A new energy aircraft integrated thermal management system trade-off evaluation method and system

Abstract

The application discloses a kind of based on energy flow's new energy aircraft comprehensive thermal management system performance evaluation method and system, and relates to thermal field. Including: establishing loss analysis model;Determine minimum loss, compare with actual loss, obtain thermal management system external characteristic index;Determine the design matching degree of all electric energy equipment of each cooling branch, adjust the selection of all electric energy equipment of each branch in combination with energy flow coupling value index;After unit value processing to take-off, climb and cruise condition, classification is carried out, energy flow operating value index is established, the operation of the determined thermal management architecture under the whole flight envelope is evaluated, and the final thermal management selection scheme is determined.The application is used to improve the accuracy of aircraft thermal management system conceptual design stage architecture trade-off, and can also be used for effective monitoring of the operating state of thermal management system under flight condition.

Description

Technical Field

[0001] This invention relates to the fields of calculation, estimation, and system trade-offs, and more specifically, to a performance evaluation method and system for an integrated thermal management system for new energy aircraft based on energy flow. Background Technology

[0002] In response to the development trends of new energy aircraft regarding fuel economy and flight thermal management, current airborne thermal management systems are mainly divided into two parts: the thermal management system architecture and the thermal management system controller. The heat exchange performance of the thermal management system is directly related to the safe, stable, and efficient output of electrical equipment, and its structure is closely coupled with the physical layout and weight distribution within the cabin. The system's energy consumption directly affects the overall energy distribution of the aircraft. Due to the deep coupling between the thermal management system and the airborne electrical system, there are currently very few standardized and universal comprehensive evaluation methods for aircraft integrated thermal management systems.

[0003] Prior art 1 discloses a game-theoretic approach for integrated aircraft thermal / energy multi-objective optimization, which involves game-theoretic modeling of the main engine system's thermal / energy system and the APTMS system. This invention focuses on the fact that the main generator's thermal management system lacks global system evaluation capabilities.

[0004] Prior art 2 discloses a multi-objective optimization design method for a hybrid thermal management system built using a regression model algorithm, and proposes a multi-objective optimization design method for a hybrid thermal management system of an on-board lithium-ion power battery pack. This invention focuses on the fact that the thermal management system of the main generator lacks global system evaluation capabilities.

[0005] The above patents primarily focus on equipment, and the algorithms used in the research methods are simple, failing to achieve the desired evaluation results in the conceptual design stage. They cannot be extended to the area of ​​trade-off evaluation for the entire subsystem. Summary of the Invention

[0006] To address the aforementioned issues, this invention provides a method and system for evaluating trade-offs in the integrated thermal management system of new energy aircraft, thereby improving the accuracy of architectural trade-offs during the aircraft conceptual design phase. It can also be used to effectively control the operational status of the thermal management system during flight, enabling timely and necessary maintenance measures, which is crucial for preventing equipment overheating failures and ensuring the safe and stable operation of the system. This invention is used for the comprehensive evaluation of the thermal management system of new energy aircraft. It allows for system-level analysis at the aircraft level using parameters such as electrical equipment output performance, temperature characteristics, mass, and the energy consumption and benefits of the thermal management system, forming a model for evaluating the integrated thermal management system and establishing a standardized and universal comprehensive evaluation method. This invention can be used to accelerate scheme iteration during the conceptual design phase, providing a theoretical basis for the optimized design and operation of the thermal management system; it can also be used for ground integration testing to study the synergy between energy management and thermal management, and to establish a system-level energy management evaluation method.

[0007] According to a first aspect of the present invention, a method for evaluating the trade-offs of an integrated thermal management system for new energy aircraft is provided, the method comprising the following steps:

[0008] Step 1: Establish the thermal management system for each cooling branch under different operating conditions Damage analysis model;

[0009] Step 2: Based on the different operating conditions of each cooling branch of the thermal management system... A damage analysis model was used to determine the minimum operating conditions of each cooling branch under different operating conditions. Damage, and the actual operating conditions of each cooling branch under different operating conditions. By comparing the damage, the external characteristic indicators of the thermal management system are obtained;

[0010] Step 3: Based on the cooling branches of the thermal management system... The loss analysis model determines the design matching degree of all electrical equipment in each cooling branch, and the selection of all electrical equipment in each branch is adjusted based on the design matching degree of all electrical equipment in each cooling branch and the energy flow coupling value index.

[0011] Step 4: After processing the takeoff, climb, and cruise conditions into per-unit values, classify them, establish energy flow operating value indicators, evaluate the operation of the determined thermal management architecture across the entire flight envelope, and determine the final thermal management selection scheme.

[0012] Furthermore, in step 1, the cooling branches of the thermal management system under different operating conditions... The damage analysis model is as follows:

[0013] I sub,j =f(t)c,in ,t c,out )

[0014] Among them, I subi,j For the i-th cooling branch under the j-th operating condition Loss, i∈[1,n], n is the number of cooling branches; j∈[1,N], N is the number of operating conditions under the full flight envelope; t c,in and t c,out These are the inlet and outlet temperatures of the cooling medium in the i-th cooling branch under the j-th operating condition, respectively.

[0015] Furthermore, step 2 specifically includes:

[0016] Step 21: Use the second-generation non-dominated sorting genetic algorithm (NSGA-II) to analyze the cooling branches of the thermal management system under different operating conditions. The parameters of the damage analysis model are optimized to obtain the minimum value of the ideal operating state of the i-th cooling branch under the j-th operating condition. damage;

[0017] Step 22: Based on the minimum ideal operating state of the i-th cooling branch under the j-th operating condition. The minimum loss of the thermal management system under the j-th operating condition is obtained. Loss, and the actual thermal management system under the j-th operating condition By comparing the losses, the overall external characteristic indicators of the thermal management system under the j-th operating condition are obtained;

[0018] Step 23: Obtain the external characteristic index of the integrated thermal management system within the entire envelope based on the external characteristic index of the overall thermal management system under the j-th operating condition.

[0019] Furthermore, in step 21, the objective function for setting the ideal operating state of each cooling branch under different operating conditions is:

[0020] minI subi,j =f(t) c,in ,t c,out )

[0021] And set the equality and inequality constraints as follows:

[0022] t c,in_min ≤t c_in,set ≤t c,in_max

[0023] t c,in_min =t air +Δt cin_air_min if t c,in_min <t air +Δt cin_air_min

[0024] t c,out_min ≤t c_out,set ≤t c,out_max .

[0025] Furthermore, in step 22:

[0026] The minimum thermal management system under the j-th operating condition Loss is:

[0027] n is the number of cooling branches. The minimum value of the nth cooling branch under the j-th operating condition. damage;

[0028] The actual thermal management system under the j-th operating condition Loss is:

[0029] n is the number of cooling branches. For the actual operating condition of the nth cooling branch under the jth operating condition damage;

[0030] The overall external characteristic parameters of the thermal management system under the j-th operating condition are:

[0031]

[0032] In the formula, IP sys,j is the external characteristic index of the overall thermal management system under the j-th operating condition.

[0033] Furthermore, in step 23, the external characteristic parameters of the integrated thermal management system within the entire thermal envelope are:

[0034]

[0035] In the formula, N represents the number of operating conditions under the entire flight envelope.

[0036] Furthermore, step 3 specifically includes:

[0037] Step 31: Based on the cooling branches of the thermal management system... The loss analysis model determines the minimum value of the m-th electrical equipment in the i-th cooling branch under ideal operating conditions. damage;

[0038] Step 32: Calculate the minimum value of the m-th electrical device in the ideal operating state of the i-th cooling branch. The actual loss of the m-th electrical equipment in the i-th cooling branch The design difference of the m-th electrical equipment in the i-th cooling branch is obtained by comparing the losses.

[0039] Step 33: Calculate the overall design difference of the i-th cooling branch based on the design difference of the m-th electrical equipment in the i-th cooling branch;

[0040] Step 34: Obtain the design matching degree of the i-th cooling branch based on the overall design difference of the i-th cooling branch. Based on the design matching degree result, adjust the selection of all electrical equipment in each branch in combination with the energy flow coupling value index.

[0041] Here, in step 31, Loss is the input of the system With output The difference was used to optimize the flow rate, inlet temperature, and outlet temperature of the thermal management system using the NSGA-II optimization algorithm, in order to find its optimal value. The operating state with minimal loss. Calculate the output under this state. Minimize damage damage.

[0042] Furthermore, in step 32, the design difference for the m-th electrical device in the i-th cooling branch is:

[0043]

[0044] In the formula, δ m This represents the design difference for the m-th electrical device in the i-th cooling branch. For the actual power supply of the m-th electrical device in the i-th cooling branch damage, The minimum value for the m-th electrical device in the i-th cooling branch damage.

[0045] Furthermore, in step 33, the overall design difference of the i-th cooling branch is:

[0046]

[0047] In the formula, χ i δ represents the overall design difference of the thermal management object during the wheel stop time of the i-th cooling branch, T represents the wheel stop time decomposition for each operating condition, and δ mt This represents the deviation value of the m-th device at time t, where m∈[1,M], and M is the total number of electrical devices in the i-th cooling branch. on,t This represents the number of electrical devices in operation at time t for the i-th cooling branch.

[0048] Furthermore, in step 34, the design matching degree of the i-th cooling branch is:

[0049]

[0050] Where, χi λ represents the overall design difference of the thermal management equipment in the i-th cooling branch. i Let i be the design weight of the thermal management equipment in the i-th cooling branch.

[0051]

[0052] In the formula, P set,sub_i P represents the sum of the rated losses of all electrical equipment in the i-th cooling branch; set,sys This represents the sum of the rated losses of all thermally managed objects in the airborne system.

[0053] Furthermore, in step 34, the energy flow coupling value index is:

[0054]

[0055] In the formula, COP represents the optimal operating efficiency of the thermal management system, with a value between [0% and 100%]; C period For the control domain constraints during the wheel chock time, the coefficients a, b, and c are adjusted based on a specific thermal management system and take values ​​between [0,1].

[0056] The control domain constraint during the wheel shift time is C. period for:

[0057]

[0058] Among them, S control,t S represents the domain characterized by the controlled parameter. all,t This represents the control domain during the wheel shift time.

[0059] Furthermore, step 34 specifically includes:

[0060] Step 341: Obtain the design matching degree of the i-th cooling branch based on the overall design difference of the i-th cooling branch;

[0061] Step 342: When the design matching degree of the i-th cooling branch is 1, it indicates that all electrical equipment in the i-th cooling branch has the minimum... If the cooling branch is in ideal operating condition, there is no need to adjust its thermal management equipment. If the design matching degree of the i-th cooling branch is not 1, it indicates that some electrical equipment in the i-th cooling branch does not have minimum performance. If the heating element, fan, and pump are not in ideal operating condition, further adjustments to their selection are necessary.

[0062] Furthermore, step 4 specifically includes:

[0063] Step 41: Perform per-unit value processing on specific operating conditions to obtain system operating condition characteristic values;

[0064] Step 42: Classify the system operating condition feature values ​​based on the improved k-means clustering algorithm, and use the classification results as the probability of different load conditions occurring;

[0065] Step 43: Establish energy flow operation value indicators, use AHP to determine the weight of each level of indicators, first establish a hierarchical structure model, construct pairwise comparison matrices and check their consistency.

[0066] Step 4 describes the thermal management system under the full flight envelope of the aircraft. The preceding steps all describe the thermal management system performance under specific operating conditions. This can be understood as the "dynamic" characteristics of the thermal management system when the load changes according to a certain pattern.

[0067] Furthermore, in step 41, the specific formula for processing per-unit values ​​for a specific working condition is as follows:

[0068]

[0069] D=|Γ unit,sys2 -Γ unit,sys |

[0070] In the formula, Γ unit,sys Γ represents the system operating condition characteristic value after the per-unit value. sys,max ,Γ sys,min These are the maximum and minimum values ​​of the system's operating condition characteristic values, Γ. sys It is the characteristic value of the system operating condition, Γ unit,sys1 It is the characteristic value of system condition 1 after the per-unit value, Γ unit,sys2 is the characteristic value of system condition 2 after per-unit value, and D is the deviation value of system operating condition.

[0071] Furthermore, in step 42, the mathematical form for classifying the system operating condition feature values ​​based on the improved k-means clustering algorithm is as follows:

[0072]

[0073] Where x represents the actual operating condition, Γ unit,sys (x) is the system operating condition characteristic value x after per-unit value, μ i Γ is the baseline value for the corresponding category in the cluster. unit,sys (μ i () is the value after unit scaling under actual operating conditions, S i It is the set of all operating conditions, and k is the category of all groups.

[0074] Furthermore, in step 43, the energy flow operating value index is:

[0075] S(m,CV)=∫ Tm(j)·CV(j)dj

[0076] In the formula, m is the heat dissipation power spectrum under the flight envelope, and CV is the energy flow coupling value index. Discretizing the above formula and applying probability weighting to CV(j) yields the corresponding energy flow operation value index under the mission profile:

[0077]

[0078] In the formula, p j Let be the probability of the j-th working condition, and l be the number of all working conditions.

[0079] Furthermore, step 43 specifically includes:

[0080] Step 431: Construct a hierarchical analysis model with energy flow coupling value index and energy flow operation value index as indicators, and different system design schemes as the scheme layer;

[0081] Step 432: Construct a judgment matrix between the indicator layer and the scheme layer by combining expert opinions;

[0082] Step 433: Calculate the score of each scheme based on the judgment matrix, and determine the final thermal management selection scheme based on the score.

[0083] Here, in step 432, the judgment matrix is ​​obtained based on expert experience, and the weight values ​​of each indicator given by the expert are between [0,1].

[0084] According to a second aspect of the present invention, a system for evaluating the trade-offs of an integrated thermal management system for new energy aircraft is provided, the system comprising: a processor and a memory for storing executable instructions; wherein the processor is configured to execute the executable instructions to perform the evaluation method for evaluating the trade-offs of an integrated thermal management system for new energy aircraft as described in any of the preceding aspects.

[0085] According to a third aspect of the present invention, a computer-readable storage medium is provided, wherein a computer program is stored thereon, which, when executed by a processor, implements the trade-off evaluation method for the integrated thermal management system of new energy aircraft as described in any of the preceding aspects.

[0086] The beneficial effects of this invention are:

[0087] (1) The technical solution of the present invention establishes an energy flow characteristic model under variable operating conditions, studies the dynamic matching relationship between the steady-state selection of thermal management equipment and load probability distribution and operation control from the perspective of energy flow analysis, and can realize the trade-off of the thermal management system of new energy aircraft under the full flight envelope, thereby achieving the technical effect of rapid iteration of technical solutions in the conceptual design stage.

[0088] (2) The technical solution of this invention utilizes the production structure theory of thermoeconomics, combined with The analytical method establishes an energy flow correlation model between various devices, analyzes the changes in energy flow characteristics of the thermal management system in steady state and transient state, and can comprehensively evaluate the energy consumption and effects of the thermal management system, thereby providing support and basis for the selection of thermal management schemes.

[0089] (3) The technical solution of the present invention evaluates the selection and design level of the thermal management system based on the highest efficiency that the system can achieve, the matching level between various devices, and the constraints imposed by the selection of devices on operation control. It can provide optimization direction for the thermal management system, thereby improving the iterative efficiency of the design scheme of the thermal management system.

[0090] (4) The technical solution of the present invention defines the probability distribution of thermal load conditions, the probability distribution of load conditions, the coordination of design selection and operation control, and can realize the trade-off of the thermal management system of new energy aircraft under the whole flight package, thereby accelerating the technical effect of iterating the technical solution in the conceptual design stage. Attached Figure Description

[0091] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0092] Figure 1 A flowchart illustrating the trade-off evaluation method for the integrated thermal management system of new energy aircraft according to the technical solution of the present invention is shown.

[0093] Figure 2 This diagram illustrates the output coordination degree of the external characteristics of the thermal management system according to the technical solution of the present invention.

[0094] Figure 3 This diagram illustrates the calculation flowchart for the energy flow coupling value index of the thermal management system according to the technical solution of the present invention.

[0095] Figure 4 A flowchart illustrating the evaluation process of the thermal management system during the design phase according to the technical solution of the present invention is shown.

[0096] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0097] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0098] The terms "first," "second," etc., used in this disclosure are for distinguishing similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented, for example, in orders other than those illustrated or described herein.

[0099] Furthermore, the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, such that a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or apparatus.

[0100] Multiple, including two or more.

[0101] And / or, it should be understood that, for the purposes of this disclosure, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone.

[0102] This invention provides a quantitative analysis method and system for the coordinated operation of a thermal management system and its components. By extracting the constraints of the thermal management system's design matching state on the control of equipment such as pumps and fans, a quantitative analysis method is established between the steady-state design of the thermal management system and the aircraft's flight conditions. Based on the extraction of the external characteristic curves, energy flow characteristics, and heat load distribution characteristics of the thermal management system, real-time evaluation of the thermal management system under the full mission profile is achieved, providing key technical support for the safe and efficient operation of aircraft in low-temperature and low-humidity environments.

[0103] The technical solution adopted in this invention combines the AHP (Analytic Hierarchy Process) with... The analytical method establishes a comprehensive thermal management trade-off model and evaluation method with the goals of optimal system operating efficiency, design matching degree, and reliability and stability, and with heat load demand, electrical load demand, and thermal management control algorithm as variables.

[0104] Meanwhile, a method for evaluating the synergy of the external characteristics output of the thermal management system is proposed. By building an electrothermal coupling model of electrical energy devices such as motors, motor controllers and batteries, and the energy flow correlation between each device, an energy flow analysis model of the thermal management system under variable operating conditions is established based on the second law of thermodynamics.

[0105] The technical solution adopted in this invention also proposes an "energy flow coupling value" index to quantify the impact of electrical equipment selection on the synergy of system electrothermal coupling output. By studying the theoretical maximum efficiency of equipment, design matching degree, and the constraints of design selection on operation control, an evaluation model and evaluation method for the "energy flow coupling value" of new energy systems based on the electrothermal coupling model are established.

[0106] This invention proposes an "energy flow operating value" index to quantitatively analyze the impact of thermal management system design, thermal management control algorithm, and equipment thermal load characteristics on the system's electrothermal coupling output synergy. The distribution of thermal load across the entire flight envelope, the design and selection of heat dissipation equipment, and the influence of the thermal management system's control unit on the system's external operating characteristics were studied. The Analytic Hierarchy Process (AHP) was used to analyze the flight envelope-equipment selection synergy and control algorithm synergy problem, and the "energy flow operating value" index was established.

[0107] like Figure 1 As shown, this achieves the following in the integrated thermal management system for new energy aircraft: Based on the analysis, an "evaluation method for the output coordination of external characteristics of thermal management system" is established to improve the evaluation method for the operation level of integrated thermal management system under certain typical operating conditions. Furthermore, from the perspective of equipment selection and matching, an evaluation method of "energy flow coupling value" is proposed. This index is applied in the conceptual design stage to provide guidance for the selection of heat exchange equipment. Finally, an "energy flow operation value" index is proposed to evaluate the operation of the determined thermal management architecture under the entire flight envelope.

[0108] Example

[0109] This invention establishes a comprehensive thermal management trade-off evaluation method for new energy aircraft from the perspectives of thermal management system design, operation, and control. It includes two aspects: First, it establishes an electrothermal coupling model for electrical equipment such as motors, motor controllers, and batteries, as well as an external characteristic output model for the thermal management system. Based on this model, an evaluation method for the external characteristic output coordination degree is proposed. Second, from three perspectives—electrical equipment selection, flight envelope influence, and failure protection—the optimal values ​​of each variable in the external characteristic output model are solved, proposing the "energy flow coupling value" index. Furthermore, based on the operation of the thermal management system across the entire flight envelope, the "energy flow operation value" index is proposed.

[0110] 1. Evaluation method for the coordination degree of external characteristic output of thermal management system operation

[0111] At any given moment within the flight envelope, the thermal management system theoretically exists in an operating state with the highest heat exchange efficiency. This efficiency can be achieved through multi-objective optimization methods to optimize the variables across the entire mission profile. The ideal operating state is when the loss is minimized. Using this ideal state as a benchmark, a suitable thermal management control strategy is derived by calculating the difference between the actual state and the ideal state at that moment. The ideal operating state of the thermal management system is optimized using the NSGA-II algorithm.

[0112] For the thermal management cooling circuit of the equipment, Loss I subI It is mainly affected by the inlet and outlet temperatures t of the cooling working fluid c,in and t c,out The effects can be observed as follows:

[0113] I subI =f(t) c,in ,t c,out )

[0114] The NSGA-II algorithm is used to optimize the above parameters. The objective function for the ideal operating state of a single branch of the thermal management system is:

[0115] minI subI =f(t) c,in ,t c,out )

[0116] The equality and inequality constraints are as follows:

[0117] t c,in_min ≤t c_in,set ≤t c,in_max

[0118] t c,in_min =t air +Δt cin_air_min ift c,in_min <t air +Δt cin_air_min

[0119] t c,out_min ≤t c_out,set ≤t c,out_max

[0120] The pseudocode is as follows:

[0121]

[0122]

[0123] Based on the ideal states of different loops in the thermal management system, the ideal state of the thermal management system is defined as the set of ideal states of each sub-branch, as shown in the following formula:

[0124]

[0125] In the formula, For the ideal minimum of the system under the j-th operating condition damage, The minimum value of the nth cooling branch under the j-th operating condition. damage.

[0126] Under specific operating conditions, the thermal management system uses the ideal operating state of the branch as the evaluation benchmark. By calculating the difference between the actual state and the ideal state of the cooling branch, the actual cooling effect of the branch is evaluated, and the external characteristic index of the cooling branch is obtained.

[0127]

[0128] In the formula, IP sub,ij The external characteristic index of the i-th cooling branch under the j-th operating condition is given. The minimum value of the i-th cooling branch under the j-th operating condition. damage, For the actual cooling branch under the j-th operating condition, damage.

[0129] Based on the above analysis, the operating state of the thermal management system can be represented by an n-dimensional vector. The distance within the n-dimensional space is defined as follows:

[0130]

[0131] This n-dimensional space represents the set of possible operating states of the thermal management system under a certain working condition. The external characteristic indicators of the entire integrated thermal management system are defined as follows:

[0132]

[0133] In the formula, IP sys,j Let J represent the external characteristic index of the thermal management system under the j-th operating condition. The minimum thermal management system under the j-th operating condition damage, For the actual thermal management system under the j-th operating condition damage.

[0134] By calculating IP sys,j The weighted average value across the entire flight envelope defines the external characteristic index of the integrated thermal management system within the entire envelope as follows:

[0135]

[0136] In the formula, N represents the number of operating conditions under the entire flight envelope.

[0137] 2. Energy Flow Coupling Value Indicator of Thermal Management System

[0138] Aircraft electric propulsion systems experience variable thermal loads under different operating conditions. Assumptions are made regarding the heat transfer of the main cooling components in the thermal management system, with the following specific conditions:

[0139] ① All losses in electrical equipment are converted into the internal energy of the cooling medium;

[0140] ② Input electricity for heat pump and fan All of them are converted into the machinery that transports the working fluid.

[0141] ③The heat exchange driving force at the ram air outlet is zero.

[0142] according to The balance equations determine the cooling air side of the aircraft's thermal management system. Changes in cooling medium Changes, power equipment side Denoteed as ΔExair,s, ΔExc,s, and Exe,s, the minimum useful work required by the thermal management system can be further obtained:

[0143] P sys,id =ΔExair,s-ΔExc,s-Exe,s

[0144] For an ideal thermal management system, the air side is at saturation temperature; therefore, the energy conservation and condition conservation equations for the integrated thermal management system are as follows:

[0145] F c h c,i +F air h air +F e h e =F c h c,o +F air h air,o

[0146] Where F represents the input of the subsystem Let h represent the enthalpy of the subsystem input. By solving this system of equations, the theoretical ideal state of the thermal management system can be obtained, and this value is also used as the benchmark value for the design of the thermal management system.

[0147] The formula for measuring the difference between the actual operating state and the ideal state of each piece of equipment in the thermal management system is as follows:

[0148]

[0149] In the formula, η represents the degree to which the actual operating conditions of the equipment deviate from the rated operating conditions. Based on the actual operating conditions of the equipment, This represents the rated operating condition of the equipment. The difference between multiple electrical devices is further defined as:

[0150]

[0151] In the formula, χ represents the difference in thermal management object time during wheel chock time, T represents the wheel chock time decomposition for each working condition, and δ ij M represents the deviation value of the i-th device at time j. on,j This represents the number of devices at time j.

[0152] And further define the design weights of thermal management equipment:

[0153]

[0154] In the formula, P set,sub_i P represents the sum of the rated losses of all electrical equipment in the i-th cooling branch; set,sys This represents the sum of the rated losses of all thermally managed components in the airborne system. The design matching degree of the cooling branch is further defined as:

[0155]

[0156] When the system design matching degree is 1, it means that all devices are operating under rated conditions and the system design is well matched.

[0157] The thermal management system control algorithm is quantized using the following formula:

[0158]

[0159] In the formula, C period S represents the control domain constraint during the wheel chock time. control,j S represents the domain characterized by the controlled parameter. all,j This represents the control domain during the wheel shift time.

[0160] In summary, the design evaluation indicators for thermal management systems are defined as follows:

[0161]

[0162] In the formula, COP represents the optimal operating efficiency of the thermal management system, and coefficients a, b, and c can be adjusted based on a specific thermal management system.

[0163] For specific operating conditions, the per-unit value processing is performed using the following formula:

[0164] Γunit,sys =(Γ sys -Γ sys,min ) / (Γ sys,max -Γ sys,min )

[0165] D=|Γ unit,sys2 -Γ unit,sys1 |

[0166] In the formula, Γ unit,sys Γ represents the system operating condition characteristic value after the per-unit value. sys,max ,Γ sys,min These represent the maximum and minimum values ​​of the operating condition characteristics, respectively. D represents the deviation value of the system's operating condition.

[0167] The operating conditions are classified based on the improved k-means clustering algorithm, and the mathematical form is as follows:

[0168]

[0169] Further establish the "energy flow operation value" indicator:

[0170] S(m,CV)=∫ T m(j)·CV(j)dj

[0171] In the formula, m represents the heat dissipation power spectrum below the flight envelope. Discretizing the above formula and applying probability weighting to CV(j) yields the "energy flow operating value" of the corresponding index under the mission profile:

[0172]

[0173] In the formula, p j To determine the probabilities under each working condition, the Analytic Hierarchy Process (AHP) is used to determine the weights of the indicators at each level. First, a hierarchical model is established, pairwise comparison matrices are constructed, and their consistency is verified. The specific process is as follows: Figure 4 As shown.

[0174] In summary, this application's technical solution, based on the second law of thermodynamics, proposes an evaluation index for the operational level of a thermal management system and establishes an evaluation method for the control unit of an airborne integrated thermal management system. This application's technical solution studies the design matching degree of thermal management system equipment and the constraints of design selection on system control, proposes an evaluation model and method for the "energy flow coupling value" of a new energy system based on an electrothermal coupling model, and proposes an "energy flow operating value" index for analyzing the coordination of the integrated thermal management system's flight envelope, equipment selection, and control algorithm.

[0175] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0176] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0177] Through the above description of the embodiments, those skilled in the art can clearly understand that the above implementation methods can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0178] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A method for trade-off evaluation of a new energy aircraft integrated thermal management system, characterized in that, The trade-off evaluation method for the integrated thermal management system of new energy aircraft includes the following steps: Step 1: Establish loss analysis models for each cooling branch of the thermal management system under different operating conditions; Step 2: Based on the loss analysis model of each cooling branch of the thermal management system under different operating conditions, determine the minimum loss of each cooling branch under the ideal operating state under different operating conditions, and compare it with the actual loss of each cooling branch under the actual operating state under different operating conditions to obtain the external characteristic index of the thermal management system. Step 3: Determine the design matching degree of all electrical equipment in each cooling branch according to the loss analysis model of each cooling branch of the thermal management system. Adjust the selection of all electrical equipment in each branch according to the design matching degree of all electrical equipment in each cooling branch and the energy flow coupling value index. Among them, by studying the theoretical maximum efficiency of the equipment, the design matching degree, and the constraints of the design selection on the operation control, a new energy system energy flow coupling value evaluation model and evaluation method based on the electrothermal coupling model are established. Step 4: After processing the takeoff, climb, and cruise conditions into per-unit values, classify them, establish energy flow operating value indices, evaluate the operation of the determined thermal management architecture under the entire flight envelope, and determine the final thermal management selection scheme; in particular, study the distribution of heat load under the entire flight envelope, the design and selection of heat dissipation equipment, and the impact of the thermal management system control unit on the external characteristics of system operation, use the AHP hierarchical analysis method to analyze the coordination problem of flight envelope-selection coordination-control algorithm coordination, and establish energy flow operating value indices; Specifically, step 2 includes: Step 21: Optimize the parameters of the loss analysis model of each cooling branch of the thermal management system under different operating conditions to obtain the minimum loss of the i-th cooling branch under the ideal operating state of the j-th operating condition; Step 22: Based on the minimum loss of the i-th cooling branch under the ideal operating state under the j-th operating condition, obtain the minimum loss of the thermal management system under the j-th operating condition. Compare it with the actual loss of the thermal management system under the j-th operating condition to obtain the overall external characteristic index of the thermal management system under the j-th operating condition. Step 23: Obtain the external characteristic index of the integrated thermal management system within the entire envelope based on the external characteristic index of the overall thermal management system under the j-th operating condition; In step 22: The minimum loss of the thermal management system under the j-th operating condition is: n is the number of cooling branches. The minimum loss of the nth cooling branch under the j-th operating condition; The actual loss of the thermal management system under the j-th operating condition is: n is the number of cooling branches. The actual loss of the nth cooling branch under the j-th operating condition; The overall external characteristic parameters of the thermal management system under the j-th operating condition are: In the formula, The external characteristic index of the overall thermal management system under the j-th operating condition; In step 23, the external characteristic parameters of the integrated thermal management system within the entire envelope are: In the formula, N represents the number of operating conditions under the entire flight envelope.

2. The trade-off evaluation method for the integrated thermal management system of new energy aircraft according to claim 1, characterized in that, In step 1, the loss analysis model for each cooling branch of the thermal management system under different operating conditions is as follows: in, The loss of the i-th cooling branch under the j-th operating condition is... n is the number of cooling branches; N represents the number of operating conditions under the entire flight envelope; and These are the inlet and outlet temperatures of the cooling medium in the i-th cooling branch under the j-th operating condition, respectively.

3. The trade-off evaluation method for the integrated thermal management system of new energy aircraft according to claim 1, characterized in that, Step 3 specifically includes: Step 31: Determine the minimum loss of the m-th electrical device in the i-th cooling branch under ideal operating conditions based on the loss analysis model of each cooling branch of the thermal management system; Step 32: Compare the minimum loss of the m-th electrical device in the i-th cooling branch under ideal operating conditions with the actual loss of the m-th electrical device in the i-th cooling branch to obtain the design difference value of the m-th electrical device in the i-th cooling branch; Step 33: Calculate the overall design difference of the i-th cooling branch based on the design difference of the m-th electrical equipment in the i-th cooling branch; Step 34: Obtain the design matching degree of the i-th cooling branch based on the overall design difference of the i-th cooling branch. Based on the design matching degree result, adjust the selection of all electrical equipment in each branch in combination with the energy flow coupling value index.

4. The trade-off evaluation method for the integrated thermal management system of new energy aircraft according to claim 3, characterized in that, In step 32, the design difference of the m-th electrical device in the i-th cooling branch is: In the formula, This represents the design difference for the m-th electrical device in the i-th cooling branch. The actual loss of the m-th electrical device in the i-th cooling branch is given. The minimum energy loss of the m-th electrical device in the i-th cooling branch; In step 33, the overall design difference of the i-th cooling branch is: In the formula, Let T represent the overall design difference of the thermal management object during the wheel stop time of the i-th cooling branch, and let T represent the wheel stop time decomposition for each operating condition. Let m represent the deviation value of the m-th device at time t, where M represents the total number of electrical devices in the i-th cooling branch. This represents the number of electrical devices whose i-th cooling branch is in operation at time t. In step 34, the design matching degree of the i-th cooling branch is: in, This represents the overall design difference of the thermal management equipment in the i-th cooling branch. Let i be the design weight of the thermal management equipment in the i-th cooling branch. In the formula, This represents the sum of the rated losses of all electrical equipment in the i-th cooling branch; This represents the sum of the rated losses of all thermally managed objects in the airborne system; In step 34, the energy flow coupling value index is: COP represents the optimal operating efficiency of the thermal management system, with a value between [0% and 100%]. For the control domain constraints during the wheel chock time, the coefficients a, b, and c are adjusted based on a specific thermal management system and take values ​​between [0,1]. Among them, the control domain constraint during the wheel shift time is: for: in, The domain representing the controlled parameter. This represents the control domain during the wheel shift time.

5. The trade-off evaluation method for the integrated thermal management system of new energy aircraft according to claim 1, characterized in that, Step 4 specifically includes: Step 41: Perform per-unit value processing on specific operating conditions to obtain system operating condition characteristic values; Step 42: Classify the system operating condition characteristic values ​​and use the classification results as the probability of different load conditions occurring; Step 43: Establish energy flow operation value indicators, use AHP to determine the weight of each level of indicators, first establish a hierarchical structure model, construct pairwise comparison matrices and check their consistency.

6. The trade-off evaluation method for the integrated thermal management system of new energy aircraft according to claim 5, characterized in that, In step 41, the specific formula for processing per-unit values ​​for a specific working condition is as follows: In the formula, This represents the system operating condition characteristic value after the per-unit value. These are the maximum and minimum values ​​of the system's operating condition characteristic values, respectively. These are system operating condition characteristic values. These are the characteristic values ​​of system condition 1 after the per-unit value. It is the characteristic value of system condition 2 after the per-unit value, and D is the deviation value of system operating condition; In step 42, the mathematical form for classifying the system operating condition feature values ​​based on the improved k-means clustering algorithm is as follows: Where x represents the actual operating condition, It is the system operating condition x characteristic value after the per-unit value. It is the baseline value for the corresponding category in the cluster. This is the value after subscripting by one under actual working conditions. It is the set of all working conditions, and k is the category of all groups; In step 43, the energy flow operating value index is: In the formula, m is the heat dissipation power spectrum under the flight envelope, and CV is the energy flow coupling value index. The above formula is discretized, and... By applying probability weighting, we obtain the energy flow operation values ​​of the corresponding indicators under the task profile: In the formula, Let be the probability under each working condition, and l be the category of all groups.

7. A trade-off evaluation method system for an integrated thermal management system for new energy aircraft, the system comprising: A processor and a memory for storing executable instructions; characterized in that the processor is configured to execute the executable instructions to perform the trade-off evaluation method for the integrated thermal management system of new energy aircraft according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a processor, implements the trade-off evaluation method for the integrated thermal management system of new energy aircraft according to any one of claims 1 to 6.

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