CN115086358B - Enterprise fleet oiling and oil consumption management system and method based on Internet of things - Google Patents
Enterprise fleet oiling and oil consumption management system and method based on Internet of things Download PDFInfo
- Publication number
- CN115086358B CN115086358B CN202210427749.9A CN202210427749A CN115086358B CN 115086358 B CN115086358 B CN 115086358B CN 202210427749 A CN202210427749 A CN 202210427749A CN 115086358 B CN115086358 B CN 115086358B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- enterprise
- information
- oil
- driver
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 65
- 230000008569 process Effects 0.000 claims abstract description 35
- 238000012790 confirmation Methods 0.000 claims abstract description 11
- 238000004364 calculation method Methods 0.000 claims description 72
- 238000007726 management method Methods 0.000 claims description 44
- 239000000446 fuel Substances 0.000 claims description 42
- 239000007788 liquid Substances 0.000 claims description 39
- 230000008859 change Effects 0.000 claims description 28
- 238000012545 processing Methods 0.000 claims description 20
- 239000002828 fuel tank Substances 0.000 claims description 10
- 238000011156 evaluation Methods 0.000 claims description 9
- 230000009471 action Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
Classifications
-
- 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
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60S—SERVICING, CLEANING, REPAIRING, SUPPORTING, LIFTING, OR MANOEUVRING OF VEHICLES, NOT OTHERWISE PROVIDED FOR
- B60S5/00—Servicing, maintaining, repairing, or refitting of vehicles
- B60S5/02—Supplying fuel to vehicles; General disposition of plant in filling stations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- Game Theory and Decision Science (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Theoretical Computer Science (AREA)
- Computing Systems (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Educational Administration (AREA)
- Chemical & Material Sciences (AREA)
- Chemical Kinetics & Catalysis (AREA)
- General Chemical & Material Sciences (AREA)
- Oil, Petroleum & Natural Gas (AREA)
- Mechanical Engineering (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an enterprise fleet oiling and oil consumption management system and method based on the Internet of things, and belongs to the technical field of intelligent traffic Internet of things oiling. The invention comprises the following steps: step one: after receiving the oiling information applied by the vehicle driver, the mobile terminal of the service platform judges whether to control the enterprise storage tank to apply for the oiling of the vehicle driver according to the historical oiling data of the vehicle and the condition of the vehicle going out; step two: the service platform mobile terminal confirms whether the vehicle oil filling amount is correct or not according to the received vehicle oil filling information, and feeds the confirmation information back to the enterprise driver terminal for secondary confirmation; step three: predicting whether the vehicle needs to be refueled outside an enterprise and evaluating the safety of the vehicle in the driving process; step four: after the vehicle returns to the enterprise, the service platform mobile terminal reminds a vehicle driver to record external oiling information at the service platform mobile terminal; step five: the mobile terminal of the service platform judges whether the external oiling information recorded by the driver is accurate or not.
Description
Technical Field
The invention relates to the technical field of intelligent traffic internet of things oiling, in particular to an enterprise fleet oiling and oil consumption management system and method based on the internet of things.
Background
The enterprise fleet is the vehicle that supplies the inside use of enterprise, in order to reduce enterprise fleet and refuels the cost, and the enterprise sets up the storage tank that refuels for enterprise fleet in its inside refuels, in order to realize to enterprise fleet refuels and oil consumption condition carries out intelligent management and control, adds enterprise fleet refuels and oil consumption management service in the thing networking.
The existing enterprise fleet fueling and fuel consumption management system is characterized in that when an enterprise vehicle is fueling, a storage tank worker performs fueling for the enterprise vehicle according to fueling application information submitted by a vehicle driver, the process lacks management and control of fueling application standards of the enterprise vehicle, so that the fueling cost of the enterprise fleet is not effectively improved, and when the vehicle driver is in an out-going task, the fuel consumption of the vehicle cannot be calculated according to road condition information and the fuel level change condition of the vehicle when the vehicle is in the out-going task, and then the optimal time of external fueling of the vehicle is predicted, so that the vehicle cannot be normally used due to insufficient fuel quantity, and when the enterprise vehicle is in external fueling, whether fueling information reported by the vehicle driver is accurate or not cannot be judged, and further, when the fueling storage tank is used for fueling the vehicle according to historical data, the situation that the fueling quantity is inconsistent with the actual demand of the vehicle occurs is unfavorable for the system to effectively manage and control the enterprise fleet.
Disclosure of Invention
The invention aims to provide an enterprise fleet oiling and oil consumption management system and method based on the Internet of things, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the enterprise fleet oiling and oil consumption management method based on the Internet of things comprises the following steps:
step one: recording enterprise drivers and vehicle license plate information of the enterprise drivers at a mobile terminal of a service platform, transmitting fueling application information to the mobile terminal of the service platform on line by the enterprise drivers, and judging whether to control an enterprise storage tank to supply fueling to the vehicle of the application drivers or not by vehicle history fueling data and vehicle outgoing task conditions after the mobile terminal of the service platform receives the information;
step two: after the oiling is completed, the enterprise storage tank sends oiling information to the service platform mobile terminal, and the service platform mobile terminal confirms whether the vehicle oiling amount is correct according to the received information and feeds back the confirmation information to the enterprise driver terminal for secondary confirmation;
step three: predicting whether the vehicle needs to be refueled outside an enterprise and evaluating the safety of the vehicle in the driving process;
step four: after the vehicle returns to the enterprise, the service platform mobile terminal reminds a vehicle driver to record external refueling information at the service platform mobile terminal according to a prediction result of whether the vehicle needs to be refueled outside the enterprise;
Step five: the mobile terminal of the service platform judges whether the external oiling information recorded by the driver is accurate or not.
Further, the mobile terminal of the service platform in the first step judges whether to control the enterprise storage tank to apply for the vehicle refueling of the driver according to the vehicle historical refueling data and the vehicle outgoing task condition, and the specific method is as follows:
step one (I): inquiring the number of times of outgoing tasks received in the time interval of the last refueling distance application time according to the refueling application information of the enterprise driver;
step one (II): calling historical refueling data of the corresponding vehicle according to the refueling application information of the enterprise driver, and calculating the residual oil quantity of the oil tank of the corresponding vehicle before the task is carried out on the basis of the calling information and the query result;
step one (iii): and predicting whether the residual oil quantity of the corresponding vehicle can meet the requirement according to the condition of the corresponding vehicle going out of the task, if so, informing an enterprise driver of whether to refuel the vehicle according to the residual oil quantity condition of the vehicle after the completion of the task, and otherwise, informing the enterprise driver of refuel the vehicle in a specified time.
Further, the third step includes:
Step three (I): installing a GPS module on an enterprise vehicle, recording real-time driving mileage, driving road conditions, driving time under each road condition and average rotating speed of an enterprise vehicle engine under each road condition of the corresponding enterprise vehicle, and automatically uploading recorded information to a mobile terminal of a service platform;
step three (II): the service platform mobile terminal calculates the oil consumption condition of the enterprise vehicle according to the uploading information and the load information of the corresponding enterprise vehicle, and a specific calculation formula G is as follows:
wherein, beta represents a hundred kilometers fuel consumption parameter of a corresponding enterprise vehicle, S represents a real-time driving mileage of the corresponding enterprise vehicle, i=1, 2,3, …, n represents a marking process of a special driving road condition met by the enterprise vehicle in the driving process, T i Represents the driving time of the corresponding enterprise vehicle under the ith special driving road condition,representing the average rotation speed of the corresponding enterprise vehicle engine under the ith special driving road condition, v represents the average rotation speed of the corresponding enterprise vehicle engine under the standard road condition, < >>Representing load data of corresponding enterprise vehicles under no-load condition, G representing load data of corresponding enterprise vehicles under the present task condition, G representing predicted real-time oil consumption of corresponding enterprise vehicles, and +. >Representing the relation coefficient, and adjusting the hundred kilometers fuel consumption parameter of the enterprise vehicle;
the situations that the engine rotates idly when the vehicle runs on a special road section and the friction force between the vehicle and the bottom surface is too large, so that the engine rotates at a low speed but the oil consumption is increased are considered, the error between a predicted value and a true value is reduced in the process of predicting the real-time oil quantity of the vehicle, and the management precision of the system is improved;
step three (iii): based on the calculation result and the change condition of the vehicle oil level under each road condition, predicting whether the vehicle needs to be refueled outside the enterprise, and evaluating the safety of the vehicle in the running process, the concrete method for predicting whether the vehicle needs to be refueled outside the enterprise is as follows:
1) Calculating the real-time residual oil quantity d-G of the vehicle according to the predicted real-time oil consumption of the corresponding vehicle in the step III, wherein d represents the residual oil quantity corresponding to the vehicle of the corresponding enterprise before going out the task;
2) Based on the driving road condition of the vehicle in the residual driving mileage and the driving time under each driving road condition, which are predicted by the vehicle GPS module, predicting whether the vehicle can complete the outgoing task by using the residual oil amount, wherein a specific prediction formula K is as follows:
wherein t represents the running time of the vehicle predicted by the vehicle GPS module under the standard road conditions, j=1, 2,3, …, m represents the label processing of the special running road conditions encountered by the vehicle predicted by the vehicle GPS module in the running process, and t j Represents the driving time of the corresponding enterprise vehicle under the j-th special driving road condition,representing the time required by corresponding enterprise vehicles to travel hundreds of kilometers under standard road conditions @, and @>Represents the time required by the corresponding enterprise vehicle to travel for one kilometer under the j-th special driving road condition,indicating the amount of oil consumed by the corresponding enterprise vehicle driving under standard road conditions +.>Indicating the oil consumed by the corresponding enterprise vehicle when running under the special road condition, when K is more than or equal to 0, indicating that the vehicle can finish the outgoing task by using the residual oil quantity, and when K<When 0, indicating that the vehicle cannot finish the task of going out by using the residual oil quantity;
3) When K is less than 0, the optimal oiling point is searched for oiling the vehicle by predicting the furthest distance that the corresponding vehicle can travel under the residual oil quantity, and the prediction formula of the furthest distance L is as follows:
wherein,representing the distance the corresponding enterprise vehicle travels under standard road conditions,/->Representing the distance of the corresponding enterprise vehicle running under the j-th special running road condition;
the optimal oiling point is found by comparing the numerical values of the farthest distance and the nearest distance from the nearby oiling point to the vehicle, so that the problem that the vehicle cannot normally run due to oil shortage caused by abnormal conditions of a running road section is avoided.
Further, in the third step, the safety of the vehicle during the running process is evaluated, and the specific method comprises the following steps:
Judging whether the predicted real-time oil consumption of the corresponding vehicle in the step three (II) is lower than the oil tank liquid level change value in the corresponding running time of the vehicle, if so, predicting whether the oil leakage condition exists in the running process of the vehicle based on the change condition of the corresponding enterprise vehicle oil level under each road condition, wherein the specific prediction method comprises the following steps:
(1) Representing the change values of the corresponding enterprise vehicle oil level in different time periods under each road condition by using a coordinate system, and calculating the instantaneous descending speeds of the corresponding enterprise vehicle oil level in different time points under each road condition according to the coordinate distribution condition;
(2) Constructing a linear equation according to the calculated result in the step (1) to predict whether the oil level change rate of the corresponding enterprise vehicle is in a stable state, if not, predicting that the oil leakage condition exists in the running process of the vehicle, and sending alarm information to the enterprise vehicle by the service platform mobile terminal according to the predicted result;
the instantaneous descending speed of the oil quantity of the oil tank under different road conditions is used for predicting whether the oil leakage condition exists in the oil tank of the vehicle, and informing a vehicle driver to maintain the vehicle at the first time when the oil leakage trend exists in the oil tank, so that the safety accident is avoided.
Further, the fifth step includes:
a liquid level meter is vertically arranged in the middle of the corresponding enterprise vehicle oil tank, and after the corresponding enterprise vehicle is filled with oil outside, when the corresponding enterprise vehicle runs on a slope section, the GPS module monitors the slope of the slope section, and the liquid level meter monitors the liquid level of the vehicle oil tank at the moment;
Step five (1): based on the slope section gradient monitored by the GPS module, the oil tank liquid level value monitored by the liquid level meter and the vehicle oil tank specification, the oil quantity of the vehicle oil tank at the moment is calculated, and a specific calculation formula F is as follows:
wherein alpha represents the gradient of a gradient road section monitored by the GPS module, and h 1 The liquid level of the oil tank corresponding to the slope alpha of the vehicle monitored by the liquid level meter is shown, l is the side length of the bottom surface of the oil tank of the vehicle, and l is tan alpha is the liquid level change height of the oil tank when the slope alpha is shown 2 Indicating that the liquid level of the oil tank is higher thanThe amount of oil in the portion is calculated,indicating a tank level below +.>Calculating partial oil quantity;
step five (2): calculating the oil consumption condition of the vehicle reaching the gradient road section by using a calculation formula G, and calculating the external oil filling quantity of the vehicle by combining the oil quantity of the oil tank when the vehicle reaches the gradient road section and the residual oil quantity before the vehicle is subjected to a mission;
step five (3): and (5) comparing the calculation result in the step (2) with the oiling information input by the driver into the service platform terminal, and judging whether the external oiling information input by the driver is accurate or not.
The enterprise fleet fueling and fuel consumption management system based on the Internet of things, which is realized based on the method, comprises a service platform mobile terminal, a driver terminal, a fleet fueling module, a GPS module, a prediction processing module and a fuel consumption management module;
The prediction processing module and the oil consumption management module are arranged at the mobile end of the service platform;
the service platform mobile terminal is used for inputting enterprise drivers and vehicle license plate information thereof, receiving fueling application information sent by a driver terminal, receiving vehicle running information uploaded by the GPS module, judging whether to control the fleet fueling module to fueling the vehicle of the application driver according to the fueling application information, and receiving fueling information fed back by the fleet fueling module;
the driver terminal is used for sending the vehicle refueling application information of the driver and the external refueling information of the driver to the mobile terminal of the service platform, receiving the vehicle refueling amount confirmation information fed back by the mobile terminal of the service platform, and secondarily confirming the vehicle refueling information;
the vehicle team oiling module is used for receiving the oiling information of the vehicle of the driver, which is sent by the mobile terminal of the service platform, oiling the vehicle of the driver according to the received information, and sending the oiling information to the mobile terminal of the service platform;
the GPS module is used for recording real-time running information of the corresponding enterprise vehicles and uploading the recorded information to the mobile terminal of the service platform;
the prediction processing module is used for predicting whether the vehicle needs to be refueled outside an enterprise and evaluating the safety of the vehicle in the running process;
The fuel consumption management module is used for judging whether the external refueling information of the driver vehicle uploaded by the driver terminal is accurate or not.
Further, the service platform mobile terminal comprises an information inquiry unit, an information calling unit and a control unit;
the information inquiry unit inquires corresponding vehicles according to the oiling application information of the drivers of enterprises, the number of times of outgoing tasks received in the time interval of the last oiling distance application time, and the inquiry information is transmitted to the information calling unit;
the information calling unit receives the query information transmitted by the information query unit, calls historical refueling data of the corresponding vehicle according to the refueling application information of the enterprise driver, calculates the residual oil quantity of the oil tank of the corresponding vehicle before the task is discharged at this time based on the calling information and the query result, and transmits the calculation result to the control unit and the oil consumption management module;
the control unit receives the calculation result transmitted by the information calling unit, predicts whether the residual oil quantity of the corresponding vehicle can meet the requirement according to the condition of the current outgoing task of the corresponding vehicle, controls the fleet oiling module to carry out oiling on the vehicle according to the prediction result, and transmits oiling information to the prediction processing module.
Further, the GPS module is used for recording real-time driving mileage, driving road conditions, driving time under each road condition and average rotating speed of an engine of the enterprise vehicle under each road condition of the corresponding enterprise vehicle, and uploading recorded information to a prediction processing module arranged on a mobile end of the service platform.
Further, the prediction processing module comprises an information receiving unit, an enterprise vehicle oil consumption calculating unit, an enterprise external oiling prediction unit and a safety evaluation unit;
the information receiving unit receives the record information uploaded by the GPS module and the vehicle refueling information transmitted by the control unit, and transmits the received content to the enterprise vehicle fuel consumption calculating unit;
the enterprise vehicle oil consumption calculation unit receives the recorded information transmitted by the information receiving unit, calculates the oil consumption condition of the enterprise vehicle by combining the load information of the corresponding enterprise vehicle, and transmits the calculation result to the enterprise external oil filling prediction unit and the safety evaluation unit;
the enterprise external oil filling prediction unit receives the calculation result transmitted by the enterprise vehicle oil consumption calculation unit, predicts the real-time oil consumption of the corresponding vehicle based on the calculation result, calculates the real-time residual oil quantity of the vehicle according to the predicted real-time oil consumption, predicts whether the vehicle can finish an outgoing task by using the residual oil quantity based on the running road conditions of the vehicle in the residual running mileage and the running time of the vehicle under each running road condition predicted by the vehicle GPS module, predicts the farthest distance that the corresponding vehicle can run under the residual oil quantity when the outgoing task cannot be finished by using the residual oil quantity, searches the optimal oil filling point for filling the vehicle, and transmits the vehicle oil filling information to the oil consumption management module;
The safety evaluation unit receives the calculation result transmitted by the enterprise vehicle oil consumption calculation unit, judges whether the calculation result is lower than the oil tank liquid level change value in the corresponding running time of the vehicle, if yes, the coordinate system is utilized to represent the corresponding enterprise vehicle oil level, the change values of different time periods under each road condition are represented, the instantaneous descending speed of the corresponding enterprise vehicle oil level at different time points under each road condition is calculated according to the coordinate distribution condition, a linear equation is constructed according to the calculated instantaneous descending speed, whether the corresponding enterprise vehicle oil level change speed is in a stable state is predicted, if not, the oil leakage condition of the vehicle in the running process is predicted, the prediction result is transmitted to the mobile end of the service platform, and the service platform mobile sends alarm information to the driver terminal according to the prediction result.
Further, the oil consumption management module comprises an oil tank oil quantity calculation unit, a driver oil filling quantity calculation unit and a judgment unit;
the fuel tank fuel quantity calculation unit receives the prediction result transmitted by the enterprise external fuel filling prediction unit, calculates the fuel quantity of the fuel tank of the vehicle at the moment by utilizing the gradient of the vehicle running on a gradient road section monitored by the GPS module, the fuel tank liquid level value monitored by the liquid level meter and the vehicle fuel tank specification when the vehicle is predicted to be externally refueled, and transmits the calculation result to the driver fuel filling quantity calculation unit;
The driver oil filling amount calculating unit receives the calculation result transmitted by the oil tank oil amount calculating unit and the calculation result transmitted by the information calling unit, calculates the external oil filling amount of the vehicle by calculating the oil consumption condition of the vehicle reaching the gradient road section and combining the oil amount of the oil tank when the vehicle reaches the gradient road section and the residual oil amount before the vehicle takes out the task, and transmits the calculation result to the judging unit;
the judging unit receives the calculation result transmitted by the driver fueling quantity calculating unit, compares the received content with fueling information of the driver input service platform terminal, and judges whether the external fueling information input by the driver is accurate or not.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the invention, the situations that the engine idles when the vehicle runs on a special road section and the friction between the vehicle and the bottom surface is overlarge, which leads to low engine speed and increased oil consumption, are considered, the error between the predicted value and the actual value is reduced in the process of predicting the real-time oil quantity of the vehicle, the management precision of the system is improved, the prediction of whether the vehicle can finish an outgoing task by using the residual oil quantity is carried out through the predicted value and the vehicle running road condition monitored by the GPS module, and when the predicted vehicle can not finish the outgoing task, the prediction is carried out on the furthest distance that the vehicle can run, the optimal oil filling point is selected for the vehicle according to the furthest distance prediction result, the smooth completion of the outgoing task of the vehicle is ensured, and the management effect of the system is improved.
2. According to the method, the oil quantity of the oil tank is calculated by utilizing the liquid level change of the vehicle in the oil tank of the slope road section, the external oil filling information of the vehicle is predicted by combining the real-time monitored oil consumption condition of the vehicle and the residual oil quantity before the vehicle goes out of the mission, the condition that a vehicle driver reports the external oil filling information in a wrong report or misreport mode is avoided, the management intensity of the system on the oil consumption of an enterprise motorcade is enhanced, the process does not need to check the external oil filling information of the vehicle manually, and the intelligent management of the oil consumption of the enterprise motorcade is ensured.
3. According to the method, after the service platform mobile terminal receives the oiling application information sent by the vehicle driver, historical oiling data of the corresponding vehicle and the number of times of outgoing tasks received by the corresponding vehicle in the time interval of the last oiling distance application time are called, the situation of the outgoing tasks of the vehicle is combined to predict the residual oil quantity of the vehicle, so that the task requirements can be met, the driver is prevented from using the enterprise vehicle to meet private requirements, the enterprise storage tank is controlled to carry out oiling on the vehicle according to the task situation, other purposes of the driver are prevented from being realized when the driver goes out the tasks, and the oiling management effect of the system on the enterprise vehicle is further improved.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic workflow diagram of an enterprise fleet fueling and fuel consumption management system and method based on the Internet of things of the present invention;
FIG. 2 is a schematic diagram of the modular relationship of the enterprise fleet fueling and fuel consumption management system and method based on the Internet of things of the present invention;
fig. 3 is a schematic structural diagram of the working principle of the enterprise fleet fueling and fuel consumption management system and method based on the internet of things.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, 2 and 3, the present invention provides the following technical solutions: the enterprise fleet oiling and oil consumption management method based on the Internet of things comprises the following steps:
Step one: the method comprises the steps that an enterprise driver and vehicle license plate information of the enterprise driver are recorded at a mobile terminal of a service platform, the enterprise driver sends oiling application information to the mobile terminal of the service platform on line, and after the mobile terminal of the service platform receives the information, whether an enterprise storage tank is controlled to apply for vehicle oiling or not is judged according to vehicle historical oiling data and vehicle outgoing task conditions, and the specific method is as follows:
step one (I): inquiring the number of times of outgoing tasks received in the time interval of the last refueling distance application time according to the refueling application information of the enterprise driver;
step one (II): calling historical refueling data of the corresponding vehicle according to the refueling application information of the enterprise driver, and calculating the residual oil quantity of the oil tank of the corresponding vehicle before the task is carried out on the basis of the calling information and the query result;
step one (iii): predicting whether the residual oil quantity of the corresponding vehicle can meet the requirement according to the condition of the outgoing task of the corresponding vehicle, if so, informing an enterprise driver of whether to refuel the vehicle according to the residual oil quantity condition of the vehicle after the outgoing task is finished, otherwise, informing the enterprise driver of refuel the vehicle in a specified time;
Step two: after the oiling is completed, the enterprise storage tank sends oiling information to the service platform mobile terminal, and the service platform mobile terminal confirms whether the vehicle oiling amount is correct according to the received information and feeds back the confirmation information to the enterprise driver terminal for secondary confirmation;
step three: predicting whether the vehicle needs to be refueled outside the enterprise and evaluating the safety of the vehicle during driving, wherein the third step comprises:
step three (I): installing a GPS module on an enterprise vehicle, recording real-time driving mileage, driving road conditions, driving time under each road condition and average rotating speed of an enterprise vehicle engine under each road condition of the corresponding enterprise vehicle, and automatically uploading recorded information to a mobile terminal of a service platform;
step three (II): the service platform mobile terminal calculates the oil consumption condition of the enterprise vehicle according to the uploading information and the load information of the corresponding enterprise vehicle, and a specific calculation formula G is as follows:
wherein, beta represents the hundred kilometers fuel consumption parameter of the corresponding enterprise vehicle, and S represents the real-time running of the corresponding enterprise vehicleI=1, 2,3, …, n, the process indicates that the special running road conditions met by the enterprise vehicles in the running process are marked, and T i Represents the driving time of the corresponding enterprise vehicle under the ith special driving road condition, Representing the average rotation speed of the corresponding enterprise vehicle engine under the ith special driving road condition, v represents the average rotation speed of the corresponding enterprise vehicle engine under the standard road condition, < >>Representing load data of corresponding enterprise vehicles under no-load condition, G representing load data of corresponding enterprise vehicles under the present task condition, G representing predicted real-time oil consumption of corresponding enterprise vehicles, and +.>Representing the relation coefficient, and adjusting the hundred kilometers fuel consumption parameter of the enterprise vehicle;
step three (iii): based on the calculation result and the change condition of the vehicle oil level under each road condition, predicting whether the vehicle needs to be refueled outside the enterprise, and evaluating the safety of the vehicle in the running process, the concrete method for predicting whether the vehicle needs to be refueled outside the enterprise is as follows:
1) Calculating the real-time residual oil quantity d-G of the vehicle according to the predicted real-time oil consumption of the corresponding vehicle in the step III, wherein d represents the residual oil quantity corresponding to the vehicle of the corresponding enterprise before going out the task;
2) Based on the driving road condition of the vehicle in the residual driving mileage and the driving time under each driving road condition, which are predicted by the vehicle GPS module, predicting whether the vehicle can complete the outgoing task by using the residual oil amount, wherein a specific prediction formula K is as follows:
Wherein t represents the standard road condition of the vehicle predicted by the vehicle GPS moduleTravel time, j=1, 2,3, …, m represents a reference number of a special travel road condition predicted by the vehicle GPS module to be encountered during travel, t j Represents the driving time of the corresponding enterprise vehicle under the j-th special driving road condition,representing the time required by corresponding enterprise vehicles to travel hundreds of kilometers under standard road conditions @, and @>Representing the time required by the corresponding enterprise vehicle to travel for one kilometer under the j-th special travel road condition>Indicating the amount of oil consumed by the corresponding enterprise vehicle driving under standard road conditions +.>Indicating the oil consumed by the corresponding enterprise vehicle when running under the special road condition, when K is more than or equal to 0, indicating that the vehicle can finish the outgoing task by using the residual oil quantity, and when K<When 0, indicating that the vehicle cannot finish the task of going out by using the residual oil quantity;
3) When K is less than 0, the optimal oiling point is searched for oiling the vehicle by predicting the furthest distance that the corresponding vehicle can travel under the residual oil quantity, and the prediction formula of the furthest distance L is as follows:
wherein,representing the distance the corresponding enterprise vehicle travels under standard road conditions,/->Representing the distance of the corresponding enterprise vehicle running under the j-th special running road condition;
Searching for an optimal oiling point by comparing the numerical values of the farthest distance and the nearest distance from the nearby oiling point to the vehicle;
the specific method for evaluating the safety of the vehicle in the running process comprises the following steps:
judging whether the predicted real-time oil consumption of the corresponding vehicle in the step three (II) is lower than the oil tank liquid level change value in the corresponding running time of the vehicle, if so, predicting whether the oil leakage condition exists in the running process of the vehicle based on the change condition of the corresponding enterprise vehicle oil level under each road condition, wherein the specific prediction method comprises the following steps:
(1) Representing the change values of the corresponding enterprise vehicle oil level in different time periods under each road condition by using a coordinate system, and calculating the instantaneous descending speeds of the corresponding enterprise vehicle oil level in different time points under each road condition according to the coordinate distribution condition;
(2) Constructing a linear equation according to the calculated result in the step (1) to predict whether the oil level change rate of the corresponding enterprise vehicle is in a stable state, if not, predicting that the oil leakage condition exists in the running process of the vehicle, and sending alarm information to the enterprise vehicle by the service platform mobile terminal according to the predicted result;
step four: after the vehicle returns to the enterprise, the service platform mobile terminal reminds a vehicle driver to record external refueling information at the service platform mobile terminal according to a prediction result of whether the vehicle needs to be refueled outside the enterprise;
Step five: the mobile terminal of the service platform judges whether the external oiling information recorded by the driver is accurate or not, and the fifth step comprises the following steps:
a liquid level meter is vertically arranged in the middle of the corresponding enterprise vehicle oil tank, and after the corresponding enterprise vehicle is filled with oil outside, when the corresponding enterprise vehicle runs on a slope section, the GPS module monitors the slope of the slope section, and the liquid level meter monitors the liquid level of the vehicle oil tank at the moment;
step five (1): based on the slope section gradient monitored by the GPS module, the oil tank liquid level value monitored by the liquid level meter and the vehicle oil tank specification, the oil quantity of the vehicle oil tank at the moment is calculated, and a specific calculation formula F is as follows:
wherein alpha represents the gradient of a gradient road section monitored by the GPS module, and h 1 The liquid level of the oil tank corresponding to the slope alpha of the vehicle monitored by the liquid level meter is shown, l is the side length of the bottom surface of the oil tank of the vehicle, and l is tan alpha is the liquid level change height of the oil tank when the slope alpha is shown 2 Indicating that the liquid level of the oil tank is higher thanThe amount of oil in the portion is calculated,indicating a tank level below +.>Calculating partial oil quantity;
step five (2): calculating the oil consumption condition of the vehicle reaching the gradient road section by using a calculation formula G, and calculating the external oil filling quantity of the vehicle by combining the oil quantity of the oil tank when the vehicle reaches the gradient road section and the residual oil quantity before the vehicle is subjected to a mission;
Step five (3): and (5) comparing the calculation result in the step (2) with the oiling information input by the driver into the service platform terminal, and judging whether the external oiling information input by the driver is accurate or not.
The enterprise fleet fueling and fuel consumption management system based on the Internet of things, which is realized based on the method, comprises a service platform mobile terminal, a driver terminal, a fleet fueling module, a GPS module, a prediction processing module and a fuel consumption management module;
the prediction processing module and the oil consumption management module are arranged at the mobile end of the service platform;
the service platform mobile terminal is used for inputting enterprise drivers and vehicle license plate information thereof, receiving fueling application information sent by a driver terminal, receiving vehicle running information uploaded by the GPS module, judging whether to control the fleet fueling module to fueling the vehicle of the application driver according to the fueling application information, and receiving fueling information fed back by the fleet fueling module;
the service platform mobile terminal comprises an information inquiry unit, an information calling unit and a control unit;
the information inquiry unit inquires corresponding vehicles according to the oiling application information of the drivers of the enterprises, the number of times of outgoing tasks received in the time interval of the latest oiling distance application time, and the inquiry information is transmitted to the information calling unit;
The information calling unit receives the query information transmitted by the information query unit, calls historical refueling data of the corresponding vehicle according to the refueling application information of the enterprise driver, calculates the residual oil quantity of the oil tank of the corresponding vehicle before the task is carried out at this time based on the calling information and the query result, and transmits the calculation result to the control unit and the oil consumption management module;
the control unit receives the calculation result transmitted by the information calling unit, predicts whether the residual oil quantity of the corresponding vehicle can meet the requirement according to the condition of the corresponding vehicle going out of the mission, controls the fleet oiling module to carry out oiling on the vehicle according to the prediction result, and transmits oiling information to the prediction processing module;
the driver terminal is used for sending the vehicle refueling application information of the driver and the external refueling information of the driver to the mobile terminal of the service platform, receiving the vehicle refueling amount confirmation information fed back by the mobile terminal of the service platform, and secondarily confirming the vehicle refueling information;
the motorcade oiling module is used for receiving the oiling information of the vehicle of the application driver sent by the mobile terminal of the service platform, oiling the vehicle of the application driver according to the received information, and sending the oiling information to the mobile terminal of the service platform;
The GPS module is used for recording real-time driving mileage, driving road conditions, driving time under each road condition and average rotating speed of an engine of the enterprise vehicle under each road condition of the corresponding enterprise vehicle, and uploading recorded information to the prediction processing module arranged on the mobile end of the service platform;
the prediction processing module is used for predicting whether the vehicle needs to be refueled outside an enterprise and evaluating the safety of the vehicle in the running process;
the prediction processing module comprises an information receiving unit, an enterprise vehicle oil consumption calculating unit, an enterprise external oiling prediction unit and a safety evaluation unit;
the information receiving unit receives the record information uploaded by the GPS module and the vehicle refueling information transmitted by the control unit, and transmits the received content to the enterprise vehicle fuel consumption calculating unit;
the enterprise vehicle oil consumption calculation unit receives the recorded information transmitted by the information receiving unit, calculates the oil consumption condition of the enterprise vehicle by combining the load information of the corresponding enterprise vehicle, and transmits the calculation result to the enterprise external oil filling prediction unit and the safety evaluation unit;
the method comprises the steps that an enterprise external oiling prediction unit receives a calculation result transmitted by an enterprise vehicle oil consumption calculation unit, predicts the real-time oil consumption of a corresponding vehicle based on the calculation result, calculates the real-time residual oil quantity of the vehicle according to the predicted real-time oil consumption, predicts whether the vehicle can finish an outgoing task by using the residual oil quantity based on the running road conditions of the vehicle in residual driving mileage and the running time of the vehicle under each running road condition, and when the predicted vehicle cannot finish the outgoing task by using the residual oil quantity, searches the optimal oiling point for oiling the vehicle by predicting the furthest distance which the corresponding vehicle can travel under the residual oil quantity, and transmits the vehicle oiling information to an oil consumption management module;
The safety evaluation unit receives the calculation result transmitted by the enterprise vehicle oil consumption calculation unit, judges whether the calculation result is lower than the oil tank liquid level change value in the corresponding running time of the vehicle, if yes, the coordinate system is utilized to represent the corresponding enterprise vehicle oil level, the change values of different time periods under each road condition are represented, the instantaneous descending speed of the corresponding enterprise vehicle oil level at different time points under each road condition is calculated according to the coordinate distribution condition, a linear equation is constructed according to the calculated instantaneous descending speed, whether the corresponding enterprise vehicle oil level change speed is in a stable state is predicted, if not, the oil leakage condition of the vehicle in the running process is predicted, the prediction result is transmitted to the mobile end of the service platform, and the service platform mobile transmits alarm information to the driver terminal according to the prediction result
The fuel consumption management module is used for judging whether the external fueling information of the driver vehicle uploaded by the driver terminal is accurate or not;
the fuel consumption management module comprises a fuel tank fuel quantity calculation unit, a driver fuel quantity calculation unit and a judgment unit;
the oil tank oil quantity calculation unit receives the prediction result transmitted by the enterprise external oil filling prediction unit, calculates the oil quantity of the vehicle oil tank at the moment by utilizing the gradient of the vehicle running on the gradient road section monitored by the GPS module, the oil tank liquid level value monitored by the liquid level meter and the vehicle oil tank specification when the vehicle is predicted to be externally filled, and transmits the calculation result to the driver oil filling quantity calculation unit;
The driver oil filling amount calculating unit receives the calculation result transmitted by the oil tank oil amount calculating unit and the calculation result transmitted by the information calling unit, calculates the external oil filling amount of the vehicle by calculating the oil consumption condition of the vehicle reaching the gradient road section and combining the oil amount of the oil tank when the vehicle reaches the gradient road section and the residual oil amount before the vehicle takes out the task, and transmits the calculation result to the judging unit;
the judging unit receives the calculation result transmitted by the driver fueling quantity calculating unit, compares the received content with fueling information of the driver input service platform terminal, and judges whether the external fueling information input by the driver is accurate or not.
Examples: let the slope highway section slope of GPS module monitoring be 30, the oil tank liquid level value 20cml of level gauge monitoring be with vehicle oil tank specification be 50cml 30cml, the oil consumption of vehicle from the place of departure to slope highway section be 12L, the remaining oil mass before the vehicle goes out the task be 20L, then:
the fuel quantity of the vehicle fuel tank at this time is:
the external fuel filling amount of the vehicle is 18-12+20=10L;
and comparing the calculated result 10L with the oiling information input by the driver into the service platform terminal to judge whether the external oiling information input by the driver is accurate or not.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. The enterprise motorcade oiling and oil consumption management method based on the Internet of things is characterized by comprising the following steps of: the method comprises the following steps:
step one: recording enterprise drivers and vehicle license plate information of the enterprise drivers at a mobile terminal of a service platform, transmitting fueling application information to the mobile terminal of the service platform on line by the enterprise drivers, and judging whether to control an enterprise storage tank to supply fueling to the vehicle of the application drivers or not by vehicle history fueling data and vehicle outgoing task conditions after the mobile terminal of the service platform receives the information;
step two: after the oiling is completed, the enterprise storage tank sends oiling information to the service platform mobile terminal, and the service platform mobile terminal confirms whether the vehicle oiling amount is correct according to the received information and feeds back the confirmation information to the enterprise driver terminal for secondary confirmation;
Step three: predicting whether the vehicle needs to be refueled outside an enterprise and evaluating the safety of the vehicle in the driving process;
the third step comprises the following steps:
step three (I): installing a GPS module on an enterprise vehicle, recording real-time driving mileage, driving road conditions, driving time under each road condition and average rotating speed of an enterprise vehicle engine under each road condition of the corresponding enterprise vehicle, and automatically uploading recorded information to a mobile terminal of a service platform;
step three (II): the service platform mobile terminal calculates the oil consumption condition of the enterprise vehicle according to the uploading information and the load information of the corresponding enterprise vehicle, and a specific calculation formula G is as follows:
wherein, beta represents a hundred kilometers fuel consumption parameter of a corresponding enterprise vehicle, S represents a real-time driving mileage of the corresponding enterprise vehicle, i=1, 2,3, …, n represents a marking process of a special driving road condition met by the enterprise vehicle in the driving process, T i Represents the driving time of the corresponding enterprise vehicle under the ith special driving road condition,representing the average rotation speed of the corresponding enterprise vehicle engine under the ith special driving road condition, v represents the average rotation speed of the corresponding enterprise vehicle engine under the standard road condition, < >>Representing load data of corresponding enterprise vehicles under no-load condition, G representing load data of corresponding enterprise vehicles under the present task condition, G representing predicted real-time oil consumption of corresponding enterprise vehicles, and +. >Representing the relation coefficient, for the enterprise vehicle BaigongAdjusting the fuel consumption parameter;
step three (iii): based on the calculation result and the change condition of the vehicle oil level under each road condition, predicting whether the vehicle needs to be refueled outside the enterprise, and evaluating the safety of the vehicle in the running process, the concrete method for predicting whether the vehicle needs to be refueled outside the enterprise is as follows:
1) Calculating the real-time residual oil quantity d-G of the vehicle according to the predicted real-time oil consumption of the corresponding vehicle in the step III, wherein d represents the residual oil quantity corresponding to the vehicle of the corresponding enterprise before going out the task;
2) Based on the driving road condition of the vehicle in the residual driving mileage and the driving time under each driving road condition, which are predicted by the vehicle GPS module, predicting whether the vehicle can complete the outgoing task by using the residual oil amount, wherein a specific prediction formula K is as follows:
wherein t represents the running time of the vehicle predicted by the vehicle GPS module under the standard road conditions, j=1, 2,3, …, m represents the label processing of the special running road conditions encountered by the vehicle predicted by the vehicle GPS module in the running process, and t j Represents the driving time of the corresponding enterprise vehicle under the j-th special driving road condition,representing the time required by corresponding enterprise vehicles to travel hundreds of kilometers under standard road conditions @, and @ >Representing the time required by the corresponding enterprise vehicle to travel for one kilometer under the j-th special driving road condition;
3) When the vehicle cannot finish the outgoing task by using the residual oil quantity, the optimal oiling point is searched for oiling the vehicle by predicting the farthest distance which can be travelled by the corresponding vehicle under the residual oil quantity, and the prediction formula of the farthest distance L is as follows:
wherein,representing the distance the corresponding enterprise vehicle travels under standard road conditions,/->Representing the distance of the corresponding enterprise vehicle running under the j-th special running road condition;
searching for an optimal oiling point by comparing the numerical values of the farthest distance and the nearest distance from the nearby oiling point to the vehicle;
step four: after the vehicle returns to the enterprise, the service platform mobile terminal reminds a vehicle driver to record external refueling information at the service platform mobile terminal according to a prediction result of whether the vehicle needs to be refueled outside the enterprise;
step five: the mobile terminal of the service platform judges whether the external oiling information recorded by the driver is accurate or not.
2. The internet of things-based enterprise fleet fueling and fuel consumption management method as set forth in claim 1, wherein: in the first step, the mobile terminal of the service platform judges whether to control the enterprise storage tank to apply for the vehicle refueling of the driver according to the vehicle historical refueling data and the vehicle outgoing task condition, and the specific method comprises the following steps:
Step one (I): inquiring the number of times of outgoing tasks received in the time interval of the last refueling distance application time according to the refueling application information of the enterprise driver;
step one (II): calling historical refueling data of the corresponding vehicle according to the refueling application information of the enterprise driver, and calculating the residual oil quantity of the oil tank of the corresponding vehicle before the task is carried out on the basis of the calling information and the query result;
step one (iii): and predicting whether the residual oil quantity of the corresponding vehicle can meet the requirement according to the condition of the corresponding vehicle going out of the task, if so, informing an enterprise driver of whether to refuel the vehicle according to the residual oil quantity condition of the vehicle after the completion of the task, and otherwise, informing the enterprise driver of refuel the vehicle in a specified time.
3. The internet of things-based enterprise fleet fueling and fuel consumption management method as set forth in claim 2, wherein: in the third step, the safety of the vehicle in the running process is evaluated, and the specific method comprises the following steps:
judging whether the predicted real-time oil consumption of the corresponding vehicle in the step three (II) is lower than the oil tank liquid level change value in the corresponding running time of the vehicle, if so, predicting whether the oil leakage condition exists in the running process of the vehicle based on the change condition of the corresponding enterprise vehicle oil level under each road condition, wherein the specific prediction method comprises the following steps:
(1) Representing the change values of the corresponding enterprise vehicle oil level in different time periods under each road condition by using a coordinate system, and calculating the instantaneous descending speeds of the corresponding enterprise vehicle oil level in different time points under each road condition according to the coordinate distribution condition;
(2) And (3) constructing a linear equation according to the calculated result in the step (1) to predict whether the oil level change rate of the corresponding enterprise vehicle is in a stable state, if not, predicting that the oil leakage condition exists in the running process of the vehicle, and sending alarm information to the enterprise vehicle by the service platform mobile terminal according to the predicted result.
4. The internet of things-based enterprise fleet fueling and fuel consumption management method as set forth in claim 3, wherein: the fifth step comprises the following steps:
a liquid level meter is vertically arranged in the middle of the corresponding enterprise vehicle oil tank, and after the corresponding enterprise vehicle is filled with oil outside, when the corresponding enterprise vehicle runs on a slope section, the GPS module monitors the slope of the slope section, and the liquid level meter monitors the liquid level of the vehicle oil tank at the moment;
step five (1): based on the slope section gradient monitored by the GPS module, the oil tank liquid level value monitored by the liquid level meter and the vehicle oil tank specification, the oil quantity of the vehicle oil tank at the moment is calculated, and a specific calculation formula F is as follows:
Wherein alpha represents the gradient of a gradient road section monitored by the GPS module, and h 1 The liquid level height of the oil tank corresponding to the slope alpha of the vehicle monitored by the liquid level meter is shown, and l represents the side length of the bottom surface of the oil tank of the vehicle;
step five (2): calculating the oil consumption condition of the vehicle reaching the gradient road section by using a calculation formula G, and calculating the external oil filling quantity of the vehicle by combining the oil quantity of the oil tank when the vehicle reaches the gradient road section and the residual oil quantity before the vehicle is subjected to a mission;
step five (3): and (5) comparing the calculation result in the step (2) with the oiling information input by the driver into the service platform terminal, and judging whether the external oiling information input by the driver is accurate or not.
5. An enterprise fleet fueling and fuel consumption management system based on the internet of things implemented based on the method of any one of claims 1-4, characterized in that: the system comprises a service platform mobile terminal, a driver terminal, a fleet fueling module, a GPS module, a prediction processing module and a fuel consumption management module;
the prediction processing module and the oil consumption management module are arranged at the mobile end of the service platform;
the service platform mobile terminal is used for inputting enterprise drivers and vehicle license plate information thereof, receiving fueling application information sent by a driver terminal, receiving vehicle running information uploaded by the GPS module, judging whether to control the fleet fueling module to fueling the vehicle of the application driver according to the fueling application information, and receiving fueling information fed back by the fleet fueling module;
The service platform mobile terminal comprises an information inquiry unit, an information calling unit and a control unit;
the information inquiry unit inquires corresponding vehicles according to the oiling application information of the drivers of enterprises, the number of times of outgoing tasks received in the time interval of the last oiling distance application time, and the inquiry information is transmitted to the information calling unit;
the information calling unit receives the query information transmitted by the information query unit, calls historical refueling data of the corresponding vehicle according to the refueling application information of the enterprise driver, calculates the residual oil quantity of the oil tank of the corresponding vehicle before the task is discharged at this time based on the calling information and the query result, and transmits the calculation result to the control unit and the oil consumption management module;
the control unit receives the calculation result transmitted by the information calling unit, predicts whether the residual oil quantity of the corresponding vehicle can meet the requirement according to the condition of the current outgoing task of the corresponding vehicle, controls the fleet oiling module to carry out oiling on the vehicle according to the prediction result, and transmits oiling information to the prediction processing module;
the driver terminal is used for sending the vehicle refueling application information of the driver and the external refueling information of the driver to the mobile terminal of the service platform, receiving the vehicle refueling amount confirmation information fed back by the mobile terminal of the service platform, and secondarily confirming the vehicle refueling information;
The vehicle team oiling module is used for receiving the oiling information of the vehicle of the driver, which is sent by the mobile terminal of the service platform, oiling the vehicle of the driver according to the received information, and sending the oiling information to the mobile terminal of the service platform;
the GPS module is used for recording real-time running information of the corresponding enterprise vehicles and uploading the recorded information to the mobile terminal of the service platform;
the GPS module is used for recording real-time driving mileage, driving road conditions, driving time under each road condition and average rotating speed of an engine of the enterprise vehicle under each road condition of the corresponding enterprise vehicle, and uploading recorded information to a prediction processing module arranged on a mobile end of the service platform;
the prediction processing module is used for predicting whether the vehicle needs to be refueled outside an enterprise and evaluating the safety of the vehicle in the running process;
the prediction processing module comprises an information receiving unit, an enterprise vehicle oil consumption calculating unit, an enterprise external oiling prediction unit and a safety evaluation unit;
the information receiving unit receives the record information uploaded by the GPS module and the vehicle refueling information transmitted by the control unit, and transmits the received content to the enterprise vehicle fuel consumption calculating unit;
The enterprise vehicle oil consumption calculation unit receives the recorded information transmitted by the information receiving unit, calculates the oil consumption condition of the enterprise vehicle by combining the load information of the corresponding enterprise vehicle, and transmits the calculation result to the enterprise external oil filling prediction unit and the safety evaluation unit;
the enterprise external oil filling prediction unit receives the calculation result transmitted by the enterprise vehicle oil consumption calculation unit, predicts the real-time oil consumption of the corresponding vehicle based on the calculation result, calculates the real-time residual oil quantity of the vehicle according to the predicted real-time oil consumption, predicts whether the vehicle can finish an outgoing task by using the residual oil quantity based on the running road conditions of the vehicle in the residual running mileage and the running time of the vehicle under each running road condition predicted by the vehicle GPS module, predicts the farthest distance that the corresponding vehicle can run under the residual oil quantity when the outgoing task cannot be finished by using the residual oil quantity, searches the optimal oil filling point for filling the vehicle, and transmits the vehicle oil filling information to the oil consumption management module;
the safety evaluation unit receives the calculation result transmitted by the enterprise vehicle oil consumption calculation unit, judges whether the calculation result is lower than the oil tank liquid level change value in the corresponding running time of the vehicle, if yes, the coordinate system is utilized to represent the corresponding enterprise vehicle oil level, the change values of different time periods under each road condition are represented, the instantaneous descending speed of the corresponding enterprise vehicle oil level at different time points under each road condition is calculated according to the coordinate distribution condition, a linear equation is constructed according to the calculated instantaneous descending speed, whether the corresponding enterprise vehicle oil level change speed is in a stable state is predicted, if not, the oil leakage condition of the vehicle in the running process is predicted, the prediction result is transmitted to the mobile end of the service platform, and the service platform mobile transmits alarm information to the driver terminal according to the prediction result;
The fuel consumption management module is used for judging whether the external refueling information of the driver vehicle uploaded by the driver terminal is accurate or not.
6. The internet of things-based enterprise fleet fueling and fuel consumption management system as set forth in claim 5, wherein: the oil consumption management module comprises an oil tank oil quantity calculation unit, a driver oil filling quantity calculation unit and a judgment unit;
the fuel tank fuel quantity calculation unit receives the prediction result transmitted by the enterprise external fuel filling prediction unit, calculates the fuel quantity of the fuel tank of the vehicle at the moment by utilizing the gradient of the vehicle running on a gradient road section monitored by the GPS module, the fuel tank liquid level value monitored by the liquid level meter and the vehicle fuel tank specification when the vehicle is predicted to be externally refueled, and transmits the calculation result to the driver fuel filling quantity calculation unit;
the driver oil filling amount calculating unit receives the calculation result transmitted by the oil tank oil amount calculating unit and the calculation result transmitted by the information calling unit, calculates the external oil filling amount of the vehicle by calculating the oil consumption condition of the vehicle reaching the gradient road section and combining the oil amount of the oil tank when the vehicle reaches the gradient road section and the residual oil amount before the vehicle takes out the task, and transmits the calculation result to the judging unit;
The judging unit receives the calculation result transmitted by the driver fueling quantity calculating unit, compares the received content with fueling information of the driver input service platform terminal, and judges whether the external fueling information input by the driver is accurate or not.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210427749.9A CN115086358B (en) | 2022-04-22 | 2022-04-22 | Enterprise fleet oiling and oil consumption management system and method based on Internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210427749.9A CN115086358B (en) | 2022-04-22 | 2022-04-22 | Enterprise fleet oiling and oil consumption management system and method based on Internet of things |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115086358A CN115086358A (en) | 2022-09-20 |
| CN115086358B true CN115086358B (en) | 2024-04-09 |
Family
ID=83246819
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210427749.9A Active CN115086358B (en) | 2022-04-22 | 2022-04-22 | Enterprise fleet oiling and oil consumption management system and method based on Internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115086358B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106289297A (en) * | 2016-10-09 | 2017-01-04 | 思建科技有限公司 | A kind of vehicle Fuel Oil Remaining distance travelled computational methods and system |
| CN109902869A (en) * | 2019-02-26 | 2019-06-18 | 广州恒众车联网智能电子技术有限公司 | Method, apparatus, computer equipment and the storage medium that vehicle is predicted up to mileage |
| CN112785055A (en) * | 2021-01-18 | 2021-05-11 | 优必爱信息技术（北京）有限公司 | Vehicle refueling date prediction method and device |
| CN113626435A (en) * | 2021-08-04 | 2021-11-09 | 成都趣油科技有限公司 | Skid-mounted gas station vehicle management method and system |
| CN114202313A (en) * | 2021-12-15 | 2022-03-18 | 中国电信股份有限公司 | Vehicle fuel consumption management method and device, computer storage medium and electronic equipment |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9909889B2 (en) * | 2016-06-21 | 2018-03-06 | David R. Hall | Mobile vehicle refueling method |
| US10268199B2 (en) * | 2016-08-16 | 2019-04-23 | Ford Global Technologies, Llc | Managing vehicle refueling operations |
-
2022
- 2022-04-22 CN CN202210427749.9A patent/CN115086358B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106289297A (en) * | 2016-10-09 | 2017-01-04 | 思建科技有限公司 | A kind of vehicle Fuel Oil Remaining distance travelled computational methods and system |
| CN109902869A (en) * | 2019-02-26 | 2019-06-18 | 广州恒众车联网智能电子技术有限公司 | Method, apparatus, computer equipment and the storage medium that vehicle is predicted up to mileage |
| CN112785055A (en) * | 2021-01-18 | 2021-05-11 | 优必爱信息技术（北京）有限公司 | Vehicle refueling date prediction method and device |
| CN113626435A (en) * | 2021-08-04 | 2021-11-09 | 成都趣油科技有限公司 | Skid-mounted gas station vehicle management method and system |
| CN114202313A (en) * | 2021-12-15 | 2022-03-18 | 中国电信股份有限公司 | Vehicle fuel consumption management method and device, computer storage medium and electronic equipment |
Non-Patent Citations (2)
| Title |
|---|
| 《车载加油蒸汽回收系统设计与系统建模及实验研究》;蔡锦榕;《工程科技Ⅱ辑》(第2011年第05期);全文 * |
| Alexander Czenczek ; Victoria Clatterbuck ; Iksu Oh ; Thomas Hutson ; Preston Williams ; William Scherer.《Domestic oil by rail distribution analysis》.《 2015 Systems and Information Engineering Design Symposium》.2015,全文. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115086358A (en) | 2022-09-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20230237857A1 (en) | System and Method for Scheduling Vehicle Maintenance and Service | |
| CA2951583C (en) | System and method for recommending charging station for electric vehicle | |
| US20020059075A1 (en) | Method and system for managing a land-based vehicle | |
| CN109915245B (en) | Heavy-duty vehicle emission supervision system | |
| KR100871913B1 (en) | System and its method for providing information of driver's driving pattern | |
| US20110208567A9 (en) | System and method for managing a fleet of remote assets | |
| US8095279B2 (en) | Systems and methods for improving haul route management | |
| CN101064025A (en) | System and method for vehicle information early warning and part service-life forecasting | |
| US20020065698A1 (en) | System and method for managing a fleet of remote assets | |
| CN108417022B (en) | Vehicle utilization scheduling method suitable for new energy special vehicle platform | |
| US20070250229A1 (en) | Vehicle information early warning and parts life prediction system and method therefor | |
| US20130226392A1 (en) | Systems and methods for advising customers regarding vehicle operation and maintenance | |
| CN107228679A (en) | A kind of low oil mass based reminding method of automobile based on road conditions and device | |
| CN115086358B (en) | Enterprise fleet oiling and oil consumption management system and method based on Internet of things | |
| CN112740243A (en) | Remote fuel monitoring system, vehicle-mounted device, vehicle or machine, server, remote fuel monitoring method, remote fuel monitoring program, and storage medium | |
| EP1191156B1 (en) | System for supplying fuel to construction machine | |
| CN110645985B (en) | Voice navigation system and method for strip mine truck | |
| CN202994245U (en) | Tracking and tracing system used for monitoring oil quantity | |
| CN108133345A (en) | A kind of method and system that off-duty train is judged based on lorry magnanimity track data | |
| DE102017104195A1 (en) | Method for the maintenance of an autonomous vehicle and autonomous vehicle for carrying out the method | |
| JP2022069173A (en) | Charging reservation system | |
| CN106709633A (en) | On-line supervision system for casting type asphalt concrete, and supervision method | |
| JP3656358B2 (en) | Engine management device | |
| US20230094983A1 (en) | Vehicle management system and store control device | |
| CN113532454A (en) | Vehicle oil quantity early warning method based on historical oil consumption and path planning |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20240304 Address after: Room 401-35, Building A, No. 159 Chengjiang Middle Road, Jiangyin City, Wuxi City, Jiangsu Province, 214431 Applicant after: Jiangsu Ruiyuan Information Technology Co.,Ltd. Country or region after: China Address before: Room 407-8, Block A, No. 159, Chengjiang Middle Road, Jiangyin, Wuxi City, Jiangsu Province, 214000 Applicant before: Jiangyin Shengyu Information Technology Co.,Ltd. Country or region before: China |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |