CN115086377B - Engine oil maintenance site prediction method based on big data - Google Patents
Engine oil maintenance site prediction method based on big data Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
- B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
- B60R16/023—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for transmission of signals between vehicle parts or subsystems
- B60R16/0231—Circuits relating to the driving or the functioning of the vehicle
- B60R16/0232—Circuits relating to the driving or the functioning of the vehicle for measuring vehicle parameters and indicating critical, abnormal or dangerous conditions
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3469—Fuel consumption; Energy use; Emission aspects
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Abstract
The invention relates to the technical field of automobile engines and discloses an engine oil maintenance site prediction method based on big data. According to the engine oil maintenance site prediction method based on big data, the engine oil replacement site is predicted based on the operation working condition and the operation condition of the engine, and the health state of a vehicle is accurately estimated.
Description
Technical Field
The invention relates to the technical field of automobile engines, in particular to an engine oil maintenance site prediction method based on big data.
Background
Engine oil plays an important role in long-term and better use of engines, and engine oil has mainly five roles: the first function is lubrication, and in the process of the operation of engine parts, due to the existence of engine oil lubrication, metal friction is reduced, and stable operation of the engine is ensured; the second function is a sealing function, which seals the gap between the piston and the piston ring by using the tightness of engine oil to prevent gas from escaping and maintain power; the third function is a cooling function, and the engine oil can achieve the function of preventing the interior of the engine from overheating by absorbing and releasing heat in the interior of the engine generated by combustion; the fourth function is a cleaning function which keeps the engine clean by absorbing dirt inside the engine generated by combustion; the fifth function is an anti-rust function, and the engine oil can protect the engine from rust and corrosion caused by moisture and acid in the engine.
However, engine oil is lost during use, and the engine oil needs to be replaced regularly in order to ensure that the engine can normally perform daily work. Because the types of engine oil are many, if the engine oil is not qualified, the engine of the vehicle is damaged, and great loss is caused. Therefore, for better customer service, the automobile manufacturer needs to know the place where the engine is changed, and can further confirm that the engine oil change does not cause the vehicle to malfunction. Typically, vehicle-to-4S shop repairs will record oil change time and vehicle mileage, but changing oil elsewhere will not preserve the service record, resulting in the following disadvantages:
1) If the vehicle is not subjected to engine oil maintenance in a 4S shop, an automobile manufacturer cannot grasp the engine oil replacement place of the vehicle, so that a complete engine oil maintenance record cannot be obtained, and further the health state of the vehicle cannot be accurately estimated;
2) If the vehicle is not subjected to engine oil maintenance in a 4S shop, an automobile manufacturer cannot grasp the engine oil replacement place of the vehicle, cannot confirm the quality of engine oil used for the vehicle maintenance, and cannot evaluate whether the vehicle is damaged due to the replacement of engine oil;
3) Automobile manufacturers cannot obtain the engine oil maintenance sites of all vehicles, so that an accurate engine oil storage plan of an after-market cannot be formulated, and the engine oil replacement requirement of the market is effectively met.
The Chinese patent (publication day: 2021, month 08, 31, publication number: CN 113320538A) discloses a maintenance place selection system recommended according to vehicle tracks, relates to the technical field of automobile aftermarket, and solves the problems that the maintenance scheme generated by the existing vehicle maintenance system is only generated according to vehicle information and the arrangement of similar maintenance enterprises, and whether the maintenance enterprises have 'pit customers', 'binding consumption', 'maintenance traps' and the like cannot be identified. The maintenance place selection system recommended according to the vehicle track comprises a vehicle information acquisition unit and a maintenance scheme generation unit, wherein the maintenance scheme generation unit is in network data transmission connection with the vehicle information acquisition unit. The key word comparison module in the network automatic inquiry module inquires the maintenance enterprises in the maintenance scheme through the key word through the 5G module A network, and the data inquired through the key word network is simultaneously displayed on the touch display module, so that a driver can discriminate and reference the maintenance enterprises in the maintenance scheme to determine the maintenance scheme of the subsequent vehicle required maintenance. However, this scheme is to track the vehicle according to the vehicle track, and oil maintenance data is required, and if the vehicle is not subjected to oil maintenance in a 4S shop, the data cannot be obtained.
Chinese patent (publication No. 2008, 03, 26, CN 101149337) discloses a mounting structure of a vehicle oil change time indicator; comprises a light emitting part for making the emitted light irradiate the engine oil, a light receiving part for absorbing the light emitted by the light emitting part and changing the resistance value, and a display part for displaying whether the engine oil is replaced or not or whether the device is abnormal or not through the change of the resistance value. The user can be effectively informed of the engine oil replacement timing with a simple structure. It is also possible to know whether the device is abnormal. The present invention relates to a vehicle oil change time presentation device capable of effectively presenting the time of engine oil change in a high-temperature and high-pressure environment like a vehicle, and a vehicle oil change time presentation device mounting structure. This scheme also cannot acquire data that the vehicle is not subjected to oil maintenance at the 4S shop.
The Chinese patent (publication No. 2015: 04-29; publication No. CN 104568466A) discloses a method for calculating the engine oil replacement time point of a vehicle, which divides the running process of the vehicle into a plurality of time periods, calculates the engine friction equivalent in the corresponding time period according to the actual load and the actual rotating speed of the engine in the corresponding time period, and when the friction equivalent is accumulated to the rated friction total amount of the vehicle, the engine oil replacement time point is the optimal engine oil replacement time point, so that the engine oil replacement time point of the vehicle is a dynamic quantity with great variable quantity, on one hand, the engine oil can reach the longest service life, the current situation that the engine oil is wasted due to the fact that the engine oil is replaced in the service life in the prior art is solved, on the other hand, the service life of the engine is prolonged, and the current situation that the engine wear is increased and the service life is shortened due to the fact that the engine oil is not replaced in time in the prior art is solved. This scheme also cannot acquire data that the vehicle is not subjected to oil maintenance at the 4S shop.
Disclosure of Invention
The invention aims to overcome the defects of the technology, and provides an engine oil maintenance site prediction method based on big data, which predicts an engine oil replacement site based on the running working condition and the running condition of an engine and accurately evaluates the health state of a vehicle.
In order to achieve the above purpose, the engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the received change of engine oil pressure in the running state information.
Preferably, the running state information includes a rotation speed, a torque, an oil temperature, and an oil pressure.
Preferably, the recording of the engine oil replacement point is performed according to the GPS duration and the engine speed, when the GPS duration with the engine speed being 0 is greater than 60min, the location information of the period is recorded, the engine oil pressure information of the driving cycle before and after the period is read, the pressure difference value of the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval is calculated, the pressure difference value of different working condition intervals is obtained, if the pressure difference value of N working condition intervals is greater than the preset pressure difference value, the engine oil replacement is judged to occur in the period, and the location information of the period is recorded as the engine oil replacement location.
Preferably, the working condition intervals are obtained by dividing the working condition of the vehicle into a plurality of working condition intervals according to the rotation speed of the engine, storing the engine oil pressure in each working condition interval in the corresponding working condition interval, and calculating the average value of the working condition intervals once when each driving cycle is finished, wherein the average value is used as the result of the working condition intervals.
Preferably, the driving cycle includes the whole process of vehicle start, vehicle operation and vehicle parking.
Preferably, when the oil pressure data is collected, the calculation frequency is 1Hz, i.e., the result is calculated once per second.
Preferably, the difference in rotational speed between two adjacent said operating ranges is 100rpm.
Preferably, the working condition interval can be divided according to the rotation speed, the vehicle speed, the torque percentage, the fuel consumption and the exhaust gas flow, and can be defined according to a plurality of parameters.
Preferably, the time of one driving cycle is longer than 60min, if the time is shorter than 60min, the data of the time is incorporated into the previous driving cycle, so that the situation that the change of the engine oil pressure cannot be accurately judged because the working condition interval is few due to frequent short-term operation is avoided, and the prediction of the engine oil pressure replacement place is inaccurate.
Preferably, if the number of working conditions in the working condition interval is less than 600, the working condition interval is abandoned, calculation is not participated, and inaccuracy in calculation of the pressure average value in the working condition interval due to the fact that the number of working conditions in the working condition interval is small is avoided, and further the oil pressure difference value of front and rear driving circulation cannot be obtained.
Compared with the prior art, the invention has the following advantages: based on the engine operation working condition and the operation condition, the engine oil replacement place is predicted, and the health state of the vehicle is accurately estimated.
Detailed Description
The following detailed description of the present invention, in conjunction with specific embodiments, will provide a clear and complete description of the technical solutions of embodiments of the present invention, it being evident that the embodiments described are only some, but not all, embodiments of the present invention.
Example 1
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
Example 2
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
The driving state information includes rotational speed, torque, oil temperature and oil pressure.
Specifically, recording an engine oil replacement point according to the GPS duration and the engine speed, recording the position information of the period when the GPS duration with the engine speed being 0 is more than 60min, reading the engine oil pressure information of the driving cycle before and after the period, calculating the pressure difference between the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval to obtain the pressure difference between different working condition intervals, judging that the engine oil replacement occurs in the period when the pressure difference between N working condition intervals is more than a preset pressure difference, and recording the position information of the period as the engine oil replacement point, wherein in the embodiment, N is 3 and the preset pressure difference is 50kpa.
Example 3
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
The driving state information includes rotational speed, torque, oil temperature and oil pressure.
Specifically, recording an engine oil replacement point according to the GPS duration and the engine speed, recording the position information of the period when the GPS duration with the engine speed being 0 is more than 60min, reading the engine oil pressure information of the driving cycle before and after the period, calculating the pressure difference between the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval to obtain the pressure difference between different working condition intervals, judging that the engine oil replacement occurs in the period when the pressure difference between N working condition intervals is more than a preset pressure difference, and recording the position information of the period as the engine oil replacement point, wherein in the embodiment, N is 5 and the preset pressure difference is 60kpa.
In addition, in this embodiment, the working condition intervals are obtained by dividing the working conditions of the vehicle into a plurality of working condition intervals according to the rotation speed of the engine, storing the engine oil pressure in each working condition interval in the corresponding working condition interval, and calculating the average value of the working condition intervals once at the end of each driving cycle as the result of the working condition intervals. The specific working condition interval is divided as follows: (100, 900], (900, 1200], (1200,1400], (1400,1600], (1600,1800].
Example 4
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
The driving state information includes rotational speed, torque, oil temperature and oil pressure.
Specifically, recording an engine oil replacement point according to the duration of GPS and the rotational speed of the engine, recording the position information of the position of the engine in the period when the duration of GPS with the rotational speed of the engine being 0 is more than 60min, reading the engine oil pressure information of the driving cycle before and after the period, calculating the pressure difference value of the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval to obtain the pressure difference value of different working condition intervals, judging that the engine oil replacement occurs in the period if the pressure difference value of N working condition intervals is more than a preset pressure difference value, and recording the position information of the position of the engine in the period as the engine oil replacement position, wherein in the embodiment, N is 10 and the preset pressure difference is 55kpa.
In this embodiment, the working condition intervals are obtained by dividing the working condition of the vehicle into a plurality of working condition intervals according to the speed of the engine, storing the oil pressure in each working condition interval in the corresponding working condition interval, calculating the average value of the working condition intervals once when each driving cycle is finished, and as a result of the working condition intervals, in this embodiment, the rotation speed difference between two adjacent working condition intervals is 100rpm, and the specific working condition intervals are divided as follows: (100, 900), (900, 1000), (1000, 1100), … (1700, 1800).
Example 5
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
The driving state information includes rotational speed, torque, oil temperature and oil pressure.
Specifically, recording an engine oil replacement point according to the duration of GPS and the rotational speed of the engine, recording the position information of the position of the engine in the period when the duration of GPS with the rotational speed of the engine being 0 is more than 60min, reading the engine oil pressure information of the driving cycle before and after the period, calculating the pressure difference value of the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval to obtain the pressure difference value of different working condition intervals, judging that the engine oil replacement occurs in the period if the pressure difference value of N working condition intervals is more than a preset pressure difference value, and recording the position information of the position of the engine in the period as the engine oil replacement position, wherein in the embodiment, N is 6 and the preset pressure difference is 50kpa.
In this embodiment, the working condition intervals are obtained by dividing the working conditions of the vehicle into a plurality of working condition intervals according to the percentage of torque, storing the engine oil pressure in each working condition interval in the corresponding working condition interval, and calculating the average value of the working condition intervals once at the end of each driving cycle as the result of the working condition intervals.
Example 6
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
The driving state information includes rotational speed, torque, oil temperature and oil pressure.
Specifically, recording an engine oil replacement point according to the GPS duration and the engine speed, recording the position information of the period when the GPS duration with the engine speed being 0 is more than 60min, reading the engine oil pressure information of the driving cycle before and after the period, calculating the pressure difference between the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval to obtain the pressure difference between different working condition intervals, judging that the engine oil replacement occurs in the period when the pressure difference between N working condition intervals is more than a preset pressure difference, and recording the position information of the period as the engine oil replacement point, wherein in the embodiment, N is 5 and the preset pressure difference is 60kpa.
In this embodiment, the working condition intervals are obtained by dividing the working conditions of the vehicle into a plurality of working condition intervals according to the fuel consumption, storing the engine oil pressure in each working condition interval in the corresponding working condition interval, and calculating the average value of the working condition intervals once at the end of each driving cycle as the result of the working condition intervals.
Example 7
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
The driving state information includes rotational speed, torque, oil temperature and oil pressure.
Specifically, recording an engine oil replacement point according to the GPS duration and the engine speed, recording the position information of the period when the GPS duration with the engine speed being 0 is more than 60min, reading the engine oil pressure information of the driving cycle before and after the period, calculating the pressure difference between the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval to obtain the pressure difference between different working condition intervals, judging that the engine oil replacement occurs in the period when the pressure difference between N working condition intervals is more than a preset pressure difference, and recording the position information of the period as the engine oil replacement point, wherein in the embodiment, N is 5 and the preset pressure difference is 60kpa.
In this embodiment, the working condition intervals are divided into a plurality of working condition intervals according to the exhaust gas flow, the engine oil pressure in each working condition interval is stored in the corresponding working condition interval, and the average value of the working condition intervals is calculated once at the end of each driving cycle, as the result of the working condition intervals.
Example 8
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
The driving state information includes rotational speed, torque, oil temperature and oil pressure.
Specifically, recording an engine oil replacement point according to the GPS duration and the engine speed, recording the position information of the period when the GPS duration with the engine speed being 0 is more than 60min, reading the engine oil pressure information of the driving cycle before and after the period, calculating the pressure difference between the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval to obtain the pressure difference between different working condition intervals, judging that the engine oil replacement occurs in the period when the pressure difference between N working condition intervals is more than a preset pressure difference, and recording the position information of the period as the engine oil replacement point, wherein in the embodiment, N is 7 and the preset pressure difference is 60kpa.
In this embodiment, the working condition intervals are obtained by dividing the working conditions of the vehicle into a plurality of working condition intervals according to the rotation speed and the torque percentage, storing the engine oil pressure in each working condition interval in the corresponding working condition interval, and calculating the average value of the working condition intervals once when each driving cycle is finished as the result of the working condition interval.
Example 9
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
The driving state information includes rotational speed, torque, oil temperature and oil pressure.
Specifically, recording an engine oil replacement point according to the duration of GPS and the rotational speed of the engine, recording the position information of the position of the engine in the period when the duration of GPS with the rotational speed of the engine being 0 is more than 60min, reading the engine oil pressure information of the driving cycle before and after the period, calculating the pressure difference value of the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval to obtain the pressure difference value of different working condition intervals, judging that the engine oil replacement occurs in the period if the pressure difference value of N working condition intervals is more than a preset pressure difference value, and recording the position information of the position of the engine in the period as the engine oil replacement position, wherein in the embodiment, N is 6 and the preset pressure difference is 50kpa.
In this embodiment, the working condition intervals are obtained by dividing the working conditions of the vehicle into a plurality of working condition intervals according to the rotational speed of the engine, storing the engine oil pressure in each working condition interval in the corresponding working condition interval, and calculating the average value of the working condition intervals once when each driving cycle is finished.
Example 10
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
The driving state information includes rotational speed, torque, oil temperature and oil pressure.
Specifically, recording an engine oil replacement point according to the GPS duration and the engine speed, recording the position information of the period when the GPS duration with the engine speed being 0 is more than 60min, reading the engine oil pressure information of the driving cycle before and after the period, calculating the pressure difference between the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval to obtain the pressure difference between different working condition intervals, judging that the engine oil replacement occurs in the period when the pressure difference between N working condition intervals is more than a preset pressure difference, and recording the position information of the period as the engine oil replacement point, wherein in the embodiment, N is 5 and the preset pressure difference is 55kpa.
In this embodiment, the working condition intervals are obtained by dividing the working conditions of the vehicle into a plurality of working condition intervals according to the rotational speed of the engine, storing the engine oil pressure in each working condition interval in the corresponding working condition interval, and calculating the average value of the working condition intervals once when each driving cycle is finished.
In this embodiment, when the oil pressure data is collected, the calculation frequency is 1Hz, that is, the result is calculated once per second.
Example 11
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
The driving state information includes rotational speed, torque, oil temperature and oil pressure.
Specifically, recording an engine oil replacement point according to the GPS duration and the engine speed, recording the position information of the period when the GPS duration with the engine speed being 0 is more than 60min, reading the engine oil pressure information of the driving cycle before and after the period, calculating the pressure difference between the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval to obtain the pressure difference between different working condition intervals, judging that the engine oil replacement occurs in the period when the pressure difference between N working condition intervals is more than a preset pressure difference, and recording the position information of the period as the engine oil replacement point, wherein in the embodiment, N is 5 and the preset pressure difference is 55kpa.
In this embodiment, the working condition intervals are obtained by dividing the working conditions of the vehicle into a plurality of working condition intervals according to the rotation speed of the engine, storing the engine oil pressure in each working condition interval in the corresponding working condition interval, calculating the average value of one working condition interval when each driving cycle is finished, and as a result of the working condition intervals, the driving cycle comprises the whole processes of starting the vehicle, running the vehicle and stopping the vehicle, wherein the time of one driving cycle is longer than 60min, and if the time of one driving cycle is shorter than 60min, the data of the time of one driving cycle is incorporated into the previous driving cycle.
In this embodiment, when the oil pressure data is collected, the calculation frequency is 1Hz, that is, the result is calculated once per second.
Example 12
The engine oil maintenance place prediction method based on big data comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, and the cloud platform predicts engine oil replacement time and records the replacement place according to the change of engine oil pressure in the received running state information.
The driving state information includes rotational speed, torque, oil temperature and oil pressure.
Specifically, recording an engine oil replacement point according to the GPS duration and the engine speed, recording the position information of the period when the GPS duration with the engine speed being 0 is more than 60min, reading the engine oil pressure information of the driving cycle before and after the period, calculating the pressure difference between the driving cycle after the shutdown and the driving cycle before the shutdown in the same working condition interval to obtain the pressure difference between different working condition intervals, judging that the engine oil replacement occurs in the period when the pressure difference between N working condition intervals is more than a preset pressure difference, and recording the position information of the period as the engine oil replacement point, wherein in the embodiment, N is 5 and the preset pressure difference is 55kpa.
In this embodiment, the working condition intervals are obtained by dividing the working conditions of the vehicle into a plurality of working condition intervals according to the rotation speed of the engine, storing the engine oil pressure in each working condition interval in the corresponding working condition interval, calculating the average value of one working condition interval when each driving cycle is finished, and as a result of the working condition intervals, the driving cycle comprises the whole processes of starting the vehicle, running the vehicle and stopping the vehicle, wherein the time of one driving cycle is longer than 60min, and if the time of one driving cycle is shorter than 60min, the data of the time of one driving cycle is incorporated into the previous driving cycle.
In this embodiment, when the oil pressure data is collected, the calculation frequency is a result calculated once per minute.
In addition, if the number of working conditions in the working condition interval is less than 600, discarding the working condition interval and not participating in calculation.
According to the engine oil maintenance site prediction method based on big data, the engine oil replacement site is predicted based on the operation working condition and the operation condition of the engine, and the health state of a vehicle is accurately estimated.
Here, it should be noted that the description of the above technical solution is exemplary, and the present specification may be embodied in different forms and should not be construed as being limited to the technical solution set forth herein. Rather, these descriptions will be provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. Furthermore, the technical solution of the invention is limited only by the scope of the claims.
The disclosure of aspects of the present specification and claims is merely an example and, therefore, the specification and claims are not limited to the details shown. In the above description, when a detailed description of related known functions or configurations is determined to unnecessarily obscure the gist of the present specification and claims, the detailed description will be omitted.
Where the terms "comprising," "having," and "including" are used in this specification, there may be additional or alternative parts unless the use is made, the terms used may generally be in the singular but may also mean the plural.
Finally, it should be noted that the above description of the invention in connection with the specific embodiments is not to be considered as limiting the practice of the invention to these descriptions, and that simple alternatives, which would be apparent to one of ordinary skill in the art to which the invention pertains without departing from its spirit, are deemed to be within the scope of the invention. The above embodiments are merely representative examples of the present invention. Obviously, the invention is not limited to the above-described embodiments, but many variations are possible. Any simple modification, equivalent variation and modification of the above embodiments according to the technical substance of the present invention should be considered to be within the scope of the present invention.
Meanwhile, it should be noted that the above description of the technical solution is exemplary, and the present specification may be embodied in various forms and should not be construed as being limited to the technical solution set forth herein. Rather, these descriptions will be provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. Furthermore, the technical solution of the invention is limited only by the scope of the claims. The features of the various embodiments of the invention may be combined or spliced with one another, either in part or in whole, and may be implemented in a variety of different configurations as will be well understood by those skilled in the art. Embodiments of the present invention may be performed independently of each other or may be performed together in an interdependent relationship.
It will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the invention, and the above-described structure should be considered to be within the scope of the invention.
Claims (8)
1. A machine oil maintenance site prediction method based on big data is characterized in that: the vehicle-mounted T-BOX comprises a controller, a vehicle-mounted T-BOX and a cloud platform, wherein the controller collects running state information of a vehicle and sends the running state information to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the running state to the cloud platform, the cloud platform predicts engine oil replacement time according to the received change of engine oil pressure in the running state information and records a replacement place, the running state information comprises rotating speed, torque, engine oil temperature and engine oil pressure, the engine oil replacement place is recorded according to GPS duration and engine rotating speed, when the GPS duration of the engine rotating speed is 0 and is greater than 60min, place position information of the time is recorded, engine oil pressure information of driving circulation before and after the time is read, pressure difference of driving circulation after the machine halt and driving circulation before the machine halt in the same working condition interval is calculated, if the pressure difference of N working condition intervals is greater than the preset pressure difference, the engine oil replacement place is judged to occur in the time, and place position information of the time is recorded as the engine oil replacement place.
2. The big data based engine oil maintenance site prediction method according to claim 1, characterized in that: the working condition intervals are formed by dividing the working condition of the vehicle into a plurality of working condition intervals according to the rotating speed of the engine, storing the engine oil pressure in each working condition interval in the corresponding working condition interval, and calculating the average value of the working condition intervals once when each driving cycle is finished, wherein the average value is used as the result of the working condition intervals.
3. The big data based engine oil maintenance site prediction method according to claim 1, characterized in that: the driving cycle includes the overall process of vehicle start, vehicle operation, and vehicle parking.
4. The big data based engine oil maintenance site prediction method according to claim 1, characterized in that: when the engine oil pressure data is collected, the calculation frequency is 1Hz, namely, the result is calculated once per second.
5. The big data based engine oil maintenance site prediction method according to claim 2, characterized in that: the rotation speed difference between two adjacent working condition intervals is 100rpm.
6. The big data based engine oil maintenance site prediction method according to claim 1, characterized in that: the working condition interval can be divided according to the rotating speed, the vehicle speed, the torque percentage, the fuel consumption and the exhaust gas flow, and can be defined and divided according to a plurality of parameters.
7. The big data based engine oil maintenance site prediction method according to claim 1, characterized in that: the time of one of the driving cycles is greater than 60 minutes, and if less than 60 minutes, the data of that time is incorporated into the last driving cycle.
8. The big data based engine oil maintenance site prediction method according to claim 1, characterized in that: if the number of working conditions in the working condition interval is less than 600, discarding the working condition interval and not participating in calculation.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103971164A (en) * | 2014-06-03 | 2014-08-06 | 上海安车信信息技术有限公司 | Vehicle aftermarket service method for integrating cloud server, offline terminal and vehicle-mounted equipment |
| CN106302668A (en) * | 2016-08-03 | 2017-01-04 | 深圳市永兴元科技有限公司 | Vehicle maintenance prompting method and Cloud Server |
| DE102017104195A1 (en) * | 2017-03-01 | 2018-03-01 | Schaeffler Technologies AG & Co. KG | Method for the maintenance of an autonomous vehicle and autonomous vehicle for carrying out the method |
| CN107992879A (en) * | 2017-11-07 | 2018-05-04 | 上海炬宏信息技术有限公司 | The method of the potential potential loss risk of automatic decision vehicle maintenance user |
| KR20190096842A (en) * | 2018-02-09 | 2019-08-20 | 박범상 | Networking system for efficient management of vehicle using data mining |
| CN111907444A (en) * | 2020-07-31 | 2020-11-10 | 东风商用车有限公司 | Intelligent engine oil maintenance system for heavy truck |
| WO2021110005A1 (en) * | 2019-12-02 | 2021-06-10 | 长城汽车股份有限公司 | Engine oil maintenance control method and device |
| CN113221457A (en) * | 2021-05-13 | 2021-08-06 | 北京车和家信息技术有限公司 | Method, device, equipment and medium for determining vehicle maintenance information |
| CN114038085A (en) * | 2021-10-29 | 2022-02-11 | 东风商用车有限公司 | Vehicle maintenance management system and method |
-
2022
- 2022-06-29 CN CN202210764829.3A patent/CN115086377B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103971164A (en) * | 2014-06-03 | 2014-08-06 | 上海安车信信息技术有限公司 | Vehicle aftermarket service method for integrating cloud server, offline terminal and vehicle-mounted equipment |
| CN106302668A (en) * | 2016-08-03 | 2017-01-04 | 深圳市永兴元科技有限公司 | Vehicle maintenance prompting method and Cloud Server |
| DE102017104195A1 (en) * | 2017-03-01 | 2018-03-01 | Schaeffler Technologies AG & Co. KG | Method for the maintenance of an autonomous vehicle and autonomous vehicle for carrying out the method |
| CN107992879A (en) * | 2017-11-07 | 2018-05-04 | 上海炬宏信息技术有限公司 | The method of the potential potential loss risk of automatic decision vehicle maintenance user |
| KR20190096842A (en) * | 2018-02-09 | 2019-08-20 | 박범상 | Networking system for efficient management of vehicle using data mining |
| WO2021110005A1 (en) * | 2019-12-02 | 2021-06-10 | 长城汽车股份有限公司 | Engine oil maintenance control method and device |
| CN111907444A (en) * | 2020-07-31 | 2020-11-10 | 东风商用车有限公司 | Intelligent engine oil maintenance system for heavy truck |
| CN113221457A (en) * | 2021-05-13 | 2021-08-06 | 北京车和家信息技术有限公司 | Method, device, equipment and medium for determining vehicle maintenance information |
| CN114038085A (en) * | 2021-10-29 | 2022-02-11 | 东风商用车有限公司 | Vehicle maintenance management system and method |
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