Flight CI execution rate calculation method combining QAR and airplane performance data

Abstract

The invention discloses a flight CI execution rate calculation method combining QAR and airplane performance data, and the method comprises the following steps: calculating a vacuum speed TAS value corresponding to a parameter combination through flight performance calculation software, building a five-dimensional vacuum speed table, summarizing the five-dimensional vacuum speed table to form a vacuum speed performance data package, building an airplane cruise vacuum speed calculation program, and calculating the airplane vacuum speed. The method comprises the following steps: acquiring a target CI value set by a flight based on flight historical data, identifying data in a cruise stage based on QAR data of the target flight and constructing a positioning point, calling an aircraft cruise vacuum speed calculation program for data parameters of the positioning point, calculating a real CI value, comparing the real CI value with the target CI value, and judging whether execution is performed according to a target or not. And obtaining the CI execution rate of the flight. Compared with the prior art, the real CI of any point of the flight history is calculated by combining the flight QAR data and the airplane performance data, and the method can perform accurate analysis and statistics on the flight CI execution rate.

Description

Technical Field

[0001] The present invention relates to the aviation field, and in particular to a flight CI execution rate calculation method combining QAR and aircraft performance data. Background Art

[0002] QAR (Quick access recorder)-specifically refers to an airborne flight data recorder with a protective device, which can record continuously for up to 600 hours and can collect hundreds of flight data at the same time, covering most parameters such as the aircraft's flight control, flight trajectory, equipment failure, etc.

[0003] Cost Index (CI) is an important parameter for flight operations. Using CI parameters to determine the economic speed of a flight is a major means for airlines to reduce flight costs.

[0004] The lowest cost refers to the lowest overall direct operating cost during the climb, cruise and descent phases, and the economic speed refers to the flight speed with the lowest operating cost during the flight phase. The operating costs of a flight on a route can be divided into two major aspects: time cost and fuel cost. Time cost refers to the cost that is positively correlated with the flight time of the flight, such as crew salaries. Fuel cost refers to the cost of the amount of fuel consumed by the flight. The cost index CI is defined as the time cost per unit time divided by the fuel cost per unit time. If the value of the cost index CI is large, it means that the time cost accounts for a high proportion of the operating cost, the fuel cost accounts for a low proportion, and the flight speed of the flight is high; conversely, if the value of the cost index CI is small, it means that the time cost accounts for a low proportion of the operating cost, the fuel cost accounts for a high proportion, and the flight speed is low.

[0005] Generally speaking, airlines will determine a suitable CI value for a specific route and aircraft type combination based on multiple factors such as aircraft performance, route conditions, crew flight costs, fuel prices, etc., use this CI value to make a computer flight plan, and require the crew to fly the aircraft at the flight speed corresponding to the CI value in the computer flight plan. However, in the actual flight of the flight, due to factors such as deviation from the flight plan conditions, air traffic control, and pilot driving style, the flight speed will not be strictly implemented according to the pre-determined CI value, resulting in an increase in flight operating costs. Therefore, airlines need to examine the CI execution rate of a given route and aircraft type combination in order to analyze flight operating costs and improve lean management.

[0006] Airlines usually obtain the average cruising speed of a flight based on its historical flight data and compare it directly with the estimated speed in the computer flight plan. If the difference between the two exceeds a given threshold, it is considered that the flight is not in accordance with the preset CI value. After accumulating flight data for a period of time, the CI execution rate of the route and aircraft type combination is statistically calculated. Therefore, the existing method of calculating the CI execution rate of a flight has a large error and low accuracy.

[0007] The main reasons are as follows: (1) The computer flight plan is made several hours before the flight takes off and is only a theoretical calculation result. There are large differences between its calculation conditions and the aircraft's actual wind speed and direction, atmospheric temperature, flight trajectory, real-time weight and other parameters. As a result, the reference flight speed calculated by it cannot be close to the preset CI value under actual circumstances, which in turn leads to inaccurate calculated CI execution rate; (2) This method uses the average speed of the cruise phase to examine whether the preset CI value is executed. However, the flight speed in actual flight is constantly changing. Even if the average speed is very close to the speed corresponding to the CI value, it cannot be said that the flight is flying according to the preset CI value.

[0008] In recent years, some people have proposed a method based on sampling of flight history data to calculate the flight CI value under a given parameter combination. The flight history QAR data is used to obtain each parameter corresponding to the CI value, and each parameter in the associated parameter group of each CI value is sampled to construct a CI value-multidimensional parameter data cube. Based on the parameters of the target flight and the data cube, the approximate CI value of the target flight is obtained. However, research has found that the method of calculating the approximate CI value of a flight under a given parameter combination based on sampling of flight history data can solve the problem of inconsistency between the reference flight speed and the actual CI value, but it still has the following three shortcomings:

[0009] (1) This method has poor practical operability and is difficult to meet the actual needs of airlines. The historical data sampling method requires airlines to use target aircraft to fly a large amount of flight data in advance, and the historical data needs to cover the aircraft speed envelope range and environmental envelope range as evenly as possible. If the data coverage rate is low or the parameter combination distribution is uneven, the calculation result will be less accurate, and it may even be impossible to calculate the CI value under given speed and environmental parameters. In actual flight, aircraft generally choose to fly under more ideal conditions as much as possible, so the uniformity of the parameter range in the historical data is difficult to guarantee.

[0010] (2) This method cannot calculate the CI value under certain circumstances, such as when the flight speed is close to VMO / MMO or close to the speed when CI=0.

[0011] (3) This method cannot calculate the CI value of models with no historical data accumulation or only a small amount of historical data accumulation. Summary of the invention

[0012] The purpose of the present invention is to provide a flight CI execution rate calculation method combining QAR and aircraft performance data, which solves the above-mentioned problem and realizes accurate analysis and statistics of flight CI execution rate.

[0013] In order to achieve the above object, the technical solution adopted by the present invention is: a flight CI execution rate calculation method combining QAR and aircraft performance data, the method steps are as follows:

[0014] Step 1: First, use the flight performance calculation software provided by the aircraft manufacturer to take the values ​​of the four influencing parameters of atmospheric temperature ISA, flight altitude ALT, wind speed WS, and aircraft weight WGT within the performance parameter envelope for a given CI value of a certain performance model, and calculate the high-precision true airspeed TAS value corresponding to these parameter combinations;

[0015] Step 2: For each CI value of the performance model, calculate the true airspeed TAS of the four parameter variable combinations and establish a five-dimensional true airspeed table;

[0016] Step 3: For all aircraft types of the airline, calculation and processing are performed according to the above method, and finally a five-dimensional true airspeed performance data package of all aircraft types is formed;

[0017] Step 4: Based on the above performance data package, establish an aircraft cruising true airspeed calculation program, and use linear interpolation to realize the function of calculating the aircraft true airspeed according to any CI value and four related influencing parameter values;

[0018] Step 5: Select a historical target flight and obtain the target CI value set for the flight based on the historical flight data of the airline;

[0019] Step 6: Collect QAR data after the flight lands, and identify the cruise phase data based on the QAR data of the target flight;

[0020] Step 7: divide the QAR data of the target flight during the cruise phase into equal parts according to the flight time and construct positioning points;

[0021] Step 8: Extract the true flight altitude, atmospheric temperature, wind speed, gross weight and true airspeed information of each positioning point;

[0022] Step 9: For each extracted positioning point, according to these data parameters, call the aircraft cruise true airspeed calculation program, and use the dichotomy method to reversely calculate its true CI value;

[0023] Step 10: For each extracted positioning point and the calculated real CI value, compare it with the target CI value to determine whether it is executed according to the target CI;

[0024] Step 11: The percentage of all the positioning points of the flight that are executed according to the specified CI value is the CI execution rate of the flight.

[0025] Preferably, in step one, the method for calculating the high-precision true airspeed TAS value corresponding to the parameter combination is as follows: taking the five parameters of CI, atmospheric temperature ISA, flight altitude ALT, wind speed WS, and aircraft weight WGT as input, using aircraft performance calculation software to calculate the true airspeed, and outputting the result true airspeed TAS.

[0026] Preferably, in step 2, the output results of the previous step are sorted, the calculation results of the target model are summarized into a five-dimensional table, and each variable dimension is nested and expanded in sequence to form an EXCEL data table.

[0027] Preferably, in step 4, the interpolation algorithm is as follows. When the program is started, the following steps are executed in sequence:

[0028] First, read the true airspeed performance data package, and create a mapping dictionary table between the model name and the true airspeed data table according to the EXCEL table name;

[0029] Secondly, for the true airspeed data table of each aircraft model, a true airspeed data model object is established. The model includes five parameter arrays CI[], ISA[], ALT[], WIND[], WGT[], and a true airspeed five-dimensional array TAS[,,,,]; the five parameter arrays and the TAS array are initialized by reading each row of data in the table;

[0030] Then, the program initialization is completed and the user input parameters can be received to calculate the corresponding true air speed.

[0031] As a preferred embodiment, the user input parameters are recorded as the model name, cost index CI 0 , Temperature ISA 0 , height ALT 0 、Wind speed WIND 0 , weight WGT 0 , the true airspeed calculation algorithm is as follows:

[0032] a.According to the aircraft model name, obtain the corresponding true airspeed data model object from the dictionary table;

[0033] b. Based on the input CI 0 , obtain the true airspeed corresponding to the CI value from the five-dimensional table TAS[,,,,] to form a four-dimensional table TAS[,,,];

[0034] c. According to the input temperature ISA 0 , find out the index range where the value is located in the ISA[] array;

[0035] d. For the ISA values ​​on both sides of the interval (ISA 1 ISA 2 ), establish two three-dimensional tables TAS[,,] respectively, reduce the dimensionality of the four-dimensional table, and continue to recursively perform linear interpolation on the remaining three dimensions until the last dimension (weight WGT) is linearly interpolated;

[0036] e. Set each ISA value (ISA 1 ISA 2 ) are respectively subjected to recursive linear interpolation to obtain the true air speed value TAS(ISA 1 ) and TAS(ISA 2 ), according to the input temperature ISA 0 ISA 1 and its corresponding TAS(ISA 1 ), ISA 2 and its corresponding TAS(ISA 2 ), for ISA 0 Perform one-dimensional linear interpolation to obtain the final true airspeed TAS 0 ; True airspeed TAS 0 That is, the program calculates the cost index CI based on the user input. 0 , Temperature ISA 0 , height ALT 0 、Wind speed WIND 0 , weight WGT 0 , the final true airspeed is calculated.

[0037] Preferably, in step 6, the method for identifying the cruise phase of a flight based on QAR data is as follows:

[0038] a. Decode the QAR data of the target flight;

[0039] b. Identify the flight time, altitude, atmospheric temperature, wind speed, gross weight, and true airspeed information for each data record;

[0040] c. Use the sliding window method to examine the data of each data recording point and all points in the following 5 minutes;

[0041] d. Select the point after which the altitude change does not exceed 500 feet and the true airspeed does not change by more than 5 knots for 5 consecutive minutes as the cruise starting point;

[0042] e. Use the same method to determine the cruise end point;

[0043] f. The QAR data between the cruise start point and the cruise end point is the cruise stage.

[0044] Preferably, in step nine, the specific calculation method of the true CI value is as follows:

[0045] a. Using the four parameters of true flight altitude, atmospheric temperature, wind speed, and gross weight, set CI lower limit = 0, CI upper limit = 999, and calculate the true airspeed values ​​corresponding to CI lower limit and CI upper limit respectively;

[0046] b. Determine whether the calculated true airspeed range of the CI lower limit and CI upper limit includes the actual true airspeed value;

[0047] c. Set the termination condition of the iteration to the difference between the CI lower limit and the CI upper limit = 1;

[0048] d. Based on the principle of minimizing the difference between the calculated true airspeed and the actual true airspeed, the CI lower limit or CI upper limit of the termination condition is taken as the final calculated true CI value.

[0049] Preferably, the method for determining whether the calculated true airspeed range includes the actual true airspeed value is as follows: if so, take the middle value between the CI lower limit and the CI upper limit and call the aircraft cruising true airspeed calculation program again to determine the relationship between the new calculated true airspeed value and the actual true airspeed; if the new calculated true airspeed is less than the actual true airspeed, then set the CI middle value as the new CI lower limit and repeat the previous step; otherwise, set the CI middle value as the new CI upper limit and repeat the previous step.

[0050] As a preferred method, the method for determining whether the target CI is executed is as follows:

[0051]

[0052] It is considered that the position point is executed according to the specified CI value.

[0053] Compared with the prior art, the advantages of the present invention are:

[0054] (1) The present invention can combine flight QAR data and aircraft performance data to calculate the true CI at any point in the flight history. This method can then accurately analyze and count the flight CI execution rate.

[0055] (2) To address the problem of inconsistency between the reference speed value in the computer flight plan and the actual flight speed value, the present invention abandons the computer flight plan as a reference data source and uses the flight history data QAR to obtain the actual flight status parameters;

[0056] (3) In view of the problems of poor operability, uneven historical data and poor coverage, and poor CI value calculation accuracy in the current calculation of the true CI value, the present invention proposes to use aircraft performance data to achieve high-precision CI value calculation, thereby eliminating the need for a large amount of accumulation and sampling processing of historical data. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 is a flow chart of the method of the present invention;

[0058] Figure 2 For true airspeed input calculations using Airbus performance calculation software;

[0059] Figure 3 Output of true airspeed calculations for Airbus performance calculation software;

[0060] Figure 4 This is an example of the five-dimensional true airspeed data table structure for a certain aircraft model;

[0061] Figure 5 This is the true airspeed performance data package for all aircraft models of a certain airline. DETAILED DESCRIPTION

[0062] It has been found through research that the key to calculating the CI execution rate of a flight is to calculate the real CI value of the flight at a certain point in the actual flight. The CI value selected by the airline together with atmospheric parameters, flight altitude, aircraft weight and other parameters determine the final flight speed of the flight. Relevant parameters include flight altitude, aircraft true airspeed, true track angle, aircraft model, engine model, flight management computer (FMS) model, atmospheric temperature, wind speed, wind direction, aircraft gross weight, etc. Therefore, the key technology for calculating the real CI value of a flight is to reversely infer its corresponding CI value based on these parameters in the flight history data. Based on this, the present invention proposes a flight CI execution rate calculation method combining QAR and aircraft performance data, including a model performance data table, an aircraft cruise true airspeed calculation module, a CI reverse calculation module, a QAR data extraction module, and a flight CI execution rate module.

[0063] The present invention will be further described below. A method for calculating flight CI execution rate combining QAR and aircraft performance data is as follows. Figure 1 :

[0064] Step 1: First, use the flight performance calculation software provided by the aircraft manufacturer to take the values ​​of the four influencing parameters of atmospheric temperature ISA, flight altitude ALT, wind speed WS, and aircraft weight WGT within the performance parameter envelope for a given CI value of a certain performance model, and calculate the high-precision true airspeed TAS value corresponding to these parameter combinations;

[0065] In addition to the CI value, other influencing parameters of the true airspeed of the aircraft include atmospheric temperature (ISA), flight altitude (ALT), wind speed (WS), and aircraft weight (WGT). CI, atmospheric temperature (ISA), flight altitude (ALT), wind speed (WS), and aircraft weight (WGT) are used as inputs to calculate the true airspeed using aircraft performance calculation software (such as Airbus PEP Release 5.11), such as Figure 2 As shown in the figure, an example of the output result TAS of the true airspeed calculation is Figure 3 As shown in the figure, when calculating TAS of different models, the parameter range will be different, but the accuracy of the parameter value interval can remain consistent.

[0066] The influencing parameters of different aircraft models have a certain range of values, that is, the performance parameter envelope. The data in this article take the A320-214 aircraft as an example, its CI value is an integer from 0 to 999, in kg / min; the atmospheric temperature (ISA) ranges from -70 to 40, in degrees Celsius; the flight altitude (ALT) ranges from 0 to 39800, in feet; the wind speed (Ws) ranges from -250 to 250, in knots; the aircraft weight (WGT) ranges from 37000 to 90000, in kg.

[0067] Taking the A320-214 aircraft as an example, the values ​​of each parameter are set as follows:

[0068] The CI value precision is 1, that is, each CI is calculated, and the CI parameter array is [0, 1, 2, 3, ..., 999], with a total of 1000 values;

[0069] The accuracy of atmospheric temperature (ISA) is 5 degrees Celsius, that is, the temperature parameter array is [-70, -65, -60, -55, ..., 35, 40], with a total of 23 values;

[0070] The flight altitude (ALT) value accuracy is 1000 feet (except the last value, which is the aircraft ceiling), that is, the altitude parameter array is [0, 1000, 2000, ..., 38000, 39000, 39800], a total of 41 values;

[0071] The wind speed (WS) value accuracy is 10 knots, that is, the wind speed parameter array is [-250, -240, -230, ..., 240, 250], a total of 51 values;

[0072] The accuracy of the aircraft weight (WGT) is 1000kg, that is, the weight parameter array is [37000, 38000, 39000, ..., 89000, 90000], with a total of 54 values.

[0073] Step 2, for each CI value of the performance model, the true airspeed (TAS) of the four parameter (variable) combinations was calculated;

[0074] In this step, the output results of the previous step are sorted, and the calculation results of the target model are summarized into a five-dimensional table. Each variable dimension is nested and expanded in sequence to form an EXCEL data table. The table structure is as follows: Figure 4 As shown;

[0075] Step 3: For all aircraft models of the airline, the calculation and processing are performed according to the above method, and finally the five-dimensional true airspeed performance data package of all aircraft models is summarized, such as Figure 5 As shown;

[0076] Step 4: Based on the above performance data package, establish an aircraft cruising true airspeed calculation program, and use linear interpolation to realize the function of calculating the aircraft true airspeed according to any CI value and four related parameter values;

[0077] Since the parameter value ranges of different models are different, this step establishes an interpolation algorithm that is compatible with different models. The specific method is as follows:

[0078] When the program starts, the following steps are performed in order:

[0079] First, read the true airspeed performance data package, and establish a mapping dictionary table between the model name and the true airspeed data table according to the EXCEL table name; the key in the dictionary table is the EXCEL table name (model name), and the value is the true airspeed data model object.

[0080] Secondly, for the true airspeed data table of each aircraft model, a true airspeed data model object is established. The model includes five parameter arrays CI[], ISA[], AT[], WIND[], WGT[], and a true airspeed five-dimensional array TAS[,,,,]; the five parameter arrays and the TAS array are initialized by reading each row of data in the table;

[0081] Then, the program is initialized and can receive user input parameters to calculate the corresponding true airspeed;

[0082] Note that the user input parameters are: model name, cost index CI 0 , Temperature ISA 0 , height ALT 0 、Wind speed WIND 0 , weight WGT 0 , the true airspeed calculation algorithm is as follows:

[0083] a.According to the aircraft model name, obtain the corresponding true airspeed data model object from the dictionary table;

[0084] b. Based on the input CI 0 , obtain the true airspeed corresponding to the CI value from the five-dimensional table TAS[,,,,] to form a four-dimensional table TAS[,,,];

[0085] For example, for the A320 case in this article, the CI parameter array of this model is [0, 1, 2, 3, ..., 999]. Assume that the CI input by the user is 0 =10, which is the 11th value of the CI array. Then all the data of TAS[10,,,,] are taken to form a four-dimensional table TAS[,,,]. In order to subsequently calculate the four-dimensional table according to the input temperature ISA 0 , height ALT 0 、Wind speed WIND 0 , weight WGT 0 Perform four-dimensional linear interpolation.

[0086] c. According to the input temperature ISA 0 , find out the index range where the value is located in the ISA[] array;

[0087] d. For the ISA values ​​on both sides of the interval (ISA 1 ISA 2 ), establish two three-dimensional tables TAS[,,] respectively, reduce the dimensionality of the four-dimensional table, and continue to recursively perform linear interpolation on the remaining three dimensions until the last dimension (weight WGT) is linearly interpolated;

[0088] e. Set each ISA value (ISA 1 ISA 2 ) are respectively subjected to recursive linear interpolation to obtain the true air speed value TAS(ISA 1 ) and TAS(ISA 2 ), according to the input temperature ISA 0 ISA 1 and its corresponding TAS(ISA 1 ), ISA 2 and its corresponding TAS(ISA 2 ), for ISA 0 Perform one-dimensional linear interpolation to obtain the final true airspeed TAS 0 ; True airspeed TAS 0 That is, the program calculates the cost index CI based on the user input. 0 , Temperature ISA 0 , height ALT 0 、Wind speed WIND 0 , weight WGT 0 , the final true airspeed is calculated.

[0089] The method for recursive linear interpolation is as follows

[0090] For example, for the A320 case in this article, suppose the user enters CI 0 =10,ISA 0 =-58, ALT 0 =5800, WIND 0 =246, WGT 0 =89001. ISA 0 The value is between ISA[2] and ISA[3]. Next, three-dimensional linear interpolation of the remaining three parameters is performed for the two temperatures of ISA[2] and ISA[3].

[0091] For example, for ISA[2], the three-dimensional table is TAS[10, 2,,,], according to ALT 0 If the value is between ALT[5] and ALT[6], two-dimensional linear interpolation of the remaining two parameters is performed on the two height values ​​of ALT[5] and ALT[6] respectively.

[0092] For example, for ALT[5], create a two-dimensional table TAS[10, 2, 5,,], according to WIND 0 If the value is between WIND

[49] and WIND

[50] , one-dimensional linear interpolation of the weight parameter is performed on the two wind speed values ​​WIND

[49] and WIND

[50] respectively.

[0093] For example, for WIND

[49] , a one-dimensional table TAS[10, 2, 5, 49,] is established, and the true airspeed value corresponding to WIND

[49] is obtained by performing one-dimensional linear interpolation of weight according to the WGT0 value, WGT[] and TAS[10, 2, 5, 49,].

[0094] Step 5: Select a historical target flight and obtain the target CI value set for the flight based on the historical flight data of the airline;

[0095] Step 6: The QAR data of the target flight records the actual parameter data of the flight during the actual flight, with a recording frequency of seconds. The airline collects QAR data after the flight lands, and identifies the data of the cruise phase based on the QAR data of the target flight;

[0096] Because according to flight rules, the aircraft does not fly according to CI during takeoff and landing, so the cruise phase of the flight must be identified. The method for identifying the cruise phase of the flight based on QAR data is as follows:

[0097] a. Decode the QAR data of the target flight;

[0098] b. Identify the flight time, altitude, atmospheric temperature, wind speed, gross weight, and true airspeed information for each data record;

[0099] c. Use the sliding window method to examine the data of each data recording point and all points in the following 5 minutes;

[0100] d. Select the point after which the altitude change does not exceed 500 feet and the true airspeed does not change by more than 5 knots for 5 consecutive minutes as the cruise starting point;

[0101] e. Use the same method to determine the cruise end point;

[0102] f. The QAR data between the cruise start point and the cruise end point is the cruise stage.

[0103] Step 7: The QAR data of the cruise phase of the target flight is divided equally according to the flight time to construct positioning points. Since the amount of all QAR data is large, in order to improve the calculation efficiency, CI execution rate analysis is not performed on all the recorded data. In this embodiment, 100 positioning points are selected as recording points for analysis on average.

[0104] Step 8: Extract the true flight altitude, atmospheric temperature, wind speed, gross weight and true airspeed information of each positioning point;

[0105] Step 9: For each extracted positioning point, according to these data parameters, call the aircraft cruise true airspeed calculation program, that is, the calculation program constructed in step 4, and use the dichotomy method to reversely calculate its true CI value;

[0106] The specific calculation method is as follows:

[0107] a. Using the four parameters of true flight altitude, atmospheric temperature, wind speed, and gross weight, set CI lower limit = 0, CI upper limit = 999, and calculate the true airspeed values ​​corresponding to CI lower limit and CI upper limit respectively;

[0108] b. Determine whether the calculated true airspeed range of the CI lower limit and CI upper limit includes the actual true airspeed value;

[0109] If so, take the middle value of the CI lower limit and the CI upper limit and call the aircraft cruise true airspeed calculation program again to determine the relationship between the new calculated true airspeed value and the actual true airspeed. If the new calculated true airspeed is less than the actual true airspeed, set the CI middle value as the new CI lower limit and repeat the previous step; otherwise, set the CI middle value as the new CI upper limit and repeat the previous step.

[0110] c. Set the termination condition of the iteration to the difference between the lower limit of CI and the upper limit of CI = 1; because the precision of CI is 1, the CI value is approximated by binary search. When the CI values ​​on both sides of the approximation do not exceed 1, the CI is considered to be found;

[0111] d. Based on the principle of minimizing the difference between the calculated true airspeed and the actual true airspeed, the lower limit of the CI or the upper limit of the CI of the termination condition is taken as the final calculated true CI value. The one whose true airspeed is closer to the actual true airspeed is taken as the final CI.

[0112] Step 10: For each extracted positioning point and the calculated real CI value, compare it with the target CI value to determine whether it is executed according to the target CI;

[0113] The judgment method is as follows:

[0114]

[0115] It is considered that the position point is executed according to the specified CI value.

[0116] Step 11: The percentage of all the positioning points of the flight that are executed according to the specified CI value is the CI execution rate of the flight.

[0117] The above is a detailed introduction to a flight CI execution rate calculation method combining QAR and aircraft performance data provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. Changes and improvements to the present invention will be possible without exceeding the concept and scope specified in the appended claims. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for calculating flight CI execution rate combining QAR and aircraft performance data, characterized in that: The steps are as follows: Step 1: First, use the flight performance calculation software to take the values ​​of the four related influencing parameters of atmospheric temperature ISA, flight altitude ALT, wind speed WS, and aircraft weight WGT for a given CI value of a certain performance model within its performance parameter envelope according to a certain interval accuracy, and calculate the high-precision true airspeed TAS value corresponding to these parameter combinations; Step 2: For each CI value of the performance model, calculate the true airspeed TAS of the four parameter variable combinations and establish a five-dimensional true airspeed table; Step 3: For all aircraft types of the airline, calculation and processing are performed according to the above method, and finally a five-dimensional true airspeed performance data package of all aircraft types is formed; Step 4: Based on the above performance data package, establish an aircraft cruising true airspeed calculation program, and use linear interpolation to realize the function of calculating the aircraft true airspeed according to any CI value and four related influencing parameter values; Step 5: Select a historical target flight and obtain the target CI value set for the flight based on the historical flight data of the airline; Step 6: Collect QAR data after the flight lands, and identify the cruise phase data based on the QAR data of the target flight; Step 7: divide the QAR data of the target flight during the cruise phase into equal parts according to the flight time and construct positioning points; Step 8: Extract the true flight altitude, atmospheric temperature, wind speed, gross weight and true airspeed information of each positioning point; Step 9: For each extracted positioning point, according to these data parameters, call the aircraft cruise true airspeed calculation program, and use the dichotomy method to reversely calculate its true CI value; Step 10: For each extracted positioning point and the calculated real CI value, compare it with the target CI value to determine whether it is executed according to the target CI; Step 11: The percentage of all the positioning points of the flight that are executed according to the specified CI value is the CI execution rate of the flight.

2. A flight CI execution rate calculation method combining QAR and aircraft performance data according to claim 1, characterized in that: In step 1, the method for calculating the high-precision true airspeed TAS value corresponding to the parameter combination is as follows: taking the five parameters of CI, atmospheric temperature ISA, flight altitude ALT, wind speed WS, and aircraft weight WGT as input, using aircraft performance calculation software to calculate the true airspeed, and outputting the result true airspeed TAS.

3. The method for calculating flight CI execution rate combining QAR and aircraft performance data according to claim 1, characterized in that: In step 2, the output results of the previous step are sorted, the calculation results of the target model are summarized into a five-dimensional table, and each variable dimension is nested and expanded in sequence to form an EXCEL data table.

4. The method for calculating flight CI execution rate combining QAR and aircraft performance data according to claim 1, characterized in that: In step 4, the interpolation algorithm is as follows. When the program is started, the following steps are executed in sequence: First, read the true airspeed performance data package, and create a mapping dictionary table between the model name and the true airspeed data table according to the EXCEL table name; Secondly, for the true airspeed data table of each aircraft model, a true airspeed data model object is established. The model includes five parameter arrays CI[], ISA[], ALT[], WIND[], WGT[], and a true airspeed five-dimensional array TAS[″″]; the five parameter arrays and the TAS array are initialized by reading each row of data in the table; Then, the program initialization is completed and the user input parameters can be received to calculate the corresponding true air speed.

5. The method for calculating flight CI execution rate combining QAR and aircraft performance data according to claim 4, characterized in that: The user input parameters are model name, cost index CI0, temperature ISA0, altitude ALT0, wind speed WIND0, and weight WGT0. The true airspeed calculation algorithm is as follows: a.According to the aircraft model name, obtain the corresponding true airspeed data model object from the dictionary table; b. According to the input CI0, obtain the true airspeed corresponding to the CI value from the five-dimensional table TAS[""] to form a four-dimensional table TAS["']; c. According to the input temperature ISA o , find out the index range where the value is located in the ISA[] array; d. For the ISA values ​​(ISA1 and ISA2) on both sides of the interval, two three-dimensional tables TAS[,,] are established respectively, the four-dimensional table is reduced in dimension, and the remaining three dimensions are recursively linearly interpolated until the last dimension (weight WGT) is linearly interpolated; e. Each ISA value (ISA1, ISA2) on both sides of the ISA[] array interval is subjected to recursive linear interpolation to obtain true airspeed values ​​TAS(ISA1) and TAS(ISA2) respectively. According to the input temperature ISA0, ISA1 and its corresponding TAS(ISA1), ISA2 and its corresponding TAS(ISA2), ISA0 is subjected to one-dimensional linear interpolation to obtain the final true airspeed TAS0; the true airspeed TAS0 is the final true airspeed calculated by the program according to the cost index CI0, temperature ISA0, altitude ALT0, wind speed WIND0, and weight WGT0 input by the user.

6. The method for calculating flight CI execution rate combining QAR and aircraft performance data according to claim 1, characterized in that: In step 6, the method for identifying the cruise phase of a flight based on QAR data is as follows: a. Decode the QAR data of the target flight; b. Identify the flight time, altitude, atmospheric temperature, wind speed, gross weight, and true airspeed information for each data record; c. Use the sliding window method to examine the data of each data recording point and all points in the following 5 minutes; d. Select the point after which the altitude change does not exceed 500 feet and the true airspeed does not change by more than 5 knots for 5 consecutive minutes as the cruise starting point; e. Use the same method to determine the cruise end point; f. The QAR data between the cruise start point and the cruise end point is the cruise stage.

7. The method for calculating flight CI execution rate combining QAR and aircraft performance data according to claim 1, characterized in that: In step nine, the specific calculation method of the true CI value is as follows: a. Using the four parameters of true flight altitude, atmospheric temperature, wind speed, and gross weight, set CI lower limit = 0, CI upper limit = 999, and calculate the true airspeed values ​​corresponding to CI lower limit and CI upper limit respectively; b. Determine whether the calculated true airspeed range of the CI lower limit and CI upper limit includes the actual true airspeed value; c. Set the termination condition of the iteration to the difference between the CI lower limit and the CI upper limit = 1; d. Based on the principle of minimizing the difference between the calculated true airspeed and the actual true airspeed, the CI lower limit or CI upper limit of the termination condition is taken as the final calculated true CI value.

8. The method for calculating flight CI execution rate combining QAR and aircraft performance data according to claim 7, characterized in that: In step b, the method for determining whether the calculated true airspeed range includes the actual true airspeed value is as follows: if so, take the middle value between the CI lower limit and the CI upper limit and call the aircraft cruise true airspeed calculation program again to determine the relationship between the new calculated true airspeed value and the actual true airspeed; if the new calculated true airspeed is less than the actual true airspeed, then set the CI middle value as the new CI lower limit and repeat the previous step; otherwise, set the CI middle value as the new CI upper limit and repeat the previous step.

9. The method for calculating flight CI execution rate combining QAR and aircraft performance data according to claim 1, characterized in that: The method to determine whether the target CI is executed is as follows: It is considered that the position point is executed according to the specified CI value.

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