Power transmission system configuration determination method and device based on multi-mode underground vehicle, medium and product

Abstract

The invention discloses a power transmission system configuration determination method and device based on a multi-mode underground vehicle, a medium and a product, and relates to the field of vehicle design, and the method comprises the steps that an initial power transmission system configuration is determined; determining the comprehensive evaluation working condition of the structured and unstructured pavement; determining maximum power performance indexes in different driving modes; by taking the maximum power performance index as a constraint, determining maneuverability indexes under different driving scenes in the comprehensive evaluation working condition; taking the maneuverability indexes as evaluation parameters, and adopting a mode switching penalty function to construct a global evaluation function; obtaining a comprehensive evaluation result according to the global evaluation function; performing attribution analysis on the comprehensive evaluation result; carrying out iterative optimization on the key factors by adopting a multi-objective optimization algorithm and a fast non-dominated sorting genetic algorithm; and the target power transmission system configuration is obtained. The power transmission system structure which is high in dynamic property and can well adapt to the standard working condition of the underground vehicle can be obtained.

Description

Technical Field

[0001] The present application relates to the field of vehicle design, and in particular to a method, device, medium and product for determining a power transmission system configuration based on a multi-modal underground vehicle. Background Art

[0002] With the rapid development of global urbanization, the scale of underground space dominated by rail transit is constantly expanding, and it is a key area that must be considered in future global urban warfare. Underground space will become the sixth activity area after land, sea, air, space, and network. Underground space is dominated by rail transit, including underground shopping malls, underground parking lots, underground pipe galleries and other underground scenes. It is an important area of ​​future cities. Therefore, it is urgent to develop multi-modal special vehicles for underground space. The design, optimization and intelligent control of the power transmission system configuration of multi-modal underground vehicles directly affect the maneuverability of multi-modal underground vehicles.

[0003] However, the test scenarios and standard operating conditions in traditional vehicle design cannot be applied to multi-modal underground vehicles with complex and changeable operating scenarios, and thus cannot guarantee the performance and effect of a certain powertrain configuration of a multi-modal underground vehicle.

[0004] Therefore, in order to solve the problem of optimizing the configuration design of the power transmission system of a multi-modal underground vehicle, it is urgently necessary to provide a method or device that can quickly and accurately determine the configuration of the power transmission system of a multi-modal underground vehicle. Summary of the invention

[0005] The purpose of the present application is to provide a method, device, medium and product for determining a power transmission system configuration based on a multimodal underground vehicle, which can obtain a power transmission system configuration with high power performance and better adaptability to standard operating conditions of underground vehicles.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides a method for determining a configuration of a power transmission system based on a multi-modal underground vehicle, the method for determining a configuration of a power transmission system based on a multi-modal underground vehicle comprising:

[0008] Determine the initial powertrain configuration based on the vehicle driving scenario;

[0009] Determine the comprehensive evaluation conditions including structured and unstructured roads; the comprehensive evaluation conditions include: different driving scenarios; driving scenarios include: horizontal roads, mountain slopes, steps and vertical obstacles;

[0010] Determine the maximum power performance index under different driving modes according to the system parameters of the initial power transmission system configuration; the driving modes include: wheel drive, track drive and swing arm drive; the maximum power performance index includes: maximum traction, maximum climbing ability, maximum speed and maximum height of swing arm obstacle crossing; the system parameters include: maximum output power of the motor, peak torque of the motor, reduction ratio, battery energy and battery power density;

[0011] Taking the maximum power performance index as a constraint, determine the maneuverability index under different driving scenarios in the comprehensive evaluation condition; the maneuverability index includes: average passing speed, maximum acceleration, minimum turning radius, average climbing speed, average step driving speed and average swing arm obstacle crossing speed;

[0012] Taking the mobility index as the evaluation parameter and the mode switching penalty function, a global evaluation function is constructed; and a comprehensive evaluation result is obtained according to the global evaluation function;

[0013] Conduct attribution analysis on the comprehensive evaluation results to determine the key factors of multimodal vehicle mobility;

[0014] A multi-objective optimization algorithm, a fast non-dominated sorting genetic algorithm, is used to iteratively optimize the key factors of multi-modal vehicle maneuverability; the iterative optimization results replace the system parameters of the initial powertrain configuration, and the step of determining the maximum power performance index under different driving modes according to the system parameters of the initial powertrain configuration is returned until the target powertrain configuration is obtained.

[0015] Optionally, the global evaluation function specifically includes:

[0016]

[0017] Among them, k p is the weight of each evaluation parameter, f(x p ) is the evaluation parameter, f i is the global evaluation parameter, p is the pth evaluation parameter, and n is the total number of evaluation parameters.

[0018] Optionally, the attribution analysis of the comprehensive evaluation results to determine the key factors of the multimodal vehicle mobility specifically includes:

[0019] Standardize the evaluation parameters;

[0020] The principal component analysis method was performed on the standardized evaluation parameters to obtain the potential factors;

[0021] Factor analysis was used to conduct attribution analysis on latent factors and identify the key factors of multimodal vehicle mobility.

[0022] Optionally, the factor analysis method is used to perform attribution analysis on potential factors to determine the key factors of multimodal vehicle mobility, specifically including:

[0023] Using the formula Determine the factor score F j ;

[0024] in, is the evaluation parameter after standardization, p is the pth evaluation parameter, b ji is the weight factor.

[0025] Optionally, the multi-objective optimization algorithm fast non-dominated sorting genetic algorithm is used to iteratively optimize the key factors of multi-modal vehicle mobility, specifically including:

[0026] The objective function J is determined using the formula maxJ = X1 + X2 + ..., where X i is the key factor, and max is the maximum value.

[0027] Optionally, the power transmission system configuration after iterative optimization specifically includes:

[0028] U = λJ + (1-λ)I;

[0029] Among them, I is the cost constraint function, and λ is the weight.

[0030] In a second aspect, the present application provides a device for determining a configuration of a power transmission system based on a multi-modal underground vehicle, the device for determining a configuration of a power transmission system based on a multi-modal underground vehicle comprising:

[0031] An initial configuration determination module, used to determine an initial powertrain configuration according to a vehicle driving scenario;

[0032] A comprehensive evaluation condition determination module is used to determine comprehensive evaluation conditions including structured and unstructured roads; the comprehensive evaluation conditions include: different driving scenarios; the driving scenarios include: horizontal roads, mountain slopes, steps and vertical obstacles;

[0033] A maximum power performance index determination module is used to determine the maximum power performance index under different driving modes according to the system parameters of the initial power transmission system configuration; the driving modes include: wheel drive, track drive and swing arm drive; the maximum power performance index includes: maximum traction, maximum climbing ability, maximum speed and maximum height of swing arm obstacle crossing; the system parameters include: maximum output power of the motor, peak torque of the motor, reduction ratio, battery energy and battery power density;

[0034] The maneuverability index determination module is used to determine the maneuverability index under different driving scenarios in the comprehensive evaluation condition with the maximum power performance index as a constraint; the maneuverability index includes: average passing speed, maximum acceleration, minimum turning radius, average climbing speed, average step driving speed and average swing arm obstacle crossing speed;

[0035] A comprehensive evaluation result determination module is used to construct a global evaluation function using the mobility index as an evaluation parameter and a mode switching penalty function; and obtain a comprehensive evaluation result according to the global evaluation function;

[0036] The key factor determination module is used to perform attribution analysis on the comprehensive evaluation results and determine the key factors of multi-modal vehicle mobility;

[0037] The iterative optimization module is used to iteratively optimize the key factors of multi-modal vehicle mobility using a multi-objective optimization algorithm, a fast non-dominated sorting genetic algorithm; replace the system parameters of the initial powertrain configuration with the iterative optimization results, and return to the maximum power performance index determination module until the target powertrain configuration is obtained.

[0038] In a third aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for determining the powertrain configuration based on a multimodal underground vehicle.

[0039] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for determining a powertrain configuration based on a multi-modal underground vehicle.

[0040] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the method for determining the configuration of a powertrain system based on a multi-modal underground vehicle.

[0041] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0042] The present application provides a method, device, medium and product for determining the configuration of a power transmission system based on a multimodal underground vehicle. By determining the initial power transmission system configuration according to the vehicle driving scenario, and by determining the test scenario that conforms to the application scenario of the multimodal underground vehicle, it can provide a better guarantee for the design optimization effect of the power transmission system of the multimodal underground vehicle; by determining the comprehensive evaluation conditions including structured and unstructured roads, it can examine the performance and comprehensive performance of the multimodal vehicle in various scenarios; wherein, the process of constructing the global evaluation function is specifically a fast dynamic evaluation (FDE) algorithm, and combined with attribution analysis, key factors are obtained; it can reduce the complexity brought by the simultaneous optimization of all decision variables of the multimodal underground vehicle, make the optimization design of the power transmission system of the multimodal underground vehicle more targeted, and improve the efficiency of iterative optimization design. The multi-objective optimization algorithm, fast non-dominated sorting genetic algorithm (NSGA-II), is used to iteratively optimize the key factors, which can effectively retain the dominant parameters of the initial model and effectively improve other parameters in combination with the factor analysis method to prevent the over-optimization of some parameters and the under-optimization of some parameters in the optimization design, thereby obtaining a powertrain configuration with high dynamics and better adaptability to the standard working conditions of underground vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 A schematic flow chart of a method for determining a power transmission system configuration based on a multi-modal underground vehicle in one embodiment of the present application;

[0045] Figure 2 A schematic diagram of the principle of a method for determining a power transmission system configuration based on a multi-modal underground vehicle in one embodiment of the present application; DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0047] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0048] In an exemplary embodiment, Figure 1 and Figure 2 As shown, a method for determining a power transmission system configuration based on a multi-modal underground vehicle is provided, and the method includes the following S101 to S108. Among them:

[0049] S101, determining an initial power transmission system configuration according to a vehicle driving scenario;

[0050] The vehicle driving scenario is analyzed to determine the standard operating conditions that can reflect the driving scenario of the multi-modal underground vehicle. Under the standard operating conditions, the initial powertrain configuration is designed in combination with the dynamic design objectives.

[0051] The power transmission system configuration includes: four permanent magnet synchronous motors, lithium-ion batteries, four reducers, and two differentials. The power transmission system is arranged as follows: the four tracks are driven independently, the track driving wheels are connected to the reducers, the reducers are connected to the motors, and the differentials are installed in the middle of the front and rear axles.

[0052] S102, determining a comprehensive evaluation working condition including structured and unstructured roads; the comprehensive evaluation working condition includes: different driving scenarios; the driving scenarios include: horizontal roads, mountain slopes, steps, and vertical obstacles;

[0053] The comprehensive evaluation condition design covers a variety of driving scenarios, examining the performance and comprehensive performance of multimodal vehicles in various scenarios. Among them, the comprehensive evaluation conditions for structured and unstructured roads in this application are:

[0054] The starting section is a structured horizontal road with a length of L1, including a 100-meter acceleration section, straight roads, and curves of different sizes to test the vehicle's acceleration performance and energy consumption.

[0055] The second section uses an unstructured mountainous road section with a length of L2, which includes gradual climbing sections with different slopes. The slope angle is less than or equal to 30° and the road surface is a dirt road or gravel road to test the vehicle's climbing performance.

[0056] The third section uses an unstructured stepped section with a length of L3 to test the vehicle's ability to overcome obstacles under track conditions.

[0057] The fourth section uses an unstructured vertical obstacle section with a length of L4 and a height of H4 to test the vehicle's ability to cross obstacles in a swinging arm state.

[0058] The terminal section uses an unstructured ruins road surface with a length of L5 to test the stability of the vehicle under loose road conditions.

[0059] S103, determining the maximum power performance index under different driving modes according to the system parameters of the initial power transmission system configuration; the driving modes include: wheel drive, track drive and swing arm drive; the wheel drive mainly occurs on structured roads, the track drive mainly occurs on unstructured roads and steps, and the swing arm drive mainly occurs in vertical obstacle crossing;

[0060] Maximum power performance indicators include: Maximum traction F max , Maximum climbing abilityθ max , maximum speed V max And the maximum height H of the swing arm obstacle max ; System parameters include: Maximum output power of the motor P motor_max (kwh), motor peak torque T motor_max (Nm), reduction ratio i0, battery energy E battle (kwh) and battery power density D power (w / kg); where the system parameters of the initial powertrain configuration are expressed as

[0061] S104, taking the maximum power performance index as a constraint, determining the maneuverability index under different driving scenarios in the comprehensive evaluation condition; the maneuverability index includes: average passing speed V avg , maximum acceleration a max , minimum turning radius R min , average climbing speed V avg_g , average speed of step travel V avg_s and the average swing arm obstacle crossing speed V avg_b ; Calculate the average passing speed, maximum acceleration, and minimum turning radius in the starting section; calculate the average climbing speed, average passing speed, and minimum turning radius in the second and terminal sections; calculate the average step driving speed in the third section; and calculate the average swing arm obstacle crossing speed in the fourth section.

[0062] S105, using the mobility index as an evaluation parameter and a mode switching penalty function to construct a global evaluation function; and obtaining a comprehensive evaluation result according to the global evaluation function;

[0063] The global evaluation function specifically includes:

[0064]

[0065] Among them, k p is the weight of each evaluation parameter, f(x p ) is the evaluation parameter, f iis the global evaluation parameter, p is the pth evaluation parameter, and n is the total number of evaluation parameters. p )Including:Including:The average passing speed V of the starting section avg_1 , maximum acceleration of the starting section a max , the minimum turning radius R of the starting section min_1 , the average passing speed V of the second section and the terminal section avg_2 , the average climbing speed V of the second and final sections avg_g , the minimum turning radius R of the second section and the final section min_2 , average speed of step travel V avg_s , average swing arm obstacle crossing speed V avg_b ;

[0066] S106, performing attribution analysis on the comprehensive evaluation results to determine key factors of multi-modal vehicle mobility;

[0067] S106 specifically includes:

[0068] The evaluation parameters are standardized to eliminate dimensional differences. The standardization process is as follows:

[0069]

[0070]

[0071] in, s p are the parameter mean and standard deviation, is the standardized evaluation parameter.

[0072] The correlation matrix R between the various evaluation parameters is as follows:

[0073]

[0074] Among them, r ij represents the evaluation parameter f(x i ) and f(x j ),

[0075] The principal component analysis (PCA) method was used to analyze the standardized evaluation parameters to obtain potential factors. The principal component analysis (PCA) method was used to extract potential factors, and factors with eigenvalues ​​greater than 1 were selected as the main factors to obtain the initial factor loading matrix Λ. The factor loading matrix was then rotated so that each factor had a higher load on fewer variables in order to better explain the physical meaning of the factors.

[0076] After obtaining the rotated factor loading matrix Λ, the factor scores of each powertrain configuration of the multimodal underground vehicle on each evaluation parameter (i.e., average passing speed, maximum acceleration, average climbing speed with minimum turning radius, minimum turning radius, average speed of step driving, and average swing arm obstacle crossing speed) are calculated, that is, the factor analysis method (FA) is used to perform attribution analysis on the potential factors to determine the key factors of the multimodal vehicle's mobility. The factor analysis method can effectively reduce the complexity of the evaluation model and simplify the number of parameters of the optimization model by extracting potential factors. In addition, the factor analysis method can reveal the intrinsic relationship between the evaluation parameters to a certain extent:

[0077] Using the formula Determine the factor score F j ;

[0078] in, is the evaluation parameter after standardization, p is the pth evaluation parameter, b ji is the weight factor.

[0079] S107, using a multi-objective optimization algorithm, a fast non-dominated sorting genetic algorithm, to iteratively optimize the key factors of the multi-modal vehicle mobility; replacing the system parameters of the initial power transmission system configuration with the iterative optimization results, and returning to the step of determining the maximum power performance index under different driving modes according to the system parameters of the initial power transmission system configuration, until the target power transmission system configuration is obtained. The target power transmission system configuration is a power transmission system configuration with the best power performance and better adaptability to the standard working conditions of underground vehicles under the premise that the cost and appearance remain almost unchanged.

[0080] S107 specifically includes:

[0081] The objective function J is determined using the formula maxJ = X1 + X2 + ...; where X i is the key factor, and max is the maximum value. The objective function is to maximize mobility, and the cost and powertrain selection should not exceed expectations.

[0082] The decision variables of NSGA-II are the system parameters of the powertrain configuration. All non-dominated solutions are weighted and the iteratively optimized powertrain configuration is obtained, including:

[0083] U = λJ + (1-λ)I;

[0084] Among them, I is the cost constraint function, and λ is the weight.

[0085] Based on the same inventive concept, the embodiment of the present application also provides a device for determining the configuration of a power transmission system based on a multimodal underground vehicle for implementing the method for determining the configuration of a power transmission system based on a multimodal underground vehicle mentioned above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the device for determining the configuration of a power transmission system based on a multimodal underground vehicle provided below can refer to the limitations of the method for determining the configuration of a power transmission system based on a multimodal underground vehicle above, and will not be repeated here.

[0086] In an exemplary embodiment, a device for determining a powertrain configuration based on a multi-modal underground vehicle is provided, comprising:

[0087] An initial configuration determination module, used to determine an initial powertrain configuration according to a vehicle driving scenario;

[0088] A comprehensive evaluation condition determination module is used to determine comprehensive evaluation conditions including structured and unstructured roads; the comprehensive evaluation conditions include: different driving scenarios; the driving scenarios include: horizontal roads, mountain slopes, steps and vertical obstacles;

[0089] A maximum power performance index determination module is used to determine the maximum power performance index under different driving modes according to the system parameters of the initial power transmission system configuration; the driving modes include: wheel drive, track drive and swing arm drive; the maximum power performance index includes: maximum traction, maximum climbing ability, maximum speed and maximum height of swing arm obstacle crossing; the system parameters include: maximum output power of the motor, peak torque of the motor, reduction ratio, battery energy and battery power density;

[0090] The maneuverability index determination module is used to determine the maneuverability index under different driving scenarios in the comprehensive evaluation condition with the maximum power performance index as a constraint; the maneuverability index includes: average passing speed, maximum acceleration, minimum turning radius, average climbing speed, average step driving speed and average swing arm obstacle crossing speed;

[0091] A comprehensive evaluation result determination module is used to construct a global evaluation function using the mobility index as an evaluation parameter and a mode switching penalty function; and obtain a comprehensive evaluation result according to the global evaluation function;

[0092] The key factor determination module is used to perform attribution analysis on the comprehensive evaluation results and determine the key factors of multi-modal vehicle mobility;

[0093] The iterative optimization module is used to iteratively optimize the key factors of multi-modal vehicle mobility using a multi-objective optimization algorithm, a fast non-dominated sorting genetic algorithm; replace the system parameters of the initial powertrain configuration with the iterative optimization results, and return to the maximum power performance index determination module until the target powertrain configuration is obtained.

[0094] In an exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O for short) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for determining the configuration of a powertrain system based on a multimodal underground vehicle is implemented.

[0095] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0096] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0097] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0098] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0099] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0100] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0101] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for determining a power transmission system configuration based on a multi-modal underground vehicle, characterized in that: The method for determining the configuration of a power transmission system based on a multi-modal underground vehicle comprises: Determine the initial powertrain configuration based on the vehicle driving scenario; Determine the comprehensive evaluation conditions including structured and unstructured roads; the comprehensive evaluation conditions include: different driving scenarios; driving scenarios include: horizontal roads, mountain slopes, steps and vertical obstacles; Determine the maximum power performance index under different driving modes according to the system parameters of the initial power transmission system configuration; the driving modes include: wheel drive, track drive and swing arm drive; the maximum power performance index includes: maximum traction, maximum climbing ability, maximum speed and maximum height of swing arm obstacle crossing; the system parameters include: maximum output power of the motor, peak torque of the motor, reduction ratio, battery energy and battery power density; Taking the maximum power performance index as a constraint, determine the maneuverability index under different driving scenarios in the comprehensive evaluation condition; the maneuverability index includes: average passing speed, maximum acceleration, minimum turning radius, average climbing speed, average step driving speed and average swing arm obstacle crossing speed; Taking the mobility index as the evaluation parameter and the mode switching penalty function, a global evaluation function is constructed; and a comprehensive evaluation result is obtained according to the global evaluation function; Conduct attribution analysis on the comprehensive evaluation results to determine the key factors of multimodal vehicle mobility; A multi-objective optimization algorithm, a fast non-dominated sorting genetic algorithm, is used to iteratively optimize the key factors of multi-modal vehicle maneuverability; the iterative optimization results replace the system parameters of the initial powertrain configuration, and the step of determining the maximum power performance index under different driving modes according to the system parameters of the initial powertrain configuration is returned until the target powertrain configuration is obtained.

2. The method for determining the configuration of a power transmission system based on a multi-modal underground vehicle according to claim 1, characterized in that: The global evaluation function specifically includes: Among them, k p is the weight of each evaluation parameter, f(x p ) is the evaluation parameter, f i is the global evaluation parameter, p is the pth evaluation parameter, and n is the total number of evaluation parameters.

3. The method for determining the configuration of a power transmission system based on a multi-modal underground vehicle according to claim 1, characterized in that: The attribution analysis of the comprehensive evaluation results is performed to determine the key factors of multimodal vehicle mobility, specifically including: Standardize the evaluation parameters; The principal component analysis method was performed on the standardized evaluation parameters to obtain the potential factors; Factor analysis was used to conduct attribution analysis on latent factors and identify the key factors of multimodal vehicle mobility.

4. The method for determining the configuration of a power transmission system based on a multi-modal underground vehicle according to claim 3, characterized in that: The factor analysis method is used to perform attribution analysis on potential factors to determine the key factors of multimodal vehicle mobility, including: Using the formula Determine the factor score F j ; in, is the evaluation parameter after standardization, p is the pth evaluation parameter, b ji is the weight factor.

5. The method for determining a power transmission system configuration based on a multi-modal underground vehicle according to claim 1, characterized in that: The multi-objective optimization algorithm fast non-dominated sorting genetic algorithm is used to iteratively optimize the key factors of multi-modal vehicle mobility, specifically including: The objective function J is determined using the formula maxJ = X1 + X2 + ..., where X i is the key factor, and max is the maximum value.

6. The method for determining the configuration of a power transmission system based on a multi-modal underground vehicle according to claim 5, characterized in that: The iteratively optimized powertrain configuration includes: U = λJ + (1-λ)I; Among them, I is the cost constraint function, and A is the weight.

7. A device for determining a powertrain configuration of a multi-modal underground vehicle, characterized in that: The device for determining the configuration of a power transmission system based on a multi-modal underground vehicle comprises: An initial configuration determination module, used to determine an initial powertrain configuration according to a vehicle driving scenario; A comprehensive evaluation condition determination module is used to determine comprehensive evaluation conditions including structured and unstructured roads; the comprehensive evaluation conditions include: different driving scenarios; the driving scenarios include: horizontal roads, mountain slopes, steps and vertical obstacles; A maximum power performance index determination module is used to determine the maximum power performance index under different driving modes according to the system parameters of the initial power transmission system configuration; the driving modes include: wheel drive, track drive and swing arm drive; the maximum power performance index includes: maximum traction, maximum climbing ability, maximum speed and maximum height of swing arm obstacle crossing; the system parameters include: maximum output power of the motor, peak torque of the motor, reduction ratio, battery energy and battery power density; The maneuverability index determination module is used to determine the maneuverability index under different driving scenarios in the comprehensive evaluation condition with the maximum power performance index as a constraint; the maneuverability index includes: average passing speed, maximum acceleration, minimum turning radius, average climbing speed, average step driving speed and average swing arm obstacle crossing speed; A comprehensive evaluation result determination module is used to construct a global evaluation function using the mobility index as an evaluation parameter and a mode switching penalty function; and obtain a comprehensive evaluation result according to the global evaluation function; The key factor determination module is used to perform attribution analysis on the comprehensive evaluation results and determine the key factors of multi-modal vehicle mobility; The iterative optimization module is used to iteratively optimize the key factors of multi-modal vehicle mobility using a multi-objective optimization algorithm, a fast non-dominated sorting genetic algorithm; replace the system parameters of the initial powertrain configuration with the iterative optimization results, and return to the maximum power performance index determination module until the target powertrain configuration is obtained.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for determining the powertrain configuration based on a multimodal underground vehicle as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for determining the configuration of a power transmission system based on a multi-modal underground vehicle described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for determining the configuration of a power transmission system based on a multi-modal underground vehicle described in any one of claims 1 to 6 is implemented.

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