Tire pressure monitoring device and method based on passive RFID temperature tag

Abstract

The invention discloses a tire pressure monitoring device and method based on a passive RFID temperature tag. The tire pressure monitoring device comprises the passive RFID temperature tag, a reader-writer module and a data processing unit. And the passive RFID temperature measurement tag is fixed on the inner wall of the tire, receives the radio frequency energy sent by the reader-writer module, and collects the internal temperature of the tire in real time. The reader-writer module is fixed near a hub of a vehicle, performs polling communication with the passive RFID temperature measurement tag through a multi-band radio frequency technology, and transmits tire internal temperature data returned by the passive RFID temperature measurement tag to the data processing unit. And the data processing unit indirectly derives the tire pressure by utilizing a thermodynamic equation and combining parameters such as tire structure change, vehicle speed and load, so that high-precision and low-power-consumption tire pressure monitoring is realized. According to the method, the tire structure does not need to be damaged, non-contact pressure estimation and dynamic modeling can be achieved, and the method has the advantages of being simple in structure, high in reliability, wide in applicability and the like.

Description

Technical Field

[0001] The present application belongs to the field of sensor monitoring technology, relates to an automobile tire pressure monitoring system, and particularly to a tire pressure monitoring device and method based on a passive RFID temperature tag. Background Art

[0002] A tire pressure monitoring system (TPMS) automatically monitors tire pressure in real time while a vehicle is in motion and issues alerts for leaks and low tire pressure, ensuring driving safety. It can be categorized as either indirect or direct. Direct tire pressure monitoring systems use tire-mounted pressure sensors to measure tire pressure. These sensors then transmit this information from the tire's interior to a central receiver module via a wireless transmitter. Traditional pressure sensors typically rely on batteries, which are subject to limitations in battery life and ambient temperature, making them prone to data loss and poor reliability. Furthermore, since pressure sensors must be embedded within the tire's inner lining, the installation process is cumbersome and can increase the probability of tire balancing failure. External mechanical shock can also damage the sensors or increase errors.

[0003] Existing technologies such as CN102490555A and CN105015280A solve the problem of limited battery life in active direct tire pressure monitoring systems by combining an RFID reader / writer, an RFID chip, and a pressure sensor, using RFID radio frequency technology to provide the pressure sensor with the required operating power. However, no improvement solutions are proposed for the detection accuracy of the pressure sensor and the negative impact caused by the installation of the monitoring system. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention proposes a tire pressure monitoring device and method based on passive RFID temperature tags. By indirectly inferring dynamic tire pressure through passive temperature tags, this device and method achieve maintenance-free, high-precision tire health monitoring. This addresses the issues of traditional TPMS, such as battery dependence, complex installation, and insufficient model accuracy. The device is suitable for vehicle active safety warning, intelligent tire management systems, and Internet of Things (IoT) sensing node scenarios.

[0005] A tire pressure monitoring device based on a passive RFID temperature tag includes a passive RFID temperature measurement tag, a reader / writer module and a data processing unit.

[0006] The passive RFID temperature measurement tag is fixed to the inner wall of the tire, receives the radio frequency energy sent by the reader module, and collects the internal temperature of the tire in real time.

[0007] The reader-writer module is fixed near the vehicle wheel hub, and performs polling communication with the passive RFID temperature measurement tag through multi-band radio frequency technology, and transmits the tire internal temperature data returned by the passive RFID temperature measurement tag to the data processing unit.

[0008] The data processing unit receives the tire internal temperature data , combined with the vehicle's current speed and load data , calculate tire pressure :

[0009]

[0010] Where n represents the number of moles of gas, R represents the universal gas constant, Indicates the difference between the current tire temperature T and the temperature of the vehicle at rest. Indicates the static air cavity volume of the tire when the vehicle is stationary. 、 is the tire volume correction factor obtained through experimental fitting.

[0011] Preferably, the reader / writer module communicates with the data processing unit via a CAN bus or an in-vehicle Ethernet.

[0012] As a preferred method, M passive RFID temperature measurement tags are fixed at different positions of the tire, and the reader-writer module communicates with each passive RFID temperature measurement tag in turn by polling to obtain multiple tire internal temperature data values ​​T1, T2, ...T M , under experimental conditions, standard tire pressure and multi-point temperature data are collected, and the tire pressure P is constructed by data fitting method. t With multiple point temperatures T1, T2, ...T M and vehicle speed and load data Functional relationship P t =f(T1,T2,…,T M ,L,v).

[0013] As an optimal method, a deviation compensation factor is introduced , used to correct errors caused by gas leakage, temperature delay, etc., and the corrected tire pressure for:

[0014]

[0015] Preferably, the system further includes a feedback control unit. The feedback control unit calculates the tire pressure based on the tire pressure calculated by the data processing unit. , calculate the heating rate based on historical temperature data and trigger a graded alarm.

[0016] Preferably, the alarm modes include instrument prompts, voice alarms and cloud push.

[0017] Preferably, a graded warning is triggered when the tire pressure is lower than 2.0 Bar or the temperature rise rate is higher than 5°C / min.

[0018] The tire pressure monitoring method based on the passive RFID temperature tag uses the above device to measure the temperature of the automobile tire and monitor the automobile tire pressure, which specifically includes the following steps:

[0019] Step 1: Use a standard pressure sensor to obtain the reference tire pressure data P under vehicle mass L and speed v, and substitute the collected (L, v, P, T) data into , the effective volume V of the air cavity is deduced, and the relationship between the effective volume V of the air cavity and the vehicle mass L and speed v is fitted by the multivariate linear regression method:

[0020]

[0021] Here, n represents the number of moles of gas, and R represents the universal gas constant. Indicates the static air cavity volume of the tire when the vehicle is stationary. 、 is the fitted tire volume correction factor.

[0022] Step 2: The reader module sends radio frequency to read the temperature data T measured by the passive RFID temperature measurement tag fixed on the tire. The current vehicle speed v and vehicle mass L are obtained through the vehicle CAN bus.

[0023] Step 3: Use the fitted tire volume correction factor to estimate the tire internal pressure :

[0024]

[0025] in, Indicates the difference between the current tire temperature T and the temperature when the vehicle is stationary.

[0026] As a preferred method, obtain a reliable tire pressure reference value P ref , calculate the tire pressure reference value P ref and the estimated tire pressure P est The difference e of the prediction error is used to calculate the deviation compensation factor :

[0027]

[0028] in, Indicates the last tire pressure reference value P refThe value of the deviation compensation factor calculated when , the initial value is 0. α is the learning rate coefficient. Using the deviation compensation factor The internal pressure of the tire Corrected to :

[0029]

[0030] Preferably, the temperature data measured by the passive RFID temperature measurement tag at different times, the estimated tire internal pressure data, and time are mapped to the same three-dimensional coordinate system, and a three-dimensional temperature-pressure-time correlation model is fitted. The temperature change rate is calculated based on the historical temperature data, used as a precursor to the dynamic pressure change. The trajectory deviation in the three-dimensional correlation model is analyzed. When the temperature continues to rise without a synchronous increase in pressure, a gas leak is suspected. When the temperature changes abnormally rapidly and the local temperature distribution is uneven, the tire carcass damage is suspected. This can then be used as an early warning.

[0031] The present invention has the following beneficial effects:

[0032] 1. By establishing a passive temperature-pressure joint sensing method, the system can observe changes in multiple temperature measurement tags in real time and dynamically estimate tire pressure changes based on temperature trends. Pressure sensors are completely eliminated during the tire pressure estimation process, avoiding the structural complexity and reliability issues caused by airtight packaging and susceptibility to impact of pressure sensors, while also reducing maintenance costs.

[0033] 2. Simultaneously with temperature data modeling, vehicle operating parameters, including speed and load, are incorporated to achieve dynamic corrections, ensuring that the pressure estimate reflects the tire pressure state under real-world driving conditions, thereby improving detection accuracy and applicability. The modeling process further considers error factors such as gas leakage and thermal conduction lag, introduces a deviation compensation factor, and establishes a self-learning and dynamic correction mechanism to ensure the stability and long-term reliability of tire pressure estimation results.

[0034] 3. Constructing a three-dimensional mapping model of temperature, pressure, and time enables the system to capture the evolution trend of tire pressure with temperature and operating time, and realize dynamic prediction and early warning of tire pressure changes. Compared with single-point measurement methods, it has higher sensitivity and response speed.

[0035] 4. Without introducing active electronic devices, it realizes indirect perception and intelligent warning of tire pressure. It has significant advantages such as simple structure, high reliability, low maintenance cost and strong adaptability. It is suitable for tire health management in various scenarios such as passenger cars, trucks, and special vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1FIG. 1 is a system architecture diagram of a tire pressure monitoring device in an embodiment.

[0037] Figure 2 Schematic diagram of the arrangement of multiple passive RFID temperature measurement tags in an embodiment.

[0038] Figure 3 This is the hierarchical alarm logic state machine diagram.

[0039] Figure 4 FIG. 4 is a flow chart of a pressure estimation algorithm in an embodiment. DETAILED DESCRIPTION

[0040] The present invention is further explained below with reference to the accompanying drawings. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0041] A tire pressure monitoring device based on a passive RFID temperature tag includes a passive RFID temperature measurement tag, a reader / writer module, a data processing unit and a feedback control unit.

[0042] like Figure 1 As shown, the passive RFID temperature tag, affixed to the inner wall of the tire, comprises an RFID antenna and a high-precision MEMS temperature sensor. It operates passively, receiving RF energy from a reader module as its operating voltage, eliminating the need for an internal battery. This offers advantages such as a long service life, low maintenance costs, and strong environmental adaptability, making it particularly suitable for the complex environment of high temperatures, high rotation speeds, and intense vibrations found inside tires. The passive RFID temperature tag collects real-time internal tire temperature data and modulates and reflects this data back to the reader module via RFID communication.

[0043] like Figure 2 As shown, in one embodiment, four passive RFID temperature measurement tags are used to measure the temperature of the same tire, two of which are fixed at opposite positions on the tire shoulders, and the other two are fixed at the tire crown and sidewall, respectively. Through multi-point monitoring, the overall perception accuracy and robustness are further improved.

[0044] The reader / writer module is fixed near the vehicle's wheel hub or in a fixed suspension system near the tire. It incorporates a low-power radio frequency communication chip and antenna array, utilizing multi-band frequency-hopping RFID technology, offering high-sensitivity decoding and strong anti-interference performance. The reader / writer module is configured to poll the passive RFID temperature measurement tag every 100ms and transmit tire internal temperature data returned by the passive RFID temperature measurement tag to a data processing unit via the CAN bus or in-vehicle Ethernet.

[0045] The data processing unit is deployed on the vehicle central controller or an independent embedded computing platform to obtain the current speed of the vehicle and load data , and according to the received tire internal temperature data , calculate tire pressure , and transmitted to the feedback control unit:

[0046]

[0047] Where n represents the number of moles of gas, R represents the universal gas constant, Indicates the difference between the current tire temperature T and the temperature of the vehicle at rest. Indicates the static air cavity volume of the tire when the vehicle is stationary. 、 is the tire volume correction factor obtained through experimental fitting.

[0048] The feedback control unit is integrated with the vehicle system via the CAN bus, and can also be connected to the mobile phone app via Bluetooth or Wi-Fi. According to the data calculated by the data processing unit, a graded alarm is triggered, such as Figure 3 As shown: When tire pressure drops below 1.8 Par, a Level 1 alarm is triggered, with a flashing dashboard icon. When the temperature rise rate exceeds 5°C / min, a Level 2 alarm is triggered, with a voice prompt or buzzer. When tire pressure exceeds 3.5 Par, a Level 3 alarm is triggered, with the alarm information uploaded to the cloud platform via 4G or Wi-Fi for analysis by back-end maintenance systems or fleet managers.

[0049] The tire pressure monitoring method based on the passive RFID temperature tag uses the above device to measure the temperature of the automobile tire and monitor the automobile tire pressure, such as Figure 4 As shown, the specific steps include:

[0050] Step 1: Derive the model based on basic thermodynamics It can be seen that the air pressure P inside the tire is related to the temperature T and the gas volume V. Here, n and R are constants. n represents the number of moles of gas (in mol), and R = 8.314 J / mol.K, the universal gas constant. The reader module transmits radio frequency signals to read the temperature data T measured by the passive RFID temperature measurement tag on the tire.

[0051] Step 2: Consider the deformation caused by factors such as load compression and deformation during vehicle driving , calculate the effective volume V of the tire cavity as:

[0052]

[0053] in, Indicates the static air cavity volume of the tire when the vehicle is stationary. Indicates vehicle mass in kg. Indicates vehicle speed in km / h. 、 The tire volume correction coefficient is obtained through experimental fitting. The specific fitting process is as follows: Under a constant temperature environment, a standard pressure sensor is used to obtain the reference tire pressure data P under vehicle mass L and speed v, and the real-time temperature data T of the passive RFID temperature tag is recorded. The collected (L, v, P, T) data is substituted into , the effective volume V of the air cavity is deduced, and the relationship between the effective volume V of the air cavity and the vehicle mass L and speed v is fitted by the multivariate linear regression method, so as to obtain the values ​​of k1 and k2.

[0054] Step 3: Estimated tire internal pressure for:

[0055]

[0056] In one embodiment, a bias compensation factor is introduced , used to correct errors caused by gas leakage, temperature delay, etc., and the corrected tire pressure estimate for:

[0057]

[0058] The deviation compensation factor The initial value is 0, and the tire pressure reference value P can be obtained. ref The deviation compensation factor is Update, the specific method is: calculate the tire pressure reference value P ref and the estimated tire pressure P est The difference e of the prediction error is used to compensate the deviation factor Updated to :

[0059]

[0060] Among them, α is the learning rate coefficient.

[0061] In one embodiment, when the prediction error e exceeds 0.3 Bar, k1 and k2 are corrected using the least squares method. When data from a passive RFID temperature tag is lost, linear interpolation is used to complete the temperature. If reader communication fails more than three times, the backup antenna channel is switched to ensure data fault tolerance.

[0062] In one embodiment, multiple passive RFID temperature measurement tags work together to identify local tire anomalies through lateral temperature distribution analysis. Furthermore, the temperature change rate is used as a precursor to dynamic pressure changes. Combined with historical driving conditions, a three-dimensional temperature-pressure-time mapping model is established to further improve warning accuracy and system response speed. The specific method is as follows:

[0063] s4.1. Analysis of transverse temperature distribution

[0064] Calculate the temperature difference ΔTij between the temperature data Ti of the i-th temperature measurement point and the temperature data Tj of the j-th temperature measurement point at the same time:

[0065] ΔTij=|Ti−Tj|

[0066] Where i, j = 1, 2, ... M, and M represents the number of passive RFID temperature measurement tags. The temperature difference ΔTij is used to identify lateral temperature imbalance.

[0067] Calculate the average value of the temperature data T1, T2, ..., TM collected by M passive RFID temperature measurement tags at the same time , set the abnormal ratio When the temperature of a certain measuring point exceeds , it is judged that the temperature measurement point may be overheated or structurally abnormal, such as crown overheating or sidewall damage.

[0068] s4.2. Establish a temperature-pressure-time three-dimensional mapping model

[0069] Temperature data sequences measured by passive RFID temperature measurement tags at different times are collected and combined with the vehicle's timeline to form a temperature-time curve. Simultaneously, real-time pressure predictions are generated based on a pressure estimation formula to form a pressure-time curve. Temperature, pressure, and time are mapped to the same three-dimensional coordinate system, and a three-dimensional temperature-pressure-time correlation model is obtained through fitting.

[0070] The temperature change rate is used as a precursor to the dynamic change in pressure. The deviation of the trajectory in the three-dimensional correlation model is analyzed. When the temperature continues to rise without a synchronous increase in pressure, it is determined that there may be a gas leak. When the temperature changes abnormally quickly and the local temperature distribution is uneven, it is determined that there may be carcass damage. This can then be used as an early warning.

Claims

1. A tire pressure monitoring device based on a passive RFID temperature tag, comprising a passive RFID temperature measurement tag, a reader / writer module, and a data processing unit; characterized in that: The passive RFID temperature measurement tag is fixed to the inner wall of the tire, receives the radio frequency energy sent by the reader module, and collects the internal temperature of the tire in real time; The reader / writer module is fixed near the wheel hub of the vehicle and performs polling communication with the passive RFID temperature measurement tag through multi-band radio frequency technology, and transmits the tire internal temperature data returned by the passive RFID temperature measurement tag to the data processing unit; The data processing unit receives the tire internal temperature data , combined with the vehicle's current speed and load data , calculate tire pressure : ； Where n represents the number of moles of gas, R represents the universal gas constant, Indicates the difference between the current tire temperature T and the temperature of the vehicle at rest. Indicates the static air cavity volume of the tire when the vehicle is stationary. 、 is the tire volume correction factor obtained through experimental fitting.

2. The tire pressure monitoring device based on a passive RFID temperature tag according to claim 1, characterized in that: The reader / writer module communicates with the data processing unit via the CAN bus or the vehicle Ethernet.

3. The tire pressure monitoring device based on a passive RFID temperature tag according to claim 1, characterized in that: M passive RFID temperature measurement tags are fixed at different positions of the tire. The reader-writer module communicates with each passive RFID temperature measurement tag in turn through polling to obtain multiple tire internal temperature data values ​​T1, T2, ...T M , under experimental conditions, standard tire pressure and multi-point temperature data are collected, and the tire pressure P is constructed by data fitting method. t With multiple point temperatures T1, T2, ...T M and vehicle speed and load data Functional relationship P t =f(T1,T2,…,T M ,L,v).

4. The tire pressure monitoring device based on a passive RFID temperature tag according to claim 1, wherein: Also includes a feedback control unit; the feedback control unit calculates the tire pressure according to the data processing unit , calculate the heating rate based on historical temperature data and trigger a graded alarm.

5. The tire pressure monitoring device based on a passive RFID temperature tag according to claim 4, characterized in that: The alarm modes include instrument prompts, voice alarms and cloud push.

6. The tire pressure monitoring device based on a passive RFID temperature tag according to claim 4, characterized in that: Set the graded warning to be triggered when the tire pressure is lower than 2.0 Bar or the temperature rise rate is higher than 5℃ / min.

7. A tire pressure monitoring method based on a passive RFID temperature tag, characterized in that: Measuring the temperature of automobile tires and monitoring the pressure of automobile tires using the device according to any one of claims 1 to 6 specifically comprises the following steps: Step 1: Use a standard pressure sensor to obtain the reference tire pressure data P under vehicle mass L and speed v, and substitute the collected (L, v, P, T) data into , the effective volume V of the air cavity is deduced, and the relationship between the effective volume V of the air cavity and the vehicle mass L and speed v is fitted by the multivariate linear regression method: ； Where n represents the number of moles of gas and R represents the universal gas constant; Indicates the static air cavity volume of the tire when the vehicle is stationary; 、 is the fitted tire volume correction factor; Step 2: The reader module sends radio frequency to read the temperature data T measured by the passive RFID temperature measurement tag fixed on the tire; the current vehicle speed v and vehicle mass L are obtained through the vehicle CAN bus; Step 3: Use the fitted tire volume correction factor to estimate the tire internal pressure : ； in, Indicates the difference between the current tire temperature T and the temperature when the vehicle is stationary.

8. The tire pressure monitoring method based on a passive RFID temperature tag according to claim 7, wherein: Obtain a reliable tire pressure reference value P ref , calculate the tire pressure reference value P ref and the estimated tire pressure P est The difference e of the prediction error is used to calculate the deviation compensation factor : ； in, Indicates the last tire pressure reference value P ref The value of the deviation compensation factor calculated when , the initial value is 0; α is the learning rate coefficient; using the deviation compensation factor The internal pressure of the tire Corrected to : 。 9. The tire pressure monitoring method based on a passive RFID temperature tag according to claim 7, wherein: The temperature data measured by the passive RFID temperature measurement tag at different times, the estimated internal tire pressure data, and time are mapped to the same three-dimensional coordinate system to fit a three-dimensional temperature-pressure-time correlation model. The temperature change rate is calculated based on the historical temperature data and used as a precursor to the dynamic change of pressure. The deviation of the trajectory in the three-dimensional correlation model is analyzed. When the temperature continues to rise without a synchronous increase in pressure, it is determined that there may be a gas leak. When the temperature changes abnormally rapidly and the local temperature distribution is uneven, it is determined that there may be tire damage.

10. The tire pressure monitoring method based on a passive RFID temperature tag according to claim 7, wherein: Calculate the temperature difference ΔTij between the temperature data Ti of the i-th temperature measurement point on the tire and the temperature data Tj of the j-th temperature measurement point on the tire at the same time: ΔTij=|Ti−Tj| Where i, j = 1, 2, ... M, M represents the number of passive RFID temperature measurement tags; the temperature difference ΔTij is used to identify the lateral temperature imbalance.

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