Kinematic modeling method and system for electric forklift

Abstract

The invention belongs to the technical field of electric forklift modeling, particularly relates to a kinematics modeling method and system for an electric forklift, and aims to solve the problem that the accuracy of forklift kinematics modeling cannot be guaranteed due to the fact that environmental parameters, electrical load data and battery data of the forklift are inconvenient to comprehensively collect in the prior art. According to the scheme, the method comprises the following steps that S1, forklift environment data and forklift motor parameter data are set firstly, and the set data are collected and sorted; s2, forklift whole vehicle data, electrical load data and battery data are collected, and the collected data are sorted and uploaded; and S3, recording all the collected data, in the using process, the environmental parameters, the electrical load data and the battery data of the forklift can be conveniently and comprehensively collected, then the accuracy of forklift kinematics modeling can be effectively improved, and a solid foundation is provided for forklift optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of electric forklift modeling, and in particular to a kinematic modeling method and system for an electric forklift. Background Art

[0002] An electric forklift is an industrial vehicle that uses an electric drive system instead of an internal combustion engine to move and stack materials. They are often used in warehousing, manufacturing, and logistics environments to improve efficiency and reduce pollution and noise. The kinematic modeling method for electric forklifts is a mathematical method used to describe and control the position, speed, and posture of electric forklifts, which can be used to optimize the performance, safety, and efficiency of forklifts.

[0003] The patent document with announcement number CN117852189A discloses a kinematic modeling method and system for electric forklifts. The method comprises the following steps: collecting the real-time output torque, speed, current and voltage parameters of the electric forklift motor to obtain motor parameter data; simulating the speed response of the motor output torque with a neural network model according to the motor parameter data to obtain a motor response model; using a visual sensor to capture the structural information and external environment information of the forklift in real time during operation to obtain forklift visual image data; analyzing the kinematic relationship between the motor input and the forklift motion parameters according to the reduction transmission ratio relationship between the motor and the tire in the forklift structure, the forklift mass distribution data and the motor response model to obtain forklift motion relationship data. The present invention improves the accuracy of kinematic modeling of electric forklifts.

[0004] However, during the use of the above patent document, it is not convenient to comprehensively collect the environmental parameters, electrical load data and battery data of the forklift, which makes it impossible to ensure the accuracy of the kinematic modeling of the forklift. For this reason, we propose a kinematic modeling method and system for an electric forklift to solve the above problem. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings in the prior art that it is inconvenient to comprehensively collect the environmental parameters, electrical load data and battery data of the forklift, which leads to the inability to ensure the accuracy of the forklift kinematic modeling, and to propose a kinematic modeling method and system for an electric forklift.

[0006] The kinematic modeling method and system of an electric forklift provided in this application adopts the following technical solutions:

[0007] A kinematic modeling method for an electric forklift comprises the following steps:

[0008] S1: First, set the forklift's environment data and forklift motor parameter data, and collect and organize the set data;

[0009] S2: Collect the forklift vehicle data, electrical load data and battery data, and organize and upload the collected data;

[0010] S3: Record all collected data, analyze and compare them according to different parameter data set, and classify the analysis and comparison results;

[0011] S4: Calculate the motion equation of the forklift according to the classified data, and establish a corresponding motion model according to the motion equation;

[0012] S5: Conduct simulation experiments on the motion model, conduct verification analysis based on the experimental data, and optimize the forklift design based on the analysis results.

[0013] The present invention also proposes a kinematic modeling system for an electric forklift, comprising:

[0014] Forklift vehicle module;

[0015] A forklift data acquisition module, wherein the forklift data acquisition module is connected to the forklift vehicle module, the forklift data acquisition module is connected to a recording module, the recording module is connected to an analysis and comparison module, the analysis and comparison module is connected to a classification module, and the analysis and comparison module is used to compare and analyze the motion data of different parameters of the forklift;

[0016] A modeling module, wherein the modeling module is connected to the classification module, wherein the modeling module is connected to a simulation module, wherein the simulation module is connected to a verification analysis module, wherein the verification analysis module is connected to an optimization design module, and wherein the optimization design module is used to optimize the forklift design according to the simulation analysis results;

[0017] An environment setting module, wherein the environment setting module is connected to an environment data acquisition module, wherein the environment data acquisition module is connected to an electrical load data acquisition module, and both the electrical load data acquisition module and the environment data acquisition module are connected to a recording module;

[0018] A parameter setting module, wherein the parameter setting module is connected to a motor data acquisition module, the motor parameter acquisition module is connected to a battery data acquisition module, and both the motor parameter data acquisition module and the battery data acquisition module are connected to a recording module.

[0019] Furthermore, the motor data acquisition module includes a temperature data acquisition unit, a current and voltage data acquisition unit, and an output torque acquisition unit. The temperature data acquisition unit is connected to the current and voltage data acquisition unit, and the current and voltage data acquisition unit is connected to the output torque acquisition unit.

[0020] Furthermore, the battery data acquisition module includes a battery temperature acquisition unit, a power acquisition unit and a charge and discharge data acquisition unit, the battery temperature data acquisition unit is connected to the power acquisition unit, and the power acquisition unit is connected to the charge and discharge data acquisition unit.

[0021] Furthermore, the parameter setting module is used to set the motor parameters, and to set the driving speed, driving acceleration and driving displacement distance parameters of the forklift.

[0022] Furthermore, the environment setting module is used to set the environment in which the forklift is located, including setting the resistance parameters of the forklift, the load parameters of the forklift and the travel path parameters of the forklift.

[0023] Furthermore, the environmental data collection module includes a path data collection unit, a resistance data collection unit and a load data collection unit, the path data collection unit is connected to the resistance data collection unit, and the resistance data collection unit is connected to the load data collection unit.

[0024] Furthermore, the forklift data acquisition module includes a speed acquisition unit, an acceleration acquisition unit and a displacement distance acquisition unit, the speed acquisition unit is connected to the acceleration acquisition unit, and the acceleration acquisition unit is connected to the displacement distance acquisition unit.

[0025] In summary, the present application includes at least one of the following beneficial technical effects:

[0026] 1. This solution is set up through the environment setting module and the parameter setting module. The environment setting module and the parameter setting module can set the environment in which the forklift is located and the parameters of the forklift, so as to facilitate the comparison and analysis of the movement status of the forklift under different parameters;

[0027] 2. This solution can comprehensively collect the data of the entire forklift by setting up the forklift data acquisition module, motor data acquisition module, environmental data acquisition module and battery data acquisition module, thereby effectively improving the accuracy of the forklift kinematic modeling.

[0028] The present invention can facilitate the comprehensive collection of the environmental parameters, electrical load data and battery data of the forklift during use, thereby effectively improving the accuracy of the forklift kinematic modeling and providing a solid foundation for forklift optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A structural block diagram of a kinematic modeling system for an electric forklift proposed by the present invention;

[0030] Figure 2 A structural block diagram of a forklift data acquisition module of a kinematic modeling system for an electric forklift proposed by the present invention;

[0031] Figure 3 A structural block diagram of a motor data acquisition module of a kinematic modeling system for an electric forklift proposed by the present invention;

[0032] Figure 4 This is a structural block diagram of an environmental data acquisition module of a kinematic modeling system for an electric forklift proposed by the present invention;

[0033] Figure 5 This is a structural block diagram of a battery data acquisition module of a kinematic modeling system for an electric forklift proposed in the present invention. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0035] Embodiment 1

[0036] Reference Figure 1-Figure 5 , a kinematic modeling method for an electric forklift, comprising the following steps:

[0037] S1: First, set the forklift's environment data and forklift motor parameter data, and collect and organize the set data;

[0038] S2: Collect the forklift vehicle data, electrical load data and battery data, and organize and upload the collected data;

[0039] S3: Record all collected data, analyze and compare them according to different parameter data set, and classify the analysis and comparison results;

[0040] S4: Calculate the motion equation of the forklift according to the classified data, and establish a corresponding motion model according to the motion equation;

[0041] S5: Conduct simulation experiments on the motion model, conduct verification analysis based on the experimental data, and optimize the forklift design based on the analysis results.

[0042] This embodiment also proposes a kinematic modeling system for an electric forklift, including:

[0043] Forklift vehicle module;

[0044] A forklift data acquisition module, the forklift data acquisition module is connected to the forklift vehicle module, the forklift data acquisition module is connected to the recording module, the recording module is connected to the analysis and comparison module, the analysis and comparison module is connected to the classification module, and the analysis and comparison module is used to compare and analyze the motion data of different parameters of the forklift;

[0045] Modeling module, the modeling module is connected with the classification module, the modeling module is connected with the simulation module, the simulation module is connected with the verification analysis module, the verification analysis module is connected with the optimization design module, the optimization design module is used to optimize the forklift design according to the simulation analysis results, the optimization design module adopts the optimization algorithm, and the optimization algorithm includes:

[0046] 1. Batch Gradient Descent (BGD)

[0047] (1) Take the partial derivative of J(theta) with respect to theta and get the gradient corresponding to each theta:

[0048]

[0049] (2) Since the goal is to minimize the risk function, each theta is updated in the negative direction of its gradient:

[0050]

[0051] (3) From the above formula, we can notice that it obtains a global optimal solution. However, all the data in the training set must be used in each iteration. If m is very large, then it is conceivable that the iteration speed of this method will be quite slow. Therefore, another method is introduced: stochastic gradient descent.

[0052] For the batch gradient descent method, the number of samples is m, x is an n-dimensional vector, and all m samples need to be brought into the calculation for one iteration. The amount of calculation for one iteration is m*n2;

[0053] 2. Stochastic Gradient Descent (SGD)

[0054] (1) The risk function above can be written as follows. The loss function corresponds to the gradient of each sample in the training set, while the batch gradient descent above corresponds to all training samples:

[0055]

[0056] (2) For each sample, the loss function is derived from theta to obtain the corresponding gradient to update theta:

[0057]

[0058] (3) Stochastic gradient descent is iteratively updated once for each sample. If the sample size is large (e.g., hundreds of thousands), then only tens of thousands or thousands of samples may be used to iterate theta to the optimal solution. Compared with the batch gradient descent above, one iteration requires hundreds of thousands of training samples, and one iteration is unlikely to be optimal. If iterates 10 times, it needs to traverse the training samples 10 times. However, one problem with SGD is that it has more noise than BGD, so that SGD does not move towards the overall optimization direction every iteration;

[0059] An environment setting module, the environment setting module is connected to an environment data acquisition module, the environment data acquisition module is connected to an electrical load data acquisition module, the electrical load data acquisition module and the environment data acquisition module are both connected to the recording module, the environment setting module is used to set the environment in which the forklift is located, including setting the resistance parameters, load parameters and travel path parameters of the forklift, and the electrical load data acquisition module can collect the load characteristic data of the battery and the motor of other electrical equipment in the forklift vehicle module, and these electrical equipment include air conditioners, electric windows, etc.;

[0060] A parameter setting module, the parameter setting module is connected to the motor data acquisition module, the motor parameter acquisition module is connected to the battery data acquisition module, the motor parameter data acquisition module and the battery data acquisition module are both connected to the recording module, the parameter setting module is used to set the motor parameters, as well as the forklift's driving speed, driving acceleration and driving displacement distance parameters.

[0061] Reference Figure 2 The forklift data acquisition module includes a speed acquisition unit, an acceleration acquisition unit and a displacement distance acquisition unit. The speed acquisition unit is connected to the acceleration acquisition unit, and the acceleration acquisition unit is connected to the displacement distance acquisition unit. The forklift data acquisition module can determine the position, speed and acceleration of the object. The position is the spatial position of the object during the movement, the speed is the distance moved by the object per unit time, and the acceleration is the rate of change of the speed.

[0062] Reference Figure 3 The motor data acquisition module includes a temperature data acquisition unit, a current and voltage data acquisition unit, and an output torque acquisition unit. The temperature data acquisition unit is connected to the current and voltage data acquisition unit, and the current and voltage data acquisition unit is connected to the output torque acquisition unit.

[0063] Reference Figure 4 The environmental data acquisition module includes a path data acquisition unit, a resistance data acquisition unit and a load data acquisition unit. The path data acquisition unit is connected to the resistance data acquisition unit, and the resistance data acquisition unit is connected to the load data acquisition unit.

[0064] Reference Figure 5 The battery data acquisition module includes a battery temperature acquisition unit, a power acquisition unit and a charge and discharge data acquisition unit. The battery temperature data acquisition unit is connected to the power acquisition unit, and the power acquisition unit is connected to the charge and discharge data acquisition unit.

[0065] The implementation principle in this embodiment is: when in use, the environment data of the forklift and the parameter data of the forklift vehicle and the motor are set through the environment setting module and the parameter setting module, the set data is collected and sorted through the environment data acquisition module and the motor data acquisition module, and then the forklift vehicle data, electrical load data and battery data are collected through the forklift data acquisition module, and the collected data are sorted and uploaded. The recording module records all the collected data, the analysis and comparison module analyzes and compares according to the different parameter data set, the classification module classifies the analysis and comparison results, the modeling module calculates the motion equation of the forklift according to the classified data, and establishes the corresponding motion model according to the motion equation, the simulation module performs simulation experiments on the motion model, the verification analysis module performs verification analysis based on the experimental data, and finally the optimization design module optimizes the forklift design through the analysis results.

[0066] Embodiment 2

[0067] The difference between this embodiment and the first embodiment is that the simulation module is connected to the operating simulation module, which can virtually restore and detect the operation system of the forklift, and can simulate the operating ability and actual operating skills under different operating environments, thereby improving the operator's skill proficiency.

[0068] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A kinematic modeling method for an electric forklift, characterized in that: The following steps are involved: S1: First, set the forklift's environment data and forklift motor parameter data, and collect and organize the set data; S2: Collect the forklift vehicle data, electrical load data and battery data, and organize and upload the collected data; S3: Record all collected data, analyze and compare them according to different parameter data set, and classify the analysis and comparison results; S4: Calculate the motion equation of the forklift according to the classified data, and establish a corresponding motion model according to the motion equation; S5: Conduct simulation experiments on the motion model, conduct verification analysis based on the experimental data, and optimize the forklift design based on the analysis results.

2. A kinematic modeling system for an electric forklift, characterized in that: include: Forklift vehicle module; A forklift data acquisition module, wherein the forklift data acquisition module is connected to the forklift vehicle module, the forklift data acquisition module is connected to a recording module, the recording module is connected to an analysis and comparison module, the analysis and comparison module is connected to a classification module, and the analysis and comparison module is used to compare and analyze the motion data of different parameters of the forklift; A modeling module, wherein the modeling module is connected to the classification module, wherein the modeling module is connected to a simulation module, wherein the simulation module is connected to a verification analysis module, wherein the verification analysis module is connected to an optimization design module, and wherein the optimization design module is used to optimize the forklift design according to the simulation analysis results; An environment setting module, wherein the environment setting module is connected to an environment data acquisition module, wherein the environment data acquisition module is connected to an electrical load data acquisition module, and both the electrical load data acquisition module and the environment data acquisition module are connected to a recording module; A parameter setting module, wherein the parameter setting module is connected to a motor data acquisition module, the motor parameter acquisition module is connected to a battery data acquisition module, and both the motor parameter data acquisition module and the battery data acquisition module are connected to a recording module.

3. The kinematic modeling system of an electric forklift according to claim 2, characterized in that: The forklift data acquisition module includes a speed acquisition unit, an acceleration acquisition unit and a displacement distance acquisition unit. The speed acquisition unit is connected to the acceleration acquisition unit, and the acceleration acquisition unit is connected to the displacement distance acquisition unit.

4. The kinematic modeling system of an electric forklift according to claim 3, characterized in that: The motor data acquisition module includes a temperature data acquisition unit, a current and voltage data acquisition unit, and an output torque acquisition unit. The temperature data acquisition unit is connected to the current and voltage data acquisition unit, and the current and voltage data acquisition unit is connected to the output torque acquisition unit.

5. The kinematic modeling system of an electric forklift according to claim 4, characterized in that: The environmental data acquisition module includes a path data acquisition unit, a resistance data acquisition unit and a load data acquisition unit. The path data acquisition unit is connected to the resistance data acquisition unit, and the resistance data acquisition unit is connected to the load data acquisition unit.

6. The kinematic modeling system of an electric forklift according to claim 5, characterized in that: The battery data acquisition module includes a battery temperature acquisition unit, a power acquisition unit and a charge and discharge data acquisition unit. The battery temperature data acquisition unit is connected to the power acquisition unit, and the power acquisition unit is connected to the charge and discharge data acquisition unit.

7. The kinematic modeling system of an electric forklift according to claim 6, characterized in that: The environment setting module is used to set the environment in which the forklift is located, including setting the resistance parameters of the forklift, the load parameters of the forklift and the travel path parameters of the forklift.

8. The kinematic modeling system of an electric forklift according to claim 7, characterized in that: The parameter setting module is used to set the motor parameters, and to set the driving speed, driving acceleration and driving displacement distance parameters of the forklift.

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