and performing difference operation on the current tire pressure data and the last valid tire pressure data to obtain tire pressure difference data. The current tire pressure data is measured by the tire pressure sensor in each sampling period, and the last valid tire pressure data refers to the verified and confirmed tire pressure value in the previous sampling period.

[0057] In an embodiment, the calculation method of the difference operation can be that the microprocessor reads the current tire pressure data, then retrieves the last valid tire pressure data from the storage unit, and then subtracts the two to obtain the tire pressure difference data. For example, the current tire pressure data is 2.5 bar, and the last valid tire pressure data is 2.4 bar, then the tire pressure difference data is the difference between the current tire pressure data and the valid tire pressure data, i.e. 0.1 bar, so that the tire pressure difference data can reflect the change of the tire pressure between two sampling periods. In order to ensure the accuracy of the data, the tire pressure data can also be verified for validity, only the verified and confirmed tire pressure data will be stored as the last valid tire pressure data, and the validity verification can be performed in various ways, such as checking whether the data is within a reasonable range, whether it conforms to the physical law, etc., to ensure that the data used for difference operation is reliable, thereby improving the accuracy of tire pressure change monitoring.

[0058] In an embodiment, a moving average algorithm can also be used to preprocess the tire pressure data to reduce the influence of short-term fluctuations, so that the result of the difference operation is more smooth and stable, or a Kalman filter algorithm can be used to filter the tire pressure data to predict and correct the tire pressure value, thereby improving the accuracy and reliability of the data.

[0059] Step S4002, the tire pressure difference data is compressed and encoded into a compressed data packet, and the compressed data packet is sent to the vehicle gateway when the next tire pressure sampling period arrives.

[0060] In this embodiment, in order to efficiently utilize the communication resources, the tire pressure difference data needs to be compressed and encoded, and after the microprocessor obtains the tire pressure difference data, it will use a preset compression algorithm to compress and encode it, and convert it into a compressed data packet. Specifically, a lossless compression algorithm such as Huffman coding or arithmetic coding can be used to effectively reduce the data volume and improve the data transmission efficiency without losing the accuracy of the data.

[0061] The trigger data sending mechanism is triggered when the next tire pressure sampling period is entered. The arrival of the next sampling period is usually controlled by a timer or a counter inside the microprocessor, which ensures that after the data collection is performed according to the corresponding tire pressure sampling frequency, when the next sampling period is reached, the microprocessor will send the compressed and encoded tire pressure difference value data corresponding to the compression data packet together with other data that needs to be sent, through the wireless transceiver module to the vehicle gateway. The wireless transceiver module can use a low-power high-version Bluetooth protocol to ensure the stability and energy saving of data transmission. The vehicle gateway as the receiving end of the data will decode the received compression data packet to restore the original tire pressure difference value data for further analysis and processing.

[0062] In an embodiment, the tire pressure monitoring node can also dynamically adjust the data sending strategy according to the network load and the vehicle operating state. When the network is congested, the microprocessor can increase the data compression ratio or reduce the sending frequency, while in critical working conditions such as high-speed driving of the vehicle, the priority of data transmission can be improved to ensure timely delivery of important data, so as to further optimize the use of communication resources under the premise of ensuring data integrity.

[0063] As can be seen, the present embodiment obtains the tire pressure difference value data by performing difference operation on the current tire pressure data and the last valid tire pressure data, and compresses and encodes the tire pressure difference value data into a compression data packet, which is sent to the vehicle gateway when the next tire pressure sampling period arrives. The difference operation and compression encoding can reduce the data volume, reduce the transmission burden, and improve the data transmission efficiency. At the same time, the present embodiment only sends data when the next sampling period arrives, avoiding the immediate transmission of non-urgent data in unnecessary cases, and further optimizing the system power consumption. In addition, the data sent by the microprocessor can not only include the compression data packet, but also integrate other tire state information, so that the vehicle gateway can more comprehensively master the tire condition, effectively utilize the communication resources while ensuring data integrity, and further enhance the stability and reliability of tire pressure monitoring by dynamically adjusting the sending strategy to adapt to different working conditions.

[0064] On the basis of any embodiment of the method of the present application, the tire pressure abnormal event is generated based on the tire pressure data, the tire temperature data, and the tire pressure change rate, comprising: Step S5001, when the tire pressure data is less than the tire pressure threshold value, or the tire pressure change rate is greater than the first tire pressure threshold value, a first abnormal event is generated.

[0065] In this embodiment, the tire pressure data is collected in real time by a tire pressure sensor installed in each tire. The tire pressure sensor can accurately measure the pressure value inside the tire and convert the measurement result into an electrical signal, usually using piezoresistive or capacitive sensing technology. The piezoresistive sensor detects pressure changes by using the resistance change of silicon material, while the capacitive sensor senses pressure by measuring the change in capacitance. The sensor collects data at a preset tire pressure sampling frequency. The tire pressure threshold is pre-set according to the specifications of the tire, the load of the vehicle and the safety standards. For example, for a heavy truck tire, the tire pressure threshold can be set to 2.0 bar. When the real-time tire pressure data collected by the tire pressure sensor is lower than this tire pressure threshold, the microprocessor will determine that the current tire is in an under-inflated state, which may affect the handling stability and driving safety of the vehicle. For example, if the real-time monitoring tire pressure data drops to 1.8 bar, it will be identified as an abnormal situation. The tire pressure change rate can be calculated by the microprocessor. The microprocessor calculates the change in tire pressure by comparing the current tire pressure data with the tire pressure data of the previous sampling period, and divides the change by the sampling time interval to obtain the tire pressure change rate. The tire pressure change rate reflects the rate of change of tire pressure per unit time, usually in bar / s. The first tire pressure threshold is pre-set according to the driving conditions of the vehicle and the performance of the tire, and is used to identify abnormal fluctuations in tire pressure. If the first tire pressure threshold is set to 0.05 bar / s and the real-time tire pressure change rate calculated by the microprocessor is 0.06 bar / s, it may mean that the tire is at risk of rapid air leakage or tire burst. In this case, a first abnormal event will be generated immediately.

[0066] When the first abnormal event is triggered, a data packet containing the corresponding abnormal information is generated. This data packet not only includes the tire pressure data and tire pressure change rate that triggered the abnormality, but also includes the current tire temperature data, the position identifier of the tire and other related auxiliary information, such as the current tire temperature value and the position identifier of the vehicle, to help the driver quickly locate the tire with high tire temperature. After the data packet is generated, it is sent to the vehicle gateway through the wireless transceiver module. The wireless transceiver module uses low-power Bluetooth Mesh network for data transmission. After receiving the data packet, the vehicle gateway will take appropriate measures according to the emergency level of the corresponding event in the data packet.

[0067] In one embodiment, since tires at different positions play different roles in vehicle handling, the tire pressure threshold and tire pressure change rate threshold need to be adjusted according to different tire positions and vehicle types. For example, different tire pressure thresholds can be set for steering wheels and drive wheels. In addition, the threshold data such as tire pressure threshold or tire pressure change threshold can be dynamically adjusted by combining historical data and machine learning algorithms to adapt to different driving habits and road conditions.

[0068] In one embodiment, the tire pressure monitoring system can support OTA (Over-The-Air) update function in terms of maintenance and upgrade of the system. After receiving the firmware update package through the vehicle gateway, the package is distributed to each tire pressure monitoring node, which not only effectively reduces the maintenance cost, but also ensures that the tire pressure monitoring system can obtain the latest functions and security patches in a timely manner. In addition, the tire pressure monitoring system also has a self-diagnosis function, which can periodically check the working state of the sensor and the integrity of data transmission. By comparing the data consistency of different sensors or detecting the response time of the sensor, the tire pressure monitoring system can timely discover and report potential hardware failures.

[0069] Step S5002, when the tire temperature data is greater than the tire temperature threshold, or the tire pressure change rate is greater than the second tire pressure threshold and less than the first tire pressure threshold, a second abnormal event is generated.

[0070] In this embodiment, the tire pressure monitoring system continuously receives the tire temperature data output by the tire temperature sensor and the tire pressure change rate calculated by the microprocessor. The tire temperature threshold is set in advance according to the tire material tolerance limit and the vehicle driving environment temperature range, for example, it can be set to 70°C in a high temperature summer scenario. When the tire temperature data exceeds this threshold, it indicates that the tire may be at risk of overheating, affecting the stability of the rubber components and the strength of the cords, and the system determines that it is abnormal.

[0071] The second tire pressure threshold can be used to identify moderate risk fluctuations in tire pressure, for example, it can be set to 0.03 bar / s. When the first tire pressure threshold is 0.05 bar / s, if the tire pressure change rate is between the second tire pressure threshold and the first tire pressure threshold, for example, the value obtained by monitoring is 0.04 bar / s, which indicates that the vehicle tire may be slowly leaking or other progressive abnormalities, that is, a second abnormal event is generated. When the second abnormal event is generated, a data packet containing the corresponding abnormal information is also generated, including the tire temperature data, the tire pressure change rate that triggered the abnormality, and other related auxiliary information such as the location identifier and timestamp of the tire. The data packet is sent to the vehicle gateway through the low-power Bluetooth Mesh network by the wireless transceiver module, and the vehicle gateway decides the response mode according to the emergency level of the event.

[0072] In one embodiment, if the data collected in the current sampling period is within the normal range, the corresponding data is aggregated and compressed, and then transmitted according to the normal network priority. When there is a firmware version number change or a heartbeat packet maintenance, the corresponding data is transmitted to the vehicle gateway together with the data collected in the next sampling period.

[0073] In an embodiment, to adapt to different vehicle configurations, the embodiment supports adjusting the tire temperature threshold and the second tire pressure threshold according to the tire position, for example, the steering wheel can be set to a lower tire temperature threshold due to the complex force it bears. In addition, the tire pressure monitoring system also supports OTA update function, which can distribute firmware update package to each monitoring node through the vehicle gateway, reducing maintenance cost and keeping the system function advanced.

[0074] By implementing the above embodiment, the application can realize comprehensive monitoring and accurate prediction of the tire state of the vehicle. By monitoring the tire pressure data and the tire pressure change rate in real time, a first abnormal event is generated as soon as the tire pressure is found to be lower than the preset tire pressure threshold or the change rate exceeds the first tire pressure threshold, which can ensure a quick response to possible tire burst or serious air leakage risk and ensure driving safety. When the tire temperature exceeds the preset tire temperature threshold or the tire pressure change rate is between the second tire pressure threshold and the first tire pressure threshold, a second abnormal event is generated to capture and handle potential slow air leakage or other progressive abnormalities. By generating a data packet containing detailed abnormal information and using low-power Bluetooth Mesh network to efficiently transmit to the vehicle gateway, the embodiment ensures timely delivery of abnormal information, allowing the driver to take appropriate measures according to the urgency of the event. By combining historical data and machine learning algorithms to dynamically adjust the threshold and supporting monitoring strategy optimization according to the tire position, the embodiment can adapt to different vehicle configurations and use scenarios. In addition, the tire pressure monitoring system in the embodiment supports OTA update function, which can distribute firmware update package to each monitoring node through the vehicle gateway, reducing maintenance cost and keeping the system function advanced. At the same time, it also has a self-diagnosis function, which can periodically check the working state of the sensor and the integrity of the data transmission, thereby significantly improving the driving safety and providing comprehensive protection for the safe operation of the vehicle.

[0075] On the basis of any embodiment of the method of the application, the event abnormality level corresponding to the tire pressure abnormal event is determined, and the corresponding vehicle alarm signal is sent to the vehicle gateway of the vehicle based on the event abnormality level, comprising: Step S6001, when the tire pressure abnormal event is the first abnormal event, the event abnormality level is determined as the first abnormality level, the network priority of the vehicle alarm signal is configured as the first priority, and the vehicle alarm signal is sent to the vehicle gateway through the exclusive channel multiple times.

[0076] In this embodiment, when the tire pressure monitoring system detects a first abnormal event, the microprocessor immediately determines the first abnormal event as a first abnormal level. The first abnormal level is the highest priority preset by the tire pressure monitoring system, which is used to identify an emergency situation that may endanger road safety, such as a flat tire or a serious air leak. At this time, the tire pressure monitoring system configures the first priority, i.e. the highest network priority, for the corresponding vehicle alarm signal, ensuring that the vehicle alarm signal can be quickly and unobstructed transmitted to the vehicle gateway.

[0077] In order to ensure the reliable delivery of the alarm signal, the tire pressure monitoring system sends the alarm signal in an exclusive channel mode. When sending the alarm signal of the first abnormal event, other non-emergency data transmission will be temporarily suspended, and the vehicle alarm signal will have exclusive use of the communication resources. At this time, the tire pressure monitoring system will send the alarm signal continuously for multiple times, for example, retransmitting every two seconds for a total of three times, in order to enhance the receiving reliability of the signal and prevent false negatives caused by signal interference or loss.

[0078] In one embodiment, after generating the first abnormal event, the microprocessor immediately constructs a data packet containing abnormal details, which is sent through the wireless transceiver module via the Bluetooth Mesh network. After the vehicle gateway receives the corresponding vehicle alarm signal, it will immediately trigger an audible and visual alarm, and display the location and type of the abnormal tire on the vehicle display screen, reminding the driver to take emergency measures.

[0079] In one embodiment, when the tire pressure change rate per minute is greater than 5% or the tire pressure data is less than 1.8 bar, a first abnormal event is immediately generated. At this time, the network priority of the first abnormal event is set to the highest, and after transmission through an exclusive channel, the retransmission of the vehicle alarm signal is triggered three times.

[0080] Step S6002, when the tire pressure abnormal event is the second abnormal event, determine the event abnormal level as the second abnormal level, correspondingly configure the network priority of the vehicle alarm signal as the second priority, and after sending the vehicle alarm signal to the vehicle gateway, repeat sending the vehicle alarm signal to the vehicle gateway once.

[0081] When the tire pressure monitoring system detects a second abnormal event, the microprocessor determines that the event is of a second abnormal level. The second abnormal level is a medium priority level lower than the first abnormal level, which identifies a situation that needs attention but is not urgent, such as a slow leak. At this time, the tire pressure monitoring system configures a second priority for the corresponding vehicle alarm signal to ensure that the alarm signal can be transmitted to the vehicle gateway in a competitive channel. After receiving the second abnormal event, the microprocessor constructs a data packet containing abnormal details, which is sent to the vehicle gateway through the low-power Bluetooth Mesh network via the wireless transceiver module. In the Mesh network, the node identifies the second priority signal and reasonably schedules the transmission resources to ensure the timely delivery of the alarm signal. After receiving the alarm signal, the vehicle gateway displays the corresponding tire position and abnormal type on the vehicle display screen, reminding the driver to check or take appropriate measures in a timely manner.

[0082] To ensure reliable signal delivery, the tire pressure monitoring system will resend the alarm signal immediately after the first transmission, thereby enhancing the reliability of receiving the tire pressure monitoring signal and preventing false negatives due to signal interference or loss. In addition, the tire pressure monitoring system can be integrated with the intelligent diagnostic system of the vehicle to record and analyze the second abnormal event, providing data support for subsequent vehicle maintenance. During the transmission of the vehicle alarm signal, the vehicle gateway will schedule tasks according to the received signal priority to ensure that the abnormal information corresponding to the second priority vehicle alarm signal can be timely known by the driver. The above hierarchical processing mechanism enables the vehicle gateway to efficiently manage different types and priorities of vehicle alarm signals, improving the overall response efficiency of the tire pressure monitoring system.

[0083] In one embodiment, when the tire pressure change rate per minute is greater than 2% and less than 5%, or the tire temperature data is higher than 90°C, a second abnormal event is immediately generated. At this time, the network priority corresponding to the second abnormal event is set to high, and the corresponding tire pressure monitoring node sends the data corresponding to the second abnormal event to the vehicle gateway immediately, and triggers the retransmission of the vehicle alarm signal once again.

[0084] This embodiment assigns the highest network priority to the first abnormal event and continuously retransmits it exclusively, and configures the second highest priority to the second abnormal event and retransmits it once after immediate transmission. This can not only notify the driver in zero delay and zero interference in critical scenarios such as tire burst and severe leak, but also ensure reliable information delivery at a lower bandwidth cost in medium-risk scenarios such as slow leak and abnormal tire temperature. In addition, it can transmit information to the vehicle gateway in a low-risk scenario, cooperate with the channel scheduling of the low-power Bluetooth Mesh network, the priority queue of the vehicle gateway, and the self-diagnosis and OTA remote maintenance function. The tire pressure monitoring system not only ensures driving safety, but also significantly reduces power consumption and operation and maintenance costs, achieving efficient, stable, and sustainable tire pressure abnormal response.

[0085] On the basis of any embodiment of the method of the application, further comprising: Step S7001, based on the tire pressure change rate and the driving speed data, switching the power consumption mode of the tire pressure monitoring node to the first power consumption mode or the second power consumption mode.

[0086] In the tire pressure monitoring system of the application, the power consumption mode switching of the tire pressure monitoring node is based on the tire pressure change rate and the driving speed data. The tire pressure change rate is calculated by the microprocessor according to the current tire pressure data and the tire pressure data of the previous sampling period, reflecting the change rate of the tire pressure in unit time, and the driving speed data is collected by the vehicle speed sensor in real time. The microprocessor divides the driving state of the vehicle into different speed intervals, such as parking, low speed, medium speed and high speed, according to these data.

[0087] When the tire pressure change rate exceeds the preset first tire pressure threshold, or the driving speed data is in the high speed interval, the tire pressure monitoring node switches to the first power consumption mode. The first power consumption mode is a full power running mode, at this time the tire pressure sensor of the node increases the sampling frequency to collect tire pressure data, and the wireless transceiver module transmits data in high power mode, to ensure that data can be captured and transmitted in time when driving at high speed or tire pressure changes rapidly, to ensure driving safety. Conversely, when the tire pressure change rate is lower than the preset second tire pressure threshold, and the driving speed data is in the parking or low speed interval, the tire pressure monitoring node switches to the second power consumption mode. The second power consumption mode is a low power consumption running mode, at this time the tire pressure sensor of the node reduces the sampling frequency, and the wireless transceiver module enters the sleep state, and only sends data when necessary to wake up, to reduce energy consumption and prolong battery life.

[0088] In one embodiment, when it is monitored that the current vehicle has a tire burst or the vehicle speed is in the high speed interval, such as when the tire pressure change rate is greater than 5% or the vehicle speed is greater than 80km / h, the tire pressure monitoring node runs at full power; when it is monitored that the vehicle speed at this time is 0-80km / h, it is considered that the vehicle is in a normal driving state at this time, and the tire pressure monitoring node corresponds to dynamic sampling at a fixed frequency; when the vehicle may be in a temporary parking or unloading scene, the corresponding vehicle speed of the vehicle is equal to 0 and the tire pressure change rate is less than 1% per hour, at this time the tire pressure monitoring node enters the light sleep state; and when the vehicle may be in a long-term parking or overnight state, the vehicle is turned off at this time and the signal monitored by the acceleration sensor is less than 0.1G for 10 minutes, at this time the tire pressure monitoring node enters the deep sleep state.

[0089] Step S7002, when the tire pressure monitoring node is in the first power consumption mode, the tire pressure monitoring node performs tire pressure data collection at the current tire pressure sampling frequency, and sends a corresponding vehicle alarm signal to the vehicle gateway.

[0090] When the tire pressure monitoring node is in the first power consumption mode, the node performs tire pressure data collection at the currently set tire pressure sampling frequency. At the same time, the tire pressure monitoring node generates a vehicle alarm signal according to the processed data, and sends the alarm signal to the vehicle gateway through the wireless transceiver module. The vehicle alarm signal contains the specific reason for triggering the alarm, such as low tire pressure, rapid tire pressure change rate, etc. The wireless transceiver module uses low-power Bluetooth Mesh network for data transmission to ensure that the alarm signal can be quickly and stably sent to the vehicle gateway. After receiving the alarm signal, the vehicle gateway will take corresponding measures according to the abnormal level in the signal. For the first abnormal level alarm signal, the vehicle gateway will immediately trigger the sound and light alarm, and display the specific abnormal tire position and type on the vehicle display screen, reminding the driver to take emergency measures. The tire pressure monitoring node in the first power consumption mode also continuously monitors the tire pressure change and dynamically adjusts the content of the alarm signal according to the real-time data. For example, if the tire pressure change rate further increases, the tire pressure monitoring node will update the vehicle alarm signal to reflect the latest abnormal situation, so that the tire pressure monitoring system can provide continuous monitoring and early warning in emergency situations to ensure driving safety.

[0091] In practical applications, the trigger condition of the first power consumption mode can be adjusted according to the specific configuration and use scene of the vehicle. For example, for heavy trucks, the first power consumption mode can be triggered when the tire pressure change rate exceeds 0.05 bar / s; while for passenger cars, the corresponding tire pressure change rate triggering the first power consumption mode is set to 0.03 bar / s.

[0092] Step S7003, when the tire pressure monitoring node is in the second power consumption mode, the tire pressure monitoring node reduces the tire pressure collection frequency and the signal transmission frequency of the vehicle alarm signal, and switches to the first power consumption mode when the preset power consumption switching condition is met.

[0093] When the tire pressure monitoring node is in the second power consumption mode, it reduces the tire pressure collection frequency and the transmission frequency of the vehicle alarm signal. The microprocessor switches the tire pressure monitoring node to the second power consumption mode according to the preset tire pressure change rate and driving speed data. At this time, the sampling frequency of the tire pressure sensor is reduced from a high frequency, such as once every 10 seconds, to a low frequency, such as once every 60 seconds, in the first power consumption mode. The transmission frequency of the wireless transceiver module is also reduced accordingly. In the second power consumption mode, the tire pressure monitoring node continuously monitors the tire pressure change rate and driving speed data. When the preset power consumption switching condition is met, such as when the tire pressure change rate exceeds the preset second tire pressure threshold or the driving speed enters the high speed interval, the tire pressure monitoring node immediately switches back to the first power consumption mode. The preset power consumption switching condition can be adjusted according to the specific configuration and use scenario of the vehicle to ensure that the system can operate efficiently under different working conditions. For example, for a heavy truck, it can be set that when the tire pressure change rate exceeds 0.03 bar / s or the driving speed exceeds 80 km / h, the node switches from the second power consumption mode to the first power consumption mode. This dynamic switching mechanism enables the system to maximize energy consumption while ensuring monitoring accuracy and prolonging battery life.

[0094] In addition, the tire pressure monitoring node wakes up regularly in the second power consumption mode to check the tire pressure change rate and driving speed data, ensuring that the system can respond promptly to any abnormal conditions. For example, the tire pressure monitoring node can wake up every 10 minutes to check the current tire pressure change rate and driving speed. If an abnormality is found, it immediately switches to the first power consumption mode and sends the corresponding vehicle alarm signal.

[0095] The unique and significant technical advantage of this embodiment is that the tire pressure monitoring system dynamically adjusts the power consumption mode of the tire pressure monitoring node according to the actual operating state of the vehicle, thereby significantly optimizing the energy consumption management of the tire pressure monitoring system while ensuring monitoring accuracy and timeliness. When the vehicle is driving at high speed or in an emergency situation where the tire pressure change rate exceeds the preset threshold, the tire pressure monitoring system switches to the first power consumption mode, ensuring that tire pressure data can be collected at a high frequency and transmitted to the vehicle gateway in a timely manner, providing immediate alarm signals for the driver and ensuring safe driving. When the vehicle is parked or driving at low speed and the tire pressure changes slowly, the tire pressure monitoring system switches to the second power consumption mode, reducing the tire pressure collection frequency and the alarm signal transmission frequency, reducing energy consumption and prolonging battery life. Not only can it improve the energy efficiency of the tire pressure monitoring system, but it also ensures efficient operation under different working conditions, providing a more reliable guarantee for the safe operation of the vehicle.

[0096] Please refer to Figure 2According to an aspect of the present application, a tire pressure data processing device is provided, comprising a frequency determination module 8100, a tire pressure monitoring module 8200 and an abnormality alarm module 8300. The frequency determination module 8100 is configured to monitor current driving speed data of a vehicle in real time, and determine a current tire pressure sampling frequency of the vehicle based on the driving speed data. The driving speed data is in a plurality of preset driving speed intervals, and the tire pressure sampling frequency corresponds to each driving speed interval one by one. The tire pressure monitoring module 8200 is configured to obtain tire pressure change data of the vehicle based on the tire pressure sampling frequency, and trigger a tire pressure abnormality event when the tire pressure change data exceeds a preset tire pressure change threshold. The abnormality alarm module 8300 is configured to determine an event abnormality level corresponding to the tire pressure abnormality event, and send a corresponding vehicle alarm signal to a vehicle gateway of the vehicle based on the event abnormality level. The event abnormality level comprises a plurality of preset event levels, and the vehicle alarm signal is transmitted based on a network priority and a signal retransmission strategy corresponding to the event level.

[0097] On the basis of any embodiment of the device of the present application, the frequency determination module 8100 comprises an interval matching module configured to obtain the driving speed data, match the driving speed data with the driving speed intervals, and determine a driving speed interval in which the vehicle currently locates. The device further comprises a tire pressure collection module configured to call a corresponding tire pressure sampling frequency based on the driving speed interval in which the vehicle currently locates, output the tire pressure sampling frequency to a tire pressure collection unit, and enable the tire pressure collection unit to collect the tire pressure change data based on the tire pressure sampling frequency.

[0098] On the basis of any embodiment of the device of the present application, the tire pressure monitoring module 8200 comprises a change monitoring module configured to collect current tire pressure data and tire temperature data of the vehicle based on the tire pressure sampling frequency, and calculate a tire pressure change rate of the vehicle according to the current tire pressure data and previously obtained tire pressure data. The device further comprises an event generation module configured to generate the tire pressure abnormality event based on the tire pressure data, the tire temperature data and the tire pressure change rate when the tire pressure data is less than a preset tire pressure threshold, or the tire temperature data is higher than a preset tire temperature threshold, or the tire pressure change rate is greater than the tire pressure change threshold.

[0099] On the basis of any embodiment of the device of the present application, the tire pressure monitoring module 8200 further comprises a difference calculation module configured to perform difference operation on the current tire pressure data and last obtained effective tire pressure data to obtain tire pressure difference data, and a data compression module configured to compress and encode the tire pressure difference data into a compressed data packet, and send the compressed data packet to the vehicle gateway when a next tire pressure sampling period arrives.

[0100] On the basis of any embodiment of the device of the present application, the event generation module further comprises: a first judging unit configured to correspondingly generate a first abnormal event when the tire pressure data is less than the tire pressure threshold value or the tire pressure change rate is greater than a first tire pressure threshold value; and a second judging unit configured to correspondingly generate a second abnormal event when the tire temperature data is greater than the tire temperature threshold value or the tire pressure change rate is greater than a second tire pressure threshold value and less than the first tire pressure threshold value.

[0101] On the basis of any embodiment of the device of the present application, the abnormal alarm module 8300 comprises: a first alarm module configured to determine that the event abnormality level is a first abnormality level when the tire pressure abnormal event is the first abnormal event, correspondingly configure the network priority of the vehicle alarm signal as a first priority, and continuously send the vehicle alarm signal to the vehicle gateway multiple times through an exclusive channel; and a second alarm module configured to determine that the event abnormality level is a second abnormality level when the tire pressure abnormal event is the second abnormal event, correspondingly configure the network priority of the vehicle alarm signal as a second priority, and after immediately sending the vehicle alarm signal to the vehicle gateway, repeatedly send the vehicle alarm signal to the vehicle gateway once.

[0102] On the basis of any embodiment of the device of the present application, the device further comprises: a power consumption adjustment module configured to switch the power consumption mode of the tire pressure monitoring node to a first power consumption mode or a second power consumption mode based on the tire pressure change rate and the driving speed data; a first power consumption module configured to, when the tire pressure monitoring node is in the first power consumption mode, the tire pressure monitoring node performs tire pressure data collection at a current tire pressure sampling frequency and sends a corresponding vehicle alarm signal to the vehicle gateway; and a second power consumption module configured to, when the tire pressure monitoring node is in the second power consumption mode, the tire pressure monitoring node reduces the tire pressure collection frequency and the signal sending frequency of the vehicle alarm signal, and switches to the first power consumption mode when a preset power consumption switching condition is met.

[0103] Another embodiment of the present application also provides a tire pressure data processing device. As shown in Figure 3 The internal structure of the tire pressure data processing device is shown in the figure. The tire pressure data processing device comprises a processor, a computer readable storage medium, a memory and a network interface connected through a system bus. Among them, the computer readable non-volatile readable storage medium of the tire pressure data processing device stores an operating system, a database and computer readable instructions, the database can store information sequences, and the computer readable instructions can make the processor realize a tire pressure data processing method when executed by the processor.

[0104] The processor of the tire pressure data processing device is configured to provide computing and control capabilities to support the operation of the entire tire pressure data processing device. The memory of the tire pressure data processing device can store computer readable instructions, which, when executed by the processor, can cause the processor to perform the tire pressure data processing method of the present application. The network interface of the tire pressure data processing device is configured to communicate with the terminal.

[0105] Those skilled in the art can understand that, Figure 3 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the tire pressure data processing device to which the scheme of the present application is applied. A specific tire pressure data processing device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0106] The processor in the embodiment is configured to perform the specific functions of each module in Figure 2 The memory stores program codes and various data required for executing the above-mentioned modules or sub-modules. The network interface is configured to realize data transmission between the user terminal or the server. The non-volatile readable storage medium in the embodiment of the present application stores program codes and data required for executing all modules in the tire pressure data processing device of the present application. The server can call the program codes and data of the server to execute the functions of all modules.

[0107] The present application also provides a non-volatile readable storage medium storing computer readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the tire pressure data processing method of any embodiment of the present application.

[0108] The present application also provides a computer program product, which includes computer programs / instructions, which, when executed by one or more processors, implement the steps of the method described in any embodiment of the present application.

[0109] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments of the present application can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments of each method. The storage medium can be a computer readable storage medium such as a magnetic disc, an optical disc, a read-only memory (ROM), or a random access memory (RAM).

Claims

1. A tire pressure data processing method characterized by, The method comprises the following steps: monitoring current driving speed data of a vehicle in real time, determining a current tire pressure sampling frequency of the vehicle based on the driving speed data, wherein the driving speed data is in a preset plurality of driving speed intervals, and the tire pressure sampling frequency corresponds to each driving speed interval; acquiring tire pressure change data of the vehicle based on the tire pressure sampling frequency, and triggering a tire pressure abnormal event when the tire pressure change data exceeds a preset tire pressure change threshold; determining an event abnormality level corresponding to the tire pressure abnormal event, and sending a corresponding vehicle alarm signal to a vehicle gateway of the vehicle based on the event abnormality level, wherein the event abnormality level comprises a plurality of event levels divided in advance, and the vehicle alarm signal is transmitted based on a network priority and a signal retransmission strategy corresponding to the event level.

2. The tire pressure data processing method according to claim 1, characterized by, The method of monitoring current driving speed data of a vehicle in real time, and determining a current tire pressure sampling frequency of the vehicle based on the driving speed data, comprises the following steps: acquiring the driving speed data, matching the driving speed data with the driving speed intervals, and determining a driving speed interval in which the vehicle currently locates; calling a corresponding tire pressure sampling frequency based on the driving speed interval in which the vehicle currently locates, and outputting the tire pressure sampling frequency to a tire pressure acquisition unit, so that the tire pressure acquisition unit acquires the tire pressure change data based on the tire pressure sampling frequency.

3. The tire pressure data processing method according to claim 1, characterized by, The method of acquiring tire pressure change data of the vehicle based on the tire pressure sampling frequency, and triggering a tire pressure abnormal event when the tire pressure change data exceeds a preset tire pressure change threshold, comprises the following steps: acquiring current tire pressure data and tire temperature data of the vehicle based on the tire pressure sampling frequency, and calculating a tire pressure change rate of the vehicle according to the current tire pressure data and previously acquired tire pressure data of the vehicle; generating the tire pressure abnormal event based on the tire pressure data, the tire temperature data and the tire pressure change rate when the tire pressure data is less than a preset tire pressure threshold, or the tire temperature data is higher than a preset tire temperature threshold, or the tire pressure change rate is greater than the tire pressure change threshold.

4. The tire pressure data processing method according to any one of claim 3, characterized by, When the tire pressure data does not exceed the tire pressure change threshold, the method further comprises the following steps: performing difference operation on the current tire pressure data and the last acquired effective tire pressure data to obtain tire pressure difference data; compressing and encoding the tire pressure difference data into a compressed data packet, and sending the compressed data packet to the vehicle gateway when a next tire pressure sampling period arrives.

5. The tire pressure data processing method according to claim 3, characterized by, The method of generating the tire pressure abnormal event based on the tire pressure data, the tire temperature data and the tire pressure change rate, comprises the following steps: correspondingly generating a first abnormal event when the tire pressure data is less than the tire pressure threshold, or the tire pressure change rate is greater than a first tire pressure threshold; correspondingly generating a second abnormal event when the tire temperature data is greater than the tire temperature threshold, or the tire pressure change rate is greater than a second tire pressure threshold and less than the first tire pressure threshold.

6. The tire pressure data processing method according to claim 5, characterized by, The method of determining an event abnormality level corresponding to the tire pressure abnormal event, and sending a corresponding vehicle alarm signal to a vehicle gateway of the vehicle based on the event abnormality level, comprises the following steps: When the tire pressure abnormal event is the first abnormal event, the event abnormal level is determined as a first abnormal level, a network priority corresponding to the vehicle alarm signal is configured as a first priority, and the vehicle alarm signal is sent to the vehicle gateway through an exclusive channel for multiple times in succession; When the tire pressure abnormal event is the second abnormal event, the event abnormal level is determined as a second abnormal level, a network priority corresponding to the vehicle alarm signal is configured as a second priority, and the vehicle alarm signal is sent to the vehicle gateway once more after being sent to the vehicle gateway immediately.

7. The tire pressure data processing method according to any one of claims 1 to 6, characterized by, Further comprising: Based on the tire pressure change rate and the driving speed data, the power consumption mode of the tire pressure monitoring node is switched to a first power consumption mode or a second power consumption mode; When the tire pressure monitoring node is in the first power consumption mode, the tire pressure monitoring node performs tire pressure data collection at a current tire pressure sampling frequency and sends a corresponding vehicle alarm signal to the vehicle gateway; When the tire pressure monitoring node is in the second power consumption mode, the tire pressure monitoring node reduces the tire pressure collection frequency and the signal transmission frequency of the vehicle alarm signal until it switches to the first power consumption mode when the preset power consumption switching condition is met.

8. A tire pressure data processing device characterized by comprising: Comprise: The frequency determination module is configured to monitor the current driving speed data of the vehicle in real time, and determine the current tire pressure sampling frequency of the vehicle based on the driving speed data, wherein the driving speed data is in a plurality of preset driving speed intervals, and the tire pressure sampling frequency corresponds to each driving speed interval one by one; The tire pressure monitoring module is configured to obtain tire pressure change data of the vehicle based on the tire pressure sampling frequency, and trigger a tire pressure abnormal event when the tire pressure change data exceeds a preset tire pressure change threshold; The abnormal alarm module is configured to determine the event abnormal level corresponding to the tire pressure abnormal event, and send a corresponding vehicle alarm signal to the vehicle gateway based on the event abnormal level, wherein the event abnormal level comprises a plurality of event levels, and the vehicle alarm signal is transmitted based on the network priority and the signal retransmission strategy corresponding to the event level.

9. A tire pressure data processing device characterized by comprising: The application relates to a tire pressure monitoring system, which comprises a tire pressure sensor, a vehicle speed sensor, a tire temperature sensor, a microprocessor, a wireless transceiver module, a vehicle gateway and a battery management module, wherein the tire pressure sensor is arranged in a tire and is used for collecting tire pressure data in real time according to a sampling frequency given by the microprocessor; the vehicle speed sensor is used for reading vehicle speed from a vehicle bus or a GPS module in real time and outputting the vehicle speed to the microprocessor; the tire temperature sensor is used for measuring the current temperature of a vehicle tire; the microprocessor is used for setting the sampling frequency of the tire pressure sensor according to a vehicle speed interval, and generating a tire pressure abnormal event and a corresponding event level when a tire pressure variation exceeds a set threshold; the wireless transceiver module is connected with the microprocessor and is used for sending a vehicle alarm signal to the vehicle gateway according to a network priority and a retransmission strategy corresponding to the event level; the vehicle gateway is arranged in a driver's cabin and is used for receiving and forwarding the alarm signal to a vehicle-mounted display terminal or a mobile terminal; and the battery management module is electrically connected with the tire pressure sensor, the microprocessor and the wireless transceiver module and is used for switching between at least two power consumption modes according to an event level and a vehicle running state.

10. A non-volatile readable storage medium, characterized by The computer program is stored in the form of computer readable instructions and is realized according to the method in any one of claims 1 to 7, and when the computer program is called and run by a computer, the steps included in the corresponding method are executed.

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