Full-load vehicle characteristic parameter determination method, device, equipment, medium and product

Abstract

The invention discloses a full-load vehicle characteristic parameter determination method and device, equipment, a medium and a product. The method comprises the steps of generating a whole vehicle part model of a target vehicle according to vehicle part parameters of the target vehicle; determining the weight, the height and the body posture of people in the target vehicle under the condition that the vehicle is fully loaded; generating a human body centroid ball model according to the weight, the height and the body posture of the person in the vehicle; generating a full-load whole vehicle model according to the whole vehicle part model and the human body centroid sphere model; according to the full-load state whole vehicle model, vehicle characteristic parameters of the target vehicle under the vehicle full-load condition are determined; the vehicle characteristic parameters comprise axle load parameters, the mass center of the whole vehicle and the rotational inertia of the whole vehicle. According to the technical scheme of the embodiment of the invention, the vehicle characteristic parameter determination accuracy under the vehicle full-load scene is improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle control, and in particular to a method, apparatus, equipment, medium, and product for determining characteristic parameters of a fully loaded vehicle. Background Technology

[0002] Full load mass, which is the sum of curb weight and all occupants, has a significant impact on the axle load, center of gravity, and moment of inertia of a vehicle under full load mass. The accuracy of its calculation affects the design of systems such as the subframe, suspension, braking, and wheels, as well as the development of performance characteristics such as handling, stability, braking, and safety.

[0003] Existing methods for determining vehicle characteristic parameters often only calculate axle load, center of gravity, and moment of inertia for curb weight. For fully loaded vehicles, the calculation of vehicle characteristic parameters becomes extremely complex due to the addition of occupants. Therefore, these methods often rely solely on the R-point position of passengers to make rough estimates of characteristic parameters such as axle load and center of gravity, resulting in low accuracy in calculating vehicle characteristic parameters. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, medium, and product for determining the characteristic parameters of a fully loaded vehicle, in order to improve the accuracy of determining the vehicle characteristic parameters under fully loaded vehicle scenarios.

[0005] According to one aspect of the present invention, a method for determining characteristic parameters of a fully loaded vehicle is provided, the method comprising:

[0006] Based on the vehicle component parameters of the target vehicle, generate a complete vehicle component model of the target vehicle;

[0007] Determine the weight, height, and posture of the occupants of the target vehicle when it is fully loaded;

[0008] A human centroid sphere model is generated based on the weight, height, and posture of the occupants in the vehicle.

[0009] Based on the vehicle component model and the human body center of mass sphere model, generate a fully loaded vehicle model.

[0010] Based on the fully loaded vehicle model, determine the vehicle characteristic parameters of the target vehicle under full load conditions; the vehicle characteristic parameters include axle load parameters, vehicle center of mass, and vehicle moment of inertia.

[0011] According to another aspect of the present invention, a device for determining characteristic parameters of a fully loaded vehicle is provided, the device comprising:

[0012] The vehicle model generation module is used to generate a vehicle component model of the target vehicle based on the vehicle component parameters of the target vehicle.

[0013] The personnel data determination module is used to determine the weight, height, and posture of the occupants of the target vehicle when it is fully loaded.

[0014] The human body center of mass sphere model generation module is used to generate a human body center of mass sphere model based on the weight, height, and posture of the occupants in the vehicle.

[0015] The full-load model generation module is used to generate a full-load vehicle model based on the vehicle component model and the human body center of mass sphere model.

[0016] The characteristic parameter determination module is used to determine the vehicle characteristic parameters of the target vehicle under full load conditions based on the full-load vehicle model; the vehicle characteristic parameters include axle load parameters, vehicle center of mass, and vehicle moment of inertia.

[0017] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0018] At least one processor; and

[0019] A memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the method for determining the characteristic parameters of a fully loaded vehicle as described in any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement the method for determining the characteristic parameters of a fully loaded vehicle as described in any embodiment of the present invention.

[0022] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method for determining the characteristic parameters of a fully loaded vehicle as described in any embodiment of the present invention.

[0023] The technical solution of this invention generates a complete vehicle component model based on the vehicle component parameters of the target vehicle. It then determines the weight, height, and posture of the occupants of the target vehicle under full load conditions. Based on these parameters, a human center of mass sphere model is generated. Finally, based on the complete vehicle component model and the human center of mass sphere model, a fully loaded vehicle model is generated. Finally, based on the fully loaded vehicle model, the vehicle characteristic parameters under full load conditions are determined. These vehicle characteristic parameters include axle load parameters, the vehicle's center of mass, and the vehicle's moment of inertia. This technical solution achieves the determination of vehicle characteristic parameters under full load conditions, improving the accuracy of such determination.

[0024] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart of a method for determining characteristic parameters of a fully loaded vehicle according to Embodiment 1 of the present invention;

[0027] Figure 2 This is a flowchart of a method for determining characteristic parameters of a fully loaded vehicle according to Embodiment 2 of the present invention;

[0028] Figure 3 This is a schematic diagram of a device for determining the characteristic parameters of a fully loaded vehicle according to Embodiment 3 of the present invention;

[0029] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the method for determining the characteristic parameters of a fully loaded vehicle according to an embodiment of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Example 1

[0033] Figure 1 This is a flowchart of a method for determining characteristic parameters of a fully loaded vehicle according to Embodiment 1 of the present invention. This embodiment is applicable to situations where vehicle characteristic parameters need to be accurately determined under fully loaded vehicle scenarios. This method can be executed by a device for determining the characteristic parameters of a fully loaded vehicle, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0034] S110. Generate a complete vehicle component model of the target vehicle based on the vehicle component parameters of the target vehicle.

[0035] S120. Determine the weight, height, and posture of the occupants of the target vehicle when it is fully loaded.

[0036] S130. Generate a human body center of mass sphere model based on the weight, height, and posture of the people inside the vehicle.

[0037] S140. Generate a fully loaded vehicle model based on the vehicle component model and the human body center of mass sphere model.

[0038] S150. Based on the full-load vehicle model, determine the vehicle characteristic parameters of the target vehicle under full load conditions; the vehicle characteristic parameters include axle load parameters, vehicle center of mass, and vehicle moment of inertia.

[0039] The parameters for vehicle components can include the target weight and volume of each part. Different vehicles have different component compositions, and different components have different volumes; the volume of a component can be predetermined during the component design phase and can be directly obtained later. The target weight for each component can be pre-set during the design phase, i.e., the expected weight of the component.

[0040] In one optional embodiment, generating a whole vehicle component model of the target vehicle based on the vehicle component parameters of the target vehicle includes: determining the material density of each vehicle component based on the weight target and component volume of each vehicle component in the vehicle component parameters of the target vehicle; and generating a whole vehicle component model with material density attributes based on the material density of each vehicle component.

[0041] The material density of any vehicle component can be determined by the ratio between the component's target weight and its volume.

[0042] For example, an initial model of the vehicle components can be pre-built based on open-source CAD (Computer-Aided Design) software. Then, a material density attribute parameter can be assigned to each vehicle component in the initial model, generating a vehicle component model with material density properties.

[0043] The system determines the weight, height, and posture of occupants in a fully loaded vehicle. The weight and height can be dynamically determined based on actual calculation needs, meaning they can be dynamically and in real-time determined under different fully loaded vehicle scenarios. Alternatively, fixed parameters can be pre-set by relevant technical personnel based on practical experience or experimental values. For example, the total weight of any occupant could be set to 75 kg, and the height to 180 cm.

[0044] The postures of occupants differ depending on their position within the vehicle. These postures can be pre-determined by technical personnel, meaning the specific postures for each occupant at different positions are defined. For instance, occupant postures are used to describe the distances and positional relationships between different joint points. For example, the total length of the thigh segment differs depending on whether the occupant is sitting upright or bent over.

[0045] Based on the weight, height, and posture of the occupants, a human center-of-mass sphere model is generated. For example, key joint points of the occupants are marked in the vehicle component model, and the human body is segmented. Parameters for each segment are calculated, and these parameters are fused to obtain the final human center-of-mass sphere model.

[0046] In one optional embodiment, a human center-of-mass sphere model is generated based on the weight, height, and posture of the occupants, including:

[0047] Step a1: Determine the mass of each body segment corresponding to the weight and height of the people in the vehicle.

[0048] The body segments of the occupants inside the vehicle are divided into head and neck, torso, thighs, calves, feet, upper arms, forearms, and hands. It should be noted that different body segments correspond to different mass ratio regression equations. The equation can be expressed as Y = a × H + b × M + c; where Y represents the mass ratio of the body segment; M represents the weight of the person; H represents the height of the person; and a, b, and c represent the regression coefficients of the mass ratio regression equation, which are different for different body segments.

[0049] For example, for any human body segment, based on the weight and height of the occupants, the segment's mass ratio can be determined using the corresponding mass ratio regression equation. The segment's mass is the product of the occupant's mass and the segment's mass ratio. For instance, the mass ratio regression equation for a certain human body segment might be Y = 0.002 × H + 0.001 × M + 0.06. Assuming the occupant's mass M is 75 kg and height H is 1.75 m, substituting these values ​​into the regression equation yields a mass ratio of 13.85%. Therefore, the segment's mass is approximately 10.39 kg (0.1385 × 75). The mass ratios for all human body segments can be determined using the same method.

[0050] Step a2: Based on the weight and height of the people in the vehicle, and based on the posture information of the starting joints of the body segments in the human body posture, determine the position of the center of mass corresponding to each body segment of the people in the vehicle.

[0051] For any human body segment, the position of its corresponding center of mass is the absolute distance of the center of mass, which can be calculated as the product of the total length of the segment and the ratio of the center of mass to the total length of the segment. The total length of the segment is related to the posture information of the segment's starting joint; the ratio of the center of mass to the total length of the segment is related to the person's height and weight.

[0052] The starting joint points include the cervical joint point, hip joint point (H point), knee joint point, ankle joint point, shoulder joint point, elbow joint point, and wrist joint point.

[0053] The regression equation for the relative proportion of the center of mass differs for different body segments. The equation can be in the form of K = d × H + e × M + f. Here, K represents the proportion of the segment's center of mass relative to the total length; for example, 0.45 means 45%, indicating that the center of mass is located at 45% of the line connecting the starting and ending joints. M represents the person's weight; H represents the person's height; d, e, and f represent given regression coefficients, which differ for different body segments. Furthermore, the regression coefficients for the same body segment also differ depending on the gender of the individual. For example, for the thigh segment (male), the coefficients are: d = 0.005, e = 0.0003, f = 0.4.

[0054] Specifically, the total length of a body segment is determined based on the posture information of the starting joint of the body segment in the human body posture; the ratio of the body segment's center of mass to the total length is determined based on the weight and height of the person and the relative proportion regression equation of the center of mass; the product of the total length of the body segment and the ratio of the body segment's center of mass to the total length is determined as the absolute distance of the center of mass of the human body segment relative to the starting joint, that is, the position of the center of mass of the human body segment.

[0055] Step a3: Generate a human body center-of-mass sphere model of the people inside the vehicle based on the mass and center-of-mass position of each body segment.

[0056] In one optional embodiment, a human center of mass sphere model of the occupants is generated based on the mass and center of mass position of each body segment of the occupants. This includes: determining the center of mass sphere model of each body segment based on the posture information of the starting joints of the body segments in the occupants' posture, according to the mass and center of mass position of the corresponding body segments; and performing model fusion on the solid sphere models of each body segment to generate the human center of mass sphere model of the occupants.

[0057] For example, based on open-source CAD software, body segments are labeled in an initial human body center-of-mass sphere model according to the posture information of the starting joints of the body segments in the human body posture. Then, based on the determined mass and center-of-mass position of each body segment, a center-of-mass sphere model for that body segment is created. The solid sphere models of each body segment are then fused in the CAD software to generate a center-of-mass sphere model of the person inside the vehicle.

[0058] A fully loaded vehicle model is generated based on the vehicle component models and the human body center of mass sphere model. For example, the vehicle component models and the human body center of mass sphere model can be merged in CAD software to obtain the fully loaded vehicle model.

[0059] In one optional embodiment, a fully loaded vehicle model is generated based on the vehicle component model and the human center of mass sphere model, including: performing model format verification on the vehicle component model and the human center of mass sphere model based on a preset model fusion method, and aligning the model coordinate systems of the vehicle component model and the human center of mass sphere model after the verification passes; and performing model fusion on the aligned vehicle component model and the human center of mass sphere model based on the model fusion method to obtain the fully loaded vehicle model.

[0060] For example, the model fusion method is related to the selected CAD software or CAD tool. The model fusion method can be a model fusion tool included in the selected CAD software or CAD tool. Specifically, verifying the model format of the vehicle component model and the human center of mass sphere model can involve checking whether the two models conform to the format supported by the CAD software or CAD tool. Furthermore, the two models need to be based on a unified coordinate system; therefore, the coordinate systems of the vehicle component model and the human center of mass sphere model are aligned. Based on the model fusion method, the aligned vehicle component model and the human center of mass sphere model are fused to obtain the fully loaded vehicle model.

[0061] Based on the fully loaded vehicle model, the vehicle characteristic parameters of the target vehicle under full load conditions are determined. These parameters include axle load parameters, vehicle center of gravity, and vehicle moment of inertia. All axle load parameters, vehicle center of gravity, and vehicle moment of inertia are vehicle characteristic parameters under full load conditions.

[0062] In one optional embodiment, the vehicle characteristic parameters of the target vehicle under full load conditions are determined based on the fully loaded vehicle model, including:

[0063] Step b1: Based on the fully loaded vehicle model, determine the vehicle's center of mass, mass, and moment of inertia under full load conditions.

[0064] Step b2: Obtain the front axle coordinates and rear axle coordinates of the target vehicle when it is fully loaded.

[0065] Step b31: Determine the front axle load based on the front axle coordinates and the vehicle's center of gravity, taking into account the vehicle's mass.

[0066] For example, the longitudinal distance L1 of the center of gravity relative to the front axle is the difference between the front axle coordinate X1 and the vehicle's center of gravity Xc. The distance between the front and rear axles can be determined based on the front and rear axle coordinates. The front axle load can be determined based on the vehicle mass, the distance between the front and rear axles, and the longitudinal distance L1 of the center of gravity relative to the front axle.

[0067] Step b32 determines the rear axle load based on the rear axle coordinates and the vehicle's center of gravity, taking into account the vehicle's mass.

[0068] For example, the longitudinal distance L2 of the center of gravity relative to the rear axle is the difference between the rear axle coordinate X2 and the vehicle's center of gravity Xc. The distance between the front and rear axles can be determined based on the front and rear axle coordinates. The rear axle load can be determined based on the vehicle mass, the distance between the front and rear axles, and the longitudinal distance L2 of the center of gravity relative to the rear axle.

[0069] Step b4: Generate axle load parameters including front and rear axle loads.

[0070] Step b5: Generate vehicle characteristic parameters including axle load parameters, vehicle center of gravity, and vehicle moment of inertia.

[0071] The technical solution of this invention generates a complete vehicle component model based on the vehicle component parameters of the target vehicle. It then determines the weight, height, and posture of the occupants of the target vehicle under full load conditions. Based on these parameters, a human center of mass sphere model is generated. Finally, based on the complete vehicle component model and the human center of mass sphere model, a fully loaded vehicle model is generated. Finally, based on the fully loaded vehicle model, the vehicle characteristic parameters under full load conditions are determined. These vehicle characteristic parameters include axle load parameters, the vehicle's center of mass, and the vehicle's moment of inertia. This technical solution achieves the determination of vehicle characteristic parameters under full load conditions, improving the accuracy of such determination.

[0072] Example 2

[0073] Figure 2 This is a schematic flowchart illustrating a method for determining characteristic parameters of a fully loaded vehicle according to Embodiment 2 of the present invention. Based on the above embodiments, this embodiment provides a preferred example.

[0074] like Figure 2 As shown, the method includes the following steps:

[0075] S21. Determine the material density of each vehicle component based on the weight target and volume of each component in the vehicle component parameters of the target vehicle.

[0076] S22. Generate a complete vehicle component model with material density attributes based on the material density of each vehicle component.

[0077] S23. Determine the weight, height, and posture of the occupants of the target vehicle when it is fully loaded.

[0078] S24. Based on the weight and height of the people inside the vehicle, determine the mass of each body segment corresponding to the person inside the vehicle.

[0079] S25. Based on the weight and height of the occupants, and using the posture information of the starting joints of the body segments in the occupants' body posture, determine the position of the center of mass corresponding to each body segment of the occupants.

[0080] S26. Generate a human body center-of-mass sphere model of the people inside the vehicle based on the mass and center-of-mass position of each body segment.

[0081] S27. Generate a fully loaded vehicle model based on the vehicle component model and the human body center of mass sphere model.

[0082] S28. Based on the fully loaded vehicle model, determine the vehicle's center of mass, mass, and moment of inertia under full load conditions.

[0083] S29. Obtain the front axle coordinates and rear axle coordinates of the target vehicle when it is fully loaded.

[0084] S30A. Based on the front axle coordinates and the vehicle's center of gravity, and taking into account the vehicle's mass, determine the front axle load.

[0085] S30B: Based on the rear axle coordinates and the vehicle's center of gravity, and taking into account the vehicle's mass, determine the rear axle load.

[0086] S31. Generate axle load parameters including front axle load and rear axle load, and generate vehicle characteristic parameters including axle load parameters, vehicle center of gravity and vehicle moment of inertia.

[0087] Example 3

[0088] Figure 3 This is a schematic diagram of a device for determining the characteristic parameters of a fully loaded vehicle according to Embodiment 3 of the present invention. The device provided in this embodiment of the present invention is applicable to situations requiring accurate determination of vehicle characteristic parameters under fully loaded vehicle scenarios. This device can be implemented in hardware and / or software, such as… Figure 3 As shown, the device includes: a vehicle model generation module 301, a personnel data determination module 302, a human body center of mass sphere model generation module 303, a full-load model generation module 304, and a characteristic parameter determination module 305. Among them,

[0089] The vehicle model generation module 301 is used to generate a vehicle component model of the target vehicle based on the vehicle component parameters of the target vehicle.

[0090] The personnel data determination module 302 is used to determine the weight, height, and posture of the personnel inside the target vehicle when the vehicle is fully loaded.

[0091] The human body center of mass sphere model generation module 303 is used to generate a human body center of mass sphere model based on the weight, height and posture of the people in the vehicle.

[0092] The full-load model generation module 304 is used to generate a full-load vehicle model based on the vehicle component model and the human body center of mass sphere model.

[0093] The characteristic parameter determination module 305 is used to determine the vehicle characteristic parameters of the target vehicle under full load conditions based on the full-load vehicle model; the vehicle characteristic parameters include axle load parameters, vehicle center of mass and vehicle moment of inertia.

[0094] The technical solution of this invention generates a complete vehicle component model based on the vehicle component parameters of the target vehicle. It then determines the weight, height, and posture of the occupants of the target vehicle under full load conditions. Based on these parameters, a human center of mass sphere model is generated. Finally, based on the complete vehicle component model and the human center of mass sphere model, a fully loaded vehicle model is generated. Finally, based on the fully loaded vehicle model, the vehicle characteristic parameters under full load conditions are determined. These vehicle characteristic parameters include axle load parameters, the vehicle's center of mass, and the vehicle's moment of inertia. This technical solution achieves the determination of vehicle characteristic parameters under full load conditions, improving the accuracy of such determination.

[0095] Optionally, the human body center-of-mass sphere model generation module 303 includes:

[0096] The body segment mass determination unit is used to determine the body segment mass corresponding to each body segment of the occupants of the vehicle based on their weight and height.

[0097] The center of mass position determination unit is used to determine the center of mass position of each body segment of the occupant based on the occupant's weight and height, and the posture information of the starting joints of the body segments in the occupant's body posture.

[0098] The human body center of mass sphere model generation unit is used to generate a human body center of mass sphere model of the person inside the vehicle based on the mass of each body segment and the position of the center of mass of the person inside the vehicle.

[0099] Optional, the human body center of mass sphere model generation unit is specifically used for:

[0100] Based on the mass and center of mass position of the corresponding human body segment, and based on the posture information of the starting joints of the body segment in the human body posture, determine the center of mass sphere model of each human body segment.

[0101] The solid sphere models of each of the human body segments are fused to generate the human body centroid sphere model of the person inside the vehicle.

[0102] Optional, the characteristic parameter determination module 305 is specifically used for:

[0103] Based on the fully loaded vehicle model, determine the vehicle's center of mass, mass, and moment of inertia under full load conditions.

[0104] Obtain the front axle coordinates and rear axle coordinates of the target vehicle when it is fully loaded;

[0105] Based on the front axle coordinates and the vehicle's center of gravity, and considering the vehicle's mass, determine the front axle load; and,

[0106] Based on the rear axle coordinates and the vehicle's center of gravity, and based on the vehicle's mass, the rear axle load is determined.

[0107] Generate axle load parameters including the front axle load and the rear axle load;

[0108] Generate vehicle characteristic parameters including the axle load parameters, the vehicle center of gravity, and the vehicle moment of inertia.

[0109] Optionally, the fully loaded model generation module 304 is specifically used for:

[0110] Based on a preset model fusion method, the model format of the vehicle component model and the human body center of mass sphere model is verified, and after the verification is passed, the model coordinate systems of the vehicle component model and the human body center of mass sphere model are aligned.

[0111] Based on the model fusion method, the vehicle component model and the human body center of mass sphere model after the model coordinate system alignment are fused to obtain the full-load vehicle model.

[0112] Optional, the vehicle model generation module 301 is specifically used for:

[0113] Based on the weight target and volume of each vehicle component in the vehicle component parameters of the target vehicle, determine the material density of each vehicle component.

[0114] Based on the material density of each of the vehicle components, a complete vehicle component model with material density attributes is generated.

[0115] The device for determining the characteristic parameters of a fully loaded vehicle provided in this embodiment of the invention can execute the method for determining the characteristic parameters of a fully loaded vehicle provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0116] Example 4

[0117] Figure 4 A schematic diagram of an electronic device 40 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0118] like Figure 4 As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42 or a random access memory (RAM) 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the ROM 42 or loaded from storage unit 48 into the RAM 43. The RAM 43 may also store various programs and data required for the operation of the electronic device 40. The processor 41, ROM 42, and RAM 43 are interconnected via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0119] Multiple components in electronic device 40 are connected to I / O interface 45, including: input unit 46, such as keyboard, mouse, etc.; output unit 47, such as various types of monitors, speakers, etc.; storage unit 48, such as disk, optical disk, etc.; and communication unit 49, such as network card, modem, wireless transceiver, etc. Communication unit 49 allows electronic device 40 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0120] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as the method for determining the characteristic parameters of a fully loaded vehicle.

[0121] In some embodiments, the method for determining the characteristic parameters of a fully loaded vehicle can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the method for determining the characteristic parameters of a fully loaded vehicle described above can be performed. Alternatively, in other embodiments, processor 41 can be configured to perform the method for determining the characteristic parameters of a fully loaded vehicle by any other suitable means (e.g., by means of firmware).

[0122] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0123] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0124] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0125] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0126] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0127] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0128] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0129] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for determining characteristic parameters of a fully loaded vehicle, characterized in that, include: Based on the vehicle component parameters of the target vehicle, generate a complete vehicle component model of the target vehicle; Determine the weight, height, and posture of the occupants of the target vehicle when it is fully loaded; A human centroid sphere model is generated based on the weight, height, and posture of the occupants in the vehicle. Based on the vehicle component model and the human body center of mass sphere model, generate a fully loaded vehicle model. Based on the fully loaded vehicle model, determine the vehicle characteristic parameters of the target vehicle under full load conditions; the vehicle characteristic parameters include axle load parameters, vehicle center of mass, and vehicle moment of inertia.

2. The method according to claim 1, characterized in that, The step of generating a human centroid sphere model based on the weight, height, and posture of the occupants includes: Based on the weight and height of the occupants, determine the mass of each body segment corresponding to the occupants. Based on the weight and height of the occupants, and using the posture information of the starting joints of the body segments in the occupants' body posture, the center of mass positions corresponding to each of the body segments of the occupants are determined. Based on the mass and center of mass position of each body segment of the occupant in the vehicle, a human center of mass sphere model of the occupant is generated.

3. The method according to claim 2, characterized in that, The step of generating a human center-of-mass sphere model of the occupants based on the mass and center-of-mass position of each body segment of the occupants includes: Based on the mass and center of mass position of the corresponding human body segment, and based on the posture information of the starting joints of the body segment in the human body posture, determine the center of mass sphere model of each human body segment. The solid sphere models of each of the human body segments are fused to generate the human body centroid sphere model of the person inside the vehicle.

4. The method according to claim 1, characterized in that, The step of determining the vehicle characteristic parameters of the target vehicle under full load conditions based on the fully loaded vehicle model includes: Based on the fully loaded vehicle model, determine the vehicle's center of mass, mass, and moment of inertia under full load conditions. Obtain the front axle coordinates and rear axle coordinates of the target vehicle when it is fully loaded; Based on the front axle coordinates and the vehicle's center of gravity, and considering the vehicle's mass, determine the front axle load; and, Based on the rear axle coordinates and the vehicle's center of gravity, and based on the vehicle's mass, the rear axle load is determined. Generate axle load parameters including the front axle load and the rear axle load; Generate vehicle characteristic parameters including the axle load parameters, the vehicle center of gravity, and the vehicle moment of inertia.

5. The method according to claim 1, characterized in that, The step of generating a fully loaded vehicle model based on the vehicle component model and the human body center of mass sphere model includes: Based on a preset model fusion method, the model format of the vehicle component model and the human body center of mass sphere model is verified, and after the verification is passed, the model coordinate systems of the vehicle component model and the human body center of mass sphere model are aligned. Based on the model fusion method, the vehicle component model and the human body center of mass sphere model after the model coordinate system alignment are fused to obtain the full-load vehicle model.

6. The method according to claim 1, characterized in that, The step of generating a complete vehicle component model of the target vehicle based on the vehicle component parameters of the target vehicle includes: Based on the weight target and volume of each vehicle component in the vehicle component parameters of the target vehicle, determine the material density of each vehicle component. Based on the material density of each of the vehicle components, a complete vehicle component model with material density attributes is generated.

7. A device for determining characteristic parameters of a fully loaded vehicle, characterized in that, include: The vehicle model generation module is used to generate a vehicle component model of the target vehicle based on the vehicle component parameters of the target vehicle. The personnel data determination module is used to determine the weight, height, and posture of the occupants of the target vehicle when it is fully loaded. The human body center of mass sphere model generation module is used to generate a human body center of mass sphere model based on the weight, height, and posture of the occupants in the vehicle. The full-load model generation module is used to generate a full-load vehicle model based on the vehicle component model and the human body center of mass sphere model. The characteristic parameter determination module is used to determine the vehicle characteristic parameters of the target vehicle under full load conditions based on the full-load vehicle model; the vehicle characteristic parameters include axle load parameters, vehicle center of mass, and vehicle moment of inertia.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the method for determining the characteristic parameters of a fully loaded vehicle as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method for determining the characteristic parameters of a fully loaded vehicle as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method for determining the characteristic parameters of a fully loaded vehicle according to any one of claims 1-6.

Images