Method and apparatus for optimizing housing of electric drive controller, computer device, and storage medium

Abstract

The present application provides a method and apparatus for optimizing a housing of an electric drive controller, a computer device, and a storage medium. The method comprises: simulating an all-in-one electric drive loading state by means of adjusting coordinates of a simulation analysis model and adjusting rubber stiffness of a suspension support (201); setting a modal optimization boundary, determining an equivalent acoustic power, and loading electromagnetic excitation (202); on the basis of a design scheme of an electric drive assembly and layout space of a whole vehicle, determining an optimized design space model of a housing (203); on the basis of a topology optimization result of topology optimization analysis performed on the optimized design space model, obtaining a material density distribution of the housing (204); and on the basis of the material density distribution of the housing, determining a surface topography topological feature distribution of the housing (205).

Description

Methods, apparatus, computer equipment, and storage media for optimizing the housing of an electric drive controller

[0001] This application claims priority to Chinese Patent Application No. 202411925116.6, filed on December 25, 2024, entitled "Method, Apparatus, Computer Equipment and Storage Medium for Optimizing Housing of Electric Drive Controller", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of computer technology, and in particular to a method, apparatus, computer device, and storage medium for optimizing the housing of an electric drive controller. Background Technology

[0003] The vibration and noise issues of the housing in multi-functional electric drive systems for new energy vehicles have always been a key focus during the design and development phase. For thin-walled components such as controllers or motors in multi-functional electric drives, they are typically subjected to radial or tangential electromagnetic forces originating from the motor side during actual use. This often leads to significant surface-radiated noise, affecting the NVH (Noise, Vibration, and Harshness) quality and performance of the electric drive product, thereby reducing its competitiveness. Summary of the Invention

[0004] This application provides a method, apparatus, computer device, and storage medium for optimizing the housing of an electric drive controller, thereby improving the optimization effect on NVH (Noise, Vibration, and Harshness). The technical solution is as follows:

[0005] On one hand, a method for optimizing the housing of an electric drive controller is provided, the method comprising:

[0006] The vehicle installation status of the multi-functional electric drive was simulated by adjusting the coordinates of the simulation analysis model and the rubber stiffness of the suspension bracket.

[0007] Set modal optimization boundaries, determine equivalent acoustic power, and apply electromagnetic excitation;

[0008] Based on the design scheme of the electric drive assembly and the overall vehicle layout space, the optimized design space model of the shell is determined;

[0009] Based on the topology optimization results of the topology optimization analysis of the optimized design space model, the material density distribution of the shell is obtained;

[0010] Based on the material density distribution of the shell, the surface topographic feature distribution of the shell is determined.

[0011] On the other hand, a housing optimization device for an electric drive controller is provided, the device comprising:

[0012] The adjustment module is used to simulate the vehicle installation state of the all-in-one electric drive by adjusting the coordinates of the simulation analysis model and the rubber stiffness of the suspension bracket.

[0013] The configuration module is used to set the modal optimization boundary, determine the equivalent acoustic power, and apply electromagnetic excitation.

[0014] The first determining module is used to determine the optimized design space model of the housing based on the design scheme of the electric drive assembly and the overall vehicle layout space.

[0015] The optimization module is used to obtain the material density distribution of the shell based on the topology optimization results of the topology optimization analysis of the optimized design space model;

[0016] The second determining module is used to determine the surface topographic feature distribution of the shell based on the material density distribution of the shell.

[0017] In some embodiments, the second determining module is used to obtain a shell design scheme for the shell based on the material density distribution of the shell; and to perform morphological optimization design on the shell based on the shell design scheme to obtain the surface morphological topological feature distribution of the shell.

[0018] In some embodiments, the topology optimization analysis includes modal analysis conditions and vibration analysis conditions;

[0019] The optimization module is used to perform the modal analysis condition with frequency as the optimization response target; to perform the vibration analysis condition with surface vibration velocity as the optimization response target; or to perform the vibration analysis condition with equivalent acoustic power as the optimization response target.

[0020] In some embodiments, the apparatus further includes:

[0021] The acquisition module is used to acquire the multi-in-one electric drive housing, controller model, motor model, suspension model, and geometric models of multiple components;

[0022] The model processing module is used to perform geometric assembly on the geometric models of the multiple components;

[0023] The modeling module is used to build the simulation analysis model.

[0024] In some embodiments, the apparatus further includes:

[0025] The third determining module is used to determine the parameters of the load spectrum and the common operating conditions based on at least one of the bench test conditions or the vehicle road spectrum; and to determine the electromagnetic excitation of the common operating conditions in the load spectrum based on the parameters of the common operating conditions.

[0026] In some embodiments, the apparatus further includes:

[0027] The fourth determination module is used to perform preliminary evaluation and analysis of the controller assembly modes, and determine whether the weakest structural area of ​​the housing should be fixed with bolts based on the frequency and mode shape performance.

[0028] In some embodiments, the apparatus further includes:

[0029] The design module is used for secondary design of the housing;

[0030] The verification module is used to perform assembly modal evaluation verification on the shell obtained by secondary design, or to perform vibration response evaluation in other dynamic software, so as to verify the design effect of the shell.

[0031] On the other hand, a computer device is provided, the computer device including a processor and a memory, the memory being used to store at least one computer program, the at least one computer program being loaded and executed by the processor to implement the operations performed by the housing optimization method of the electric drive controller in the embodiments of this application.

[0032] On the other hand, a computer-readable storage medium is provided that stores at least one computer program, which is loaded and executed by a processor to perform operations as performed by the housing optimization method of the electric drive controller in the embodiments of this application.

[0033] On the other hand, a computer program product is provided, which includes computer program code stored in a computer-readable storage medium. A processor of a computer device reads the computer program code from the computer-readable storage medium and executes the computer program code, causing the computer device to perform the housing optimization method of the electric drive controller provided in various alternative implementations of the above aspects.

[0034] This application provides a housing optimization scheme for an electric drive controller. By accurately simulating the vehicle's installation state, the optimization can closely match the actual operating conditions. Reasonably setting modal optimization boundaries and determining the equivalent acoustic power and applied electromagnetic excitation allows for in-depth analysis of the housing's vibration and noise characteristics, providing a scientific basis for optimization. Determining the optimization design space model based on the design scheme and the vehicle's space ensures the feasibility and adaptability of the optimization. Topology optimization analysis yields the material density distribution and determines the surface morphology topological feature distribution, helping to achieve lightweight housing design while meeting performance requirements, improving the overall performance, reliability, and economy of the electric drive controller, and enhancing product competitiveness. Furthermore, by combining optimization design, vibration simulation, and load spectrum, a complete analysis and design process is established for multi-condition joint vibration simulation optimization design of the housing. This allows for comprehensive evaluation of the housing's vibration performance and NVH characteristics during the product development and design phase, solving the problems of long development cycles and high costs. Attached Figure Description

[0035] Figure 1 is a schematic diagram of the implementation environment of the housing optimization method for the electric drive controller provided according to an embodiment of this application;

[0036] Figure 2 is a flowchart of a housing optimization method for an electric drive controller according to an embodiment of this application;

[0037] Figure 3 is a flowchart of another housing optimization method for an electric drive controller according to an embodiment of this application;

[0038] Figure 4 is a schematic diagram of a controller part model provided according to an embodiment of this application;

[0039] Figure 5 is a schematic diagram of an electromagnetic excitation provided according to an embodiment of this application;

[0040] Figure 6 is a schematic diagram of a controller part model and an optimization design space model provided according to an embodiment of this application;

[0041] Figure 7 is a schematic diagram of a surface topology feature distribution according to an embodiment of this application;

[0042] Figure 8 is a schematic diagram of a redesigned housing according to an embodiment of this application;

[0043] Figure 9 is a flowchart of another housing optimization method for an electric drive controller according to an embodiment of this application;

[0044] Figure 10 is a block diagram of a housing optimization device for an electric drive controller according to an embodiment of this application;

[0045] Figure 11 is a structural block diagram of a terminal according to an embodiment of this application;

[0046] Figure 12 is a schematic diagram of the structure of a server provided according to an embodiment of this application. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0048] It should be noted that all information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in this application have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the snapshot data and faults involved in this application were obtained with full authorization.

[0049] Figure 1 is a schematic diagram of the implementation environment of the housing optimization method for an electric drive controller provided according to an embodiment of this application. Referring to Figure 1, the implementation environment includes: a terminal 110 and a server 120.

[0050] Terminal 110 can be a smartphone, tablet, laptop, desktop computer, smartwatch, etc., but is not limited to these. Terminal 110 can connect to server 120 via wireless network or wired network.

[0051] Server 120 may include at least one of a single server, multiple servers, a cloud computing platform, or a virtualization center. Server 120 is used to provide background services for applications that support virtual scenarios. Optionally, server 120 may undertake the primary computing task, and terminal 110 may undertake the secondary computing task; or, server 120 may undertake the secondary computing task, and terminal 110 may undertake the primary computing task; or, server 120 and terminal 110 may collaborate on computing using a distributed computing architecture.

[0052] Figure 2 is a flowchart of a housing optimization method for an electric drive controller according to an embodiment of this application. As shown in Figure 2, this embodiment is illustrated using a computer device as an example. The housing optimization method for the electric drive controller includes the following steps:

[0053] 201. By adjusting the coordinates of the simulation analysis model and the rubber stiffness of the suspension bracket, the vehicle installation state of the multi-in-one electric drive is simulated.

[0054] In this embodiment, adjusting the coordinates allows the position of the electric drive controller in the virtual environment to match its installation position in the actual vehicle. The suspension bracket connects the electric drive controller to the vehicle body, and rubber serves as the material for cushioning and support. Adjusting the rubber stiffness simulates the elastic characteristics of the bracket during actual vehicle installation. Different rubber stiffnesses affect the vibration transmission of the electric drive controller during vehicle operation.

[0055] A simulation analysis model is a digital representation of a real-world system, process, or phenomenon, abstracted, simplified, and simulated using computer or mathematical methods. Its purpose is to predict, evaluate, optimize, or understand the operating mechanism of a system by simulating its behavior or dynamic processes. Simulation analysis models typically combine theory, experimental data, and algorithms to virtually reproduce or predict the performance of a real-world system.

[0056] 202. Set modal optimization boundaries, determine equivalent acoustic power, and apply electromagnetic excitation.

[0057] In this embodiment, the modal optimization boundary refers to the constraint conditions determined when performing modal analysis on the electric drive controller housing. Equivalent acoustic power is an important indicator for measuring the noise generated by the electric drive controller. Since the electric drive controller is subjected to electromagnetic forces during operation, the effect of these electromagnetic forces on the housing can be simulated in the simulation model by applying electromagnetic excitation. Applying electromagnetic excitation refers to applying an external electromagnetic field or current / voltage signal to the system in simulation or experiment to simulate or stimulate its electromagnetic response behavior.

[0058] 203. Based on the design scheme of the electric drive assembly and the overall vehicle layout space, determine the optimized design space model of the housing.

[0059] In this embodiment, the electric drive assembly includes multiple components such as a motor and a controller. Its design specifies numerous factors, including the performance, size, and connection method of each component. Vehicle layout space refers to the actual space inside the vehicle available for installing the electric drive controller. The vehicle layout is limited by various factors such as vehicle type and body structure.

[0060] 204. Based on the topology optimization results of the topology optimization analysis of the optimized design space model, the material density distribution of the shell is obtained.

[0061] In this embodiment, topology optimization considers various factors such as the stress conditions, vibration characteristics, and space constraints of the shell during actual operation. Based on these conditions, within a given design space, the material distribution is continuously adjusted to find a layout that allows the shell to meet various performance requirements (such as sufficient strength and appropriate stiffness) while also achieving certain optimization goals, such as reducing weight or improving heat dissipation efficiency.

[0062] The results of topology optimization are presented in the form of material density distribution. Material density distribution refers to the density variation or spatial arrangement characteristics of different locations within a material. In short, this material density distribution is like a "map" that shows how the material should be distributed in different locations within the shell.

[0063] 205. Based on the material density distribution of the shell, determine the distribution of the surface topological features of the shell.

[0064] In this embodiment, the material density distribution reflects the amount of material at different locations within the shell. Determining the surface topological feature distribution based on this distribution means planning the shape of the shell surface according to the density of the material. This distribution allows the surface shape of the shell to better match the needs of its internal materials.

[0065] This application provides a housing optimization scheme for an electric drive controller. By accurately simulating the vehicle's installation state, the optimization can closely match the actual operating conditions. Reasonably setting modal optimization boundaries and determining the equivalent acoustic power and applied electromagnetic excitation allows for in-depth analysis of the housing's vibration and noise characteristics, providing a scientific basis for optimization. Determining the optimization design space model based on the design scheme and the vehicle's space ensures the feasibility and adaptability of the optimization. Topology optimization analysis yields the material density distribution and determines the surface morphology topological feature distribution, helping to achieve lightweight housing design while meeting performance requirements, improving the overall performance, reliability, and economy of the electric drive controller, and enhancing product competitiveness. Furthermore, by combining optimization design, vibration simulation, and load spectrum, a complete analysis and design process is established for multi-condition joint vibration simulation optimization design of the housing. This allows for comprehensive evaluation of the housing's vibration performance and NVH characteristics during the product development and design phase, solving the problems of long development cycles and high costs.

[0066] Figure 3 is a flowchart of another housing optimization method for an electric drive controller according to an embodiment of this application. As shown in Figure 3, this embodiment of the application illustrates the method as being executed by a computer device. The housing optimization method for the electric drive controller includes the following steps:

[0067] 301. Obtain the multi-in-one electric drive housing, controller model, motor model, suspension model, and geometric models of multiple components.

[0068] In this embodiment, the all-in-one electric drive housing is a shell structure used to house and protect multiple key components in an electric drive system. The shape, size, and internal space layout of the all-in-one electric drive housing must comprehensively consider the installation, heat dissipation, and protection requirements of the integrated controller, motor, and other components.

[0069] For example, in the electric drive system of new energy vehicles, the housing must ensure that the motor and controller are protected from external factors such as dust and moisture during operation, while providing a reasonable channel for internal heat dissipation. Obtaining a model of the all-in-one electric drive housing involves creating a digital representation that accurately reflects the geometry, structural details, and spatial characteristics of the housing through certain methods, so as to facilitate subsequent engineering studies such as strength analysis, modal analysis, and optimization design.

[0070] Alternatively, engineers can use professional 3D CAD (computer-aided design) software, such as SolidWorks, CATIA, UG, etc., to gradually build the various surface and volume features of the shell according to the pre-planned design requirements, starting from sketching, defining details such as thickness, holes, and mounting bosses, and finally generating a complete 3D model of the shell.

[0071] Optionally, when an actual shell sample is available, reverse engineering can be employed. For example, a 3D scanner can be used to scan the shell surface from all angles, acquiring a large amount of point cloud data. Then, specialized data processing software (such as Geomagic Wrap) can be used to convert the point cloud data into a triangular patch model. Further model repair, surface reconstruction, and other operations can be performed to finally obtain a 3D geometric model of the shell that can be used for subsequent analysis.

[0072] The electric drive controller is the "brain" of the entire electric drive system, responsible for regulating the motor's operating state, such as controlling its speed and torque. The controller model is a digital representation of the controller's physical entity, encompassing the geometry and layout information of its circuit boards, chips, heat sinks, and housing. This model allows for analysis of the controller's installation compatibility within the housing, heat dissipation, and electromagnetic compatibility.

[0073] For example, you can check whether the gap between it and the internal space of the casing is reasonable to ensure that the heat dissipation air can flow smoothly.

[0074] Alternatively, using 3D CAD software, the external dimensions of each component can be determined first, based on the controller's circuit design and functional module layout requirements. Then, virtual assembly can be performed in the software to form a complete controller model. Alternatively, if 2D engineering drawings of the controller already exist, the drawing information can be imported using the CAD software's import function for 3D modeling, converting the 2D dimensions and shape information into a 3D geometric model, facilitating subsequent simulation analysis and optimization.

[0075] An electric motor is the core component that converts electrical energy into mechanical energy. Its model shows the specific geometric shapes and relative positions of its stator, rotor, housing, shaft, and other parts. This is crucial for analyzing the motor's vibration characteristics, magnetic field distribution, and its interaction with other components during operation.

[0076] Alternatively, engineers can use software such as ANSYS Maxwell, which is specifically designed for electromagnetic field analysis and design of motors. By inputting key parameters of the motor (such as the number of pole pairs, the number of stator slots, and the number of winding turns), the software will automatically generate the corresponding motor model.

[0077] Mounts are used to connect electric drive systems and vehicle bodies, providing support, cushioning, and vibration isolation. Mount models demonstrate the shape and structural characteristics of the rubber components and metal connectors, aiding in the analysis of their vibration isolation performance, stiffness characteristics, and connection reliability with surrounding parts under different operating conditions.

[0078] Optionally, by conducting mechanical property tests on actual suspended samples, such as tensile tests and compression tests, deformation data under different stress states can be obtained. Then, based on these data, a suitable material model (such as a hyperelastic material model to simulate rubber) can be used in finite element analysis software (such as ANSYS, ABAQUS, etc.) to construct a model of the suspension so that it can accurately reflect the actual mechanical properties.

[0079] The components here encompass other related parts of the electric drive system besides the main components mentioned above, such as various sensors, connecting harnesses, and heat dissipation pipes. Their respective geometric models reflect their shape, size, and positional relationship within the entire electric drive system, which is of great significance for constructing a complete virtual model of the electric drive system, studying the collaborative work between components, and evaluating the overall system performance.

[0080] Optionally, based on the design specifications, engineering drawings, and other documents for each component, 3D modeling is performed individually using CAD software to construct the detailed geometry of each component. Then, these components are assembled in the software according to their actual assembly relationships to form a complete set of geometric models for multiple components. For some common, highly standardized components, geometric models of existing products of the same type can be referenced, and appropriate modifications and adjustments can be made based on the specific design requirements of the product. This allows for the rapid acquisition of geometric models for the corresponding components, improving modeling efficiency while ensuring the accuracy and usability of the models.

[0081] For example, see Figure 4, which is a schematic diagram of a controller part model provided according to an embodiment of this application.

[0082] 302. Perform geometric assembly on the geometric models of multiple components.

[0083] In this embodiment, geometric assembly is the process of combining multiple component geometric models (such as an all-in-one electric drive housing, controller model, motor model, suspension model, etc.) according to their relative positions and connection relationships in the actual product. Its main purpose is to construct a complete virtual model that realistically reflects the actual structure and spatial layout of the product. Through geometric assembly, the state of the product in its actual working environment can be simulated, and important issues such as interference between components, space occupancy, and the rationality of connections can be studied.

[0084] Optionally, before assembly, the assembly sequence of each component should be determined based on the product's structural characteristics and assembly process requirements. Before assembly, the integrity of the geometric model of each component must be carefully checked to ensure that the model has no missing surfaces, geometric errors, or dimensional deviations.

[0085] Optionally, the positioning tools in 3D modeling software can be used to accurately place each component in its predetermined position. To ensure the accuracy and stability of the assembly, it is necessary to set constraints between the components. Common constraints include coincidence constraints, parallel constraints, perpendicular constraints, and distance constraints.

[0086] It should be noted that the assembly relationship must be consistent with the actual situation, and the mass and center of gravity of the electric drive assembly, controller, and all-in-one electronic and electrical component assembly must be consistent with the actual state. Parameters include elastic modulus, density, Poisson's ratio, etc., but this application embodiment does not impose strict limitations on these parameters. Optionally, each component adopts a geometric model containing detailed features.

[0087] 303. Establish a simulation analysis model.

[0088] In this application embodiment, establishing a simulation analysis model is a process of transforming an actual physical system (such as an all-in-one electric drive system) into a digital model that can be recognized and computed by a computer. This will not be elaborated further in this application embodiment. A simulation analysis model refers to a digital representation of a real-world system, process, or phenomenon that is abstracted, simplified, and simulated using computer or mathematical methods. Its purpose is to predict, evaluate, optimize, or understand the operating mechanism of a system by simulating its behavior or dynamic processes. Simulation analysis models typically combine theory, experimental data, and algorithms to virtually reproduce or predict the performance of an actual system.

[0089] 304. Determine the parameters of the load spectrum and common operating conditions based on at least one of the bench test conditions or the vehicle road spectrum.

[0090] In this embodiment, bench testing is the process of testing an electric drive system or its components in a laboratory environment using specialized testing equipment (such as a motor performance test bench, vibration test bench, etc.). Bench test conditions refer to the various operating states simulated in these tests, including but not limited to different motor speeds, torque outputs, and loading methods.

[0091] For example, in motor performance bench tests, the motor is set to accelerate from a standstill to its rated speed, maintain that speed for a certain period of time, and then decelerate, in order to evaluate the motor's performance at different operating stages.

[0092] A vehicle road spectrum is a record describing the changes in various physical quantities (such as acceleration, displacement, and force) of a vehicle over time or mileage during actual road driving. It includes dynamic information about the vehicle under different road conditions (such as urban roads, highways, and rural dirt roads) and different driving conditions (such as constant speed, acceleration, deceleration, and turning). A vehicle road spectrum can be obtained by installing sensors (such as accelerometers and strain gauges) on an actual vehicle for long-term data collection.

[0093] For example, on a bumpy road, the vibration acceleration spectrum of a vehicle's suspension system can reflect the severity of the vehicle's vibration under those road conditions.

[0094] For electric drive systems, the loads mainly include mechanical loads (such as vibration, shock, inertial force, etc.) and electromagnetic loads (such as electromagnetic force, current, magnetic field, etc.). Under bench test conditions, the mechanical loads come from the vibration excitation or torque fluctuations generated by the torque loading device applied to the electric drive system by the test bench; the electromagnetic loads are caused by the changes in current and voltage provided by the test power supply.

[0095] During bench testing, various load data are recorded through the data acquisition system of the testing equipment.

[0096] The extracted and processed load data are combined into a load spectrum according to certain rules. The load spectrum is usually a statistical description, which can be a curve showing the relationship between load amplitude and frequency, or the distribution pattern of load over time or distance.

[0097] Both bench test conditions and vehicle road test profiles encompass a variety of operating conditions. It is necessary to select commonly used operating conditions based on the actual usage of the product and the research focus. For these selected commonly used operating conditions, key parameters must be determined and quantified.

[0098] 305. Based on the parameters of commonly used operating conditions, determine the electromagnetic excitation of commonly used operating conditions in the load spectrum.

[0099] In the embodiments of this application, commonly used operating parameters describe the working states that electric drive systems frequently encounter in actual operation, such as the motor's speed range, torque range, and operating time ratio. These operating conditions directly affect the electromagnetic processes within the electric drive system, thereby determining the characteristics of electromagnetic excitation. Electromagnetic excitation is the force or energy input generated by the interaction of electromagnetic fields. It is the power source for the operation of electric drive components such as motors, but it can also lead to problems such as vibration and noise.

[0100] Optionally, the electromagnetic excitation can be calculated using relevant formulas based on electromagnetic theory. The electromagnetic force between the stator and rotor of the motor can be calculated using Maxwell's stress tensor method.

[0101] For example, see Figure 5, which is a schematic diagram of an electromagnetic excitation provided according to an embodiment of this application.

[0102] 306. By adjusting the coordinates of the simulation analysis model and the rubber stiffness of the suspension bracket, the vehicle installation state of the all-in-one electric drive is simulated.

[0103] In this embodiment, during simulation analysis, the model's position and orientation are defined based on a specific coordinate system. This coordinate system is similar to a three-dimensional spatial reference frame, with x, y, and z axes. By adjusting the model's position within this coordinate system, i.e., changing its coordinates, the model's position in the virtual environment can be matched to its position in the actual vehicle loading state.

[0104] For example, in a car's electric drive system, the motor and controller have specific mounting positions on the vehicle body. Assuming the car's coordinate system has the front of the car as the positive x-axis, the vertical upward direction as the positive z-axis, and the left lateral direction as the positive y-axis, then the position of the electric drive system within this coordinate system can be precisely represented by coordinate values. If the electric drive model is arbitrarily placed without coordinate adjustment, adjusting the coordinates can place the motor in a specific location close to the car chassis, and the controller above the motor, etc., in a position consistent with the actual vehicle layout.

[0105] Optionally, in addition to position, coordinate adjustment can also be used to simulate the actual installation angles and orientations of various components of the electric drive system.

[0106] For example, the motor shaft may need to maintain a certain parallelism and angular relationship with the vehicle's drive shaft to ensure efficient power transmission. This installation angle can be simulated by rotating the model in a coordinate system.

[0107] In vehicle installation, the suspension bracket serves to connect the electric drive system and the vehicle body. It can effectively isolate the vibration generated by the electric drive system from being transmitted to the vehicle body, while also supporting the weight of the electric drive system.

[0108] Rubber is a crucial material component in suspension brackets, and rubber stiffness refers to the rubber material's ability to resist deformation. The magnitude of rubber stiffness directly affects the vibration isolation performance and support characteristics of the suspension bracket. Greater stiffness results in less deformation of the rubber under the same force; conversely, lower stiffness leads to greater deformation.

[0109] In actual vehicle installation, the rubber stiffness of the suspension bracket is determined based on the vehicle's design requirements and the characteristics of the electric drive system. By adjusting the rubber stiffness of the suspension bracket in the simulation model, different vibration isolation and support effects can be simulated, making it closer to the actual vehicle installation situation.

[0110] 307. Set modal optimization boundaries, determine equivalent acoustic power, and apply electromagnetic excitation.

[0111] In this embodiment, a mode refers to the inherent vibration characteristics of a structure under free vibration, including natural frequencies and mode shapes. When performing modal analysis on an electric drive system, the boundary conditions of the structure significantly affect its modes. Boundary conditions define where and how the structure is constrained. Setting modal optimization boundaries aims to find the optimal structural modal parameters while meeting actual installation and operating conditions.

[0112] For example, by adjusting the boundary conditions, the natural frequency of the electric drive system can be prevented from being close to the excitation frequency during vehicle operation (such as the road excitation frequency, motor rotation frequency, etc.), thus preventing resonance and reducing vibration and noise.

[0113] Electric drive systems generate vibrations during operation. These vibrations propagate through the structure and interact with the surrounding air, producing noise. Sound power is a physical quantity that measures the rate at which a sound source radiates sound energy; it is directly related to the intensity of the noise.

[0114] Since the noise of an electric drive system is generated by the combined action of multiple components (such as the motor, controller, and housing), and the frequency components of the noise are complex, determining the equivalent sound power allows for a comprehensive evaluation of these complex noise sources. Equivalent sound power is an equivalent physical quantity that represents the noise generation capability of the entire electric drive system, providing a unified power value to express the intensity of the noise generated by the system.

[0115] In electric drive systems, electromagnetic excitation primarily originates from the interaction of electromagnetic fields within the motor. When current flows through the stator windings of the motor, a magnetic field is generated. This magnetic field interacts with the rotor's magnetic field, producing an electromagnetic force. Electromagnetic excitation is the power source for the electric drive system, driving the motor rotor to rotate; however, it is also a significant factor causing vibration and noise.

[0116] It should be noted that the boundary constraints of the simulation analysis must be consistent with those of the bench vibration test or actual driving conditions. Ensuring consistency in fixed constraints, excitation sources, and transmission paths can improve the accuracy of the simulation analysis.

[0117] 308. Based on the design scheme of the electric drive assembly and the overall vehicle layout space, determine the optimized design space model of the housing.

[0118] In the embodiments of this application, the electric drive assembly typically includes several key components such as a motor, a controller, and transmission components. The motor, as the core of power output, has its size, shape, and performance characteristics that determine the spatial layout of the housing in this area. The controller is a crucial component for controlling the motor's operation; its circuit board size, electronic component layout, and connection interface locations also impose requirements on the housing space. The controller may need to maintain a certain distance from the motor to avoid electromagnetic interference, and the wiring channels for its connection lines within the housing also need to be considered in the design space model. Transmission components (if any), such as reducers, have dimensions and transmission methods that affect the shape and spatial allocation of the housing in this area.

[0119] In the overall vehicle design, the location of the electric drive assembly is determined by a combination of factors, including the vehicle type, the powertrain layout (such as front-wheel drive, rear-wheel drive, four-wheel drive, etc.), and the location of other components (such as the battery, chassis suspension, etc.).

[0120] The vibration, impact, and dynamic deformation conditions that occur during vehicle operation require the housing to be stably installed and function within the vehicle's overall layout space.

[0121] External environmental factors of a vehicle, such as temperature changes and wading depth, also impose requirements on the design of the vehicle body.

[0122] Taking all these factors into account, an optimized design space model for the housing is determined within the framework of the vehicle layout space to achieve the best performance and reliability of the electric drive assembly in the vehicle environment.

[0123] For example, see Figure 6, which is a schematic diagram of a controller part model and an optimization design space model provided according to an embodiment of this application.

[0124] It should be noted that the optimized design space of the housing needs to avoid interference or compression with other electric drive components, while also taking into account the layout space on the side of the vehicle.

[0125] 309. Based on the topology optimization results of the topology optimization analysis of the optimized design space model, the material density distribution of the shell is obtained.

[0126] In this embodiment, topology optimization is a mathematical method used to find the optimal material distribution of a structure under given design space, load conditions, constraints, and other factors. In the optimized design of the electric drive housing, within the scope of the optimized design space model, various forces (such as electromagnetic forces, forces generated by mechanical vibrations, etc.) experienced by the housing during actual operation, performance requirements (such as strength, stiffness, etc.) that need to be met, and manufacturing process constraints are considered to determine how the material distribution can achieve optimal housing performance.

[0127] The results of topology optimization analysis are presented in the form of material density distribution. In the optimized model, each element has a corresponding material density value. This material density value represents the relative amount of material at the element's location. Optionally, this process can consider lightweight design to appropriately reduce the volume of the topology design space.

[0128] For example, a material density of 1 indicates that the unit should be a solid material, a density of 0 indicates that the unit should ideally have no material, and values ​​between 0 and 1 indicate that the unit can be a region with gradually changing material properties (such as porous materials or composite materials), or that the material can be weakened to some extent at this location. This material density distribution provides a visual indication of the recommended material layout for the shell in space, offering clear guidance for subsequent shell design. For example, it helps determine which parts require solid materials to ensure strength, and which parts can use hollow or lightweight materials to reduce weight.

[0129] In some embodiments, topology optimization analysis includes modal analysis and vibration analysis. The computer equipment can perform modal analysis with frequency as the optimization response target, or vibration analysis with surface vibration velocity as the optimization response target; alternatively, it can perform vibration analysis with equivalent sound power as the optimization response target. Optimizing modal analysis with frequency can precisely adjust the structure's natural frequencies, avoiding resonance; optimizing vibration analysis with surface vibration velocity or equivalent sound power can effectively reduce vibration amplitude and noise, improve overall structural performance, enhance stability and comfort, and reduce the risk of failure.

[0130] In the modal analysis, the reference target frequency value should avoid the minimum frequency value corresponding to the main vibration order. The mass target is expressed in the form of volume fraction and the optimization target is to minimize the value. The optimization constraints are set as follows: the vibration velocity of the shell surface is minimized or the equivalent acoustic power ERP is minimized.

[0131] 310. Based on the material density distribution of the shell, determine the distribution of the surface topological features of the shell.

[0132] In this embodiment, the material density distribution is the result of topology optimization analysis, reflecting how much material should be allocated at different locations in the shell to achieve optimal performance. The surface morphology topology feature distribution refers to the spatial arrangement of the shell surface shape and features.

[0133] In some embodiments, determining the surface topological feature distribution of the shell based on its material density distribution includes: the computer device obtaining a shell design scheme based on the shell's material density distribution; and then, the computer device performing topological optimization design on the shell based on the shell design scheme to obtain the surface topological feature distribution of the shell.

[0134] For example, see Figure 7, which is a schematic diagram of a surface topology feature distribution according to an embodiment of this application.

[0135] 311. Conduct a preliminary evaluation and analysis of the controller assembly modes, and determine whether to use a bolt fixing scheme for the weakest area of ​​the housing structure based on the frequency and mode shape performance.

[0136] In this embodiment, modality refers to the inherent vibration characteristics of a structure, including natural frequencies and mode shapes. Modal analysis of the controller assembly aims to determine these characteristics under free vibration conditions. Natural frequencies are the frequencies at which the structure vibrates when no external dynamic forces are applied. By conducting a preliminary evaluation of the controller assembly's modes, its fundamental vibrational characteristics can be understood.

[0137] Resonance occurs when the natural frequency of the controller assembly approaches the external excitation frequency. During resonance, the vibration amplitude increases dramatically, causing significant damage to the structure. Frequency data obtained through modal analysis can identify these potential resonance risks. Observing the distribution of the controller assembly at different natural frequencies can also help identify weak areas. Generally, the mode shapes corresponding to lower natural frequencies reflect the overall stiffness characteristics of the structure. If the vibration amplitude is large in a certain area at lower frequencies, it indicates that the stiffness of that area is relatively low, and it may be a weak area.

[0138] Mode shapes are an important result of modal analysis, graphically displaying the displacement of various parts of a structure during vibration. By observing the mode shape diagram, one can visually see which areas deform significantly during vibration. Mode shapes also include vibrations in different directions, such as axial, radial, and tangential. For controller assemblies, mode shapes in different directions may affect different components.

[0139] Bolting is a common method for connecting and reinforcing structures. In controller assemblies, bolts securely connect the housing to other components (such as the frame or other supporting structures), increasing the overall integrity and rigidity of the structure. Once weak points in the structure are identified, bolting can effectively limit vibrational displacement in these areas, improving structural stability. Optionally, if the weak point is a small, localized area, such as a protruding corner of the housing, bolts can be placed near this corner to tightly connect it to the supporting structure. If a large surface is weak, multiple bolts may be needed to form a reasonable fixing layout to evenly distribute the forces generated by vibration.

[0140] It should be noted that this step is optional.

[0141] 312. Secondary design of the shell.

[0142] In this embodiment, after evaluating and analyzing the modal characteristics of the controller assembly, the weak areas and potential problems of the housing structure, such as resonance risk and insufficient local stiffness, have been identified. The main goal of the secondary design is to optimize these problems and improve the performance of the housing so that it can better meet the requirements of the actual working environment.

[0143] Optionally, reinforcement can be carried out in various ways based on the previously identified weak areas. If the weak area is due to insufficient local stiffness, stiffeners can be added. The shape, size, and distribution of the stiffeners need to be determined based on the specific stress conditions and space constraints.

[0144] Optionally, the shape and dimensions of the shell can be optimized from an overall structural perspective. If certain parts of the shell are found to cause stress concentration or hinder force transmission, they can be modified.

[0145] For example, see Figure 8, which is a schematic diagram of a redesigned housing according to an embodiment of this application.

[0146] 313. Perform assembly modal evaluation and verification on the shell obtained from the secondary design, or conduct vibration response evaluation in other dynamic software to verify the design effect of the shell.

[0147] In this embodiment, after the secondary design of the housing, it is necessary to evaluate and verify whether it has achieved the expected performance improvement goals. Assembly modal evaluation can determine whether the inherent vibration characteristics of the housing structure have been optimized.

[0148] Vibration response assessment provides a more comprehensive understanding of the enclosure's behavior under actual dynamic loads (such as road surface excitation during vehicle operation or motor vibration). This helps determine the enclosure's vibration amplitude and stress distribution under complex operating conditions, thereby verifying whether the designed enclosure can withstand these dynamic loads and maintain good performance.

[0149] It should be noted that, to make the housing optimization scheme of the electric drive controller provided in this application embodiment easier to understand, please refer to Figure 9, which is a flowchart of another housing optimization method for an electric drive controller provided in this application embodiment. As shown in Figure 9, the method includes the following steps: 901. Assembly of the electric drive all-in-one model. 902. Setting optimization boundaries and loading load data. 903. Modal evaluation of the controller assembly to determine the fixed point scheme. 904. Housing topology optimization. 905. Housing morphology optimization. 906. Secondary design of the housing. 907. Modal evaluation and verification. 908. End if requirements are met; otherwise, perform tertiary design and optimization. 909. Multi-condition calculation of the motor and electromagnetic excitation output. 910. ERP analysis of the assembly model. 911. Modal analysis of the assembly.

[0150] This application provides a housing optimization scheme for an electric drive controller. By accurately simulating the vehicle's installation state, the optimization can closely match the actual operating conditions. Reasonably setting modal optimization boundaries and determining the equivalent acoustic power and applied electromagnetic excitation allows for in-depth analysis of the housing's vibration and noise characteristics, providing a scientific basis for optimization. Determining the optimization design space model based on the design scheme and the vehicle's space ensures the feasibility and adaptability of the optimization. Topology optimization analysis yields the material density distribution and determines the surface morphology topological feature distribution, helping to achieve lightweight housing design while meeting performance requirements, improving the overall performance, reliability, and economy of the electric drive controller, and enhancing product competitiveness. Furthermore, by combining optimization design, vibration simulation, and load spectrum, a complete analysis and design process is established for multi-condition joint vibration simulation optimization design of the housing. This allows for comprehensive evaluation of the housing's vibration performance and NVH characteristics during the product development and design phase, solving the problems of long development cycles and high costs.

[0151] Figure 10 is a block diagram of a housing optimization device for an electric drive controller according to an embodiment of this application. This device is used to perform the steps of the above-described housing optimization method for the electric drive controller. Referring to Figure 10, the device includes:

[0152] The adjustment module 1001 is used to simulate the vehicle installation state of the multi-in-one electric drive by adjusting the coordinates of the simulation analysis model and the rubber stiffness of the suspension bracket.

[0153] The setting module 1002 is used to set the modal optimization boundary, determine the equivalent acoustic power, and apply electromagnetic excitation.

[0154] The first determining module 1003 is used to determine the optimized design space model of the housing based on the design scheme of the electric drive assembly and the overall vehicle layout space.

[0155] Optimization module 1004 is used to obtain the material density distribution of the shell based on the topology optimization results of the topology optimization analysis of the optimized design space model;

[0156] The second determining module 1005 is used to determine the surface topographic feature distribution of the shell based on the material density distribution of the shell.

[0157] In some embodiments, the second determining module 1005 is used to obtain a shell design scheme for the shell based on the material density distribution of the shell; and to perform morphological optimization design on the shell based on the shell design scheme to obtain the surface morphological topological feature distribution of the shell.

[0158] In some embodiments, topology optimization analysis includes modal analysis cases and vibration analysis cases;

[0159] The optimization module 1004 is used to perform modal analysis with frequency as the optimization response target; to perform vibration analysis with surface vibration velocity as the optimization response target; or to perform vibration analysis with equivalent acoustic power as the optimization response target.

[0160] In some embodiments, the apparatus further includes:

[0161] The acquisition module is used to acquire the multi-in-one electric drive housing, controller model, motor model, suspension model, and geometric models of multiple components;

[0162] The model processing module is used for geometric assembly of multiple component geometric models;

[0163] The modeling module is used to build simulation analysis models.

[0164] In some embodiments, the apparatus further includes:

[0165] The third determining module is used to determine the parameters of the load spectrum and common operating conditions based on at least one of the bench test conditions or the vehicle road spectrum; and to determine the electromagnetic excitation of the common operating conditions in the load spectrum based on the parameters of the common operating conditions.

[0166] In some embodiments, the apparatus further includes:

[0167] The fourth determination module is used to perform preliminary evaluation and analysis of the controller assembly modes, and to determine whether to use a bolt fixing scheme for the weakest area of ​​the housing structure based on frequency and mode shape performance.

[0168] In some embodiments, the apparatus further includes:

[0169] The design module is used for secondary design of the shell;

[0170] The verification module is used to perform assembly modal evaluation and verification on the shell obtained from the secondary design, or to perform vibration response evaluation in other dynamic software to verify the design effect of the shell.

[0171] It should be noted that the housing optimization device for the electric drive controller provided in the above embodiments is only illustrated by the division of the above functional modules when running the application. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the housing optimization device for the electric drive controller provided in the above embodiments and the housing optimization method embodiments for the electric drive controller belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0172] In the embodiments of this application, the computer device can be configured as a terminal or a server. When the computer device is configured as a terminal, the terminal can act as the execution subject to implement the technical solutions provided in the embodiments of this application. When the computer device is configured as a server, the server can act as the execution subject to implement the technical solutions provided in the embodiments of this application. Alternatively, the technical solutions provided in this application can be implemented through the interaction between the terminal and the server. The embodiments of this application do not limit this.

[0173] Figure 11 is a structural block diagram of a terminal according to an embodiment of this application. The terminal 1100 can be a portable mobile terminal, such as a smartphone, tablet computer, MP3 player (Moving Picture Experts Group Audio Layer III), MP4 player (Moving Picture Experts Group Audio Layer IV), laptop computer, or desktop computer. The terminal 1100 may also be referred to as a user device, portable terminal, laptop terminal, desktop terminal, or other names.

[0174] Typically, terminal 1100 includes a processor 1111 and a memory 1102.

[0175] Processor 1111 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 1111 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 1111 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 1111 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 1111 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0176] The memory 1102 may include one or more computer-readable storage media, which may be non-transitory. The memory 1102 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 1102 are used to store at least one computer program, which is executed by the processor 1111 to implement the housing optimization method for the electric drive controller provided in the method embodiments of this application.

[0177] In some embodiments, the terminal 1100 may also optionally include a peripheral device interface 1103 and at least one peripheral device. The processor 1111, memory 1102, and peripheral device interface 1103 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 1103 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of the following: a radio frequency circuit 1104, a display screen 1105, a camera assembly 1106, an audio circuit 1107, and a power supply 1108.

[0178] Peripheral device interface 1103 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 1111 and memory 1102. In some embodiments, processor 1111, memory 1102 and peripheral device interface 1103 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 1111, memory 1102 and peripheral device interface 1103 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0179] The radio frequency (RF) circuit 1104 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 1104 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 1104 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. In some embodiments, the RF circuit 1104 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit 1104 can communicate with other terminals via at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 1104 may also include circuitry related to NFC (Near Field Communication), which is not limited in this application.

[0180] Display screen 1105 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 1105 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 1111 for processing. In this case, display screen 1105 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one display screen 1105, disposed on the front panel of terminal 1100; in other embodiments, there may be at least two display screens, disposed on different surfaces of terminal 1100 or in a folded design; in still other embodiments, display screen 1105 may be a flexible display screen, disposed on a curved or folded surface of terminal 1100. Furthermore, display screen 1105 may be configured as a non-rectangular, irregular shape, i.e., a non-rectangular screen. The display screen 1105 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0181] The camera assembly 1106 is used to acquire images or videos. In some embodiments, the camera assembly 1106 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the terminal, and the rear-facing camera is located on the back of the terminal. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, a wide-angle camera, and a telephoto camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, panoramic shooting by fusion of the main camera and the wide-angle camera, VR (Virtual Reality) shooting, or other fusion shooting functions. In some embodiments, the camera assembly 1106 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cool light flash, which can be used for light compensation at different color temperatures.

[0182] The audio circuit 1107 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting the sound waves into electrical signals that are input to the processor 1111 for processing, or input to the radio frequency circuit 1104 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each located at a different part of the terminal 1100. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert electrical signals from the processor 1111 or the radio frequency circuit 1104 into sound waves. The speaker may be a conventional diaphragm speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, the audio circuit 1107 may also include a headphone jack.

[0183] Power supply 1108 is used to power the various components in terminal 1100. Power supply 1108 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 1108 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired line, and a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0184] In some embodiments, the terminal 1100 further includes one or more sensors 1109. The one or more sensors 1109 include, but are not limited to: an acceleration sensor 1110, a gyroscope sensor 1111, a pressure sensor 1112, an optical sensor 1113, and a proximity sensor 1114.

[0185] Accelerometer 1110 can detect the magnitude of acceleration along the three axes of a coordinate system established with terminal 1100. For example, accelerometer 1110 can be used to detect the components of gravitational acceleration along the three axes. Processor 1111 can control display screen 1105 to display the user interface in either a landscape or portrait view based on the gravitational acceleration signal acquired by accelerometer 1110. Accelerometer 1110 can also be used for collecting motion data from games or users.

[0186] The gyroscope sensor 1111 can detect the orientation and rotation angle of the terminal 1100. The gyroscope sensor 1111 can work in conjunction with the accelerometer sensor 1110 to collect the user's 3D movements on the terminal 1100. Based on the data collected by the gyroscope sensor 1111, the processor 1111 can perform the following functions: motion sensing (e.g., changing the UI based on the user's tilt), image stabilization during shooting, game control, and inertial navigation.

[0187] The pressure sensor 1112 can be disposed on the side bezel of the terminal 1100 and / or on the lower layer of the display screen 1105. When the pressure sensor 1112 is disposed on the side bezel of the terminal 1100, it can detect the user's grip signal on the terminal 1100, and the processor 1111 can perform left / right hand recognition or quick operation based on the grip signal collected by the pressure sensor 1112. When the pressure sensor 1112 is disposed on the lower layer of the display screen 1105, the processor 1111 can control the operable controls on the UI interface based on the user's pressure operation on the display screen 1105. The operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0188] An optical sensor 1113 is used to collect ambient light intensity. In one embodiment, the processor 1111 can control the display brightness of the display screen 1105 based on the ambient light intensity collected by the optical sensor 1113. Specifically, when the ambient light intensity is high, the display brightness of the display screen 1105 is increased; when the ambient light intensity is low, the display brightness of the display screen 1105 is decreased. In another embodiment, the processor 1111 can also dynamically adjust the shooting parameters of the camera assembly 1106 based on the ambient light intensity collected by the optical sensor 1113.

[0189] The proximity sensor 1114, also known as a distance sensor, is typically located on the front panel of the terminal 1100. The proximity sensor 1114 is used to detect the distance between the user and the front of the terminal 1100. In one embodiment, when the proximity sensor 1114 detects that the distance between the user and the front of the terminal 1100 is gradually decreasing, the processor 1111 controls the display screen 1105 to switch from a screen-on state to a screen-off state; when the proximity sensor 1104 detects that the distance between the user and the front of the terminal 1100 is gradually increasing, the processor 1111 controls the display screen 1105 to switch from a screen-off state to a screen-on state.

[0190] Those skilled in the art will understand that the structure shown in FIG11 does not constitute a limitation on terminal 1100, and may include more or fewer components than shown, or combine certain components, or employ different component arrangements.

[0191] Figure 12 is a schematic diagram of a server according to an embodiment of this application. The server 1200 can vary considerably depending on its configuration or performance. It may include one or more Central Processing Units (CPUs) 1201 and one or more memories 1202. The memory 1202 stores at least one computer program, which is loaded and executed by the processor 1201 to implement the housing optimization method of the electric drive controller provided in the above-described method embodiments. Of course, the server may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input and output. The server may also include other components for implementing device functions, which will not be elaborated here.

[0192] This application also provides a computer-readable storage medium storing at least one computer program. This computer program is loaded and executed by a processor of a computer device to implement the operations performed by the computer device in the housing optimization method of the electric drive controller described above. For example, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, or optical data storage device, etc.

[0193] This application also provides a computer program product including computer program code stored in a computer-readable storage medium. A processor of a computer device reads the computer program code from the computer-readable storage medium and executes the computer program code, causing the computer device to perform the housing optimization method for the electric drive controller provided in the various optional implementations described above.

[0194] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0195] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for optimizing the housing of an electric drive controller, executed by a computer device, the method comprising: The vehicle installation status of the multi-functional electric drive was simulated by adjusting the coordinates of the simulation analysis model and the rubber stiffness of the suspension bracket. Set modal optimization boundaries, determine equivalent acoustic power, and apply electromagnetic excitation; Based on the design scheme of the electric drive assembly and the overall vehicle layout space, the optimized design space model of the shell is determined; Based on the topology optimization results of the topology optimization analysis of the optimized design space model, the material density distribution of the shell is obtained; Based on the material density distribution of the shell, the surface topographic feature distribution of the shell is determined.

2. The method according to claim 1, wherein, The determination of the surface topographic feature distribution of the shell based on the material density distribution of the shell includes: Based on the material density distribution of the shell, the shell design scheme is obtained; Based on the aforementioned shell design scheme, the shell is morphologically optimized to obtain the surface topological feature distribution of the shell.

3. The method according to claim 1, wherein, The topology optimization analysis includes modal analysis conditions and vibration analysis conditions; The method further includes: The modal analysis is performed with frequency values ​​as the target for optimizing the response. The vibration analysis condition is performed with surface vibration velocity as the target for optimizing the response; or... The vibration analysis condition is performed with the objective of optimizing the response based on equivalent acoustic power.

4. The method according to claim 1, wherein, The method further includes: Obtain the all-in-one electric drive housing, controller model, motor model, suspension model, and geometric models of multiple components; Perform geometric assembly on the geometric models of the multiple components; Establish the simulation analysis model.

5. The method according to claim 1, wherein, The method further includes: Determine the load spectrum and parameters of common operating conditions based on at least one of the bench test conditions or vehicle road spectrum. Based on the parameters of the commonly used operating conditions, the electromagnetic excitation of the commonly used operating conditions in the load spectrum is determined.

6. The method according to any one of claims 1-5, wherein, The method further includes: A preliminary evaluation and analysis of the controller assembly modes was conducted, and based on the frequency and mode shape performance, it was determined whether a bolt fixing scheme should be used for the weakest area of ​​the housing structure.

7. The method according to any one of claims 1-5, wherein, The method further includes: The housing is redesigned. The shell obtained from the secondary design is subjected to assembly modal evaluation and verification, or vibration response evaluation is performed in other dynamic software to verify the design effect of the shell.

8. A housing optimization device for an electric drive controller, configured in a computer device, the device comprising: The adjustment module is used to simulate the vehicle installation state of the all-in-one electric drive by adjusting the coordinates of the simulation analysis model and the rubber stiffness of the suspension bracket. The configuration module is used to set the modal optimization boundary, determine the equivalent acoustic power, and apply electromagnetic excitation. The first determining module is used to determine the optimized design space model of the housing based on the design scheme of the electric drive assembly and the overall vehicle layout space. The optimization module is used to obtain the material density distribution of the shell based on the topology optimization results of the topology optimization analysis of the optimized design space model; The second determining module is used to determine the surface topographic feature distribution of the shell based on the material density distribution of the shell.

9. The apparatus according to claim 8, wherein, The second determining module is used for: Based on the material density distribution of the shell, the shell design scheme is obtained; Based on the aforementioned shell design scheme, the shell is morphologically optimized to obtain the surface topological feature distribution of the shell.

10. The apparatus according to claim 8, wherein, The topology optimization analysis includes modal analysis conditions and vibration analysis conditions; The optimization module is used for: The modal analysis is performed with frequency values ​​as the target for optimizing the response. The vibration analysis condition is performed with surface vibration velocity as the target for optimizing the response. or, The vibration analysis condition is performed with the objective of optimizing the response based on equivalent acoustic power.

11. The apparatus according to claim 8, wherein, The device further includes: The acquisition module is used to acquire the multi-in-one electric drive housing, controller model, motor model, suspension model, and geometric models of multiple components; The model processing module is used to perform geometric assembly on the geometric models of the multiple components; The modeling module is used to build the simulation analysis model.

12. The apparatus according to claim 8, wherein, The device further includes: The third determination module is used to determine the parameters of the load spectrum and common operating conditions based on at least one of the bench test conditions or the whole vehicle road spectrum. The third determining module is also used to determine the electromagnetic excitation of the common working conditions in the load spectrum based on the parameters of the common working conditions.

13. The apparatus according to any one of claims 8-12, wherein, The device further includes: The fourth determination module is used to perform preliminary evaluation and analysis of the controller assembly modes, and determine whether the weakest structural area of ​​the housing should be fixed with bolts based on the frequency and mode shape performance.

14. The apparatus according to any one of claims 8-12, wherein, The device further includes: The design module is used for secondary design of the housing; The verification module is used to perform assembly modal evaluation verification on the shell obtained by secondary design, or to perform vibration response evaluation in other dynamic software, so as to verify the design effect of the shell.

15. A computer device, wherein, The computer device includes a processor and a memory, the memory being used to store at least one computer program, the at least one computer program being loaded by the processor and executed as the fault data processing method according to any one of claims 1 to 7.

16. A computer-readable storage medium, wherein, The computer-readable storage medium is used to store at least one computer program for performing the fault data processing method according to any one of claims 1 to 7.

17. A computer program product comprising a computer program, wherein, When the computer program is executed by the processor, it implements the fault data processing method as described in any one of claims 1 to 7.

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