CN112918198A - TPMS tire detection system and method - Google Patents
TPMS tire detection system and method Download PDFInfo
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- CN112918198A CN112918198A CN202110313688.9A CN202110313688A CN112918198A CN 112918198 A CN112918198 A CN 112918198A CN 202110313688 A CN202110313688 A CN 202110313688A CN 112918198 A CN112918198 A CN 112918198A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60C—VEHICLE TYRES; TYRE INFLATION; TYRE CHANGING; CONNECTING VALVES TO INFLATABLE ELASTIC BODIES IN GENERAL; DEVICES OR ARRANGEMENTS RELATED TO TYRES
- B60C23/00—Devices for measuring, signalling, controlling, or distributing tyre pressure or temperature, specially adapted for mounting on vehicles; Arrangement of tyre inflating devices on vehicles, e.g. of pumps or of tanks; Tyre cooling arrangements
- B60C23/02—Signalling devices actuated by tyre pressure
- B60C23/04—Signalling devices actuated by tyre pressure mounted on the wheel or tyre
- B60C23/0408—Signalling devices actuated by tyre pressure mounted on the wheel or tyre transmitting the signals by non-mechanical means from the wheel or tyre to a vehicle body mounted receiver
- B60C23/0479—Communicating with external units being not part of the vehicle, e.g. tools for diagnostic, mobile phones, electronic keys or service stations
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60C—VEHICLE TYRES; TYRE INFLATION; TYRE CHANGING; CONNECTING VALVES TO INFLATABLE ELASTIC BODIES IN GENERAL; DEVICES OR ARRANGEMENTS RELATED TO TYRES
- B60C23/00—Devices for measuring, signalling, controlling, or distributing tyre pressure or temperature, specially adapted for mounting on vehicles; Arrangement of tyre inflating devices on vehicles, e.g. of pumps or of tanks; Tyre cooling arrangements
- B60C23/02—Signalling devices actuated by tyre pressure
- B60C23/04—Signalling devices actuated by tyre pressure mounted on the wheel or tyre
- B60C23/0486—Signalling devices actuated by tyre pressure mounted on the wheel or tyre comprising additional sensors in the wheel or tyre mounted monitoring device, e.g. movement sensors, microphones or earth magnetic field sensors
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60C—VEHICLE TYRES; TYRE INFLATION; TYRE CHANGING; CONNECTING VALVES TO INFLATABLE ELASTIC BODIES IN GENERAL; DEVICES OR ARRANGEMENTS RELATED TO TYRES
- B60C23/00—Devices for measuring, signalling, controlling, or distributing tyre pressure or temperature, specially adapted for mounting on vehicles; Arrangement of tyre inflating devices on vehicles, e.g. of pumps or of tanks; Tyre cooling arrangements
- B60C23/02—Signalling devices actuated by tyre pressure
- B60C23/04—Signalling devices actuated by tyre pressure mounted on the wheel or tyre
- B60C23/0486—Signalling devices actuated by tyre pressure mounted on the wheel or tyre comprising additional sensors in the wheel or tyre mounted monitoring device, e.g. movement sensors, microphones or earth magnetic field sensors
- B60C23/0488—Movement sensor, e.g. for sensing angular speed, acceleration or centripetal force
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Abstract
The invention discloses a TPMS tire detection system and a TPMS tire detection method, relates to the technical field of tire detection, and solves the technical problem that the tire pressure monitoring accuracy is reduced due to the fact that fluctuation faults of tire pressure cannot be accurately detected in the prior art; after receiving the tire pressure monitoring coefficient, the intelligent control platform acquires a tire pressure monitoring coefficient difference Xi in the detection time period of the detected vehicle through a formula, and then acquires a discrete coefficient Wi of the tire pressure monitoring coefficient difference in the detection time period of the detected vehicle through the formula; the tire is detected, tire faults are divided into tire pressure faults and tire pressure fluctuation faults, the accuracy of tire pressure detection is improved, the use quality of a vehicle owner is improved, and the risk of accidents is reduced.
Description
Technical Field
The invention relates to the technical field of tire detection, in particular to a TPMS tire detection system and a TPMS tire detection method.
Background
The TPMS is used for automatically monitoring the air pressure of the tire in real time in the running process of the automobile and giving an alarm on the air leakage and the low air pressure of the tire so as to ensure the running safety. As an important component of an automobile, a main consideration of tire performance is the air pressure of the tire, and the low or high air pressure of the tire affects the use performance of the tire and reduces the service life of the tire, and ultimately affects the driving safety.
However, in the related art, the fluctuation failure of the tire pressure cannot be accurately detected, resulting in a decrease in tire pressure monitoring accuracy.
Disclosure of Invention
The invention aims to provide a TPMS tire detection system and a TPMS tire detection method, wherein a tire detection unit is used for analyzing vehicle information so as to detect a vehicle tire, a tire pressure detection coefficient TIO of a detected vehicle is obtained through a formula, and then the tire pressure detection coefficient TIO of the detected vehicle is sent to an intelligent control platform; after receiving the tire pressure monitoring coefficient, the intelligent control platform acquires a tire pressure monitoring coefficient difference Xi in the detection time period of the detected vehicle through a formula, and then acquires a discrete coefficient Wi of the tire pressure monitoring coefficient difference Wi in the detection time period of the detected vehicle through the formula, wherein Xi and Wi are in one-to-one correspondence; the obtained tire pressure monitoring coefficient difference Xi and the corresponding discrete coefficient Wi are respectively and correspondingly compared with the tire pressure monitoring coefficient difference threshold value X1 and the discrete coefficient threshold value W1, the tire is detected, and the tire faults are divided into tire pressure faults and tire pressure fluctuation faults, so that the accuracy of tire pressure detection is improved, the use quality of a vehicle owner is improved, and the risk of accidents is reduced.
The purpose of the invention can be realized by the following technical scheme:
a TPMS tire detection system comprises a registration login unit, a database, an intelligent management and control platform, a tire detection unit, a road selection unit, an environment detection unit and a replacement prediction unit;
the tire detection unit is used for analyzing vehicle information so as to detect the vehicle tire, the vehicle information comprises rotation speed data, flow speed data and ratio data, the rotation speed data is the rotation speed of the detected vehicle tire, the flow speed data is the air flow speed around the valve of the detected vehicle tire, the ratio data is the ratio of the self weight of the detected vehicle to the radius of the tire, the detected vehicle is marked as i, i is 1, 2, … …, n and n are positive integers, the detection time period is marked as o, o is 1, 2, … …, m and m are positive integers, and the specific analysis and detection process is as follows:
step S1: acquiring the rotating speed of a detected vehicle tire in a detection time period, and marking the rotating speed of the detected vehicle tire as ZVio;
step S2: acquiring the air flow speed around the valve of the tire of the detected vehicle in the detection time period, and marking the air flow speed around the valve of the detected vehicle as LVio;
step S3: acquiring the ratio of the self weight of the detected vehicle to the radius of the tire in the detection time period, and marking the ratio of the self weight of the detected vehicle to the radius of the tire as BZio;
step S4: by the formula
Acquiring a tire pressure detection coefficient TIO of a detected vehicle, wherein a1, a2 and a3 are proportional coefficients, and a1 is greater than a2 is greater than a3 is greater than 0; then sending the tire pressure detection coefficient TYio of the detected vehicle to an intelligent management and control platform;
after the intelligent control platform receives the tire pressure monitoring coefficient, the intelligent control platform passes through a formula
Acquiring a tire pressure monitoring coefficient difference Xi in a detection time period of a detected vehicle, wherein TY1 is a tire pressure monitoring coefficient threshold value, and then passing through a formula
Acquiring discrete coefficients Wi of tire pressure monitoring coefficient differences in a detection time period of a detected vehicle, wherein Xi and Wi are in one-to-one correspondence; the obtained tire pressure monitoring coefficient difference Xi and the corresponding discrete coefficient Wi are correspondingly compared with a tire pressure monitoring coefficient difference threshold value X1 and a discrete coefficient threshold value W1 respectively, if the tire pressure monitoring coefficient difference Xi is not more than the tire pressure monitoring coefficient difference threshold value X1, and the corresponding discrete coefficient Wi is not more than the discrete coefficient threshold value W1, the tire pressure of the detected vehicle is judged to be normal and stable, an environment detection signal is generated, and the environment detection signal is sent to an environment detection unit; if the tire pressure monitoring coefficient difference Xi is larger than the tire pressure monitoring coefficient difference threshold value X1, and the corresponding discrete coefficient Wi is smaller than or equal to the discrete coefficient threshold value W1, and the tire pressure monitoring coefficient differenceXi is greater than a tire pressure monitoring coefficient difference threshold value X1, and a corresponding discrete coefficient Wi is greater than a discrete coefficient threshold value W1, the tire pressure of the detected vehicle is judged to be abnormal, a danger signal is generated, and the danger signal is sent to a road selection unit; if the tire pressure monitoring coefficient difference Xi is less than or equal to a tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is greater than a discrete coefficient threshold value W1, judging that the tire pressure of the detected vehicle fluctuates, generating an early warning signal and sending the early warning signal to a mobile phone terminal of a vehicle owner;
the environment detecting unit receives the environment detection signal, and then analyzes the surrounding environment information of the detected vehicle, so as to detect the environment of the detected vehicle, wherein the surrounding environment information of the detected vehicle comprises temperature data, wading data and humidity data, the temperature data is the difference value between the temperature inside the tire of the detected vehicle and the surrounding environment temperature, the wading data is the frequency of wading of the tire in the driving process of the detected vehicle, the humidity data is the average humidity of the surrounding environment of the tire when the detected vehicle is parked, and the specific analysis and detection process is as follows:
step SS 1: acquiring a difference value between the temperature inside the tire of the detected vehicle and the ambient temperature, and marking the difference value between the temperature inside the tire of the detected vehicle and the ambient temperature as Ci;
step SS 2: acquiring the frequency of wading of a tire in the running process of the vehicle, and marking the frequency of wading of the tire in the running process of the vehicle as Pi;
step SS 3: acquiring the average humidity of the tire surrounding environment when the detected vehicle is parked, and marking the average humidity of the tire surrounding environment when the detected vehicle is parked as Si;
step SS 4: by the formula
Acquiring an environment detection coefficient HJi of a detected vehicle, wherein c1, c2 and c3 are proportional coefficients, c1 is more than c2 is more than c3 is more than 0, beta is an error correction factor, and the value is 2.0321522;
step SS 4: the environment detection coefficient HJi of the detected vehicle is compared to an environment detection coefficient threshold:
if the environment detection coefficient HJi of the detected vehicle is larger than or equal to the environment detection coefficient threshold value, judging that the surrounding environment of the detected vehicle is abnormal, generating an environment abnormal signal and sending the environment abnormal signal to the mobile phone terminal of the vehicle owner;
if the environment detection coefficient HJi of the detected vehicle is less than the environment detection coefficient threshold value, the surrounding environment of the detected vehicle is judged to be normal, an environment normal signal is generated, and the environment normal signal is sent to the mobile phone terminal of the vehicle owner.
Further, after receiving the danger signal, the road selection unit reasonably plans a driving route for the detected vehicle, and the specific planning process is as follows:
step Y1: acquiring the current position of a detection vehicle, acquiring the positions of peripheral maintenance stations by taking the current position of the detection vehicle as a center, and then acquiring a driving route of the detection vehicle and the maintenance stations, wherein m is 1, 2, … …, k is a positive integer;
step Y2: acquiring the driving distance between the detected vehicle and the driving route of the maintenance station, and marking the driving distance between the detected vehicle and the driving route of the maintenance station as XSm;
step Y3: acquiring the number of traffic lights on the driving route of the detection vehicle and the maintenance station, and marking the number of the traffic lights on the driving route of the detection vehicle and the maintenance station as SLm;
step Y4: acquiring the average speed of the detected vehicle and the vehicle on the driving route of the maintenance station, and marking the average speed of the detected vehicle and the vehicle on the driving route of the maintenance station as CSm;
step Y5: by the formula
Acquiring a selection coefficient GHm of a driving route, wherein s1, s2 and s3 are proportional coefficients, s1 is more than s2 is more than s3 is more than 0, and e is a natural constant;
step Y6: the selection factor GHm for the travel route is compared to a selection factor threshold for the travel route:
if the selection coefficient GHm of the driving route is larger than or equal to the selection coefficient threshold of the driving route, determining that the driving route is unqualified, generating a route exclusion signal and marking the corresponding route as an unrevealed route;
if the selection coefficient GHm of the driving route is less than the selection coefficient threshold of the driving route, the driving route is judged to be qualified, then the corresponding driving route is marked as the qualified route, the qualified routes are sorted according to the sequence of the selection coefficients of the driving routes from small to large, the route with the first ranking is marked as the selected route, and the route with the second ranking is marked as the alternative route.
Further, the replacement prediction unit is used for analyzing the tire operation data of the detection vehicle so as to predict the tire replacement of the detection vehicle, the tire operation data of the detection vehicle comprises the average usage time and frequency of the detection vehicle tire per day and the number of times of tire pressure alarm of the detection vehicle tire in the whole month, and the specific analysis and detection processes are as follows:
step YY 1: acquiring the average usage time per day of a detected vehicle tire, and marking the average usage time per day of the detected vehicle tire as SYSi;
step YY 2: acquiring the average daily use frequency of the detected vehicle tires, and marking the average daily use frequency of the detected vehicle tires as SPLi;
step YY 3: acquiring the frequency of tire pressure alarm of the detected vehicle tire in the whole month, and marking the frequency of tire pressure alarm of the detected vehicle tire in the whole month as CTYi;
step YY 4: by the formula
Acquiring a replacement prediction coefficient YCi of a detected vehicle tire, wherein v1, v2 and v3 are proportional coefficients, and v1 is more than v2 is more than v3 is more than 0;
step YY 5: the replacement prediction coefficient YCi of the detected vehicle tire is compared to a replacement prediction coefficient threshold:
if the replacement prediction coefficient YCi of the detected vehicle tire is not less than the replacement prediction coefficient threshold, judging that the detected tire replacement prediction coefficient is high, generating a predicted replacement signal and sending the predicted replacement signal to the mobile phone terminal of the vehicle owner;
if the replacement prediction coefficient YCi of the detected vehicle tire is less than the replacement prediction coefficient threshold value, the tire replacement prediction coefficient is judged to be low, a prediction normal use signal is generated, and the prediction normal use signal is sent to the mobile phone terminal of the vehicle owner.
Further, the registration login unit is used for the owner and the manager to submit owner information and manager information for registration through the mobile phone terminal, and send the owner information and the manager information which are successfully registered to the database for storage, wherein the owner information comprises the name and the driving age of the owner and the mobile phone number of the real name authentication of the owner, and the manager information comprises the name and the age of the manager, the time of entry and the mobile phone number of the real name authentication of the manager.
A TPMS tire detection method comprises the following specific steps:
the method comprises the steps that firstly, a tire of a vehicle is detected through a tire detection unit, then a tire pressure detection coefficient TIO of the detected vehicle is obtained through a formula, and the tire pressure detection coefficient TIO of the detected vehicle is sent to an intelligent management and control platform;
step two, after receiving the tire pressure monitoring coefficient, the intelligent control platform obtains a tire pressure monitoring coefficient difference Xi in a detection time period of the detected vehicle and a discrete coefficient Wi of the tire pressure monitoring coefficient difference in the detection time period of the detected vehicle through a formula, then compares the tire pressure monitoring coefficient difference Xi and the discrete coefficient Wi with corresponding threshold values respectively, generates an environment monitoring signal and enters step three if the tire pressure monitoring coefficient difference Xi is not less than the tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is not less than the discrete coefficient threshold value W1, generates a danger signal if the tire pressure monitoring coefficient difference Xi is greater than the tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is not less than the discrete coefficient threshold value W1 and the tire pressure monitoring coefficient difference Xi is greater than the tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is greater than the discrete coefficient threshold value W1, and enters step four;
after receiving the environment detection signal through the environment detection unit, analyzing the surrounding environment information of the detected vehicle, obtaining an environment detection coefficient HJi of the detected vehicle through a formula, and then comparing an environment detection coefficient HJi of the detected vehicle with an environment detection coefficient threshold;
and step four, after receiving the danger signal, the road selection unit reasonably plans a driving route for the detected vehicle, obtains a selection coefficient GHm of the driving route through a formula, and then compares the selection coefficient GHm of the driving route with a selection coefficient threshold of the driving route.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the vehicle information is analyzed through the tire detection unit so as to detect the vehicle tire, the tire pressure detection coefficient TIO of the detected vehicle is obtained through a formula, and then the tire pressure detection coefficient TIO of the detected vehicle is sent to the intelligent management and control platform; after receiving the tire pressure monitoring coefficient, the intelligent control platform acquires a tire pressure monitoring coefficient difference Xi in the detection time period of the detected vehicle through a formula, and then acquires a discrete coefficient Wi of the tire pressure monitoring coefficient difference Wi in the detection time period of the detected vehicle through the formula, wherein Xi and Wi are in one-to-one correspondence; the obtained tire pressure monitoring coefficient difference Xi and the corresponding discrete coefficient Wi are respectively and correspondingly compared with the tire pressure monitoring coefficient difference threshold value X1 and the discrete coefficient threshold value W1, the tire is detected, and the tire faults are divided into tire pressure faults and tire pressure fluctuation faults, so that the accuracy of tire pressure detection is improved, the use quality of a vehicle owner is improved, and the risk of accidents is reduced.
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In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a TPMS tire detection system includes a registration unit, a database, an intelligent management and control platform, a tire detection unit, a road selection unit, an environment detection unit, and a replacement prediction unit;
the registration login unit is used for submitting owner information and manager information for registration by a vehicle owner and a manager through a mobile phone terminal, and sending the owner information and the manager information which are successfully registered to a database for storage, wherein the owner information comprises the name and the driving age of a vehicle owner and the mobile phone number of real name authentication of a person, and the manager information comprises the name, the age, the time of entry and the mobile phone number of real name authentication of the person;
the tire detection unit is used for analyzing vehicle information so as to detect the vehicle tire, the vehicle information comprises rotation speed data, flow speed data and ratio data, the rotation speed data is the rotation speed of the detected vehicle tire, the flow speed data is the air flow speed around the valve of the detected vehicle tire, the ratio data is the ratio of the self weight of the detected vehicle to the radius of the tire, the detected vehicle is marked as i, i is 1, 2, … …, n and n are positive integers, the detection time period is marked as o, o is 1, 2, … …, m and m are positive integers, and the specific analysis and detection process is as follows:
step S1: acquiring the rotating speed of a detected vehicle tire in a detection time period, and marking the rotating speed of the detected vehicle tire as ZVio;
step S2: acquiring the air flow speed around the valve of the tire of the detected vehicle in the detection time period, and marking the air flow speed around the valve of the detected vehicle as LVio;
step S3: acquiring the ratio of the self weight of the detected vehicle to the radius of the tire in the detection time period, and marking the ratio of the self weight of the detected vehicle to the radius of the tire as BZio;
step S4: by the formula
Acquiring a tire pressure detection coefficient TIO of a detected vehicle, wherein a1, a2 and a3 are proportional coefficients, and a1 is greater than a2 is greater than a3 is greater than 0; followed byThen sending the tire pressure detection coefficient TIO of the detected vehicle to an intelligent management and control platform;
after the intelligent control platform receives the tire pressure monitoring coefficient, the intelligent control platform passes through a formula
Acquiring a tire pressure monitoring coefficient difference Xi in a detection time period of a detected vehicle, wherein TY1 is a tire pressure monitoring coefficient threshold value, and then passing through a formula
Acquiring discrete coefficients Wi of tire pressure monitoring coefficient differences in a detection time period of a detected vehicle, wherein Xi and Wi are in one-to-one correspondence; the obtained tire pressure monitoring coefficient difference Xi and the corresponding discrete coefficient Wi are correspondingly compared with a tire pressure monitoring coefficient difference threshold value X1 and a discrete coefficient threshold value W1 respectively, if the tire pressure monitoring coefficient difference Xi is not more than the tire pressure monitoring coefficient difference threshold value X1, and the corresponding discrete coefficient Wi is not more than the discrete coefficient threshold value W1, the tire pressure of the detected vehicle is judged to be normal and stable, an environment detection signal is generated, and the environment detection signal is sent to an environment detection unit; if the tire pressure monitoring coefficient difference Xi is larger than the tire pressure monitoring coefficient difference threshold value X1, the corresponding discrete coefficient Wi is smaller than or equal to the discrete coefficient threshold value W1, the tire pressure monitoring coefficient difference Xi is larger than the tire pressure monitoring coefficient difference threshold value X1, and the corresponding discrete coefficient Wi is larger than the discrete coefficient threshold value W1, judging that the tire pressure of the detected vehicle is abnormal, generating a dangerous signal and sending the dangerous signal to a road selection unit; if the tire pressure monitoring coefficient difference Xi is less than or equal to a tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is greater than a discrete coefficient threshold value W1, judging that the tire pressure of the detected vehicle fluctuates, generating an early warning signal and sending the early warning signal to a mobile phone terminal of a vehicle owner;
the environment detecting unit receives the environment detection signal, and then analyzes the surrounding environment information of the detected vehicle, so as to detect the environment of the detected vehicle, wherein the surrounding environment information of the detected vehicle comprises temperature data, wading data and humidity data, the temperature data is the difference value between the temperature inside the tire of the detected vehicle and the surrounding environment temperature, the wading data is the frequency of wading of the tire in the driving process of the detected vehicle, the humidity data is the average humidity of the surrounding environment of the tire when the detected vehicle is parked, and the specific analysis and detection process is as follows:
step SS 1: acquiring a difference value between the temperature inside the tire of the detected vehicle and the ambient temperature, and marking the difference value between the temperature inside the tire of the detected vehicle and the ambient temperature as Ci;
step SS 2: acquiring the frequency of wading of a tire in the running process of the vehicle, and marking the frequency of wading of the tire in the running process of the vehicle as Pi;
step SS 3: acquiring the average humidity of the tire surrounding environment when the detected vehicle is parked, and marking the average humidity of the tire surrounding environment when the detected vehicle is parked as Si;
step SS 4: by the formula
Acquiring an environment detection coefficient HJi of a detected vehicle, wherein c1, c2 and c3 are proportional coefficients, c1 is more than c2 is more than c3 is more than 0, beta is an error correction factor, and the value is 2.0321522;
step SS 4: the environment detection coefficient HJi of the detected vehicle is compared to an environment detection coefficient threshold:
if the environment detection coefficient HJi of the detected vehicle is larger than or equal to the environment detection coefficient threshold value, judging that the surrounding environment of the detected vehicle is abnormal, generating an environment abnormal signal and sending the environment abnormal signal to the mobile phone terminal of the vehicle owner;
if the environment detection coefficient HJi of the detected vehicle is smaller than the environment detection coefficient threshold value, judging that the surrounding environment of the detected vehicle is normal, generating an environment normal signal and sending the environment normal signal to the mobile phone terminal of the vehicle owner;
after receiving the danger signal, the road selection unit reasonably plans a driving route for the detected vehicle, and the specific planning process is as follows:
step Y1: acquiring the current position of a detection vehicle, acquiring the positions of peripheral maintenance stations by taking the current position of the detection vehicle as a center, and then acquiring a driving route of the detection vehicle and the maintenance stations, wherein m is 1, 2, … …, k is a positive integer;
step Y2: acquiring the driving distance between the detected vehicle and the driving route of the maintenance station, and marking the driving distance between the detected vehicle and the driving route of the maintenance station as XSm;
step Y3: acquiring the number of traffic lights on the driving route of the detection vehicle and the maintenance station, and marking the number of the traffic lights on the driving route of the detection vehicle and the maintenance station as SLm;
step Y4: acquiring the average speed of the detected vehicle and the vehicle on the driving route of the maintenance station, and marking the average speed of the detected vehicle and the vehicle on the driving route of the maintenance station as CSm;
step Y5: by the formula
Acquiring a selection coefficient GHm of a driving route, wherein s1, s2 and s3 are proportional coefficients, s1 is more than s2 is more than s3 is more than 0, and e is a natural constant;
step Y6: the selection factor GHm for the travel route is compared to a selection factor threshold for the travel route:
if the selection coefficient GHm of the driving route is larger than or equal to the selection coefficient threshold of the driving route, determining that the driving route is unqualified, generating a route exclusion signal and marking the corresponding route as an unrevealed route;
if the selection coefficient GHm of the driving route is less than the selection coefficient threshold of the driving route, judging that the driving route is qualified, then marking the corresponding driving route as the qualified route, sequencing the qualified routes according to the sequence of the selection coefficients of the driving routes from small to large, marking the route with the first ranking as the selected route, and marking the route with the second ranking as the alternative route;
the replacement prediction unit is used for analyzing the tire operation data of the detection vehicle so as to predict the tire replacement of the detection vehicle, the tire operation data of the detection vehicle comprises the average usage time and frequency of the detection vehicle tire each day and the number of times of tire pressure alarm of the detection vehicle tire in the whole month, and the specific analysis and detection processes are as follows:
step YY 1: acquiring the average usage time per day of a detected vehicle tire, and marking the average usage time per day of the detected vehicle tire as SYSi;
step YY 2: acquiring the average daily use frequency of the detected vehicle tires, and marking the average daily use frequency of the detected vehicle tires as SPLi;
step YY 3: acquiring the frequency of tire pressure alarm of the detected vehicle tire in the whole month, and marking the frequency of tire pressure alarm of the detected vehicle tire in the whole month as CTYi;
step YY 4: by the formula
Acquiring a replacement prediction coefficient YCi of a detected vehicle tire, wherein v1, v2 and v3 are proportional coefficients, and v1 is more than v2 is more than v3 is more than 0;
step YY 5: the replacement prediction coefficient YCi of the detected vehicle tire is compared to a replacement prediction coefficient threshold:
if the replacement prediction coefficient YCi of the detected vehicle tire is not less than the replacement prediction coefficient threshold, judging that the detected tire replacement prediction coefficient is high, generating a predicted replacement signal and sending the predicted replacement signal to the mobile phone terminal of the vehicle owner;
if the replacement prediction coefficient YCi of the detected vehicle tire is smaller than the replacement prediction coefficient threshold value, judging that the replacement prediction coefficient of the detected vehicle tire is low, generating a predicted normal use signal and sending the predicted normal use signal to a mobile phone terminal of a vehicle owner;
a TPMS tire detection method comprises the following specific steps:
the method comprises the steps that firstly, a tire of a vehicle is detected through a tire detection unit, then a tire pressure detection coefficient TIO of the detected vehicle is obtained through a formula, and the tire pressure detection coefficient TIO of the detected vehicle is sent to an intelligent management and control platform;
step two, after receiving the tire pressure monitoring coefficient, the intelligent control platform obtains a tire pressure monitoring coefficient difference Xi in a detection time period of the detected vehicle and a discrete coefficient Wi of the tire pressure monitoring coefficient difference in the detection time period of the detected vehicle through a formula, then compares the tire pressure monitoring coefficient difference Xi and the discrete coefficient Wi with corresponding threshold values respectively, generates an environment monitoring signal and enters step three if the tire pressure monitoring coefficient difference Xi is not less than the tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is not less than the discrete coefficient threshold value W1, generates a danger signal if the tire pressure monitoring coefficient difference Xi is greater than the tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is not less than the discrete coefficient threshold value W1 and the tire pressure monitoring coefficient difference Xi is greater than the tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is greater than the discrete coefficient threshold value W1, and enters step four;
after receiving the environment detection signal through the environment detection unit, analyzing the surrounding environment information of the detected vehicle, obtaining an environment detection coefficient HJi of the detected vehicle through a formula, and then comparing an environment detection coefficient HJi of the detected vehicle with an environment detection coefficient threshold;
and step four, after receiving the danger signal, the road selection unit reasonably plans a driving route for the detected vehicle, obtains a selection coefficient GHm of the driving route through a formula, and then compares the selection coefficient GHm of the driving route with a selection coefficient threshold of the driving route.
The working principle of the invention is as follows:
when the TPMS tire detection system and the TPMS tire detection method work, a tire detection unit is used for detecting a vehicle tire, then a tire pressure detection coefficient TYio of a detected vehicle is obtained through a formula, and the tire pressure detection coefficient TYio is sent to an intelligent management and control platform; after receiving the tire pressure monitoring coefficient, the intelligent control platform acquires a tire pressure monitoring coefficient difference Xi in a detection time period of a detected vehicle and a discrete coefficient Wi of the tire pressure monitoring coefficient difference in the detection time period of the detected vehicle through a formula, then compares the tire pressure monitoring coefficient difference Xi and the discrete coefficient Wi with corresponding threshold values respectively, analyzes the peripheral environment information of the detected vehicle after receiving an environment detection signal through an environment detection unit, acquires an environment detection coefficient HJi of the detected vehicle through the formula, and then compares the environment detection coefficient HJi of the detected vehicle with the environment detection coefficient threshold value; after receiving the danger signal, the road selection unit reasonably plans a driving route for the detected vehicle, obtains a selection coefficient GHm of the driving route through a formula, and then compares the selection coefficient GHm of the driving route with a selection coefficient threshold of the driving route.
The above formulas are all calculated by taking the numerical value of the dimension, the formula is a formula which obtains the latest real situation by acquiring a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. A TPMS tire detection system is characterized by comprising a registration login unit, a database, an intelligent management and control platform, a tire detection unit, a road selection unit, an environment detection unit and a replacement prediction unit;
the tire detection unit is used for analyzing vehicle information so as to detect the vehicle tire, the vehicle information comprises rotation speed data, flow speed data and ratio data, the rotation speed data is the rotation speed of the detected vehicle tire, the flow speed data is the air flow speed around the valve of the detected vehicle tire, the ratio data is the ratio of the self weight of the detected vehicle to the radius of the tire, the detected vehicle is marked as i, i is 1, 2, … …, n and n are positive integers, the detection time period is marked as o, o is 1, 2, … …, m and m are positive integers, and the specific analysis and detection process is as follows:
step S1: acquiring the rotating speed of a detected vehicle tire in a detection time period, and marking the rotating speed of the detected vehicle tire as ZVio;
step S2: acquiring the air flow speed around the valve of the tire of the detected vehicle in the detection time period, and marking the air flow speed around the valve of the detected vehicle as LVio;
step S3: acquiring the ratio of the self weight of the detected vehicle to the radius of the tire in the detection time period, and marking the ratio of the self weight of the detected vehicle to the radius of the tire as BZio;
step S4: by the formula
Acquiring a tire pressure detection coefficient TIO of a detected vehicle, wherein a1, a2 and a3 are proportional coefficients, and a1 is greater than a2 is greater than a3 is greater than 0; then sending the tire pressure detection coefficient TYio of the detected vehicle to an intelligent management and control platform;
after the intelligent control platform receives the tire pressure monitoring coefficient, the intelligent control platform passes through a formula
Acquiring a tire pressure monitoring coefficient difference Xi in a detection time period of a detected vehicle, wherein TY1 is a tire pressure monitoring coefficient threshold value, and then passing through a formula
Acquiring discrete coefficients Wi of tire pressure monitoring coefficient differences in a detection time period of a detected vehicle, wherein Xi and Wi are in one-to-one correspondence; the obtained tire pressure monitoring coefficient difference Xi and the corresponding discrete coefficient Wi are correspondingly compared with a tire pressure monitoring coefficient difference threshold value X1 and a discrete coefficient threshold value W1 respectively, if the tire pressure monitoring coefficient difference Xi is not more than the tire pressure monitoring coefficient difference threshold value X1, and the corresponding discrete coefficient Wi is not more than the discrete coefficient threshold value W1, the tire pressure of the detected vehicle is judged to be normal and stable, an environment detection signal is generated, and the environment detection signal is sent to an environment detection unit; if the tire pressure monitoring coefficient difference Xi is larger than the tire pressure monitoring coefficient difference threshold value X1, the corresponding discrete coefficient Wi is smaller than or equal to the discrete coefficient threshold value W1, the tire pressure monitoring coefficient difference Xi is larger than the tire pressure monitoring coefficient difference threshold value X1, and the corresponding discrete coefficient Wi is larger than the discrete coefficient threshold value W1, judging that the tire pressure of the detected vehicle is abnormal, generating a dangerous signal and sending the dangerous signal to a road selection unit; if the tire pressure monitoring coefficient difference Xi is less than or equal to a tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is greater than a discrete coefficient threshold value W1, judging that the tire pressure of the detected vehicle fluctuates, generating an early warning signal and sending the early warning signal to a mobile phone terminal of a vehicle owner;
the environment detecting unit receives the environment detection signal, and then analyzes the surrounding environment information of the detected vehicle, so as to detect the environment of the detected vehicle, wherein the surrounding environment information of the detected vehicle comprises temperature data, wading data and humidity data, the temperature data is the difference value between the temperature inside the tire of the detected vehicle and the surrounding environment temperature, the wading data is the frequency of wading of the tire in the driving process of the detected vehicle, the humidity data is the average humidity of the surrounding environment of the tire when the detected vehicle is parked, and the specific analysis and detection process is as follows:
step SS 1: acquiring a difference value between the temperature inside the tire of the detected vehicle and the ambient temperature, and marking the difference value between the temperature inside the tire of the detected vehicle and the ambient temperature as Ci;
step SS 2: acquiring the frequency of wading of a tire in the running process of the vehicle, and marking the frequency of wading of the tire in the running process of the vehicle as Pi;
step SS 3: acquiring the average humidity of the tire surrounding environment when the detected vehicle is parked, and marking the average humidity of the tire surrounding environment when the detected vehicle is parked as Si;
step SS 4: by the formula
Acquiring an environment detection coefficient HJi of a detected vehicle, wherein c1, c2 and c3 are proportional coefficients, c1 is more than c2 is more than c3 is more than 0, beta is an error correction factor, and the value is 2.0321522;
step SS 4: the environment detection coefficient HJi of the detected vehicle is compared to an environment detection coefficient threshold:
if the environment detection coefficient HJi of the detected vehicle is larger than or equal to the environment detection coefficient threshold value, judging that the surrounding environment of the detected vehicle is abnormal, generating an environment abnormal signal and sending the environment abnormal signal to the mobile phone terminal of the vehicle owner;
if the environment detection coefficient HJi of the detected vehicle is less than the environment detection coefficient threshold value, the surrounding environment of the detected vehicle is judged to be normal, an environment normal signal is generated, and the environment normal signal is sent to the mobile phone terminal of the vehicle owner.
2. The TPMS tire testing system of claim 1, wherein the road selection unit reasonably plans the driving route of the tested vehicle after receiving the danger signal, and the planning process is as follows:
step Y1: acquiring the current position of a detection vehicle, acquiring the positions of peripheral maintenance stations by taking the current position of the detection vehicle as a center, and then acquiring a driving route of the detection vehicle and the maintenance stations, wherein m is 1, 2, … …, k is a positive integer;
step Y2: acquiring the driving distance between the detected vehicle and the driving route of the maintenance station, and marking the driving distance between the detected vehicle and the driving route of the maintenance station as XSm;
step Y3: acquiring the number of traffic lights on the driving route of the detection vehicle and the maintenance station, and marking the number of the traffic lights on the driving route of the detection vehicle and the maintenance station as SLm;
step Y4: acquiring the average speed of the detected vehicle and the vehicle on the driving route of the maintenance station, and marking the average speed of the detected vehicle and the vehicle on the driving route of the maintenance station as CSm;
step Y5: by the formula
Acquiring a selection coefficient GHm of a driving route, wherein s1, s2 and s3 are proportional coefficients, s1 is more than s2 is more than s3 is more than 0, and e is a natural constant;
step Y6: the selection factor GHm for the travel route is compared to a selection factor threshold for the travel route:
if the selection coefficient GHm of the driving route is larger than or equal to the selection coefficient threshold of the driving route, determining that the driving route is unqualified, generating a route exclusion signal and marking the corresponding route as an unrevealed route;
if the selection coefficient GHm of the driving route is less than the selection coefficient threshold of the driving route, the driving route is judged to be qualified, then the corresponding driving route is marked as the qualified route, the qualified routes are sorted according to the sequence of the selection coefficients of the driving routes from small to large, the route with the first ranking is marked as the selected route, and the route with the second ranking is marked as the alternative route.
3. The TPMS tire testing system of claim 1, wherein the replacement prediction unit is configured to analyze tire operation data of the test vehicle to predict tire replacement of the test vehicle, the tire operation data of the test vehicle comprises average usage time and frequency of the vehicle tires per day and the number of tire pressure alarms occurring in the vehicle tires throughout the month, and the analysis and detection processes are as follows:
step YY 1: acquiring the average usage time per day of a detected vehicle tire, and marking the average usage time per day of the detected vehicle tire as SYSi;
step YY 2: acquiring the average daily use frequency of the detected vehicle tires, and marking the average daily use frequency of the detected vehicle tires as SPLi;
step YY 3: acquiring the frequency of tire pressure alarm of the detected vehicle tire in the whole month, and marking the frequency of tire pressure alarm of the detected vehicle tire in the whole month as CTYi;
step YY 4: by the formula
Acquiring a replacement prediction coefficient YCi of a detected vehicle tire, wherein v1, v2 and v3 are proportional coefficients, and v1 is more than v2 is more than v3 is more than 0;
step YY 5: the replacement prediction coefficient YCi of the detected vehicle tire is compared to a replacement prediction coefficient threshold:
if the replacement prediction coefficient YCi of the detected vehicle tire is not less than the replacement prediction coefficient threshold, judging that the detected tire replacement prediction coefficient is high, generating a predicted replacement signal and sending the predicted replacement signal to the mobile phone terminal of the vehicle owner;
if the replacement prediction coefficient YCi of the detected vehicle tire is less than the replacement prediction coefficient threshold value, the tire replacement prediction coefficient is judged to be low, a prediction normal use signal is generated, and the prediction normal use signal is sent to the mobile phone terminal of the vehicle owner.
4. The TPMS tire inspection system according to claim 1, wherein the registration login unit is configured to allow the owner and the manager to submit owner information and manager information via the mobile phone terminal for registration, and send the owner information and the manager information that are successfully registered to the database for storage, the owner information includes the name of the owner, the driving age, and the mobile phone number for authenticating the real name of the owner, and the manager information includes the name, the age, the time of entry, and the mobile phone number for authenticating the real name of the manager.
5. A TPMS tire detection method is characterized by comprising the following specific steps:
the method comprises the steps that firstly, a tire of a vehicle is detected through a tire detection unit, then a tire pressure detection coefficient TIO of the detected vehicle is obtained through a formula, and the tire pressure detection coefficient TIO of the detected vehicle is sent to an intelligent management and control platform;
step two, after receiving the tire pressure monitoring coefficient, the intelligent control platform obtains a tire pressure monitoring coefficient difference Xi in a detection time period of the detected vehicle and a discrete coefficient Wi of the tire pressure monitoring coefficient difference in the detection time period of the detected vehicle through a formula, then compares the tire pressure monitoring coefficient difference Xi and the discrete coefficient Wi with corresponding threshold values respectively, generates an environment monitoring signal and enters step three if the tire pressure monitoring coefficient difference Xi is not less than the tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is not less than the discrete coefficient threshold value W1, generates a danger signal if the tire pressure monitoring coefficient difference Xi is greater than the tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is not less than the discrete coefficient threshold value W1 and the tire pressure monitoring coefficient difference Xi is greater than the tire pressure monitoring coefficient difference threshold value X1 and the corresponding discrete coefficient Wi is greater than the discrete coefficient threshold value W1, and enters step four;
after receiving the environment detection signal through the environment detection unit, analyzing the surrounding environment information of the detected vehicle, obtaining an environment detection coefficient HJi of the detected vehicle through a formula, and then comparing an environment detection coefficient HJi of the detected vehicle with an environment detection coefficient threshold;
and step four, after receiving the danger signal, the road selection unit reasonably plans a driving route for the detected vehicle, obtains a selection coefficient GHm of the driving route through a formula, and then compares the selection coefficient GHm of the driving route with a selection coefficient threshold of the driving route.
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