TPMS (Tire Pressure Monitor System) omnibearing automatic adaptation device

Abstract

The invention discloses a TPMS (Tire Pressure Monitor System) omnibearing automatic adaptation device, which relates to the technical field of new energy automobiles and comprises an energy data acquisition module, a tire data acquisition module, a data processing module, a data processing module, a data processing module and a data processing module, and is characterized in that the energy data acquisition module comprises pressure monitoring, temperature monitoring, wear monitoring, load monitoring and dynamic data monitoring; and the sensor monitoring module comprises a pressure sensor, a temperature sensor, an accelerometer, a wear sensor and a wireless tag. In the invention, in order to realize safety maximization of tire pressure monitoring, a tire pressure signal is converted into an electric signal which can be identified by an MCU (Microprogrammed Control Unit) and is communicated through a modbus protocol, so that the MCU of a vehicle body predicts that the tire has a fault or is about to have a fault in advance, and meanwhile, based on an anti-interference communication protocol, a high-frequency band or frequency hopping technology is adopted, so that the signal conflict with other wireless equipment is reduced, and the safety of the tire pressure monitoring is improved. A redundant communication mechanism is introduced, stable data transmission is ensured, signal processing filters noise signals through an AI algorithm, the accuracy of data receiving is improved, accidents can be effectively avoided, and casualties of personnel and property are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicles, and specifically to a TPMS all-round automatic adaptation device. Background Art

[0002] As an important part of an automobile, the main factor considered for tire performance is tire pressure. Too low or too high tire pressure will affect the service performance of the tire and reduce its service life, ultimately affecting driving safety. The full name of TPMS is Tire Pressure Monitoring System. The function of TPMS is to automatically monitor the tire pressure in real time during vehicle driving and alarm for tire air leakage and low pressure to ensure driving safety.

[0003] The existing technology cannot accurately help us identify abnormal tire pressure and temperature, capture subtle abnormalities, resulting in hazards during driving, and thus unable to make corresponding instructions and treatment measures in a timely manner. Therefore, a TPMS all-round automatic adaptation device is urgently needed. Summary of the Invention

[0004] The purpose of the present invention is to provide a TPMS all-round automatic adaptation device to solve the problem that the existing technology cannot accurately help us identify abnormal tire pressure and temperature, capture subtle abnormalities, resulting in hazards during driving, and thus unable to make corresponding instructions and treatment measures in a timely manner.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A TPMS all-round automatic adaptation device, including: Tire data acquisition module: including pressure monitoring, temperature monitoring, wear monitoring, load monitoring and dynamic data monitoring; Sensor monitoring module: The module includes a pressure sensor, a temperature sensor, an accelerometer, a wear sensor and a wireless tag; Data processing module: used for data parsing, verification, signal filtering and smoothing, temperature compensation and calibration, data storage, and also includes communication protocol and signal processing; Early warning module: including early warning and diagnosis and data fusion.

[0006] Preferably, the hardware composition of the tire data acquisition module includes sensors and data acquisition units, and the software algorithm content includes real-time data processing, data filtering, feature extraction and fault diagnosis.

[0007] Preferably, the pressure monitoring is to detect the internal air pressure of the tire in real time to prevent tire blowout or insufficient tire pressure. The temperature monitoring senses the working temperature of the tire to avoid rubber aging or failure caused by overheating. The wear monitoring analyzes the tread wear degree through vibration or optical sensors. The load monitoring estimates the load-bearing weight of the tire to optimize vehicle balance. The dynamic data: collects driving dynamic parameters such as acceleration, rotational speed, and slip ratio.

[0008] Preferably, the data acquisition unit includes a signal conditioning circuit, an analog-to-digital conversion, a microcontroller, and a wireless transmission module.

[0009] Preferably, in the sensor monitoring module, the sensor group selects a suitable model according to the vehicle model, and the sensor group is divided into two categories, left and right, which are respectively adapted to the left and right front wheels.

[0010] Preferably, in the data processing module, the data parsing receives wireless signals from sensors, including RF and BLE, and parses the frame structure of the data packet, including ID, tire pressure, temperature, battery voltage, check bits, etc. The data verification uses CRC verification or parity check to verify the data integrity, discards invalid data packets and filters outlier values. The signal filtering and smoothing suppress environmental noise. The temperature compensation and calibration correct the tire pressure value according to the temperature sensor data, and compensate for the non-linear error based on the calibration table (Lookup Table). The data storage can cache recent data for trend analysis and store fault logs.

[0011] Preferably, in the data processing module, based on an anti-interference communication protocol, high-frequency bands or frequency hopping technologies are adopted to reduce signal conflicts with other wireless devices, and a redundant communication mechanism is introduced to ensure stable data transmission. The signal processing filters out noise signals through AI algorithms to improve the accuracy of data reception.

[0012] Preferably, in the warning module, the warning and diagnosis combine vehicle load, driving speed, and environmental temperature to provide dynamic tire pressure suggestions, and push detailed alarm information through the mobile phone APP, and attach processing suggestions.

[0013] Preferably, in the warning module, the data fusion integrates tire pressure, temperature, and acceleration data to monitor the dynamic balance state or abnormal wear of the tire and early warn of potential risks.

[0014] Compared with the prior art, the beneficial effects of the present invention are: In the present invention, to maximize the safety of tire pressure monitoring, the tire pressure signal is converted into an electrical signal recognizable by the MCU and communicated through the Modbus protocol, enabling the vehicle body MCU to predict in advance that a tire failure has occurred or is about to occur. At the same time, based on the anti-interference communication protocol, a high-frequency band or frequency hopping technology is adopted to reduce signal conflicts with other wireless devices, and a redundant communication mechanism is introduced to ensure stable data transmission. Signal processing filters noise signals through AI algorithms to improve the accuracy of data reception, effectively avoiding accidents and reducing casualties and property losses of personnel.

[0015] In the present invention, the warning module of the tire pressure monitoring system (TPMS) monitors the health status of the tire through multi-sensor data fusion technology (tire pressure, temperature, acceleration). Through multi-source data acquisition and preprocessing, in the warning module, warning and diagnosis are combined with vehicle load, driving speed, and environmental temperature to provide dynamic tire pressure suggestions, and detailed alarm information is pushed through the mobile phone APP, along with processing suggestions, which is beneficial to reducing the risks caused by tires, playing a key detection function for the tire pressure, tire temperature, etc., reducing the later maintenance cost, increasing the service life, and improving the driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic flow diagram of the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0018] Please refer to Figure 1 , the TPMS all-round automatic adaptation device, including: Tire data acquisition module: including pressure monitoring, temperature monitoring, wear monitoring, load monitoring, and dynamic data monitoring; Sensor monitoring module: The module includes a pressure sensor, a temperature sensor, an accelerometer, a wear sensor, and a wireless tag; Data processing module: used for data parsing, verification, signal filtering and smoothing, temperature compensation and calibration, data storage, and also includes communication protocol and signal processing; Warning module: including warning and diagnosis and data fusion.

[0019] Embodiment 1 As a preferred embodiment of the present invention: The hardware composition of the tire data acquisition module includes sensors and a data acquisition unit, and the software algorithm content includes real-time data processing, data filtering, feature extraction, and fault diagnosis; Pressure sensors, temperature sensors, accelerometers, wear sensors, and wireless tags are used in the tire pressure monitoring system to monitor the tire pressure, temperature, acceleration, tire wear, etc. of the tire. These sensors are installed on the wheel hub for direct monitoring. The monitored data is converted into an electrical signal and then into a radio frequency signal and transmitted to the receiver. Real-time data processing compresses and encrypts the data to reduce the transmission bandwidth. Data filtering eliminates noise such as Kalman filtering and moving average filtering. Feature extraction identifies features such as abnormal tire pressure, unbalanced vibration, and tread peeling. Fault diagnosis predicts the tire life or potential faults based on a machine learning model.

[0020] Embodiment 2 As a preferred embodiment of the present invention: Pressure monitoring is to detect the internal air pressure of the tire in real time to prevent tire blowouts or underinflation. Temperature monitoring senses the working temperature of the tire to avoid rubber aging or failure caused by overheating. Wear monitoring analyzes the tread wear degree through vibration or optical sensors. Load monitoring estimates the tire load weight to optimize vehicle balance. Dynamic data: Collect driving dynamic parameters such as acceleration, rotational speed, and slip ratio; The pressure sensor is a MEMS sensor installed on the wheel hub to detect the internal air pressure of the tire in real time to prevent tire blowouts or underinflation. The temperature sensor is a thermistor sensor that senses the working temperature of the tire to avoid rubber aging or failure caused by overheating. The wear sensor uses an optical / ultrasonic sensor or a tread-embedded wear indicator strip to analyze the tread wear degree. Load monitoring estimates the tire load weight to optimize vehicle balance. The accelerometer measures tire vibration and centrifugal force to analyze road conditions and dynamic balance.

[0021] Embodiment 3 As a preferred embodiment of the present invention: The data acquisition unit includes a signal conditioning circuit, an analog-to-digital conversion, a microcontroller, and a wireless transmission module; The signal conditioning circuit amplifies and filters the sensor signal. The analog-to-digital conversion (ADC) converts the analog signal into a digital signal. The microcontroller (MCU) processes the data and controls the communication module. The wireless transmission module includes Bluetooth, LoRa, NB-IoT, CAN bus, etc., and supports real-time data upload.

[0022] Embodiment 4 As a preferred embodiment of the present invention: In the sensor monitoring module, the sensor group selects a suitable model according to the vehicle model, and the sensor group is divided into two categories, left and right, which are respectively adapted to the left and right front wheels; The sensor adopts automatic identification technology to adapt to a unique address. There are batches and categories between the sensor and the tire pressure monitoring system. According to the vehicle model, the appropriate sensor is selected. The left front wheel uses the left front wheel sensor to adapt. When adapting, no professional and dedicated adaptation tools are required. As long as the specified position signal is triggered within the distance range, the system can be connected. After connection, there is a function to prevent misoperation to ensure that no other devices can be connected to this position to avoid generating error signals.

[0023] Embodiment 5 As a preferred embodiment of the present invention: In the data processing module, the data parsing receives wireless signals from the sensor, including RF and BLE, and parses the frame structure of the data packet, including ID, tire pressure, temperature, battery voltage, parity bit, etc. The data verification uses CRC verification or parity check to verify the data integrity, discards invalid data packets and filters outlier values. The signal filtering and smoothing suppresses environmental noise. The temperature compensation and calibration corrects the tire pressure value according to the temperature sensor data, and compensates for the non-linear error based on the calibration table (LookupTable). The data storage can cache recent data for trend analysis and store fault logs. The data processing module of the tire pressure monitoring system (TPMS) is its core part, responsible for parsing, verifying, analyzing and making decisions on the raw data collected by the sensor, and finally triggering an alarm or providing status information. The data parsing receives wireless signals from the sensor and parses the frame structure of the data packet. The data verification uses CRC verification or parity check to verify the data integrity, discards invalid data packets and filters outlier values. The signal filtering and smoothing suppresses environmental noise through moving average filtering. The temperature compensation and calibration corrects the tire pressure value according to the temperature sensor data, and compensates for the non-linear error based on the calibration table (Lookup Table). The data storage can cache recent data for trend analysis and store fault logs.

[0024] Embodiment 6 As a preferred embodiment of the present invention: In the data processing module, based on the anti-interference communication protocol, high-frequency bands or frequency hopping technologies are adopted to reduce signal conflicts with other wireless devices, and a redundant communication mechanism is introduced to ensure stable data transmission. The signal processing filters out noise signals through AI algorithms to improve the accuracy of data reception. The high-frequency band has a wider bandwidth, can support higher data transmission rates, and has relatively fewer interference sources compared to the low-frequency band (such as 433 MHz). Frequency hopping pseudo-randomly switches the carrier frequency in a preset frequency table, avoiding the fixed frequency bands of devices such as Wi-Fi / Bluetooth, and reducing the collision probability. The redundant communication mechanism includes: Time redundancy: Key data is retransmitted multiple times, combined with CRC check and ACK confirmation mechanism to ensure that the receiving end receives correctly at least once. Spatial redundancy: Deploy multiple receivers (such as at the four corners of the vehicle body), and improve fault tolerance through multi-path signal fusion. Dynamic redundancy strategy: Dynamically adjust the redundancy according to the channel quality (such as RSSI, bit error rate) to balance reliability and power consumption. The AI-driven noise filtering algorithm includes: Environmental noise: Signal distortion caused by vehicle vibration and temperature change. Cross-interference: Co-channel interference from other wireless devices (such as vehicle-mounted radar). Signal processing uses a convolutional neural network (CNN) in the AI algorithm to classify the time-frequency domain signal features (such as spectrogram) to distinguish valid signals from noise. In order to maximize the safety of tire pressure monitoring, the tire pressure signal is converted into an electrical signal recognizable by the MCU and communicated through the Modbus protocol, enabling the vehicle body MCU to predict in advance that the tire has a fault or is about to have a fault.

[0025] Embodiment 7 As a preferred embodiment of the present invention: In the warning module, the warning and diagnosis combine the vehicle load, driving speed, and environmental temperature to provide dynamic tire pressure suggestions, and push detailed alarm information through the mobile phone APP, and attach treatment suggestions. Combining the vehicle load, driving speed, and environmental temperature, judge the tire pressure status: normal, low pressure, high pressure, rapid air leakage (such as the pressure change rate exceeds the threshold), and detect sensor faults. For example, a sudden drop in tire pressure (>0.2 bar / minute) may indicate a flat tire and trigger an immediate alarm. High temperature causes the tire pressure to rise, and the algorithm needs to correct the threshold in combination with temperature data (such as for every 10°C increase, the tire pressure increases by about 0.1 bar). Detect the tire rotation difference through the ABS wheel speed sensor, and a higher sensitivity algorithm is required to identify small changes. After detecting an abnormality in the tire, Primary alarm: The dashboard icon lights up to indicate abnormal tire pressure. Advanced alarm: Specifically display the position and value of the faulty tire, accompanied by a sound prompt. Remote notification: Send to the mobile phone APP through the vehicle network, and attach treatment suggestions based on AI.

[0026] Embodiment 8 As a preferred embodiment of the present invention: In the warning module, data fusion integrates tire pressure, temperature, and acceleration data to monitor the dynamic balance state or abnormal wear of the tire, and early warning of potential risks. The warning module of the Tire Pressure Monitoring System (TPMS) monitors the health status of tires through multi-sensor data fusion technology (tire pressure, temperature, acceleration). Through multi-source data acquisition and preprocessing, feature engineering and spatio-temporal alignment, dynamic balance anomaly detection model, wear state prediction algorithm, multi-modal data fusion architecture, adaptive warning strategy, and edge computing optimization, it upgrades traditional threshold detection to data-driven prediction based on physical models, which can reduce the false alarm rate to 0.8% per thousand kilometers. At the same time, it can give early warnings of potential tire burst risks 15 - 30 minutes in advance, which is beneficial to reducing risks caused by tires, plays a key role in detecting the tire pressure, tire temperature, etc., reduces the later maintenance cost, increases the service life, and improves the driving safety.

[0027] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced by the present invention. Any reference signs in the claims should not be regarded as limiting the claimed rights.

Claims

1. TPMS full - range automatic adaptation device, characterized in that: Including: Tire data acquisition module: including pressure monitoring, temperature monitoring, wear monitoring, load monitoring and dynamic data monitoring; Sensor monitoring module: the module includes a pressure sensor, a temperature sensor, an accelerometer, a wear sensor and a wireless tag; Data processing module: used for data parsing, verification, signal filtering and smoothing, temperature compensation and calibration, data storage, and also includes communication protocol and signal processing; Early warning module: including early warning and diagnosis and data fusion.

2. The TPMS all-round automatic adaptation device according to claim 1, wherein: The hardware composition of the tire data acquisition module includes sensors and a data acquisition unit, and the software algorithm content includes real-time data processing, data filtering, feature extraction and fault diagnosis.

3. The TPMS all-round automatic adaptation device according to claim 1, characterized in that: The pressure monitoring is to detect the internal air pressure of the tire in real time to prevent tire blowout or insufficient tire pressure. The temperature monitoring senses the working temperature of the tire to avoid rubber aging or failure caused by overheating. The wear monitoring analyzes the tread wear degree through vibration or optical sensors. The load monitoring estimates the bearing weight of the tire to optimize the vehicle balance. The dynamic data: collects driving dynamic parameters such as acceleration, rotation speed, and slip ratio.

4. The TPMS all-round automatic adaptation device according to claim 2, characterized in that: The data acquisition unit includes a signal conditioning circuit, analog-to-digital conversion, a microcontroller and a wireless transmission module.

5. The TPMS all-round automatic adaptation device according to claim 1, characterized in that: In the sensor monitoring module, the sensor group selects a suitable model according to the vehicle model, and the sensor group is divided into two categories, left and right, which are respectively adapted to the left and right front wheels.

6. The TPMS all-round automatic adaptation device according to claim 1, characterized in that: In the data processing module, the data parsing receives wireless signals from sensors, including RF and BLE, and parses the frame structure of the data packet, including ID, tire pressure, temperature, battery voltage, check bits, etc. The data verification uses CRC verification or parity check to verify the data integrity, discards invalid data packets and filters outliers. The signal filtering and smoothing suppresses environmental noise. The temperature compensation and calibration corrects the tire pressure value according to the temperature sensor data, compensates for the non-linear error based on the calibration table (Lookup Table). The data storage can cache recent data for trend analysis and store fault logs.

7. The TPMS all-round automatic adaptation device according to claim 1, characterized in that: In the data processing module, based on an anti-interference communication protocol, high-frequency band or frequency hopping technology is adopted to reduce signal conflicts with other wireless devices, and a redundant communication mechanism is introduced to ensure stable data transmission. The signal processing filters noise signals through AI algorithms to improve the accuracy of data reception.

8. The TPMS all-round automatic adaptation device according to claim 1, characterized in that: In the early warning module, the early warning and diagnosis combines vehicle load, driving speed and environmental temperature to provide dynamic tire pressure suggestions, and pushes detailed alarm information through the mobile phone APP, and attaches processing suggestions.

9. The TPMS all-round automatic adaptation device according to claim 1, characterized in that: In the early warning module, the data fusion integrates tire pressure, temperature, and acceleration data to monitor the dynamic balance state or abnormal wear of the tire, and early warns of potential risks.

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