Method and system for using oil at construction site

Abstract

The present invention provides a method and system for using oil at construction sites, which relates to the technical field of data processing in commerce or finance. By comprehensively analyzing historical oil consumption demand data, the execution situation and status information of fuel trucks, the invention introduces the oil consumption demand fluctuation coefficient of the user side and the completion coefficient of the fuel truck, so as to realize the priority classification and screening of fuel trucks; it can not only effectively predict the oil consumption demand trend of users, but also optimize the fuel truck scheduling based on real-time data, reduce resource waste and improve refueling efficiency; at the same time, through the analysis and calculation of the cloud data platform, the economic fluctuation coefficient of each fuel truck is incorporated into the decision-making process to ensure that the finally selected fuel truck not only meets the user's needs, but also achieves the best economic effect; it improves the intelligent level of oil use management at construction sites, realizes more efficient resource allocation, and provides a reliable guarantee for the smooth progress of the construction site.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing in business or finance, and specifically to a method and system for fuel use at construction sites. Background Art

[0002] With the rapid development of urban construction and infrastructure projects, the scientific and intelligent level of fuel management at construction sites has been increasingly emphasized. Traditional fueling methods at construction sites often rely on manual experience and lack systematic monitoring and data analysis, resulting in resource waste and low efficiency during the fueling process. In recent years, with the rapid development of technologies such as the Internet of Things, big data, and cloud computing, fuel management at construction sites has gradually developed towards automation and intelligence. Through the collection and analysis of historical data, relevant enterprises have begun to explore how to use data-driven decision-making to optimize the fueling process at construction sites, improve the utilization efficiency of resources, and meet user needs. For example, using sensors to monitor the fuel quantity status and implementing precise fueling has become a trend in more and more construction sites;

[0003] In the prior art, the publication number is CN116862139A, and the name is an intelligent scheduling decision method, device, and system for a refueling vehicle; wherein, the method includes using airport flight information, airport apron information, refueling vehicle information, and refueling staff information to plan the priority order of flights to be refueled, and planning the target refueling staff and target refueling vehicle respectively matching the flights to be refueled to obtain task planning information; according to the task planning information, allocating corresponding refueling tasks to the target refueling staff, and the data information of the refueling tasks includes refueling task numbers, flight numbers of the flights to be refueled, aircraft types of the flights to be refueled, aprons where the flights to be refueled are located, fuel quantities required for the flights to be refueled, remaining time estimated to complete the refueling tasks, and recommended routes.

[0004] However, the existing fueling technologies at construction sites still have many deficiencies: First, although there are existing technical means to collect and upload fueling data, most systems lack in-depth analysis of historical fuel demand and cannot accurately predict the fluctuations in fuel demand at the user end; this lack of prediction directly affects the scheduling efficiency of refueling vehicles, resulting in overly long waiting times and inability to meet construction needs in a timely manner; Second, for the status of different refueling vehicles and their execution situations in meeting user needs, there is often a lack of effective comprehensive evaluation mechanisms in the prior art; information such as the actual available fuel storage, fuel consumption, and driving time of refueling vehicles is not fully considered, resulting in a lack of sufficient scientific basis for decision-making during the selection of refueling vehicles; In addition, the prior art is relatively simple in terms of priority classification and fails to effectively distinguish the importance of different refueling vehicles in meeting fuel demand, further affecting the efficiency and economy of the entire fueling process; These deficiencies not only increase the operating costs at construction sites but also may cause project schedule delays;

[0005] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present disclosure. Therefore, it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0006] The object of the present invention is to provide a method and system for using oil at a construction site to solve the problems raised in the above background art.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A method for using oil at a construction site, the specific steps include:

[0009] Step S1: In the previous monitoring time period, collect the historical oil consumption demand data of the user side in M construction site refueling events, as well as the execution situation and status data of each refueling vehicle to complete these oil consumption demands, and upload these data to the cloud data platform for storage;

[0010] Step S2: In the current refueling event of the user side, determine that the oil consumption demand data includes the oil quantity to be refueled, the maximum waiting time, and the oil quantity demand fluctuation index;

[0011] And determine the status data of each refueling vehicle, including the remaining oil reserve, as well as the oil quantity consumed and the predicted driving time when arriving at the user side area;

[0012] The execution situation data includes the first error average value of the actual available oil reserve of each refueling vehicle after completing the oil consumption demands of the user side M times in the previous monitoring time period, and the second error average value of the actual driving time;

[0013] Step S3: In the cloud data platform, analyze the historical oil consumption demand data of the user side in the previous monitoring time period to calculate the oil consumption demand fluctuation coefficient of the user side;

[0014] Step S4: In the cloud data platform, obtain the execution situation data of each refueling vehicle to complete the oil consumption demands of the user side in the previous monitoring time period, and calculate the completion coefficient based on the execution situation data;

[0015] Step S5: In the cloud data platform, calculate the economic fluctuation coefficient of each refueling vehicle arriving at the user side area according to the oil quantity consumed and the predicted driving time when each refueling vehicle arrives at the user side area from the current position;

[0016] Step S6: According to the oil consumption demand data corresponding to the current refueling event of the user side, classify each refueling vehicle into priority levels. Among them, the refueling vehicles that meet the oil quantity to be refueled and the maximum waiting time are classified into the first priority sequence, and among the remaining refueling vehicles, the refueling vehicles that meet the maximum waiting time are classified into the second priority sequence;

[0017] Step S7: Among the several refueling trucks determined by the first priority sequence, analyze in combination with the corresponding oil demand fluctuation coefficient and completion coefficient to generate a first screening index for providing a screening strategy for the refueling trucks;

[0018] Step S8: Among the several refueling trucks determined by the second priority sequence, analyze in combination with the corresponding oil demand fluctuation coefficient and completion coefficient to generate a second screening index for providing a screening strategy for the refueling trucks;

[0019] Step S9: Among the several refueling trucks determined by the first screening index and the second screening index, determine the final selection of refueling trucks based on the economic fluctuation coefficient.

[0020] A system for oil use at a construction site, the system being used to execute the method for oil use at the construction site, including:

[0021] Data acquisition and upload module: Used to collect the historical oil demand data of the user side in M construction site refueling events, as well as the execution situation and status data of each refueling truck to complete these oil demands during the previous monitoring period, and upload this data to the cloud data platform for storage;

[0022] Data determination module: Used to determine that the oil demand data in the refueling event of the current user side includes the oil quantity to be filled, the maximum waiting time, and the oil quantity demand fluctuation index;

[0023] And determine the status data of each refueling truck, including the remaining oil reserve, as well as the oil quantity consumed and the predicted driving time when arriving at the user side area;

[0024] The execution situation data includes the first error average value of the actual available oil reserve of each refueling truck after completing the oil demands of the user side M times during the previous monitoring period, and the second error average value of the actual driving time;

[0025] Oil demand fluctuation coefficient generation module: Used to analyze the historical oil demand data of the user side during the previous monitoring period in the cloud data platform to calculate the oil demand fluctuation coefficient of the user side;

[0026] Completion coefficient generation module: Used to obtain the execution situation data of each refueling truck to complete the oil demands of the user side during the previous monitoring period in the cloud data platform, and calculate the completion coefficient based on the execution situation data;

[0027] Economic fluctuation coefficient generation module: In the cloud data platform, calculate the economic fluctuation coefficient of each refueling truck arriving at the user side area according to the oil quantity consumed and the predicted driving time when each refueling truck arrives at the user side area;

[0028] Priority Sequence Division Module: It is used to classify the priority of each refueling vehicle according to the fuel demand data corresponding to the refueling event of the current client. Among them, the refueling vehicles that meet the fuel quantity to be refueled and the maximum waiting time are classified into the first priority sequence, and among the remaining refueling vehicles, the refueling vehicles that meet the maximum waiting time are classified into the second priority sequence;

[0029] First Screening Index Generation Module: It is used to analyze among the several refueling vehicles determined by the first priority sequence, combining the corresponding fuel demand fluctuation coefficient and completion coefficient, and generate the first screening index for providing a screening strategy for the refueling vehicle;

[0030] Second Screening Index Generation Module: It is used to analyze among the several refueling vehicles determined by the second priority sequence, combining the corresponding fuel demand fluctuation coefficient and completion coefficient, and generate the second screening index for providing a screening strategy for the refueling vehicle;

[0031] Final Selection Module: It is used to determine the final selection of the refueling vehicle based on the economic fluctuation coefficient among the several refueling vehicles determined by the first screening index and the second screening index.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows: By comprehensively analyzing the historical fuel demand data, the execution situation and status information of the refueling vehicle, introducing the fuel demand fluctuation coefficient of the client and the completion coefficient of the refueling vehicle, the priority classification and screening of the refueling vehicle are realized; It can not only effectively predict the fuel demand trend of users, but also optimize the refueling vehicle scheduling based on real-time data, reduce resource waste, and improve refueling efficiency; At the same time, through the analysis and calculation of the cloud data platform, the economic fluctuation coefficient of each refueling vehicle is incorporated into the decision-making process to ensure that the finally selected refueling vehicle not only meets the user's needs, but also achieves the best economic effect; It improves the intelligent level of fuel management at the construction site, realizes more efficient resource allocation, and provides a reliable guarantee for the smooth progress of the construction site. Brief Description of the Drawings

[0033] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0034] Figure 2 It is a block diagram of the overall system module of the present invention. Detailed Embodiment

[0035] In order to make the purpose, technical solution and advantages of the present invention clearer and more understandable, the following further elaborates on the present invention in combination with specific embodiments.

[0036] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the ordinary meanings understood by those of ordinary skill in the field to which the present invention pertains. The "first", "second" and similar terms used in the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. The terms such as "comprising" or "including" mean that the elements or objects appearing before this word cover the elements or objects listed after this word and their equivalents, without excluding other elements or objects. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left" and "right" are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0037] Embodiment 1:

[0038] Please refer to Figure 1 , the present invention provides a technical solution:

[0039] A method for using oil at a construction site, the specific steps include:

[0040] Step S1: In the previous monitoring time period, collect the historical oil consumption demand data of the user side in M construction site refueling events, as well as the execution situation and status data of each refueling vehicle to complete these oil consumption demands, and upload these data to the cloud data platform for storage;

[0041] Step S2: In the current refueling event of the user side, determine that the oil consumption demand data includes the oil quantity to be filled, the maximum waiting time, and the oil quantity demand fluctuation index;

[0042] And determine the status data of each refueling vehicle, including the remaining oil storage, the oil quantity consumed when arriving at the user side area, and the predicted driving time;

[0043] The execution situation data includes the first error average value of the actual available oil storage of each refueling vehicle after completing the oil consumption demands of the user side M times in the previous monitoring time period, and the second error average value of the actual driving time;

[0044] Step S3: In the cloud data platform, analyze the historical oil consumption demand data of the user side in the previous monitoring time period to calculate the oil consumption demand fluctuation coefficient of the user side;

[0045] Step S4: In the cloud data platform, obtain the execution situation data of each refueling vehicle to complete the oil consumption demands of the user side in the previous monitoring time period, and calculate the completion coefficient based on the execution situation data;

[0046] Step S5: In the cloud data platform, calculate the economic fluctuation coefficient of each refueling vehicle when it arrives at the user's area based on the fuel consumption and predicted driving time from the current position to the user's area.

[0047] Step S6: Classify each refueling vehicle according to the priority based on the fuel demand data corresponding to the current refueling event at the user end. Among them, the refueling vehicles that meet the fuel quantity to be filled and the maximum waiting time are classified into the first priority sequence, and among the remaining refueling vehicles, the refueling vehicles that meet the maximum waiting time are classified into the second priority sequence.

[0048] Step S7: Among the several refueling vehicles determined by the first priority sequence, analyze by combining the corresponding fuel demand fluctuation coefficient and completion coefficient to generate the first screening index for providing a screening strategy for the refueling vehicle.

[0049] Step S8: Among the several refueling vehicles determined by the second priority sequence, analyze by combining the corresponding fuel demand fluctuation coefficient and completion coefficient to generate the second screening index for providing a screening strategy for the refueling vehicle.

[0050] Step S9: Among the several refueling vehicles determined by the first screening index and the second screening index, determine the final refueling vehicle selection based on the economic fluctuation coefficient.

[0051] Further explanation:

[0052] Set the previous monitoring time period as T; in this embodiment, T is the past week or month, which is used as the data collection cycle.

[0053] Mark the construction site refueling events of the current user end in the previous monitoring time period to form an event sequence set {1, 2,..., M}, where j represents the jth construction site refueling event in the event sequence set, M represents the total number of construction site refueling events of the user end, and j ∈ {1, 2,..., M}.

[0054] Mark each refueling vehicle to form a refueling vehicle quantity sequence set {1, 2,..., N}, where i represents the ith refueling vehicle in the quantity sequence set, N represents the total number of refueling vehicles, and i ∈ {1, 2,..., N}.

[0055] In the construction site refueling events of the current user end, record the fuel quantity to be filled, the maximum waiting time, and the fuel quantity demand fluctuation index included in the fuel demand data as DJy, ZDt, and YBd respectively.

[0056] And record the remaining fuel reserve, the fuel consumption when arriving at the user's area, and the predicted driving time included in the corresponding status data of each refueling vehicle as ;

[0057] Regarding the fuel consumption and predicted travel time of each refueling vehicle when it arrives at the user's area, the specific description is as follows:

[0058] Obtaining the driving distance:

[0059] Use the GPS system or map service to obtain the driving distance of the refueling vehicle from the departure location to the user's area;

[0060] The fuel consumption (L / km) is determined in the following ways:

[0061] Actual test: Conduct an actual fuel consumption test on the refueling vehicle and record the fuel consumption under different driving conditions;

[0062] Provided by the manufacturer: Refer to the fuel consumption data provided by the refueling vehicle manufacturer;

[0063] Multiply the driving distance by the fuel consumption to obtain the fuel consumed.

[0064] For the calculation of the predicted travel time:

[0065]

[0066] Among them, is the average driving speed of the i-th refueling vehicle;

[0067] For the average driving speed, estimate the average driving speed based on the vehicle's historical data or actual traffic conditions.

[0068] Define the calculation formula for the first error average value of the actual available fuel storage as follows:

[0069]

[0070] Among them represents the first error average value of the i-th refueling vehicle after completing M user-end fuel demands in the previous monitoring period, represents the actual available fuel storage corresponding to the j-th construction site refueling event of the i-th refueling vehicle in the previous monitoring period, represents the remaining fuel storage corresponding to the j-th construction site refueling event of the i-th refueling vehicle in the previous monitoring period;

[0071] Define the calculation formula for the second error average value of the actual travel time as follows:

[0072]

[0073] Among them represents the second error average value of the i-th refueling vehicle after completing M user-end fuel demands in the previous monitoring period, represents the actual travel time corresponding to the j-th construction site refueling event of the i-th refueling vehicle in the previous monitoring period, represents the predicted driving time corresponding to the j-th construction site refueling event of the i-th refueling vehicle in the previous monitoring period.

[0074] Further explanation: calculating the oil demand fluctuation coefficient of the user side specifically includes:

[0075] On the cloud data platform, obtain the historical oil demand data in the previous monitoring period;

[0076] The oil quantity to be refueled is the amount of oil required for each refueling event (unit: liter)

[0077] The maximum waiting time is the longest time expected by the user in each refueling event (unit: minute);

[0078] The oil quantity demand fluctuation index is the degree of fluctuation of the oil demand;

[0079] Store this data in a structured database for subsequent real-time analysis and processing;

[0080] Use statistical analysis methods to process the historical oil demand data and calculate the oil demand fluctuation coefficient;

[0081] Define the calculation formula of the oil quantity demand fluctuation index as follows:

[0082]

[0083] where, represents the maximum value of the oil quantity to be refueled in the previous monitoring period;

[0084] represents the minimum value of the oil quantity to be refueled in the previous monitoring period;

[0085] is the mean value of the historical oil quantity to be refueled;

[0086] The value range of YBd is [0, +∞). When YBd is closer to 0, it indicates that the oil demand of the user side is more stable; when the value of YBd is larger, it indicates that the change range of the oil demand of the user side is larger;

[0087] Denote the mean value and standard deviation of the historical oil demand data as and , and the calculation formulas are as follows:

[0088]

[0089]

[0090] Define the oil demand fluctuation coefficient as the standard deviation and the mean value The ratio is calculated using the formula:

[0091]

[0092] CV is standardized using the following formula:

[0093]

[0094] is the coefficient of fluctuation of oil demand after standardization, with a value range within (0, 1); CV is the original coefficient of fluctuation of oil demand, is the minimum value of CV in the dataset; is the maximum value of CV in the dataset;

[0095] When The closer the value is to 0, the more stable the oil demand at the user end;

[0096] When The closer the value is to 1, the greater the amplitude of fluctuation of the oil demand at the user end and the less stable it is.

[0097] Furthermore, data on the execution status of each refueling vehicle in meeting the oil demand at the user end during the previous monitoring period is obtained, and the completion coefficient is calculated based on the execution status data, specifically including:

[0098] The completion coefficient is defined as the overall completion of the refueling vehicle in executing the oil demand at the user end, and the calculation formula is:

[0099]

[0100] Among them, is the completion coefficient of the i-th refueling vehicle during the previous monitoring period; is the correction coefficient used to avoid from taking a value of 0, and is selected within the range of (0.1, 0.65); in this embodiment, The initial value of

[0101] is the first average error after the i-th refueling vehicle has completed M times of oil demand at the user end during the previous monitoring period;

[0102] is the second average error after the i-th refueling vehicle has completed M times of oil demand at the user end during the previous monitoring period;

[0103] Set The valid value range of

[0104] When The closer the value approaches 0, the worse the performance of the refueling vehicle in executing the user's requirements;

[0105] When The closer the value approaches P1, the better the performance of the refueling vehicle in executing the user's requirements. and P1 are determined according to specific numerical values by the expert group through experimental data, which will not be elaborated here, and The other value ranges of are not within the protection scope of this embodiment, so they will not be elaborated here.

[0106] Further explanation, calculating the economic fluctuation coefficient of each refueling vehicle arriving at the user end area specifically includes:

[0107] Define the economic fluctuation coefficient corresponding to the arrival of the i-th refueling vehicle at the user end area as:

[0108]

[0109] Among them, is the economic fluctuation coefficient corresponding to the arrival of the i-th refueling vehicle from the current position to the user end area;

[0110] is the fuel consumption of the i-th refueling vehicle when it arrives at the user end area; the calculation formula is:

[0111]

[0112] Among them, Xd represents the driving distance to the user end area, is the fuel consumption of the i-th refueling vehicle;

[0113] is the predicted driving time of the i-th refueling vehicle, and the calculation formula is:

[0114]

[0115] Among them, is the average driving speed of the i-th refueling vehicle;

[0116] is a weighting factor used to adjust the calculation of the economic fluctuation coefficient, The value range is [0.1, 10]; Used to ensure that The effective value range of is (P2, P3); The other value ranges of are not within the protection scope of this application embodiment, so they will not be elaborated here;

[0117] The maximum waiting time ZDt determined according to the current user end; on the premise that ≤ZDt, The economic fluctuation coefficient corresponding to the minimum value is taken as the value of P2;

[0118] When The closer it is to P2, the better the economy of the refueling vehicle, the fuel consumption is reasonable, and the driving time meets the expectation;

[0119] When The closer it is to P3, the worse the economy of the refueling vehicle.

[0120] The specific values of, P2, and P3 are determined by the expert group based on experimental data and will not be elaborated.

[0121] Further explanation, the acquisition of the first priority sequence and the second priority sequence specifically includes:

[0122] Screen out the refueling vehicles in the refueling vehicle quantity sequence set {1, 2,..., N} that meet to form the first priority sequence {1, 2,..., U1}, and set u1 ∈ {1, 2,..., U1}, and u1 represents the u1-th refueling vehicle in the first priority sequence, and U1 is the total number of refueling vehicles that meet ;

[0123] At the same time, screen among the refueling vehicles in the quantity sequence set {1, 2,..., N} other than {1, 2,..., U1}, and screen out the refueling vehicles that meet to form the second priority sequence {1, 2,..., U2}, and set u2 ∈ {1, 2,..., U2}, and u2 represents the u2-th refueling vehicle in the second priority sequence, and U2 is the total number of refueling vehicles in the second priority sequence, and U2 ≤ N - U1.

[0124] Further explanation, the calculation formula for the first screening index of the first priority sequence is defined as follows:

[0125]

[0126] Among them, is the first screening index of the u1-th refueling vehicle in the first priority sequence with respect to the oil demand fluctuation coefficient of the user end; is the standardized oil demand fluctuation coefficient;

[0127] is the completion degree coefficient of the u1-th refueling vehicle when executing the oil demand of the user end;

[0128] is the weight factor, which is used to adjust the influence of the oil demand fluctuation coefficient and the completion degree coefficient on the first screening index; , and The value ranges are all within the range of (0, 1);

[0129] Set the first screening index The effective value range of is (0, P1]; the remaining value ranges are not within the protection scope of this embodiment, so they will not be elaborated; set the initial judgment threshold of the first screening index to 0.5P1; and then divide the value range (0, P1] of the first screening index into and ; The screening strategy for the refueling vehicle is as follows:

[0130] Based on when The closer the value is to 0, the worse the performance of the refueling vehicle in executing the user's demand; The closer the value is to P1, the better the performance of the refueling vehicle in executing the user's demand;

[0131] When The closer the value is to 0, it means that the oil demand at the user end is more stable;

[0132] When The closer the value is to 1, it means that the fluctuation range of the oil demand at the user end is larger and more unstable;

[0133] When , it means that the performance of the u1-th refueling vehicle in meeting the user's demand is poor, and it is recommended to reduce the usage frequency of this refueling vehicle; based on the expert group system's analysis of experimental data, when , set , The setting of means that in the case of poor performance, the influence of the fluctuation coefficient is emphasized in order to better reflect the instability of the demand;

[0134] The setting of makes the influence of the completion degree on the screening index relatively weakened, reflecting that in a high-fluctuation environment, refueling vehicles with low completion degrees should not be emphasized;

[0135] For the influence of :

[0136] If tends to 1, the user's oil demand fluctuates greatly and is unstable. At this time, even if the refueling vehicle improves in terms of completion degree, the overall is at a low level, which means that the refueling vehicle is difficult to maintain a stable service efficiency in a frequently changing demand environment;

[0137] If the value is closer to 0, the user demand is relatively stable. If is also at a low level at this time, then will still be low, indicating that the refueling vehicle cannot effectively meet the basic needs of users;

[0138] for Impact:

[0139] like Approaching 0, the tanker truck performs poorly in executing user needs and cannot complete the scheduled task, resulting in reduce;

[0140] like Approaching P1, but At a high level, in this case, although the refueling trucks were able to complete the task, the overall performance was still poor due to the sharp fluctuations in demand;

[0141] when When it falls within this range, it is recommended to reduce the frequency of use of the refueling vehicle, and the frequency of use is reduced by 10% of the current value each time. This value is adjusted according to the experimental data of the expert group system and is not limited. Especially when and If both perform poorly, replacement or optimization of resource allocation should be considered;

[0142] when When , it means that the u1-th refueling truck performs well in meeting user needs, and it is recommended to increase the frequency of use of this refueling truck. When setting , The setting of indicates that in good performance, although demand fluctuations are small, completion is more important;

[0143] The setting of indicates that in good performance, the impact of completion is emphasized, reflecting the efficient execution of the refueling truck in a stable environment;

[0144] for Impact:

[0145] like Approaching 0, the user's oil demand is relatively stable, which provides a good service environment for refueling vehicles; in this case, even if Fluctuates, as long as its value is not at a low level, It will also remain at a high level;

[0146] like Approaching 1, although the demand fluctuates greatly, the tanker truck can effectively cope with these fluctuations, and can still maintain a high ;

[0147] for Impact:

[0148] like Approaching P1, the refueling vehicle performs well when executing user requirements and can meet the requirements quickly and accurately, which will directly improve the value;

[0149] If is a low-level value, but becomes more acceptable: If the user demand fluctuates within 0.1, the overall performance of the refueling vehicle is still regarded as good;

[0150] When falls within this interval, it is recommended to increase the usage frequency of this refueling vehicle; especially when is a low-level value and is a high-level value, the utilization efficiency of resources will be maximized.

[0151] The low level of the above content represents below 20% of the current corresponding effective value range, and the high level is above 80% of the corresponding effective value range;

[0152] For example the low-level value is ; is a high level, , and the rest will not be elaborated.

[0153] Furthermore, the calculation formula for the second screening index defining the second priority sequence is as follows:

[0154]

[0155] Among them, is the second screening index of the u2-th refueling vehicle in the second priority sequence with respect to the oil demand fluctuation coefficient of the user side; is the standardized oil demand fluctuation coefficient;

[0156] is the completion coefficient of the u2-th refueling vehicle when executing the oil demand of the user side;

[0157] is the weight factor used to adjust the influence of the oil demand fluctuation coefficient and the completion coefficient on the second screening index; , and the value ranges are all within the range of (0, 1);

[0158] Set the effective value range of the second screening index to be (0, P1]; the rest of the value range is not within the protection scope of this embodiment; similarly, set the initial judgment threshold of the second screening index to 0.5P1; furthermore, in the value range (0, P1] of the second screening index, determine the value interval for the screening strategy as ;

[0159] Only when When , it means that the u2-th refueling truck performs well in meeting user needs. At this time, it is necessary to screen out a refueling truck that matches the current u2-th refueling truck in the second priority sequence to form a refueling truck combination; the matching strategy of the refueling truck combination is: add the remaining oil reserves of the two refueling trucks to the corresponding first error average value to obtain the final real-time superimposed oil reserves, and the final real-time superimposed oil reserves need to be greater than the amount of oil to be refueled on the user side. At the same time, it is necessary to limit the difference between the real-time superimposed oil reserves and the amount of oil to be refueled to within 10% of the amount of oil to be refueled, and express the difference as DJy×0.1; if it cannot be met, then re-search for any other two refueling truck combinations in the second priority sequence for analysis;

[0160] What needs to be determined is that in the two fuel trucks combined, only at least one of them must meet That's it;

[0161] Furthermore, if any other two refueling truck combinations in the second priority sequence are searched for analysis and two refueling trucks that meet the requirements cannot be found, then among any two refueling truck combinations that exceed DJy×0.1, the two refueling trucks with the smallest value exceeding DJy×0.1 are selected as the refueling truck combination to be screened.

[0162] Further explanation: The final selection of refueling trucks is determined based on the economic fluctuation coefficient, including:

[0163] will comply with The corresponding refueling trucks are screened out and the economic fluctuation coefficient corresponding to these refueling trucks when they arrive at the user end area is calculated ;

[0164] will comply with The corresponding refueling trucks are screened out, and the corresponding refueling truck combination is determined, and the economic fluctuation coefficient corresponding to these refueling trucks when they arrive at the user end area is calculated. ;

[0165] The economic fluctuation coefficient for fuel trucks is:

[0166] When the economic fluctuation coefficient approaches P2, it means that the economy of the refueling vehicle is better, the fuel consumption is reasonable and the driving time is in line with expectations;

[0167] When the economic fluctuation coefficient approaches P3, the economic efficiency of the refueling vehicle is worse;

[0168] The economic fluctuation coefficient The corresponding refueling truck closest to P2 is given priority as the final refueling truck selection;

[0169] Secondly, the economic fluctuation coefficient The corresponding fuel truck closest to P2 is selected as an alternative fuel truck.

[0170] If the user side does not provide a fuel truck that meets in the current construction site refueling event, the initial judgment threshold for the first screening index is reduced by the K1 percentage value; and the reduced initial judgment threshold is used for the next construction site refueling event of the user side; in this embodiment, the initial value of the K1 percentage value is set to 3%; K1 can be adjusted according to the experimental data by the expert group and is not limited.

[0171] Embodiment 2:

[0172] Please refer to Figure 2 , a system for construction site fuel use, the system is used to execute the method for construction site fuel use, including:

[0173] Data collection and upload module: used to collect the historical fuel use demand data of the user side in M construction site refueling events, as well as the execution situation and status data of each fuel truck to complete these fuel use demands in the previous monitoring time period, and upload these data to the cloud data platform for storage;

[0174] Data determination module: used to determine that the fuel use demand data includes the fuel quantity to be filled, the maximum waiting time, and the fuel quantity demand fluctuation index in the current refueling event of the user side;

[0175] And determine the status data of each fuel truck, including the remaining fuel reserve, as well as the fuel consumption and predicted driving time when arriving at the user side area;

[0176] The execution situation data includes the first error average value of the actual available fuel reserve of each fuel truck after completing the fuel use demands of the user side M times in the previous monitoring time period, and the second error average value of the actual driving time;

[0177] Fuel demand fluctuation coefficient generation module: used to analyze the historical fuel use demand data of the user side in the previous monitoring time period in the cloud data platform to calculate the fuel demand fluctuation coefficient of the user side;

[0178] Completion coefficient generation module: used to obtain the execution situation data of each fuel truck to complete the fuel use demands of the user side in the previous monitoring time period in the cloud data platform, and calculate the completion coefficient based on the execution situation data;

[0179] Economic fluctuation coefficient generation module: in the cloud data platform, calculate the economic fluctuation coefficient of each fuel truck arriving at the user side area according to the fuel consumption and predicted driving time of each fuel truck from the current position to the user side area;

[0180] Priority sequence division module: used to classify each refueling vehicle into different priority levels according to the fuel consumption demand data corresponding to the current refueling event of the client. Among them, the refueling vehicles that meet the required refueling volume and the maximum waiting time are classified into the first priority sequence, and among the remaining refueling vehicles, those that meet the maximum waiting time are classified into the second priority sequence;

[0181] First screening index generation module: used to analyze among the several refueling vehicles determined by the first priority sequence, combining the corresponding fuel consumption demand fluctuation coefficient and completion coefficient, to generate the first screening index for providing a screening strategy for the refueling vehicle;

[0182] Second screening index generation module: used to analyze among the several refueling vehicles determined by the second priority sequence, combining the corresponding fuel consumption demand fluctuation coefficient and completion coefficient, to generate the second screening index for providing a screening strategy for the refueling vehicle;

[0183] Final selection module: used to determine the final refueling vehicle selection based on the economic fluctuation coefficient among the several refueling vehicles determined by the first screening index and the second screening index.

[0184] All the above formulas are dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0185] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, or by the combination of computer software and electronic hardware. Whether these functions are executed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0186] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. They can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0187] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application.

Claims

1. A method for using oil at a construction site, characterized in that, The specific steps include: Step S1: In the previous monitoring time period, collect the historical fuel consumption demand data of the user side in M construction site refueling events, as well as the execution situation and status data of each refueling vehicle to complete these fuel consumption demands, and upload this data to the cloud data platform for storage; Step S2: In the current refueling event of the user side, determine that the fuel consumption demand data includes the fuel quantity to be filled, the maximum waiting time, and the fuel quantity demand fluctuation index; And determine the status data of each refueling vehicle, including the remaining fuel storage, the fuel consumption and predicted driving time when arriving at the user side area; The execution situation data includes the first error average value of the actual available fuel storage of each refueling vehicle after completing the fuel consumption demands of the user side M times in the previous monitoring time period, and the second error average value of the actual driving time; Step S3: In the cloud data platform, analyze the historical fuel consumption demand data of the user side in the previous monitoring time period to calculate the fuel consumption demand fluctuation coefficient of the user side; Step S4: In the cloud data platform, obtain the execution situation data of each refueling vehicle to complete the fuel consumption demands of the user side in the previous monitoring time period, and calculate the completion coefficient based on the execution situation data; Step S5: In the cloud data platform, calculate the economic fluctuation coefficient of each refueling vehicle when arriving at the user side area according to the fuel consumption and predicted driving time when each refueling vehicle arrives at the user side area from the current position; Step S6: According to the fuel consumption demand data corresponding to the current refueling event of the user side, classify each refueling vehicle by priority. Among them, the refueling vehicles that meet both the fuel quantity to be filled and the maximum waiting time are classified into the first priority sequence, and among the remaining refueling vehicles, the refueling vehicles that meet the maximum waiting time are classified into the second priority sequence; Step S9: In the first screening index and the second screening index to determine a number of refueling vehicles, based on the economic fluctuation coefficient to determine the final refueling vehicle selection. Mark the construction site refueling events of the current user side in the previous monitoring time period to form an event sequence set {1, 2,..., M}, where j represents the jth construction site refueling event in the event sequence set, M represents the total number of construction site refueling events of the user side, and j ∈ {1, 2,..., M}; Mark each refueling vehicle to form a number sequence set {1, 2,..., N} of refueling vehicles, where i represents the ith refueling vehicle in the number sequence set, N represents the total number of refueling vehicles, and i ∈ {1, 2,..., N}; 2. The method for using oil at the construction site according to claim 1, wherein: Define the calculation formula for the first error average value of the actual available fuel storage as follows: Define the calculation formula for the second error average value of the actual driving time as follows: Calculate the fuel consumption demand fluctuation coefficient of the user side, specifically including: wherein represents the first error average value of the i-th refueling vehicle after completing M user-side fuel demand in the previous monitoring period, represents the actual available fuel storage corresponding to the j-th construction site refueling event of the i-th refueling vehicle in the previous monitoring period, represents the remaining fuel storage corresponding to the j-th construction site refueling event of the i-th refueling vehicle in the previous monitoring period; Define the calculation formula for the fuel quantity demand fluctuation index as follows: wherein represents the second error average value of the i-th refueling vehicle after completing M user-side fuel demand in the previous monitoring period, represents the actual driving time corresponding to the j-th construction site refueling event of the i-th refueling vehicle in the previous monitoring period, represents the predicted driving time corresponding to the j-th construction site refueling event of the i-th refueling vehicle in the previous monitoring period.

3. The method for using oil at the construction site according to claim 2, characterized in that: ​ ​ Among them, represents the maximum value of the fuel quantity to be refueled in the previous monitoring time period; Indicates the minimum value of the fuel quantity to be refueled during the previous monitoring time period; is the mean of the historical fuel quantity to be filled The value range of YBd is [0, +∞). When YBd approaches 0 more closely, it indicates that the oil consumption demand at the user end is more stable; when the value of YBd is larger, it indicates that the change range of the oil consumption demand at the user end is larger; Let the mean and standard deviation of historical oil demand data be denoted as and , respectively, and the calculation formulas are as follows: Define the oil demand fluctuation coefficient as the ratio of the standard deviation to the mean value . The formula is as follows: The following formula is used to standardize CV: is the standardized oil demand fluctuation coefficient, and its value range is within (0, 1); CV is the original oil demand fluctuation coefficient, is the minimum value of CV in the dataset; is the maximum value of CV in the dataset; When The closer its value approaches 0, the more stable the oil demand of the client is; When The closer the value is to 1, the greater the fluctuation range of the oil demand at the user end, and the more unstable it is.

4. The method for using oil at the construction site according to claim 3, characterized in that: Obtain the execution situation data of each refueling vehicle to complete the oil consumption demand at the user end in the previous monitoring time period, and calculate the completion coefficient based on the execution situation data, specifically including: Define the completion coefficient as the overall completion degree when the refueling vehicle executes the oil consumption demand at the user end. The calculation formula is: Among them, is the completion coefficient of the i-th refueling vehicle in the previous monitoring time period; is a correction coefficient used to avoid the situation where the value is 0, and the value range of is selected between (0.1, 0.65); is the first average error after the i-th refueling vehicle has completed the M user-end fuel demand in the previous monitoring time period; is the second average error after the i-th refueling vehicle completes the M times of fuel demand at the user end in the previous monitoring time period; Setting The valid value range of is [0, P1]; When The closer the value is to 0, the worse the performance of the refueling vehicle in executing the user's requirements; When The closer the value is to P1, the better the performance of the fuel truck in executing the user's requirements.

5. The method for using oil at the construction site according to claim 4, characterized in that: Calculate the economic fluctuation coefficient of each refueling vehicle arriving at the user end area, specifically including: Define the economic fluctuation coefficient corresponding to the i-th refueling vehicle when arriving at the user end area as: Among them, is the economic fluctuation coefficient corresponding to the arrival of the i-th refueling vehicle from the current position to the user end area; is the fuel consumption when the i-th refueling vehicle arrives at the user end area; the calculation formula is: where Xd represents the driving distance to the user terminal area, is the fuel consumption of the i-th refueling vehicle; is the predicted driving time of the i-th refueling vehicle, and the calculation formula is: Among them, is the average driving speed of the i-th refueling vehicle; is a weight factor used to adjust the calculation of the economic fluctuation coefficient, and its value range is [0.1, 10]; used to ensure that the effective value range of is (P2, P3); The maximum waiting time ZDt determined according to the current client; Under the premise that ≤ZDt, take The economic fluctuation coefficient corresponding to the smallest value as the value of P2; When When approaching P2 more closely, it indicates that the refueling vehicle has better economy, reasonable fuel consumption, and the driving time meets the expectations; When As it gets closer to P3, it means that the economy of the refueling vehicle is worse.

6. The method for using oil at the construction site according to claim 5, wherein: Obtain the first priority sequence and the second priority sequence, specifically including: Select the fuel trucks in the quantity sequence set {1, 2, …, N} of the fuel truck that meet to form the first priority sequence {1, 2, …, U1}, and set u1 ∈ {1, 2, …, U1}, where u1 represents the u1-th fuel truck in the first priority sequence, and U1 is the total number of fuel trucks that meet ; Meanwhile, among the fuel tankers in the quantity sequence set {1, 2, …, N} except for {1, 2, …, U1}, screening is carried out to select the fuel tankers that meet to form a second-priority sequence {1, 2, …, U2}, and it is set that u2 ∈ {1, 2, …, U2}, and u2 represents the u2-th fuel tanker in the second-priority sequence, U2 is the total number of fuel tankers in the second-priority sequence, and U2 ≤ N - U1.

7. The method for using oil at a construction site according to claim 6, characterized in that: Define the calculation formula of the first screening index of the first priority sequence as follows: Among them, is the first screening index of the fuel demand fluctuation coefficient of the u1-th refueling vehicle in the first priority sequence relative to the user side; is the standardized fuel demand fluctuation coefficient; is the completion coefficient when the u1st refueling vehicle executes the fuel demand at the user side; is a weight factor used to adjust the influence of the oil demand fluctuation coefficient and the completion coefficient on the first screening index; , and both have value ranges within (0, 1); Set the first screening index The effective value range of is (0, P1]; set the initial judgment threshold of the first screening index to 0.5P1; and then divide the value range (0, P1] of the first screening index into and ; The screening strategy for the refueling vehicle is as follows: When it indicates that the performance of the u1st refueling vehicle in meeting user needs is poor, and it is recommended to reduce the usage frequency of this refueling vehicle; When it means that the u1st refueling vehicle performs well in meeting user needs, and it is recommended to increase the usage frequency of this refueling vehicle.

8. The method for using oil at the construction site according to claim 7, characterized in that: Define the calculation formula of the second screening index of the second priority sequence as follows: Among them, is the second screening index of the u2nd refueling vehicle in the second priority sequence with respect to the oil demand fluctuation coefficient of the user side; is the completion coefficient of the u2nd refueling vehicle when executing the oil demand of the user side; is a weight factor used to adjust the impacts of the oil demand fluctuation coefficient and the completion coefficient on the second screening index; , and both have value ranges within (0, 1); Set the second screening index The effective value range of is (0, P1]; and set the initial judgment threshold of the second screening index to 0.5P1; furthermore, determine the value range for the screening strategy in the value range (0, P1] of the second screening index as ; Only when the performance of the second refueling vehicle in meeting the user's needs is good. At this time, it is necessary to screen out the refueling vehicles that match the current second refueling vehicle within the second priority sequence to form a refueling vehicle combination; The matching strategy of the refueling vehicle combination is: perform an addition calculation on the remaining oil reserves of these two refueling vehicles and the corresponding first error average value to obtain the final real-time superimposed oil reserve, and this final real-time superimposed oil reserve needs to be greater than the oil quantity to be refueled at the user end. At the same time, it is necessary to limit the difference between the real-time superimposed oil reserve and the oil quantity to be refueled within 10% of the oil quantity to be refueled, and represent this difference as DJy×0.1; if it cannot be satisfied, then re-look for any other two refueling vehicle combinations within the second priority sequence for analysis; If re-look for any other two refueling vehicle combinations within the second priority sequence for analysis and still cannot find two refueling vehicles that meet the requirements, then among any two refueling vehicle combinations exceeding DJy×0.1, select the two refueling vehicles with the smallest exceeded DJy×0.1 value as the selected refueling vehicle combination.

9. The method for using oil at a construction site according to claim 8, characterized in that: Determine the final refueling vehicle selection based on the economic fluctuation coefficient, specifically including: Filter out the corresponding fuel tank trucks that meet and calculate the corresponding economic fluctuation coefficient when these fuel tank trucks reach the user's area ; Screen out the corresponding fuel tank trucks that meet and determine the corresponding combinations of fuel tank trucks, and calculate the economic fluctuation coefficients corresponding to these fuel tank trucks when they reach the user terminal area ; The economic fluctuation coefficient The refueling vehicle closest to P2 is preferentially selected as the final refueling vehicle; Secondly, the economic fluctuation coefficient The fuel truck closest to P2 is selected as the alternative fuel truck; If, in the current construction site refueling event of the client, there is no fuel truck that meets , then the initial judgment threshold for the first screening index is reduced by the K1 percentage value, and the reduced initial judgment threshold is used for the next construction site refueling event of the client.

10. A system for oil used at a construction site, characterized in that: The system is used to execute the method for construction site oil consumption described in any one of claims 1-9, including: Data acquisition and upload module: used to collect the historical oil consumption demand data of the user end in M construction site refueling events, as well as the execution situation and status data of each refueling vehicle to complete these oil consumption demands in the previous monitoring time period, and upload these data to the cloud data platform for storage; Data determination module: used to determine the oil consumption demand data in the current refueling event of the user end, including the oil quantity to be refueled, the maximum waiting time, and the oil quantity demand fluctuation index; And determine the status data of each refueling vehicle, including the remaining oil reserves, the oil quantity consumed when arriving at the user end area, and the predicted driving time; The execution situation data includes the first error average value of the actual available oil reserves of each refueling vehicle after completing M oil consumption demands at the user end in the previous monitoring time period, and the second error average value of the actual driving time; Oil consumption demand fluctuation coefficient generation module: used to analyze the historical oil consumption demand data of the user end in the previous monitoring time period in the cloud data platform to calculate the oil consumption demand fluctuation coefficient of the user end; Completion coefficient generation module: used to obtain the execution situation data of each refueling vehicle to meet the oil demand of the user side in the previous monitoring time period in the cloud data platform, and calculate the completion coefficient based on the execution situation data; Economic fluctuation coefficient generation module: in the cloud data platform, calculate the economic fluctuation coefficient of each refueling vehicle arriving at the user side area according to the oil consumption and predicted driving time when each refueling vehicle travels from the current position to the user side area; Priority sequence division module: used to classify each refueling vehicle according to the oil demand data corresponding to the current refueling event at the user side. Among them, the refueling vehicles that meet the to-be-refueled oil volume and the maximum waiting time are classified into the first priority sequence, and among the remaining refueling vehicles, the refueling vehicles that meet the maximum waiting time are classified into the second priority sequence; First screening index generation module: used to analyze in combination with the corresponding oil demand fluctuation coefficient and completion coefficient among the several refueling vehicles determined by the first priority sequence, and generate the first screening index for providing a screening strategy for the refueling vehicle; Second screening index generation module: used to analyze in combination with the corresponding oil demand fluctuation coefficient and completion coefficient among the several refueling vehicles determined by the second priority sequence, and generate the second screening index for providing a screening strategy for the refueling vehicle; Final selection module: used to determine the final refueling vehicle selection based on the economic fluctuation coefficient among the several refueling vehicles determined by the first screening index and the second screening index.

Images