Passability analysis method for intelligent wheelchair driving on sandy road surface
By using the coupled finite element method and discrete element method, a simulation model of an intelligent wheelchair on a gravel road surface was established, which solved the problem of low simulation accuracy in the existing technology and realized accurate analysis and performance evaluation of the wheelchair's passability on gravel roads.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-08-30
- Publication Date
- 2026-03-31
AI Technical Summary
Existing technologies cannot accurately simulate and analyze the mobility of intelligent wheelchairs on loose gravel roads, resulting in low simulation accuracy and difficulty in assessing their driving performance.
Using the finite element method and discrete element method coupled method, a multi-rigid-body dynamic model of the intelligent wheelchair and a sandy and loose road surface model were established. Coupled simulation was performed to obtain the traction force, traction torque and wheel settlement of the drive wheel hook, and the curves were plotted and the critical settlement value was analyzed.
It improves the simulation accuracy and applicability of intelligent wheelchairs on gravel roads, and provides a more accurate basis for evaluating driving performance.
Smart Images
Figure CN115422801B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a method for analyzing the passability of an intelligent wheelchair on loose gravel roads, specifically a method for analyzing the passability of an intelligent wheelchair traveling on gravel roads. Background Technology
[0002] It is estimated that approximately 75 million people with disabilities worldwide rely on wheelchairs for transportation. For these individuals, manual wheelchairs are insufficient for daily mobility, while electric wheelchairs offer autonomous movement and greater convenience. As the range of activities for people with disabilities expands, researching wheelchair mobility on complex terrain has become an urgent issue. This study investigates wheelchair mobility on gravel roads, using a coupled finite element method (FEM) and discrete element method (DEM) approach to predict and analyze wheelchair performance on loose gravel surfaces.
[0003] The Discrete Element Method (DEM) was first proposed by Cundall and Strack in 1971 and has been used and gradually improved in LS-DYNA R7.0 and later versions. In LS-DYNA, the discrete element is a rigid spherical particle, each with three translational and three rotational degrees of freedom. Its motion follows Newton's second law, and the equations of motion are solved using the explicit central difference method. The embedding of the DEM into LS-DYNA software, combined with its powerful finite element method (FEM) solution capabilities, provides a new simulation approach for solving some interaction problems between granular materials and continuous media (such as tire movement on soft surfaces). Using LS-DYNA software, discrete elements can be used to simulate granular materials, and finite elements can be used to simulate continuous media, thus facilitating the construction of corresponding coupled models for more realistic simulation analyses.
[0004] Wheelchairs often get stuck and struggle to escape on loose gravel surfaces. Therefore, analyzing their traction performance on such surfaces is crucial. Evaluating the traction performance of intelligent wheelchairs involves analyzing and predicting the hook traction force, traction torque, and wheel sinkage of their drive wheels. Current technology lacks a finite element-discrete element coupling method to accurately predict and analyze the driving characteristics of intelligent wheelchairs on loose gravel surfaces. Therefore, developing a low-cost and efficient evaluation method for assessing traction performance is of great practical significance. Summary of the Invention
[0005] The purpose of this invention is to provide a method for predicting the passability of intelligent wheelchairs on loose gravel roads. By coupling the finite element method and the discrete element method, the driving of the wheelchair system on loose roads can be simulated, the passability of the intelligent wheelchair can be evaluated, and a technical basis can be provided for wheelchair development.
[0006] To achieve the above objectives, the present invention adopts the following technical solution:
[0007] A method for analyzing the passability of an intelligent wheelchair on gravel roads includes the following steps:
[0008] Step 1: Establish a finite element multi-rigid-body dynamics model of the wheelchair;
[0009] Step 2: Establish a discrete element model of loose sand and gravel road surface and couple it with a finite element model of wheelchair multi-rigid-body dynamics.
[0010] Step 3: Conduct a simulation of the intelligent wheelchair's ability to navigate on loose gravel roads;
[0011] Step 4: Collect data on the traction force, traction torque and wheel sinkage of the drive wheel hook under different slip ratios, and plot the hook traction force curve and wheel sinkage curve under different slip ratios.
[0012] Step 5: Analyze the mobility of the intelligent wheelchair and obtain the critical sinking value of the wheelchair in order to get out of trouble.
[0013] The establishment of the finite element multi-rigid-body dynamics model of the wheelchair in step 1 includes the following steps:
[0014] Step 1.1: Create each component of the wheelchair in Solidworks software, including the frame, seat back, and tires. Import them into Hypermesh software for simplification and mesh creation. Then import them into Ls-dyna software, add material properties for each component, and set connection constraints between components.
[0015] Step 1.2: Combine the existing wheelchair measuring frame and seat back to obtain dimensional data and establish a complete wheelchair model;
[0016] Step 1.3: Based on the measurement data of the existing wheelchair prototype, perform detailed finite element modeling of the wheel hub, tires and tread patterns; and set up tire characteristic tests under different pressures and speeds, and modify the parameters according to the test data.
[0017] The connection constraints are as follows: a revolute joint is set between the wheel model and the vehicle model; the revolute joint is connected to the wheel hub and the vehicle body respectively; the wheel rotates around the bearing; the tread pattern is connected to the outer surface of the tire; and the tire is connected to the wheel hub.
[0018] The tire characteristic tests include: tire modal tests, and friction characteristic tests of tread rubber under different pressures and slip speeds.
[0019] Step 2, establishing the discrete element sand and gravel loose road surface model, includes the following steps:
[0020] Step 2.1, describe the gravel road surface using discrete sand and gravel elements in Ls-dyna: establish a given spatial range and set a set of discrete sand and gravel elements within the limited spatial range;
[0021] Step 2.2: Apply a gravity field to the generated discrete sand and gravel unit set, so that these discrete sand and gravel units are compacted to a stable state under their own weight. The compacted discrete unit set is the road surface sample, which is used to simulate the real sand and gravel road surface environment.
[0022] Step 2.3: Obtain soil property parameters based on triaxial compression test and soil bearing shear test, and input the parameters into the discrete sand and gravel units in the pavement space;
[0023] Step 2.4: Contact coupling is performed on the finite element wheelchair model and the discrete element gravel road surface model to establish a finite element-discrete element coupled system simulation model.
[0024] The discrete unit is a particle that fills space, and the particle attributes are particle radius, filling percentage, density, elastic modulus and Poisson's ratio.
[0025] The soil property parameters are the normal damping coefficient (NDAMP), the tangential damping coefficient (TDAMP), the friction coefficient (Fric), the rolling friction coefficient (FricR), the normal stiffness coefficient (NormK), and the tangential stiffness coefficient (Sheark).
[0026] The contact coupling refers to the contact setup between the finite element model of the wheelchair drive wheel and the discrete element model of the gravel road surface.
[0027] The simulation of the intelligent wheelchair's ability to navigate on loose gravel roads includes the following steps:
[0028] The established finite element intelligent wheelchair simulation model was driven at a set wheel angular velocity at a constant speed through a discrete element gravel road surface. The hook traction force, traction torque, and wheel sinkage of the drive wheel were obtained as data for passability analysis and evaluation.
[0029] The passability analysis of intelligent wheelchairs includes:
[0030] Based on the hook traction force curve and wheel sinking curve of the intelligent wheelchair drive wheel under different slip ratios, the critical traction force and critical sinking amount are obtained to achieve escape: different slip ratios correspond to different wheel sinking amounts. Under a certain slip ratio, when the traction force is greater than the critical traction force of the wheel, the intelligent wheelchair can escape.
[0031] The advantages and beneficial effects of this invention are:
[0032] This invention provides a method for analyzing the passability of intelligent wheelchairs on gravel roads. It addresses the limitations and low accuracy of existing passability simulation methods, improves the accuracy of passability simulation, and enables the simulation results to accurately reflect the driving performance of intelligent wheelchairs on loose surfaces. It has high applicability and operability, and provides a basis for evaluating the passability of wheelchairs on loose gravel roads. Attached Figure Description
[0033] Figure 1 This is a technical flowchart of the present invention.
[0034] Figure 2 This is a schematic diagram of a wheelchair model of the present invention.
[0035] Figure 3 This is a schematic diagram of the road surface model of the present invention.
[0036] Figure 4 This is a schematic diagram of the finite element-discrete element coupling of the present invention.
[0037] Figure 5(a) shows the traction force curve of the drive wheel hook of the intelligent wheelchair.
[0038] Figure 5(b) shows the sinking curve of the drive wheel of the intelligent wheelchair. Detailed Implementation
[0039] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.
[0040] This example presents a method for analyzing the passability of an intelligent wheelchair on loose gravel roads. Analysis of current vehicle passability simulation methods reveals significant limitations; they fail to accurately reflect the driving characteristics of intelligent wheelchairs on loose surfaces and exhibit low simulation accuracy. This invention provides a method for analyzing the passability of an intelligent wheelchair on loose gravel roads to address these issues and effectively improve the accuracy of passability simulation. Figure 1 As shown, it includes the following steps:
[0041] Step 1: Establish a finite element multi-rigid-body dynamics model of the wheelchair.
[0042] Step 1.1: Create each component of the wheelchair in Solidworks software, including the frame, seat back, and tires, and import them into Hypermesh software for simplification and meshing. Then import them into Ls-dyna software, add material properties for each component, and set connection constraints between components.
[0043] Step 1.2: Combine existing wheelchair measuring components such as the frame and seat back to obtain dimensional data and establish a complete wheelchair model;
[0044] Step 1.3: Based on the measurement data of the existing wheelchair prototype, perform detailed finite element modeling of the wheel hub, tires and tread patterns; and set up tire characteristic tests under different pressures and speeds, and modify the parameters according to the test data.
[0045] Establish a multibody dynamics model for the wheelchair, such as Figure 2 As shown.
[0046] Step 2, establish a discrete element model of a loose sand and gravel road surface, such as... Figure 3 As shown.
[0047] Step 2.1: In Ls-dyna, discrete sand and gravel elements are used to describe the sand and gravel road surface: a given spatial range is established, and a set of discrete sand and gravel elements is set within the limited spatial range; the discrete elements are particles that fill the space, and the particle attributes are particle radius, filling percentage, density, elastic modulus and Poisson's ratio.
[0048] Step 2.2: Apply a gravity field to the generated discrete sand and gravel unit set, so that these discrete sand and gravel units are compacted to a stable state under their own weight. The compacted discrete unit set is the road surface sample, which is used to simulate the real sand and gravel road surface environment.
[0049] Step 2.3: Obtain soil property parameters based on triaxial compression test and soil bearing shear test, and input parameters into the discrete sand and gravel unit in the pavement space; the soil property parameters are normal damping coefficient (NDAMP), tangential damping coefficient (TDAMP), friction coefficient (Fric), rolling friction coefficient (FricR), normal stiffness coefficient (NormK), and tangential stiffness coefficient (Sheark).
[0050] Step 2.4: Contact coupling is established between the finite element wheelchair model and the discrete element gravel road surface model to create a finite element-discrete element coupled system simulation model. The contact coupling refers to the contact setting between the finite element model of the wheelchair drive wheel and the discrete element model of the gravel road surface.
[0051] Set the contact relationship between the discrete element road surface and the tire, such as Figure 4 As shown;
[0052] Step 3, the specific steps for performing passability simulation calculations are as follows:
[0053] Step 3.1: The finite element intelligent wheelchair simulation model established in Step 2 is driven at a set wheel angular velocity at a constant speed through a discrete element gravel road surface. The hook traction force, traction torque, and wheel sinking amount of the drive wheel are extracted as passability analysis and evaluation data.
[0054] The wheel speed is obtained by multiplying the angular velocity by the wheel radius.
[0055] 1) The wheel settlement z consists of static settlement z0 and slip settlement z i It consists of two parts. The wheelchair's own mass generates a vertical load, causing static settlement between the wheelchair and the road surface. During the wheelchair's movement, factors such as bulldozing assistance and rolling resistance cause shearing action between the wheelchair and the road surface, resulting in slip settlement. z = z0 + z i .
[0056] 2) The hook traction force is calculated by integrating the compressive and shear stresses generated between the wheel and the road surface as the wheel moves forward. The integration range is the wheel's forward angle and wheel's departure angle. Wheel sinking is an important parameter affecting the compressive stress generated between the wheel and the ground, and the shear stress generated between the wheel and the ground varies with the compressive stress.
[0057] 3) The traction torque is obtained by multiplying the hook traction force by the wheel radius.
[0058] Step 4: Collect data on the hook traction force, traction torque, and wheel sinkage of the intelligent wheelchair drive wheel under different slip rates. The specific steps are as follows:
[0059] Step 3 is performed under different slip ratios to process the simulated hook traction force.
[0060] Step 3 is performed under different slip ratios to process the simulated traction torque data.
[0061] Step 3 was performed under different slip rates to process the simulated wheel sinkage data.
[0062] Figure 5 shows the hook traction force and wheel sinking curves of the intelligent wheelchair drive wheel under different slip rates. Figure 5(a) is the hook traction force curve of the intelligent wheelchair drive wheel. In the starting stage of the intelligent wheelchair, the wheel sinks into the loose sand and gravel road surface. As the wheel sinking increases, the resistance of the sand and gravel road surface on the wheel increases rapidly. In order to overcome the road resistance and make the wheel roll normally, the hook traction force increases rapidly from zero to reach a peak value. As the intelligent wheelchair moves smoothly, the hook traction force fluctuates within a certain range. Figure 5(b) is the sinking curve of the intelligent wheelchair drive wheel. When the wheel is driving on the sand and gravel road surface, the impact shearing action generated when the wheel contacts the sand and gravel road surface causes the wheel hub sinking to increase rapidly and then reach a stable value.
[0063] Step 5, pass the sexual evaluation
[0064] The passability performance of intelligent wheelchairs was evaluated based on the hook traction force, traction torque, and wheel sinkage under different slip rates. The passability analysis of intelligent wheelchairs included:
[0065] Based on the hook traction force curve and wheel sinking curve of the intelligent wheelchair drive wheel under different slip ratios, the critical traction force and critical sinking amount are obtained to achieve the effect of getting out of trouble: different slip ratios correspond to different wheel sinking amounts. Under a certain slip ratio, when the traction force is greater than the critical traction force of the wheel, the intelligent wheelchair can get out of trouble.
[0066] The above description is merely a preferred embodiment of the present invention and should not be construed as limiting the scope of the claims. The present invention is not limited to the above examples, and various modifications and variations can be made by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A method for analyzing the passability of an intelligent wheelchair on a sandy road, characterized by, The method comprises the following steps: Step 1, a finite element wheelchair multi-rigid body dynamics model is established; comprising the following steps: Step 1.1, each component of the wheelchair, including the frame, the seat backrest and the tire, is respectively established in the Solidworks software, is imported into the Hypermesh software for simplification processing and drawing of a mesh and is then imported into the Ls-dyna software, material properties of each component are added, and a connecting constraint relationship between the components is set; Step 1.2, the size data is obtained by combining the existing wheelchair to measure the frame, the seat backrest, and a whole vehicle model of the wheelchair is established; Step 1.3, the hub, the tire and the pattern are finely modeled in combination with the measurement data of the existing wheelchair prototype; and the tire characteristics test under different pressures and speeds is set, and the parameters are modified according to the test data; Step 2, a discrete element sandstone loose pavement model is established, and is coupled with the finite element wheelchair multi-rigid body dynamics model; comprising the following steps: Step 2.1, the discrete sandstone unit is used to describe the sandstone pavement in the Ls-dyna: a given space range is established, and a discrete sandstone unit set is set in the limited space range; Step 2.2, a gravity field is applied to the generated discrete sandstone unit set, so that the discrete sandstone units are compacted to reach a stable state under the action of gravity, and the compacted discrete unit set is used to simulate the real sandstone pavement environment; Step 2.3, the soil property parameters are obtained according to the triaxial compression test and the soil bearing shear test, and the parameters of the discrete sandstone units in the pavement space are inputted; Step 2.4, the finite element wheelchair model and the discrete element sandstone pavement model are contact coupled to establish a finite element-discrete element coupling system simulation model; Step 3, the passability simulation of the intelligent wheelchair on the sandstone loose pavement is performed; Step 4, the hook traction force, the traction torque and the wheel subsidence under different slip ratios are collected, and the hook traction force curve diagram and the wheel subsidence curve diagram under different slip ratios are drawn; Step 5, the passability of the intelligent wheelchair is analyzed, and the critical subsidence value of the wheelchair is obtained to achieve the escape.
2. The method of claim 1, wherein the method is characterized by: The connecting constraint relationship is that a rotary pair is set between the wheel model and the whole vehicle model, the rotary pair is connected with the hub and the vehicle body respectively, the wheel rotates around the bearing, the pattern is connected with the outer surface of the tire, and the tire is connected with the hub.
3. The method of claim 1, wherein the method is a method of analyzing the passability of a smart wheelchair on a sandy road surface. The tire characteristics test includes a tire modal test and a friction characteristic test of the tire tread rubber under different pressures and slip speeds.
4. The method for analyzing the passability of the intelligent wheelchair on the sandy road according to claim 1, wherein: The discrete unit is a particle filled in space, and the particle attributes are particle radius, filling percentage, density, elastic modulus and Poisson's ratio.
5. The method for analyzing the passability of the intelligent wheelchair on the sandy road according to claim 1, wherein: The soil property parameters are normal damping coefficient (NDAMP), tangential damping coefficient (TDAMP), friction coefficient (Fric), rolling friction coefficient (FricR), normal stiffness coefficient (NormK) and tangential stiffness coefficient (Sheark).
6. The method for analyzing the passability of the intelligent wheelchair on the gravel road according to claim 1, wherein: The contact coupling is the contact setting of the finite element model of the wheelchair driving wheel and the discrete element model of the sandstone pavement.
7. The method of analyzing the passability of a smart wheelchair on a sandy road according to claim 1, wherein: The passability simulation of the intelligent wheelchair on the sandstone loose pavement includes the following steps: The finite element simulation model of the intelligent wheelchair is set to pass through the discrete sandstone road surface at a constant wheel angular velocity, and the hook traction force, traction torque and wheel subsidence of the driving wheel are obtained as the passability analysis evaluation data.
8. The method for analyzing the passability of the intelligent wheelchair on the gravel road according to claim 1, wherein: The passability analysis of the intelligent wheelchair includes: According to the hook traction force curve and the wheel subsidence curve of the driving wheel of the intelligent wheelchair under different slip rates, the critical traction force and the critical subsidence are obtained to achieve the escape from trouble: different slip rates correspond to different wheel subsidence, and when the traction force is greater than the critical traction force of the wheel, the intelligent wheelchair escapes from trouble.