Electric drive system optimal efficiency scheme matching method based on system engineering

Abstract

The invention relates to the field of new energy automobiles, in particular to an electric driving system optimal efficiency scheme matching method based on system engineering, which constructs a corresponding demand relationship between new energy automobile energy consumption and driving system efficiency and sets a more accurate driving system efficiency design index by applying a system engineering concept and taking a whole automobile user demand as a starting point. According to the method, the requirements are gradually refined and decomposed, so that multi-professional and multi-dimensional product design and scheme definition are guided, the optimal efficiency energy consumption control strategy is matched, and the most efficient product design structure is selected. According to the method, the design verification period can be effectively shortened, the input cost is reduced, the requirement of a whole vehicle user on the energy consumption aspect is met more accurately, the use experience of a new energy vehicle user is remarkably improved, and the competitiveness of a product in the market is enhanced.

Description

Technical Field

[0001] The present invention relates to the field of new energy vehicles, and in particular to a method for matching optimal efficiency solutions of electric drive systems based on systems engineering. Background Art

[0002] Traditional fuel vehicle powertrain energy consumption-efficiency design relies on experimental test data to analyze the discrepancy between efficiency and energy consumption, thereby optimizing the powertrain design. Specifically, during the powertrain design process, actual test models are constructed, tested under various operating conditions, and data on power output and energy consumption is collected. This data is used to assess the current design's energy consumption and efficiency performance, identify any deficiencies in the powertrain, and subsequently adjust and improve the design.

[0003] However, this traditional optimization method is not suitable for the higher efficiency requirements of new energy vehicles for electric drive systems because it has many disadvantages, as follows:

[0004] ① Long verification cycle: Power system testing requires simulating a variety of complex actual operating scenarios, and after each adjustment, comprehensive retesting is required to ensure the effectiveness of the new solution. This series of repeated testing processes, from solution modification to retesting and data analysis, is very time-consuming. For example, the power system design of an automobile engine may need to be tested under different road conditions, climate environments, and load conditions. Each test requires collecting and analyzing a large amount of data, and a complete test cycle can take months or even years.

[0005] ② High investment costs: During the power system testing process, the test platform itself requires the purchase of a large amount of specialized equipment. This equipment is expensive and consumes a lot of energy, raw materials, and labor costs during the testing process. In addition, the long verification cycle indirectly increases costs because human and material resources are continuously occupied during this period.

[0006] In summary, this traditional optimization method can often only improve individual problems exposed in the optimization test of new energy vehicle design schemes, and lacks systematic consideration of the relationship between power system energy consumption and efficiency from a holistic perspective.

[0007] Amidst the current booming new energy industry, advanced new energy drive systems, as key enablers of core technologies, face extremely complex design requirements. These requirements span multiple disciplines and encompass a wide range of attributes and characteristics. With the increasing adoption of new energy vehicles, designing and assembling highly competitive electric drive systems within a diverse industry competition landscape, while simultaneously balancing the trade-offs between these conflicting attributes and physical design characteristics, has become a significant and challenging technical challenge.

[0008] In the electric vehicle sector, electric drive assembly design based on the principles of high efficiency and low energy consumption has become a key performance indicator for current electric drive products, playing a key role in improving the overall efficiency and market competitiveness of new energy vehicles. Therefore, how to design electric drive products that combine high efficiency and high performance from multiple perspectives and address the system characteristics of electric drive products has always been a pressing issue for those skilled in the art. Summary of the Invention

[0009] The purpose of the present invention is to address the corresponding deficiencies of the existing technology and provide a method for matching the optimal efficiency solution of an electric drive system based on system engineering. This method uses the concept of system engineering, takes the needs of vehicle users as the starting point, constructs the corresponding demand relationship between the energy consumption of new energy vehicles and the efficiency of the drive system, and sets more accurate drive system efficiency design indicators. By gradually refining and decomposing the needs, it guides multi-professional and multi-dimensional product design and solution definition, and achieves the matching of the optimal efficiency and energy consumption control strategy and the selection of the most efficient product design structure. This method can effectively shorten the design verification cycle, reduce investment costs, more accurately meet the energy consumption needs of vehicle users, significantly improve the user experience of new energy vehicle users, and enhance the competitiveness of products in the market.

[0010] The purpose of the present invention is to adopt the following scheme to achieve:

[0011] A method for matching an optimal efficiency solution for an electric drive system based on systems engineering includes the following steps:

[0012] 1) Identify stakeholder needs, build a stakeholder needs database, and combine it with the experience database to build standardized energy consumption-efficiency demand characteristics for product development;

[0013] 2) Based on the standardized product development basic energy consumption-efficiency requirements, a system functional timing model is constructed to obtain a function-performance-control timing model;

[0014] 3) Complete the logical architecture design based on the system functional timing model and define the boundary relationships between each component;

[0015] 4) Establish a mathematical model of the functional timing architecture based on the logical architecture and the boundary relationships between the components;

[0016] 5) Establish a trade-off model and combine it with the mathematical model of the functional timing architecture to weigh key features and select the optimal solution.

[0017] Preferably, the basic energy consumption-efficiency requirement characteristics for product development include user energy consumption requirement characteristics, electric drive assembly / component comprehensive efficiency requirement characteristics, and boundary constraint requirement characteristics.

[0018] Preferably, the experience database includes user basic needs, a basic product efficiency database, a benchmark product efficiency database, and a user acceptance standard database.

[0019] Preferably, in step 2), the specific steps of constructing a system function timing model based on the basic energy consumption-efficiency requirement characteristics of product development to obtain a function-performance-control timing model are as follows:

[0020] 2-1) Based on the standardized product development basic energy consumption-efficiency requirements, build a system functional timing model and define standard functional characteristics;

[0021] 2-2) Based on the systematic functional timing model, extract the performance timing model and control timing model corresponding to the standard functional characteristics, complete the function-performance-control timing model scenario definition, and obtain the function-performance-control timing model;

[0022] 2-3) Standardize the definition of the nonlinear functional characteristics of the scenario model and improve the function-performance-control timing model.

[0023] Preferably, in step 3), the specific method of completing the logical architecture design and defining the boundary relationship of each component according to the system functional timing model is as follows:

[0024] 3-1) Based on the system structure characteristics of the system function timing model and the basic energy consumption-efficiency requirements of product development, set the structural characteristics and parameter characteristics of the system architecture and build a logical architecture model of the product system function timing;

[0025] 3-2) Based on the logical architecture model of the product system functional sequence and combined with boundary constraint requirements, define the boundary relationship between each component of the product.

[0026] Preferably, in step 4), the specific steps of establishing a functional timing architecture mathematical model based on the logical architecture and the boundary relationship between each component are as follows:

[0027] 4-1) Based on the standard efficiency spectrum characteristics, convert the function-performance-control timing model into the efficiency spectrum of the electric drive product assembly / components;

[0028] 4-2) Based on the efficiency spectrum obtained in step 4-1), combined with the logical architecture of the system functional timing designed in step 3) and the boundary relationship between each component, a functional timing architecture mathematical model is constructed.

[0029] Preferably, in step 5), a trade-off model is established and combined with a functional timing architecture mathematical model to perform a trade-off between key features. The specific steps for optimizing the solution are as follows:

[0030] 5-1) Set trade-off boundary standards based on the stakeholder demand database and establish a trade-off model;

[0031] 5-2) Use the functional timing architecture mathematical model to output the results, and use the trade-off model to determine whether the output results meet the needs of stakeholders;

[0032] 5-3) Based on the judgment result of step 5-2), a product efficiency achievement plan is formed.

[0033] ① If the output meets the needs of stakeholders, a product efficiency achievement plan will be directly formed;

[0034] ② If the output does not meet the needs of stakeholders, repeat steps 1) to 5).

[0035] Preferably, the trade-off model includes a user demand trade-off model, an efficiency index trade-off model, and a design parameter trade-off model.

[0036] The beneficial effects of the present invention are as follows:

[0037] A method for matching an optimal efficiency solution for an electric drive system based on systems engineering includes the following steps:

[0038] 1) Identify stakeholder needs, build a stakeholder needs database, and combine it with the experience database to build standardized energy consumption-efficiency demand characteristics for product development;

[0039] 2) Based on the standardized product development basic energy consumption-efficiency requirements, a system functional timing model is constructed to obtain a function-performance-control timing model;

[0040] 3) Complete the logical architecture design based on the system functional timing model and define the boundary relationships between each component;

[0041] 4) Establish a mathematical model of the functional timing architecture based on the logical architecture and the boundary relationships between the components;

[0042] 5) Establish a trade-off model and combine it with the mathematical model of the functional timing architecture to weigh key features and select the optimal solution.

[0043] This invention utilizes a systems engineering approach to accurately understand the needs of stakeholders, establish a corresponding demand relationship between product energy consumption and drive system efficiency, and gradually refine these demands to set more precise drive system efficiency design indicators. On this basis, by comprehensively considering multiple factors, a deep matching system is constructed to optimally achieve the energy consumption indicators of new energy vehicles and the overall efficiency of electric drive products. The goal is to achieve the optimal matching solution, thereby ensuring that the product meets the needs of all parties, enhancing overall competitiveness, and meeting market requirements for efficient and practical electric drive systems.

[0044] Preferably, in step 2), the specific steps of constructing a system function timing model based on the basic energy consumption-efficiency requirement characteristics of product development to obtain a function-performance-control timing model are as follows:

[0045] 2-1) Based on the standardized product development basic energy consumption-efficiency requirements, build a system functional timing model and define standard functional characteristics;

[0046] 2-2) Based on the systematic functional timing model, extract the performance timing model and control timing model corresponding to the standard functional characteristics, complete the function-performance-control timing model scenario definition, and obtain the function-performance-control timing model;

[0047] 2-3) Standardize the definition of the nonlinear functional characteristics of the scenario model and improve the function-performance-control timing model.

[0048] By constructing a system function timing model, the present invention converts the requirements of product design and development into specific parameter combinations that change over time, allowing R&D personnel to more intuitively see how the various system parameters change at different time points and operating conditions to meet energy consumption-efficiency requirements.

[0049] Preferably, in step 3), the specific method of completing the logical architecture design and defining the boundary relationship of each component according to the system functional timing model is as follows:

[0050] 3-1) Based on the system structure characteristics of the system function timing model and the basic energy consumption-efficiency requirements of product development, set the structural characteristics and parameter characteristics of the system architecture and build a logical architecture model of the product system function timing;

[0051] 3-2) Based on the logical architecture model of the product system functional sequence and combined with boundary constraint requirements, define the boundary relationship between each component of the product.

[0052] This invention achieves clear delineation of component functions and responsibilities by completing a logical architecture design and precisely defining the boundary relationships between components. Furthermore, by defining boundary relationships based on boundary constraint requirements and key component parameter optimization principles, it fully exploits and leverages the performance advantages of each component, thereby improving overall product performance and controlling costs. Furthermore, clear boundary relationships reduce interference and conflicts between components, ensuring stable product operation.

[0053] Preferably, in step 4), the specific steps of establishing a functional timing architecture mathematical model based on the logical architecture and the boundary relationship between each component are as follows:

[0054] 4-1) Based on the standard efficiency spectrum characteristics, convert the function-performance-control timing model into the efficiency spectrum of the electric drive product assembly / components;

[0055] 4-2) Based on the efficiency spectrum obtained in step 4-1), combined with the logical architecture of the system functional timing designed in step 3) and the boundary relationship between each component, a functional timing architecture mathematical model is constructed.

[0056] The present invention can realize the transformation analysis of demand characteristics into design characteristics by constructing a functional timing architecture mathematical model.

[0057] Preferably, in step 5), a trade-off model is established and combined with a functional timing architecture mathematical model to perform a trade-off between key features. The specific steps for optimizing the solution are as follows:

[0058] 5-1) Set trade-off boundary standards based on the stakeholder demand database and establish a trade-off model;

[0059] 5-2) Use the functional timing architecture mathematical model to output the results, and use the trade-off model to determine whether the output results meet the needs of stakeholders;

[0060] 5-3) Based on the judgment result of step 5-2), a product efficiency achievement plan is formed.

[0061] ① If the output meets the needs of stakeholders, a product efficiency achievement plan will be directly formed;

[0062] ② If the output does not meet the needs of stakeholders, repeat steps 1) to 5).

[0063] Preferably, the trade-off model includes a user demand trade-off model, an efficiency index trade-off model, and a design parameter trade-off model.

[0064] The present invention utilizes the functional timing architecture mathematical model to output results, and utilizes the trade-off model to compare and judge the output results, thereby ultimately forming a product efficiency achievement plan with optimal efficiency matching, so that it can meet the needs of stakeholders.

[0065] Glossary:

[0066] Critical Characteristics: In this invention, these characteristics play a key and decisive role in product performance, function realization, quality assurance, and meeting the needs of stakeholders, and have a significant impact on the operation, optimization and ultimate effectiveness of the entire system.

[0067] Stakeholder needs are the expectations, demands, or requirements expressed by individuals or groups with a direct or indirect interest in a project, organization, or decision. Identifying and meeting these needs is a critical step in ensuring sound decision-making and project success. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 Schematic diagram of the experience database of the present invention;

[0069] Figure 2 A schematic diagram of the function-performance-control timing model scenario definition of the present invention;

[0070] Figure 3 Schematic diagram of the nonlinear functional characteristic standardization conversion method of the present invention;

[0071] Figure 4 Schematic diagram of the trade-off model of the present invention;

[0072] Figure 5 Schematic diagram of product system structure characteristics;

[0073] Figure 6 This is a schematic diagram of the standard working condition energy consumption-efficiency related standard interval analysis of this embodiment;

[0074] Figure 7 Schematic diagram of the electric drive assembly system architecture (partial) of this embodiment;

[0075] Figure 8 is the associated parameter model of the motor stator in the motor system of this embodiment;

[0076] Figure 9 This is the mathematical model of the functional timing architecture of this embodiment;

[0077] Figure 10 is a flow chart of the present invention;

[0078] Figure 11 Schematic diagram of specific parameters of the system function timing model in an embodiment of the present invention. DETAILED DESCRIPTION

[0079] like Figures 1 to 11 As shown, a method for matching an optimal efficiency solution of an electric drive system based on system engineering includes the following steps:

[0080] 1) Identify stakeholder needs, build a stakeholder needs database, and combine it with the experience database to build standardized energy consumption-efficiency demand characteristics for product development;

[0081] The above-mentioned stakeholder demands focus on efficiency-energy consumption characteristics, covering energy consumption requirements of new energy vehicle users, energy consumption acceptance standard scenarios of new energy vehicles, basic efficiency characteristics of basic products and benchmark products, and basic efficiency characteristics requirements of core component systems. Figure 1 As shown in Figure 1, the aforementioned experience database includes user basic requirements, a basic product efficiency database, a benchmark product efficiency database, and a user acceptance criteria database. Based on the efficiency-energy consumption characteristic requirements and the experience database, a standardized product development basic energy consumption-efficiency requirement characteristic is constructed to provide guidance for subsequent product design.

[0082] The basic energy consumption-efficiency requirements for product development include user energy consumption requirements, electric drive assembly / component comprehensive efficiency requirements, and boundary constraint requirements, as follows:

[0083] ⑴User energy consumption demand characteristics

[0084] ① New Energy Vehicle Energy Consumption Acceptance Standards: Under standard operating conditions, energy consumption is calculated by counting the energy lost during vehicle operation to facilitate measurement of new energy vehicle energy consumption. Standard operating conditions include factors such as the vehicle's stable operating cycle, operating time, speed, and acceleration. Calculating energy lost during vehicle operation under these specific conditions to determine energy consumption values ​​provides a unified standard for evaluating vehicle energy consumption.

[0085] ② Comprehensive energy consumption requirement W0: This is a product development target set based on the energy consumption values ​​actually measured under the new energy vehicle energy consumption acceptance standards. It is used to guide product development and ensure that the final product meets the acceptance standards while achieving the preset energy consumption level, thereby enhancing the product's market competitiveness.

[0086] ③ System overall efficiency (η): The corresponding system efficiency converted from the comprehensive energy consumption demand W0. System efficiency = output power ÷ input power * 100%. It is used to measure the energy utilization rate of the entire product system and reflect the system's energy utilization.

[0087] (2) Comprehensive efficiency requirements of electric drive assemblies and components

[0088] ① Standard efficiency condition: Based on the relationship between speed, acceleration, time, etc. in the energy consumption acceptance standard, the speed N of the electric drive assembly and its components under the corresponding energy consumption acceptance standard is calculated. n , torque characteristics T n , where N n Represents that there are n speed values, T nThis represents n corresponding torque values. This clarifies the operating status of each component of the electric drive system under the energy consumption acceptance standard, providing a basis for evaluating its efficiency.

[0089] ② Comprehensive average efficiency E(η): This is the comprehensive average efficiency of the electric drive system assembly or a certain component, calculated according to the following formula:

[0090] E(η)=(η1+η2+…+η n-1 +η n ) / n

[0091] Where E(η) is the comprehensive average efficiency, η1 is the efficiency of the component / assembly under the first working condition, η2 is the efficiency of the component / assembly under the second working condition, and η n-1 is the efficiency of the component / assembly under the (n-1)th working condition, η n is the efficiency of the component / assembly under the nth operating condition, and n is the total number of operating conditions involved in the comprehensive efficiency calculation.

[0092] The efficiency of an electric drive assembly or component varies under different operating conditions. The efficiency spectrum reflects the efficiency of each operating point under the standard efficiency condition. Based on the efficiency spectrum corresponding to the standard efficiency condition, the above formula can be used to obtain the average efficiency of all operating conditions, which is used as the comprehensive efficiency of the electric drive system assembly or a component.

[0093] E(η) is the comprehensive average efficiency. Its main function is to standardize and define n different efficiency operating conditions in the form of an average value, and to conduct a comprehensive and comprehensive evaluation of the efficiency performance of an assembly or component.

[0094] ③ Efficiency spectrum: It can also be called standard efficiency spectrum, which mainly corresponds to the efficiency value of standard efficiency condition (Z η1 ...Z ηn ), where Z represents the structural system composed of each assembly and component; η n represents the efficiency value corresponding to the nth working condition in the structural system; n represents the existence of n different efficiency working conditions in the efficiency spectrum. Therefore, Z η1 is the efficiency value corresponding to the first working condition in the structural system Z, Z ηn is the efficiency value corresponding to the nth working condition in the structural system Z.

[0095] ⑶ Boundary constraint demand characteristics

[0096] ① Standard interval efficiency characteristic sensitivity: When analyzing the efficiency of the electric drive system, the entire cycle condition is divided into multiple intervals. The standard interval efficiency characteristic sensitivity refers to the ratio of the number of efficiency points distributed in the standard operating condition interval to the total number of cycle operating condition intervals, that is, Here, m represents the number of efficiencies distributed within a standard operating range, and P represents the total number of cyclic operating ranges. This metric effectively reflects the proportion of efficiency within the standard operating range within the entire cyclic operating range. The higher the proportion, the greater the impact of the efficiency within the standard operating range on overall efficiency, helping to identify key operating ranges.

[0097] ② High-efficiency zone efficiency: High-efficiency zone efficiency refers to the proportion of the interval efficiency that is higher than the user demand efficiency in the total operating condition interval, that is, Here, n represents the number of operating ranges that meet the high-efficiency zone efficiency requirement (i.e., the efficiency of the range exceeds the user's desired efficiency), and N represents the total number of operating ranges. This metric measures the percentage of time the electric drive system operates in a high-efficiency state. A higher percentage indicates that the system operates at a higher efficiency more of the time, which helps improve energy utilization and reduce energy consumption.

[0098] ③ Reference definition principle for efficiency characteristics within standard intervals: To better evaluate the efficiency characteristics within different standard intervals, the comprehensive characteristics of the n efficiency indicators within different standard intervals are graded and defined using the L / A / C / U grading definition principle. Grade L indicates that the comprehensive efficiency of the standard interval is greater than the n efficiency indicators within the interval, indicating excellent comprehensive efficiency performance within this interval; Grade A indicates that the comprehensive efficiency of the standard interval is equivalent to the maximum value of the n efficiency indicators within the interval, indicating a high level of efficiency; Grade C indicates that the comprehensive efficiency of the standard interval is equal to the average of the n efficiency indicators within the interval, representing a medium level; Grade U indicates that the comprehensive efficiency of the standard interval is less than the average of the n efficiency indicators within the interval (this can be defined as a non-focus interval due to its relatively low efficiency). This grading allows for rapid evaluation and comparison of efficiency characteristics across different intervals.

[0099] ④ Principles for Optimizing Key Component Parameters: When designing electric drive systems, the selection of key component parameters is crucial. These principles are determined based on market demand, supplier capabilities, product production systems, and corporate strategies aligned with key characteristics. This principle clarifies the quality-cost principle for key components, emphasizing that cost factors should be considered while ensuring quality. It also defines a prioritized order for sensitive parameter characteristics of key components, helping to prioritize and select the parameters that are most important for optimization, thereby achieving a balance between product performance, cost, and corporate strategic objectives.

[0100] 2) Based on the standardized energy consumption and efficiency requirements of product development, a system functional timing model is constructed to obtain a function-performance-control timing model. The specific steps are as follows:

[0101] 2-1) Based on the standardized product development basic energy consumption-efficiency requirements, build a system functional timing model and define standard functional characteristics;

[0102] Specifically, based on the energy consumption acceptance standard requirements of new energy vehicles in the user energy consumption requirements, the comprehensive energy consumption requirements W0 requirements, the system comprehensive efficiency (η) requirements, and the standard efficiency operating condition requirements, the electric drive assembly / component comprehensive efficiency E(η) requirements, and the efficiency spectrum requirements in the assembly comprehensive efficiency requirements, a system function timing model is constructed. The specific parameters of the system function timing model are detailed in Figure 11 The model uses the timeline as a clue and covers a variety of information such as the cycle operating range, speed, acceleration, rotational speed, torque, comprehensive energy consumption, system overall efficiency, electric drive assembly / components overall efficiency, efficiency spectrum, etc., and records in detail the operating status parameters of the vehicle at different times.

[0103] In this embodiment, the standard functions related to energy consumption and efficiency include three functional characteristics: acceleration, deceleration, and constant speed.

[0104] 2-2) Based on the systematic functional timing model, extract the performance timing model and control timing model corresponding to the standard functional characteristics, and complete the function-performance-control timing model scenario definition (such as Figure 2 As shown), and obtain the function-performance-control timing model; In this embodiment, the acceleration interval of the 14s to 21s time period of the CLTC standard working condition energy consumption-efficiency related standard interval is taken as an example, as shown Figure 6 As shown, this acceleration range is analyzed to extract the relationship between speed (v)-acceleration (a), time t, and efficiency, resulting in a performance timing model. The relationship between speed (n)-torque (T), time t, and efficiency is then extracted to form a control timing model. Organizing this information into a table forms the preliminary framework for the function-performance-control timing model. Specific parameters are detailed in Table 1, including CLTC operating point (time), speed, acceleration, operating range, speed, torque, motor model, electronic control model, reducer model, and assembly efficiency.

[0105] Table 1

[0106]

[0107] 2-3) Standardize the definition of the nonlinear functional characteristics of the scenario model and improve the function-performance-control timing model.

[0108] Specifically, if Figure 3As shown, the nonlinear working conditions of the scenario model are standardized, the nonlinear data of the same time interval in the standard functional working condition are extracted, the area of ​​the interval is extracted for data fitting, and the nonlinear data is converted into standard linear data for the standardized boundary definition of the timing model. In this embodiment, the acceleration interval of the 14s to 21s time period of the CLTC standard working condition energy consumption-efficiency related standard interval is taken as an example (see Table 2 for details), the linear acceleration of this interval is analyzed, and the acceleration change of this interval is mean fitted, and the nonlinear interval acceleration change is converted into a standard linear acceleration boundary, further improving the function-performance-control timing model. Through this series of operations, the definition of the scenario model under standard functional conditions is completed, and finally a complete function-performance-control timing model is obtained, which provides an important basis for the subsequent energy consumption-efficiency analysis and system design optimization of new energy vehicles under different working conditions.

[0109] Table 2

[0110]

[0111] 3) Based on the system functional timing model, complete the logical architecture design and define the boundary relationships between each component. The specific method is as follows:

[0112] 3-1) The system function timing model records in detail the changes in various parameters over time during vehicle operation. These parameters reflect the functional status of the system at different times. Based on the system structure characteristics of the system function timing model and the basic energy consumption and efficiency requirements of product development, the structural characteristics and parameter characteristics of the system architecture are set to build a logical architecture model of the product system function timing.

[0113] like Figure 5 As shown in the figure, the performance structure model, control structure model, and functional structure model describe the system's architectural characteristics from different perspectives. The energy-efficiency requirements underlying product development define design goals, such as requirements for overall system efficiency and energy consumption. Therefore, by analyzing the variation patterns of various parameters in the system's functional timing model and the characteristics of each structural model, and based on energy-efficiency requirements, we determine the appropriate structural and parameter characteristics of the system architecture. This allows us to construct a logical architecture model for the product system's functional timing, ensuring that the system meets both functional requirements and energy-efficiency targets.

[0114] 3-2) Based on the logical architecture model of the product system functional sequence and in combination with the key component parameter optimization principle in the boundary constraint requirement characteristics, the boundary relationship of each component of the product is defined, thereby further obtaining the correlation relationship of the parameter characteristics of the required key components. In this embodiment, taking the electric drive product as an example, for the subsystems such as the motor, electronic control, and reducer, the key component parameter optimization principle determines the role and relationship of each component in the system. Figure 7 、8 As shown in the figure, when the stator, a key component in the motor, is used as the direction of system architecture optimization, the boundary relationships such as the connection mode and energy transfer relationship between the motor and other components (such as electronic control and reducer) are determined based on the principle of key component optimization. In this way, the associated parameter model of the motor stator in the motor system is further obtained. The model covers the boundary setting relationship of the stator parameters (such as the value range of parameters such as stator phase current and phase resistance), the design formula for optimizing the stator (such as the calculation formula of stator iron loss and copper loss), and the external model connection relationship of complex calculation formulas, so that when conducting more in-depth system analysis and optimization, external professional models can be called for accurate calculations. Finally, through these relationships and calculations, the "motor efficiency parameter" is obtained. This parameter, as a key indicator for measuring motor performance, directly reflects the energy conversion efficiency of the motor under the current design, providing an important reference for subsequent product design and optimization.

[0115] 4) Based on the logical architecture and the boundary relationships between components, the specific steps for establishing the mathematical model of the functional timing architecture are as follows:

[0116] 4-1) Based on the requirements of the standard efficiency spectrum characteristics (see Table 3 for specific parameters of the standard efficiency spectrum), convert the function-performance-control timing model into the efficiency spectrum of the electric drive product assembly / component;

[0117] Table 3

[0118]

[0119] The standard efficiency spectrum characteristics mainly set three aspects, providing a standardized framework for evaluating and optimizing the efficiency of electric drive systems under different operating conditions, helping product developers to design and improve more targeted products. These three aspects include:

[0120] ① Set the speed interval n: In the standard efficiency spectrum, the speed is divided into different standard intervals, represented by N. Each standard speed interval N is further divided into smaller speed intervals n. This division helps to more carefully analyze the efficiency of the electric drive system in different speed ranges.

[0121] ②Set the interval torque segment T n :Similar to the speed, the torque is also divided into standard intervals, represented by T. Each standard interval torque T is also subdivided into interval torque segments T n Since the efficiency of the electric drive system is closely related to the torque output, the torque segment T n The efficiency performance of the system at different torque output levels can be accurately analyzed.

[0122] ③Set interval efficiency η nPrinciple: Set interval efficiency η based on boundary constraint requirements n The boundary constraint requirements include the sensitivity of the standard interval efficiency characteristics, the efficiency of the high-efficiency zone, etc. These factors will affect the interval efficiency η n Setting of interval efficiency η n The principle is to use different speed ranges n and torque ranges T n (“T n ” refers to the torque segment corresponding to the nth speed segment) combination, determine a reasonable efficiency target.

[0123] 4-2) Based on the efficiency spectrum obtained in step 4-1), combined with the logical architecture of the system functional timing designed in step 4) and the boundary relationship between each component, a functional timing architecture mathematical model is constructed to achieve the transformation analysis from demand characteristics to design characteristics. In this embodiment, Figure 9 As shown in FIG, a mathematical model is established for the standard efficiency range of 1000-1500 rpm and 10-20 Nm of torque in the acceleration condition corresponding to the CLTC drive MAP comprehensive efficiency scenario.

[0124] 5) Establish a trade-off model and combine it with the mathematical model of the functional timing architecture to weigh key features. Solution trade-off refers to system selection. For example, if system A is decomposed into B, C, and D, where subsystem B has M optional models, subsystem C has N optional models, and subsystem D has P optional models, then the permutations and combinations are M*N*P combinations. From these combinations, the optimal one is selected as the final component of system A. This selection process is called trade-off. The specific steps for solution selection are as follows:

[0125] 5-1) Set trade-off boundary standards based on the stakeholder demand database and establish a trade-off model;

[0126] The trade-off model includes a user demand trade-off model, an efficiency indicator trade-off model, and a design parameter trade-off model. The user demand trade-off model specifically refers to the M-option selection for subsystem B corresponding to system A, where M may include a combination of one or more options. The efficiency indicator trade-off model specifically refers to the N-option selection for subsystem C corresponding to subsystem B, where N may include a combination of one or more options. The design parameter trade-off model specifically refers to the P-option selection for subsystem D corresponding to subsystem C, where P may include a combination of one or more options. The trade-off boundaries of the above trade-off models are determined by stakeholders.

[0127] 5-2) To meet the requirements of the M*N*P multiple schemes for the efficiency of the electric drive system of new energy vehicles, a trade-off model covering the ABCD system layers is established, as shown in Table 4:

[0128] Table 4

[0129]

[0130]

[0131] In the table, system A can be considered a level representing the user's energy consumption requirements. Similarly, subsystem B can be considered a level representing the assembly efficiency requirements, subsystem C can be considered a level representing the component efficiency requirements, and subsystem D can be considered a level representing the component design characteristics.

[0132] After the trade-off model is established, the boundary constraint requirements and other characteristics in the trade-off model are input into the functional timing architecture mathematical model. The functional timing architecture mathematical model is run and the following results are output:

[0133] (1) Result plan M of achieving the efficiency standard of subsystem B corresponding to the energy consumption demand of system A;

[0134] (2) Result plan N of achieving the efficiency standard of the standard efficiency interval of each component of subsystem C corresponding to the efficiency requirement of subsystem B;

[0135] (3) The efficiency standard requirements of the standard efficiency interval of each component of subsystem C correspond to the design parameter boundaries of each component of subsystem D and the efficiency standard achievement result plan P;

[0136] Finally, according to the output results (i.e., result plan M, result plan N, result plan P), the optimal combination of M*N*P multiple plans is selected, and it is judged whether the output optimal solution of M*N*P multiple plans meets the system energy consumption requirements of system A;

[0137] For example, design an optimal solution for the electric drive system under the CLTC standard operating conditions and the comprehensive energy consumption requirement W0 of the vehicle economy. The specific performance is shown in Table 5, and the optimal solution results are output.

[0138] Table 5

[0139]

[0140]

[0141] 5-3) Based on the judgment results of step 5-2), a product efficiency achievement plan is formed to guide product design so that the efficiency performance indicators meet user needs:

[0142] ① If the output meets the needs of stakeholders, a product efficiency achievement plan will be directly formed;

[0143] ② If the output result does not meet the needs of stakeholders, it is necessary to negotiate and adjust with each stakeholder and redefine the stakeholder needs, that is, repeat steps 1) to 5) until the final output result meets the needs of stakeholders.

[0144] For example, in the design of an electric drive system optimization scheme under the CLTC standard operating conditions and the comprehensive energy consumption requirement W0 of the vehicle economy as described in the table above, the optimal solution combination is output. The comprehensive average efficiency E(η) of the optimal solution is 94.13%, which is greater than the target of 94% and meets the user's needs.

[0145] The preferred combination of electric drive system assembly is as follows:

[0146] M:

[0147] Model selection: motor 2* reducer 2;

[0148] According to the optimization principle, the optimization and improvement is carried out based on the comprehensive average efficiency E(η) of reducer 2: 96.84%.

[0149] N:

[0150] The comprehensive average efficiency E(η) of the reducer is targeted to be greater than 97.5%;

[0151] According to the design optimization principle: set the friction pair loss: unchanged; bearing loss: unchanged; oil stirring loss: reduced by 0.66%; wind friction loss: unchanged as the design goals.

[0152] P:

[0153] Lubricating oil level: The distance from the lowest gear center to the lubricating oil level is 37mm;

[0154] Number of teeth: Secondary gear ratio optimized number of teeth 65 / 17 = 3.82;

[0155] Gear width: Secondary gear tooth width 32mm;

[0156] Gear helix angle: secondary gear helix angle 28;

[0157] Thus, the present invention's systems engineering-based approach to matching optimal efficiency solutions for electric drive systems, employing systems engineering concepts and taking vehicle user needs as a starting point, can accurately establish the corresponding demand relationship between new energy vehicle energy consumption and drive system efficiency, thereby setting more precise drive system efficiency design indicators. Furthermore, because the present invention gradually refines and decomposes requirements, guiding multidisciplinary and multi-dimensional product design and solution definition, it can achieve matching of optimal efficiency and energy consumption control strategies, thereby selecting design solutions that maximize product efficiency.

[0158] Experimental verification has shown that the present invention can effectively shorten the verification cycle of product design, greatly reduce investment costs, more accurately meet the energy consumption needs of new energy vehicle users, significantly improve the user experience of new energy vehicle users, and enhance the product's competitiveness in the market.

[0159] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications made to the present invention by those skilled in the art without departing from the spirit of the present invention shall fall within the scope of protection of the present invention.

Claims

1. A method for matching optimal efficiency solutions for electric drive systems based on systems engineering, characterized in that: The following steps are involved: 1) Identify stakeholder needs, build a stakeholder needs database, and combine it with the experience database to build standardized energy consumption-efficiency demand characteristics for product development; 2) Based on the standardized product development basic energy consumption-efficiency requirements, a system functional timing model is constructed to obtain a function-performance-control timing model; 3) Complete the logical architecture design based on the system functional timing model and define the boundary relationships between each component; 4) Establish a mathematical model of the functional timing architecture based on the logical architecture and the boundary relationships between the components; 5) Establish a trade-off model and combine it with the mathematical model of the functional timing architecture to weigh key features and select the optimal solution.

2. The method for matching the optimal efficiency scheme of an electric drive system based on system engineering according to claim 1, characterized in that: The basic energy consumption-efficiency demand characteristics for product development include user energy consumption demand characteristics, electric drive assembly / component comprehensive efficiency demand characteristics, and boundary constraint demand characteristics.

3. The method for matching the optimal efficiency scheme of an electric drive system based on system engineering according to claim 1, characterized in that: The experience database includes user basic needs, basic product efficiency database, benchmark product efficiency database, and user acceptance standard database.

4. The method for matching the optimal efficiency scheme of an electric drive system based on system engineering according to claim 1, characterized in that: In step 2), the system function timing model is constructed based on the basic energy consumption-efficiency requirements of product development to obtain the function-performance-control timing model. The specific steps are as follows: 2-1) Based on the standardized product development basic energy consumption-efficiency requirements, build a system functional timing model and define standard functional characteristics; 2-2) Based on the systematic functional timing model, extract the performance timing model and control timing model corresponding to the standard functional characteristics, complete the function-performance-control timing model scenario definition, and obtain the function-performance-control timing model; 2-3) Standardize the definition of the nonlinear functional characteristics of the scenario model and improve the function-performance-control timing model.

5. The method for matching the optimal efficiency scheme of an electric drive system based on system engineering according to claim 2, characterized in that: In step 3), the logical architecture design is completed based on the system functional timing model, and the boundary relationship between each component is defined as follows: 3-1) Based on the system structure characteristics of the system function timing model and the basic energy consumption-efficiency requirements of product development, set the structural characteristics and parameter characteristics of the system architecture and build a logical architecture model of the product system function timing; 3-2) Based on the logical architecture model of the product system functional sequence and combined with boundary constraint requirements, define the boundary relationship between each component of the product.

6. The method for matching the optimal efficiency scheme of an electric drive system based on system engineering according to claim 1 is characterized in that: In step 4), the mathematical model of the functional timing architecture is established based on the logical architecture and the boundary relationship between each component. The specific steps are as follows: 4-1) Based on the standard efficiency spectrum characteristics, convert the function-performance-control timing model into the efficiency spectrum of the electric drive product assembly / components; 4-2) Based on the efficiency spectrum obtained in step 4-1), combined with the logical architecture of the system functional timing designed in step 3) and the boundary relationship between each component, a functional timing architecture mathematical model is constructed.

7. The method for matching the optimal efficiency scheme of an electric drive system based on system engineering according to claim 1, characterized in that: In step 5), a trade-off model is established and combined with the functional timing architecture mathematical model to perform trade-offs between key features. The specific steps for optimizing the solution are as follows: 5-1) Set trade-off boundary standards based on the stakeholder demand database and establish a trade-off model; 5-2) Use the functional timing architecture mathematical model to output the results, and use the trade-off model to determine whether the output results meet the needs of stakeholders; 5-3) Based on the judgment result of step 5-2), a product efficiency achievement plan is formed. ① If the output meets the needs of stakeholders, a product efficiency achievement plan will be directly formed; ② If the output does not meet the needs of stakeholders, repeat steps 1) to 5).

8. The method for matching the optimal efficiency scheme of an electric drive system based on system engineering according to claim 7 is characterized in that: The trade-off model includes a user demand trade-off model, an efficiency index trade-off model, and a design parameter trade-off model.

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