CN117871117A - Method and system for testing running state of field vehicle - Google Patents
Method and system for testing running state of field vehicle Download PDFInfo
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Abstract
The invention discloses a method and a system for testing running states of a field vehicle, which relate to the technical field of vehicle testing and comprise the following steps: building a virtual simulation environment, acquiring structural parameters and motion parameters of a field vehicle, building a field vehicle model, and loading a physical engine in the field vehicle model; setting a test item, wherein the test item comprises a first test, a second test and a third test, designing a corresponding sensor model according to the specification and performance parameters of an actual sensor required by the test item, and assembling the sensor model on a test point of a field vehicle model; setting test conditions of each test item, testing the field car model under the test conditions of each test item, and sorting data acquired in the test according to the sensor model to obtain a simulation test result; and analyzing the simulation test result by combining the test index to obtain a test evaluation result of the field vehicle. The invention can improve the accuracy and repeatability of the test and reduce the test cost and time.
Description
Technical Field
The invention relates to the technical field of vehicle testing, in particular to a method and a system for testing running states of a field vehicle.
Background
A field car is a transport means widely used in the industry for carrying and stacking goods. They generally have greater load carrying capacity and higher work efficiency to meet the demands of large-scale cargo handling. Court vehicles typically have more powerful power systems and more stable structures to cope with complex work environments and heavy goods.
In order to ensure the safety and performance of the field vehicle in the running state, a corresponding test method is required. Currently, there are a number of techniques for testing the running state of a field vehicle when it is dynamic: 1) Dynamic load test: the performance of the field vehicle under different load conditions is tested by placing a load with a certain weight on the field vehicle and simulating a transportation task in an actual working environment; 2) Braking distance test: testing the braking performance of the field vehicle at different speeds, including braking distance and braking time; 3) Load stability test: and placing a load with a certain weight on the field vehicle, simulating an uneven road surface in an actual working environment, and testing the load stability of the field vehicle under different road conditions.
However, the above-mentioned partial test method needs to be performed on a specific test field, and cannot simulate various complex conditions in a real working environment, so that the test result is different from the actual use situation. Some test methods require manual operations and measurements, and may result in inaccuracy of the test results due to subjective factors.
The invention patent with the Chinese application number of 202210285440.0 discloses a forklift braking performance test method and device, and a braking performance test system is built, wherein the system comprises a data acquisition module, a data processing module and an intelligent deviation rectifying module, and the accuracy of a forklift braking performance analysis result is improved by using a computer technology, and meanwhile, the intelligent degree of forklift braking performance test is improved, so that the forklift braking performance test efficiency is improved. However, in the prior art, only the braking performance is tested, and only the braking performance under the conditions of load and speed is detected, so that errors still exist in the testing mode, and the repeated correction of the braking logic makes the cost of actual cost higher.
Disclosure of Invention
In view of the above, the present invention provides a method and a system for testing running states of a field vehicle, which can more truly simulate the conditions of the field vehicle under different working conditions by performing brake performance test, climbing performance test and noise level test in a virtual simulation environment, and monitor and record test results in real time. This can improve the accuracy and repeatability of the test while reducing the test cost and time.
The technical purpose of the invention is realized as follows:
In one aspect, the invention provides a method for testing the running state of a field vehicle, which comprises the following steps:
s1, building a virtual simulation environment, comprising a test scene and a test environment, acquiring structural parameters and motion parameters of a field vehicle, constructing a field vehicle model, and loading a physical engine in the field vehicle model;
s2, setting a test item, wherein the test item comprises a first test, a second test and a third test, designing a corresponding sensor model according to the specification and performance parameters of an actual sensor required by the test item, and assembling the sensor model on a test point of a field vehicle model;
s3, setting test conditions of each test item, testing the field car model under the test conditions of each test item, and sorting data acquired in the test according to the sensor model to obtain a simulation test result;
s4, analyzing the simulation test result by combining the test indexes to obtain a test evaluation result of the field vehicle.
On the basis of the above-mentioned scheme, preferably, step S1 includes:
s11, determining a test scene, including topography, roads, obstacles, buildings and other scene elements of the test site;
s12, setting a test environment which comprises rainy days, sunny days, heavy fog and strong wind;
S13, collecting structural parameters of the field vehicle, including the total weight of the field vehicle, the size of the field vehicle, the shape of the components, the weight of the components, the tire type, the power system, the braking system and the battery management system;
s14, obtaining motion parameters of the field vehicle, including maximum speed, acceleration, steering radius and bearing capacity;
s15, constructing a field vehicle model in three-dimensional software according to the structural parameters and the motion parameters of the field vehicle;
s16, selecting a physical engine and leading the physical engine into a field vehicle model, and adding rigid body components at corresponding positions of the field vehicle model to simulate the physical characteristics and the dynamic characteristics of the field vehicle;
s17, setting related parameters in a physical engine according to physical parameters of the field vehicle, wherein the physical parameters comprise mass, inertia tensor, friction coefficient and air resistance coefficient of the field vehicle;
s18, adding driving force configuration parameters including gravity, external force, engine output force and braking force through an interface provided by the physical engine.
On the basis of the above-mentioned scheme, preferably, step S2 includes:
s21, setting test items, wherein the test items comprise a first test, a second test and a third test;
s22, determining corresponding sensor types and sensor parameters according to each test item, wherein the sensor types comprise a first sensor, a second sensor and a third sensor, and the parameters of each sensor comprise a measurement range, measurement precision and response time;
S23, creating a corresponding first sensor model, a second sensor model and a third sensor model according to the determined sensor type and the sensor parameters;
s24, acquiring a first test requirement, a second test requirement and a third test requirement, respectively determining a test point of the first test, a test point of the second test and a test point of the third test on the field vehicle model according to the first test requirement, the second test requirement and the third test requirement, assembling the created first sensor model to the test point of the first test, assembling the created second sensor model to the test point of the second test and assembling the created third sensor model to the test point of the third test.
On the basis of the above-mentioned scheme, preferably, step S3 includes:
s31, setting a first test condition, a second test condition and a third test condition, and determining an adjustment range of the first test condition, an adjustment range of the second test condition and an adjustment range of the third test condition;
s32, under a first test condition, performing a first test on the field car model, collecting first initial data acquired by the first sensor model in the process of the first test, and adjusting the first test condition within an adjustment range of the first test condition to obtain N 1 The method comprises the steps of carrying out first test on a field car model under the first test conditions after adjustment, collecting first adjustment data acquired by a first sensor model, and combining first initial data and first adjustment data to obtain first data;
s33, under a second test condition, performing a second test on the field car model, collecting second initial data acquired by a second sensor model in the process of the second test,adjusting the second test condition within the adjustment range of the second test condition to obtain N 2 The second test conditions after the group adjustment are respectively used for carrying out a second test on the field car model under the second test conditions after the adjustment, collecting second adjustment data acquired by a second sensor model, and combining second initial data and second adjustment data to be used as second data;
s34, under a third test condition, performing a third test on the field car model, collecting third initial data acquired by a third sensor model in the process of the third test, and adjusting the third test condition within an adjustment range of the third test condition to obtain N 3 The third test conditions after the group adjustment are respectively used for carrying out third test on the field car model under the third test conditions after the adjustment, collecting third adjustment data acquired by a third sensor model, and combining the third initial data and the third adjustment data to be used as third data;
S35, the first data, the second data and the third data are arranged to be used as simulation test results.
On the basis of the above-mentioned scheme, preferably, the first test is a brake performance test, and step S32 includes:
s321, setting a first test condition comprising an initial speed, a braking force and a test distance;
s322, according to the first test requirement, adjusting parameters of a test scene and a test environment;
s323 enables the field car model to run according to the current initial speed, alpha braking points are designated in the current testing distance, current braking force is applied to each braking point through a physical engine, a braking system of the field car model is triggered, and meanwhile, data in testing, including deceleration, braking time and braking distance in a braking process, are collected in real time by utilizing the first sensor model;
s324, when the on-site vehicle model reaches the end point of the current testing distance, after the testing is finished, obtaining first initial data;
s325, in the adjustment range of the first test condition, adjusting the initial speed, the braking force and the test distance to obtain N 1 A set of adjusted first test conditions, wherein each setThe adjusted first test condition accords with a first adjustment constraint condition;
s326, repeating the testing process in the step S323 for each set of adjusted first testing conditions, and obtaining N altogether when the testing is completed 1 Group first adjustment data;
s327 combines the first initial data and the first adjustment data, and adds corresponding first test conditions as labels to obtain first data.
On the basis of the above-mentioned scheme, preferably, in step S325, the first adjustment constraint condition includes:
F<μ×m×a
v 0 ≤(2×F max ×I) 0.5
wherein D is 1 For the test distance, F is the braking force, v 0 For initial speed F max Alpha is the number of braking points, mu is the friction coefficient, m is the mass of the field car, a is the acceleration of the field car, and I is the inertial tensor.
Based on the above scheme, preferably, the second test is a climbing performance test, and step S33 includes:
s331, setting second test conditions including a climbing gradient, a climbing speed and a climbing distance, and adjusting parameters of a test scene and a test environment according to second test requirements;
s332, enabling the field vehicle model to run at the current climbing speed and start climbing, designating beta detection points within the current climbing distance, and sequentially setting the battery power index of each detection point, wherein the battery power index is the first battery power indexAnd a second battery power indicator->
S333 utilizes first sensingThe device model acquires the battery power when reaching each detection point in real time, and if the current battery power is lower than a first battery power index of the current detection point Triggering a braking system to charge the battery of the field vehicle model until the battery electric quantity of the field vehicle model reaches the second battery electric quantity index of the current detection point +.>Releasing the brake and enabling the field vehicle model to continuously climb the slope;
s334, when the on-site vehicle model reaches the end point of the current climbing distance, obtaining second initial data including speed, acceleration and battery electricity in the climbing process after the test is finished;
s335, adjusting the climbing gradient, the climbing speed and the climbing distance within the adjustment range of the second test condition to obtain N 2 A set of adjusted second test conditions, wherein each set of adjusted second test conditions meets a second adjustment constraint condition;
s336, repeating the testing process in the steps S323-S333 for each set of adjusted second testing conditions, and obtaining N altogether when the testing is completed 2 A second set of adjustment data;
s337, combining the second initial data and the second adjustment data, and adding corresponding second test conditions as labels to obtain second data.
On the basis of the above-described aspect, preferably, in step S335, the second adjustment constraint includes:
v 1 ≤min(v maxpower ,v maxfriction )
wherein D is 2 V is the climbing distance 1 For climbing speed, θ is climbing gradient, g is gravitational acceleration, μ is friction coefficient, f represents the ratio of vertical force applied to the tire of the model of the motorcycle to the mass of the motorcycle, v maxpower Representing maximum ramp rate under dynamic constraints, v maxfriction Representing the maximum ramp rate under friction constraints;
wherein:
wherein P is max For maximum output power of the power system, m is mass of the field car, sqrt represents square root operation, mu max R is the tire radius and is the maximum coefficient of friction.
On the basis of the above-mentioned scheme, preferably, the third test is a noise level test, and step S34 includes:
s341 sets a third test condition comprising a running speed, a running acceleration, a running deceleration, a load amount and a test time;
s342, according to a third test requirement, parameters of a test scene and a test environment are adjusted;
s343, adding load to the field vehicle model according to the load quantity, setting a test stage, wherein the test stage is divided into three stages, namely an acceleration stage A, a uniform speed stage B and a deceleration stage C, and setting the acceleration starting speed of the acceleration stage according to the test stageAnd acceleration end speed->Constant speed driving speed in constant speed stage>Deceleration start speed in deceleration phase +.>And deceleration end speed +.>
S344, setting a test flow, wherein the test flow is a combination of test stages, the test flow is expressed as S= { A, B, C }, the field car model is subjected to a third test according to the test flow, and the data of each test stage in the test process, including sound level data, frequency data and noise change condition, are recorded by using a third sensor model;
S345, when the test time is reached, obtaining third initial data after the test is completed;
s346, in the adjustment range of the third test condition, adjusting the running speed, the running acceleration, the running deceleration, the load and the test time to obtain N 3 A set of adjusted third test conditions, wherein each set of adjusted third test conditions meets a third adjustment constraint condition;
s347 repeating the test procedure in steps S343-344 for each set of adjusted third test conditions, and obtaining N altogether when the test is completed 3 A third group of adjustment data;
s348, combining the third initial data and the third adjustment data, and adding corresponding third test conditions as labels to obtain third data;
wherein the third adjustment constraint comprises:
L≤L mCx
in the formula, v 2 For travelling speed, P max Is the maximum output power of the power system, mu is the friction coefficient, R is the tire radius, a 1 For acceleration of driving, T max For maximum traction, m is mass of the field car, L is load quantity, a 2 For the running deceleration, g is gravity acceleration, r is mass distribution coefficient of the field car, L max Is the maximum load of the field car.
On the other hand, the invention also provides a system for testing the running state of a field vehicle, wherein the system is used for executing any one of the methods, three-dimensional simulation software is loaded in the system, and the system comprises:
The virtual simulation environment module is used for creating a test scene and a test environment;
the test project management module is used for setting test projects and test conditions, including a first test, a second test and a third test, and is connected with the virtual simulation environment module to adjust a test scene and a test environment;
the model construction module is used for constructing a field vehicle model according to actual structural parameters and motion parameters of the field vehicle, loading a physical engine in the field vehicle model, designing a corresponding sensor model according to specifications and performance parameters of an actual sensor required by a test project, and assembling the sensor model on a test point of the field vehicle model;
the test execution module is used for receiving a test instruction of the test project management module, testing the field car model according to the test instruction, and synchronously calling the sensor model to acquire test data so as to acquire a simulation test result;
the test result analysis module is used for receiving and analyzing the simulation test result transmitted by the test execution module, and evaluating the simulation test result according to the test index to obtain a test evaluation result of the field vehicle;
and the test display module is used for receiving the test evaluation result of the test result analysis module and performing visual display.
Compared with the prior art, the method has the following beneficial effects:
(1) According to the invention, the brake performance test, the climbing performance test and the noise degree test are carried out in the virtual simulation environment, so that the situation of the field vehicle under different working conditions can be more truly simulated, and the test result can be monitored and recorded in real time. Thus, the accuracy and the repeatability of the test can be improved, and the test cost and time are reduced;
(2) When the field vehicle model is tested, the test conditions are adjusted within the adjustment range of the test conditions, so that the test result data are enlarged, the test diversity is increased, and the adjustment relation of each test condition is restrained, so that each aspect of the field vehicle model can be more comprehensively and reasonably evaluated accurately;
(3) The invention provides corresponding test methods for three tests respectively, and various detection indexes, detection points, test flows and the like are added during the test, so that the accuracy and the reliability of the test can be improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method according to an embodiment of the present invention;
FIG. 2 is a system frame diagram of an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will clearly and fully describe the technical aspects of the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, are intended to fall within the scope of the present invention.
As shown in fig. 1, the invention provides a method for testing running states of a field vehicle, which comprises the following steps:
s1, building a virtual simulation environment, comprising a test scene and a test environment, acquiring structural parameters and motion parameters of a field vehicle, constructing a field vehicle model, and loading a physical engine in the field vehicle model;
s2, setting a test item, wherein the test item comprises a first test, a second test and a third test, designing a corresponding sensor model according to the specification and performance parameters of an actual sensor required by the test item, and assembling the sensor model on a test point of a field vehicle model;
S3, setting test conditions of each test item, testing the field car model under the test conditions of each test item, and sorting data acquired in the test according to the sensor model to obtain a simulation test result;
s4, analyzing the simulation test result by combining the test indexes to obtain a test evaluation result of the field vehicle.
Specifically, in an embodiment of the present invention, step S1 includes:
s11 determines a test scene including terrain, roads, obstacles, buildings, and other scene elements of the test site.
Specifically, terrains such as flat ground, undulating terrain, ramps, etc. Road types such as straight roads, curves, endless roads, etc. Such as a roadblock, a road depression, a mobile facility, etc. Buildings such as fixed public facilities, shelves, etc.
S12, setting a test environment comprising rainy days, sunny days, heavy fog and strong wind.
Specifically, the test environment is set according to the setting of parameters such as light, water drops, and the like.
S13, collecting structural parameters of the field vehicle, including the total weight of the field vehicle, the size of the field vehicle, the shape of the components, the weight of the components, the tire type, the power system, the braking system and the battery management system.
S14, acquiring motion parameters of the field vehicle, including maximum speed, acceleration, steering radius and bearing capacity.
S15, constructing a field vehicle model in three-dimensional software according to the structural parameters and the motion parameters of the field vehicle.
Specifically, an appearance model of the field car is firstly created in three-dimensional software according to the size and the shape of the field car, then an internal structure model of the field car is designed according to other structural parameters, in addition, details and decorations of the field car, such as car windows, car lamps, internal decorations and the like, can be added, the appearance model and the internal structure model are combined to form the field car model, and the motion parameters of the field car are imported.
S16, selecting a physical engine and leading the physical engine into a field vehicle model, and adding rigid body components at corresponding positions of the field vehicle model to simulate the physical characteristics and the dynamic characteristics of the field vehicle.
Specifically, the physical Engine is PhysX in Unity, physX in Unreal Engine, havok, or the like. Rigid bodies are basic components in a physical engine, and the addition of the rigid body components to the body, wheels and the like of a field car can enable the field car model to have real physical behaviors such as falling, collision and movement under gravity.
S17, setting related parameters in a physical engine according to physical parameters of the field vehicle, wherein the physical parameters comprise mass, inertia tensor, friction coefficient and air resistance coefficient of the field vehicle.
S18, adding driving force configuration parameters including gravity, external force, engine output force and braking force through an interface provided by the physical engine.
Specifically, in an embodiment of the present invention, step S2 includes:
s21, setting test items, wherein the test items comprise a first test, a second test and a third test;
s22, determining corresponding sensor types and sensor parameters according to each test item, wherein the sensor types comprise a first sensor, a second sensor and a third sensor, and the parameters of each sensor comprise a measurement range, measurement precision and response time;
s23, creating a corresponding first sensor model, a second sensor model and a third sensor model according to the determined sensor type and the sensor parameters;
s24, acquiring a first test requirement, a second test requirement and a third test requirement, respectively determining a test point of the first test, a test point of the second test and a test point of the third test on the field vehicle model according to the first test requirement, the second test requirement and the third test requirement, assembling the created first sensor model to the test point of the first test, assembling the created second sensor model to the test point of the second test and assembling the created third sensor model to the test point of the third test.
In this embodiment, the first test is a brake performance test, the second test is a hill climbing performance test, and the third test is a noise level test.
Specifically, the first sensor should include at least a braking distance sensor, an acceleration sensor, and a time sensor, and parameters of the first sensor are as follows:
braking distance sensor
Measurement range: 0-100m; measurement accuracy: + -0.1 mm; response time: within 1 ms.
Acceleration sensor
Measurement range: -10m/s 2 To 10m/s 2 The method comprises the steps of carrying out a first treatment on the surface of the Measurement accuracy: + -0.01 m/s 2 The method comprises the steps of carrying out a first treatment on the surface of the Response time: within 1 ms.
Time sensor
Measurement range: 0-10s; measurement accuracy: 0.01s; response time: within 1 ms.
Specifically, the second sensor should include at least a speed sensor and an acceleration sensor, and parameters of the second sensor are as follows:
speed sensor
Measurement range: 0m/s to 10m/s; measurement accuracy: 0.01m/s; response time: within 1 ms.
Acceleration sensor
Measurement range: -10m/s 2 To 10m/s 2 The method comprises the steps of carrying out a first treatment on the surface of the Measurement accuracy: + -0.01 m/s 2 The method comprises the steps of carrying out a first treatment on the surface of the Response time: within 1 ms.
Specifically, the third sensor should include at least a speed sensor and an acceleration sensor, and parameters of the third sensor are as follows:
sound pressure level sensor
Measurement range: 30dB to 130dB; measurement accuracy: + -0.5 dB; response time: within 10 ms.
Frequency sensor
Measurement range: 20Hz to 20kHz; measurement accuracy: + -0.1 Hz; response time: within 10 ms.
Acoustic spectrum sensor
Measurement range: 20Hz to 20kHz; measurement accuracy: + -0.1 dB; response time: within 10 ms.
After various sensors and parameters thereof are acquired, a corresponding sensor model can be established, the sensor model is assembled on a corresponding test point, such as the head of a field vehicle model, the inside of the field vehicle model, the vicinity of a chassis of the field vehicle model and the like, and the sensor model is connected with the field vehicle model, so that the process of acquiring braking performance information by the sensor can be simulated.
Specifically, in an embodiment of the present invention, step S3 includes:
s31, setting a first test condition, a second test condition and a third test condition, and determining an adjustment range of the first test condition, an adjustment range of the second test condition and an adjustment range of the third test condition;
s32, under a first test condition, performing a first test on the field car model, collecting first initial data acquired by the first sensor model in the process of the first test, and adjusting the first test condition within an adjustment range of the first test condition to obtain N 1 The method comprises the steps of carrying out first test on a field car model under the first test conditions after adjustment, collecting first adjustment data acquired by a first sensor model, and combining first initial data and first adjustment data to obtain first data;
s33, under a second test condition, performing a second test on the field car model, collecting second initial data acquired by a second sensor model in the process of the second test,adjusting the second test condition within the adjustment range of the second test condition to obtain N 2 The second test conditions after the group adjustment are respectively used for carrying out a second test on the field car model under the second test conditions after the adjustment, collecting second adjustment data acquired by a second sensor model, and combining second initial data and second adjustment data to be used as second data;
s34, under a third test condition, performing a third test on the field car model, collecting third initial data acquired by a third sensor model in the process of the third test, and adjusting the third test condition within an adjustment range of the third test condition to obtain N 3 The third test conditions after the group adjustment are respectively used for carrying out third test on the field car model under the third test conditions after the adjustment, collecting third adjustment data acquired by a third sensor model, and combining the third initial data and the third adjustment data to be used as third data;
S35, the first data, the second data and the third data are arranged to be used as simulation test results.
The test procedure of each test item in step S3 will be described in a specific embodiment:
the first test is a brake performance test, and step S32 includes:
s321 sets a first test condition including an initial speed, a braking force, and a test distance.
S322, according to the first test requirement, parameters of the test scene and the test environment are adjusted.
And adjusting parameters of a test scene and a test environment according to the requirements of the brake performance test. For example, the friction coefficient, gradient, road surface condition, etc. of the field are adjusted to simulate the braking performance under different actual driving conditions.
S323 enables the field car model to run according to the current initial speed, alpha braking points are designated in the current testing distance, current braking force is applied to each braking point through a physical engine, a braking system of the field car model is triggered, and meanwhile, data in testing, including deceleration, braking time and braking distance in a braking process, are collected in real time by utilizing the first sensor model.
Specifically, these data may be obtained by direct acquisition according to the first sensor model.
S324, when the on-site vehicle model reaches the end point of the current testing distance, after the testing is finished, obtaining first initial data;
S325, in the adjustment range of the first test condition, adjusting the initial speed, the braking force and the test distance to obtain N 1 And the first test conditions after the adjustment are set, wherein each set of the first test conditions after the adjustment accords with the first adjustment constraint condition.
According to the adjustment range of the first test condition, the initial speed, the braking force and the test distance are adjusted to obtain N 1 And (3) setting the adjusted first test condition. By adjusting these conditions, the braking performance under different conditions can be tested, and the performance of the field vehicle can be further evaluated. Specifically, N 1 The value is taken as 10.
The first adjustment constraint is as follows:
F<μ×m×a
v 0 ≤(2×F max ×I) 0.5
wherein D is 1 For the test distance, F is the braking force, v 0 For initial speed F max Alpha is the number of braking points, mu is the friction coefficient, m is the mass of the field car, a is the acceleration of the field car, and I is the inertial tensor.
When the initial speed, the braking force and the test distance are adjusted, factors such as the capacity of a brake system of a field car model, the limitation of a test environment and the like are considered, wherein the test distance is proportional to the square of the initial speed and inversely proportional to the braking force and the friction coefficient. In other words, the test distance is inversely proportional to the coefficient of friction when the initial speed and braking force remain unchanged. While the initial speed and coefficient of friction remain unchanged, the test distance is inversely proportional to the braking force. The initial speed should not exceed the maximum braking force that the design and performance of the vehicle and the braking system can withstand, i.e., the initial speed should be less than or equal to the square root of the product of the maximum braking force and the rotational inertia tensor of the vehicle. The inertial tensor is a parameter describing the inertial properties of an object for rotational movement.
S326, repeating the testing process in the step S323 for each set of adjusted first testing conditions, and obtaining N altogether when the testing is completed 1 The first adjustment data is set.
By repeating the test, N can be obtained 1 And (3) braking performance data under the first test condition after the group adjustment. The data can be used for comparing the braking performance difference under different test conditions to further understand the performance characteristics of the field vehicle.
S327 combines the first initial data and the first adjustment data, and adds corresponding first test conditions as labels to obtain first data.
Specifically, the first test condition is taken as a head of a row, deceleration, braking time and braking distance in the braking process in the data are respectively taken as head of a column, specific data values are filled in corresponding columns, and a table is formed as first data.
The second test is a climbing performance test, and step S33 includes:
s331, setting second test conditions including climbing gradient, climbing speed and climbing distance, and adjusting parameters of a test scene and a test environment according to second test requirements.
S332, enabling the field vehicle model to run at the current climbing speed and start climbing, designating beta detection points within the current climbing distance, and sequentially setting the battery power index of each detection point, wherein the battery power index is the first battery power index And a second battery power indicator->
Specifically, the value of beta is 4, the first battery power index is the battery power lower limit value when the field car model reaches the current detection point, and the second battery power index is the battery power lower limit value corresponding to the residual test distance from the current detection point to the end of the test.
S333, acquiring the battery power when reaching each detection point in real time by using the second sensor model, and if the current battery power is lower than the first battery power index of the current detection pointTriggering a braking system to charge the battery of the field vehicle model until the battery electric quantity of the field vehicle model reaches the second battery electric quantity index of the current detection point +.>And releasing the brake to enable the field vehicle model to continuously climb the slope.
Specifically, when β=4,and->
And S334, when the on-site vehicle model reaches the end point of the current climbing distance, after the test is finished, obtaining second initial data including the speed, the acceleration, the charging times and the battery electric quantity of each detection point in the climbing process.
Specifically, the speed and the acceleration in the climbing process can be directly acquired by the second sensor model, and the charging times and the battery electric quantity of each detection point can be provided by a battery management system in the field vehicle model. A battery management system (Battery Management System, abbreviated as BMS) is a system integrating battery state monitoring and management functions, which can monitor charge and discharge processes of a battery and record the number of times of charge.
S335, adjusting the climbing gradient, the climbing speed and the climbing distance within the adjustment range of the second test condition to obtain N 2 And a set of adjusted second test conditions, wherein each set of adjusted second test conditions meets a second adjustment constraint.
Specifically, N 2 The second adjustment constraint includes:
v 1 ≤min(v maxpower ,v maxfriction )
wherein D is 2 V is the climbing distance 1 For climbing speed, θ is climbing gradient, g is gravitational acceleration, μ is friction coefficient, f represents the ratio of vertical force applied to the tire of the model of the motorcycle to the mass of the motorcycle, v maxpower Representing maximum ramp rate under dynamic constraints, v maxfriction Representing the maximum ramp rate under friction constraints;
wherein:
wherein P is max For maximum output power of the power system, m is mass of the field car, sqrt represents square root operation, mu max R is the tire radius and is the maximum coefficient of friction.
In the climbing test, the limitation of a power system, a friction coefficient, a gravity acceleration and other factors of a field car model needs to be considered. Wherein the uphill gradient should be less than the maximum climbable gradient of the vehicle. The maximum climbable gradient refers to the maximum gradient at which the vehicle can successfully climb the slope without running away or continuing. The maximum climbable gradient is determined by the vehicle's powertrain, coefficient of friction, gravitational acceleration, etc. If the maximum climbable gradient of the vehicle is limited, the gradient that the vehicle can climb is limited, thereby limiting the climbing distance. In addition, the climbing speed of a vehicle may be limited by the power system capabilities of the vehicle and by friction. The maximum climbing speed under the power constraint is proportional to the maximum output power of the power system and inversely proportional to the sine value of the climbing gradient. The maximum hill climbing speed under friction constraints is related to the maximum friction coefficient, gravitational acceleration, tire radius, vehicle mass, and hill climbing grade. The larger the maximum friction coefficient is, the larger the maximum climbing speed is; the larger the gravitational acceleration, the smaller the maximum climbing speed; the larger the tire radius, the greater the maximum climbing speed; the greater the vehicle mass, the less the maximum hill climbing speed; the larger the climbing gradient, the smaller the maximum climbing speed.
S336, repeating the testing process in the steps S323-S333 for each set of adjusted second testing conditions, and obtaining N altogether when the testing is completed 2 And a second set of adjustment data.
Specifically, by repeating the test, N can be obtained 2 And the data under the second test condition after the group adjustment comprises speed, acceleration, charging times and battery electric quantity of each detection point. These data can be used to compare the difference in climbing performance under different test conditions.
S337, combining the second initial data and the second adjustment data, and adding corresponding second test conditions as labels to obtain second data.
Specifically, the second test condition is taken as a head of a row, the speed, the acceleration, the charging times and the battery electric quantity of each detection point in the climbing process in the data are respectively taken as a head of a column, and specific data values are filled in corresponding columns to form a table as second data.
The third test is a noise level test, and step S34 includes:
s341 sets a third test condition comprising a running speed, a running acceleration, a running deceleration, a load amount and a test time;
s342, according to the third test requirement, parameters of the test scene and the test environment are adjusted.
According to the requirements of the third test, parameters of the test scene and the test environment need to be adjusted to ensure the accuracy and the repeatability of the test. For example, the actual usage scenario may be simulated by adjusting parameters such as background noise level, ambient temperature and humidity of the test site.
S343, adding load to the field vehicle model according to the load quantity, setting a test stage, wherein the test stage is divided into three stages, namely an acceleration stage A, a uniform speed stage B and a deceleration stage C, and setting the acceleration starting speed of the acceleration stage according to the test stageAnd acceleration end speed->Constant speed driving speed in constant speed stage>Deceleration start speed in deceleration phase +.>And deceleration end speed +.>
S344, a test flow is set, the test flow is a combination of test stages, the test flow is expressed as S= { A, B, C }, the field car model is enabled to conduct a third test according to the test flow, and data of each test stage in the test process, including sound level data, frequency data and noise change conditions, are recorded by using a third sensor model.
It should be noted that, in the test flow, there is not only one acceleration stage, one constant speed stage, one deceleration stage, but a plurality of stages, and the sequence is not necessarily acceleration, constant speed, and deceleration, and in the noise test, the test is not necessarily started from the start of the field car model at the start, for example, the field car model is started for a period of time, and the acceleration starts to the deceleration start speed of the deceleration stageAt this time, the noise test is started, the test flow is a deceleration phase, an acceleration phase, a constant speed phase and a deceleration phase, and when the test time is up, the test is completed. Thus, the speeds of each test phase may be partially or completely identical, and the speeds are selected only within the limits of the parameters of the field model and are not limited by the speeds of the other test phases.
Specifically, the third sensor model converts acoustic waves in the environment into electrical signals, and performs corresponding signal processing and analysis. By measuring parameters such as sound pressure level, frequency, sound spectrum and the like, the third sensor model can accurately capture the change condition of noise. These data can be used to evaluate the noise level of the field car model, analyze the characteristics and trend of the noise, and compare the differences in noise performance under different test conditions.
And S345, when the test time is up, obtaining third initial data after the test is completed.
S346, in the adjustment range of the third test condition, adjusting the running speed, the running acceleration, the running deceleration, the load and the test time to obtain N 3 And a set of adjusted third test conditions, wherein each set of adjusted third test conditions meets a third adjustment constraint condition.
Specifically, N 3 The third adjustment constraint condition includes:
L≤L max
in the formula, v 2 For travelling speed, P max Is the maximum output power of the power system, mu is the friction coefficient, R is the tire radius, a 1 For acceleration of driving, T max For maximum traction, m is mass of the field car, L is load quantity, a 2 For the running deceleration, g is gravity acceleration, r is mass distribution coefficient of the field car, L max Is the maximum load of the field car.
In performing noise tests, the adjustment of the test conditions needs to take into account the properties of the model of the vehicle itself, such as the coefficient of friction, the tire radius, etc. The friction coefficient reflects the friction force between the tire and the ground, and the radius of the tire influences the rotation capacity and the running stability of the forklift. The driving speed should be determined under the limitations of maximum output power of the power system, friction coefficient, radius of the tire and load capacity. The maximum traction force is the maximum traction force that the truck can provide, which determines the acceleration capacity of the truck. The maximum driving acceleration of the court car can be calculated according to the maximum traction force and the total weight of the court car. The range of travel deceleration depends on a number of performance factors of the ride vehicle, including the effectiveness of the braking system, the coefficient of friction of the tires with the ground, the mass distribution of the ride vehicle, etc. The maximum load may be calculated according to the rated load capacity in the product specification data of the field vehicle, or may be calculated according to the size and the rated load capacity of the field vehicle, for example, as the maximum load capacity, and a forklift is used as an example:
L max Y*l*c
wherein Y is the rated bearing capacity of the forklift and the unit is kg; l is the length of the fork arm, and the unit is meter; c is the length coefficient of the fork arm and is usually 0.8-1.0.
S347 repeating the test procedure in steps S343-344 for each set of adjusted third test conditions, and obtaining N altogether when the test is completed 3 And a third set of adjustment data.
S348, combining the third initial data and the third adjustment data, and adding corresponding third test conditions as labels to obtain third data.
Specifically, the third test condition is taken as a head of a row, sound level data, frequency data and noise change conditions in the data are respectively taken as head of a column, specific data values are filled in corresponding columns, and a table is formed to be taken as third data.
Specifically, in an embodiment of the present invention, step S4 includes:
in the first test, the test indexes comprise deceleration, braking time and braking distance, wherein a larger deceleration represents that the vehicle can be rapidly decelerated in the braking process, the vehicle has better braking performance, a shorter braking time represents that the vehicle can be rapidly stopped, the vehicle has better braking performance, and a shorter braking distance represents that the vehicle can be rapidly stopped in the braking process, and the vehicle has better braking performance.
In the second test, the test indexes comprise speed, acceleration, charging times and battery electric quantity, the faster climbing speed indicates that the vehicle has better climbing performance, the larger acceleration indicates that the vehicle can quickly climb a slope, the better climbing performance is achieved, the smaller charging times indicate that the battery endurance of the vehicle in the climbing process is better, and the battery electric quantity condition of each detection point can reflect the energy consumption and the battery service condition of the vehicle in the climbing process.
In the third test, the test indexes include sound level, frequency and noise change conditions, wherein a lower sound level indicates a lower noise level, a smooth frequency distribution concentrated in a low frequency band indicates a lower noise level, and the change condition of noise is observed, if there is a sudden noise change or a larger noise fluctuation.
And (3) combining the simulation test results, and carrying out overall evaluation on the braking performance, the climbing performance and the noise degree of the field vehicle to obtain test evaluation results.
Specifically, the test evaluation result may be:
if the deceleration is larger in the braking performance test, the braking time is shorter, the braking distance is shorter, and the field vehicle has better braking performance.
If the speed is higher in the climbing performance test, the acceleration is higher, the charging times are less, the battery electric quantity of each detection point is higher, and the field vehicle has better climbing performance and cruising ability.
If the sound level is lower in the noise level test, the frequency data is smooth and concentrated in a low frequency band, the noise change condition is more stable, and the field vehicle has lower noise level.
Specifically, each test index may be test data under each test condition of the integrated value, such as taking an average value, and evaluating the corresponding performance according to the test index based on the result of the average value.
According to the invention, three-dimensional simulation is utilized to test the running state of the field vehicle, during testing, the field vehicle model is tested for multiple times according to the set testing condition range to obtain more comprehensive testing data, the performance difference of the field vehicle under different conditions can be evaluated by comparing and analyzing the data under different testing conditions, the basis is provided for optimization and improvement, the performance evaluation result of the field vehicle under different testing conditions can be obtained by arranging and analyzing the simulation testing result, the reference basis is provided for decision and design, the performance change of the field vehicle under different testing conditions can be intuitively presented through visual display, and the understandability and the visual degree of the result are improved.
In addition, referring to fig. 2, the present invention further provides a system for testing running states of a train, where the system is used to execute any one of the methods described above, and three-dimensional simulation software is loaded in the system, and the system includes:
and the virtual simulation environment module is used for creating a test scene and a test environment. The module may generate virtual roads, terrain, and other environments or facilities to simulate real scenes and provide a realistic environment for testing.
And the test item management module is used for setting test items and test conditions, including a first test, a second test and a third test, and is connected with the virtual simulation environment module to adjust the test scene and the test environment. The module can set different test items such as a brake performance test, a climbing performance test and a noise degree test, and adjust test scenes and test environments in the virtual simulation environment module so as to meet test requirements.
The model construction module is used for constructing a field vehicle model according to actual structural parameters and motion parameters of the field vehicle, loading a physical engine in the field vehicle model, designing a corresponding sensor model according to specifications and performance parameters of an actual sensor required by a test project, and assembling the sensor model on a test point of the field vehicle model.
The test execution module is used for receiving the test instruction of the test project management module, testing the field car model according to the test instruction, synchronously calling the sensor model to collect test data, and obtaining a simulation test result.
The test result analysis module is used for receiving and analyzing the simulation test result transmitted by the test execution module, and evaluating the simulation test result according to the test index to obtain a test evaluation result of the field vehicle. By analyzing the simulation test results, the performance of the field vehicle under different test items can be evaluated.
And the test display module is used for receiving the test evaluation result of the test result analysis module and performing visual display. The module can display the test evaluation result in the forms of graphs, charts and the like, so that a user can intuitively know the test result of the field vehicle.
In the embodiment, by embedding the three-dimensional simulation software in the system, the testing system executes the testing process in the three-dimensional virtual environment, and all modules cooperate with each other to realize comprehensive testing of the field vehicle.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (10)
1. The method for testing the running state of the field vehicle is characterized by comprising the following steps of:
s1, building a virtual simulation environment, comprising a test scene and a test environment, acquiring structural parameters and motion parameters of a field vehicle, constructing a field vehicle model, and loading a physical engine in the field vehicle model;
S2, setting a test item, wherein the test item comprises a first test, a second test and a third test, designing a corresponding sensor model according to the specification and performance parameters of an actual sensor required by the test item, and assembling the sensor model on a test point of a field vehicle model;
s3, setting test conditions of each test item, testing the field car model under the test conditions of each test item, and sorting data acquired in the test according to the sensor model to obtain a simulation test result;
s4, analyzing the simulation test result by combining the test indexes to obtain a test evaluation result of the field vehicle.
2. The method for testing the running state of a train in the field according to claim 1, wherein the step S1 includes:
s11, determining a test scene, including topography, roads, obstacles, buildings and other scene elements of the test site;
s12, setting a test environment which comprises rainy days, sunny days, heavy fog and strong wind;
s13, collecting structural parameters of the field vehicle, including the total weight of the field vehicle, the size of the field vehicle, the shape of the components, the weight of the components, the tire type, the power system, the braking system and the battery management system;
s14, obtaining motion parameters of the field vehicle, including maximum speed, acceleration, steering radius and bearing capacity;
S15, constructing a field vehicle model in three-dimensional software according to the structural parameters and the motion parameters of the field vehicle;
s16, selecting a physical engine and leading the physical engine into a field vehicle model, and adding rigid body components at corresponding positions of the field vehicle model to simulate the physical characteristics and the dynamic characteristics of the field vehicle;
s17, setting related parameters in a physical engine according to physical parameters of the field vehicle, wherein the physical parameters comprise mass, inertia tensor, friction coefficient and air resistance coefficient of the field vehicle;
s18, adding driving force configuration parameters including gravity, external force, engine output force and braking force through an interface provided by the physical engine.
3. The method for testing the running state of a train in the field according to claim 2, wherein the step S2 includes:
s21, setting test items, wherein the test items comprise a first test, a second test and a third test;
s22, determining corresponding sensor types and sensor parameters according to each test item, wherein the sensor types comprise a first sensor, a second sensor and a third sensor, and the parameters of each sensor comprise a measurement range, measurement precision and response time;
s23, creating a corresponding first sensor model, a second sensor model and a third sensor model according to the determined sensor type and the sensor parameters;
S24, acquiring a first test requirement, a second test requirement and a third test requirement, respectively determining a test point of the first test, a test point of the second test and a test point of the third test on the field vehicle model according to the first test requirement, the second test requirement and the third test requirement, assembling the created first sensor model to the test point of the first test, assembling the created second sensor model to the test point of the second test and assembling the created third sensor model to the test point of the third test.
4. The method for testing a running state of a motor vehicle according to claim 3, wherein the step S3 includes:
s31, setting a first test condition, a second test condition and a third test condition, and determining an adjustment range of the first test condition, an adjustment range of the second test condition and an adjustment range of the third test condition;
s32, under a first test condition, performing a first test on the field car model, collecting first initial data acquired by a first sensor model in the process of the first test, and performing a first test on the field car modelAdjusting the first test condition within the adjustment range of the first test condition to obtain N 1 The method comprises the steps of carrying out first test on a field car model under the first test conditions after adjustment, collecting first adjustment data acquired by a first sensor model, and combining first initial data and first adjustment data to obtain first data;
S33, under a second test condition, performing a second test on the field car model, collecting second initial data acquired by the second sensor model in the process of the second test, and adjusting the second test condition within the adjustment range of the second test condition to obtain N 2 The second test conditions after the group adjustment are respectively used for carrying out a second test on the field car model under the second test conditions after the adjustment, collecting second adjustment data acquired by a second sensor model, and combining second initial data and second adjustment data to be used as second data;
s34, under a third test condition, performing a third test on the field car model, collecting third initial data acquired by a third sensor model in the process of the third test, and adjusting the third test condition within an adjustment range of the third test condition to obtain N 3 The third test conditions after the group adjustment are respectively used for carrying out third test on the field car model under the third test conditions after the adjustment, collecting third adjustment data acquired by a third sensor model, and combining the third initial data and the third adjustment data to be used as third data;
s35, the first data, the second data and the third data are arranged to be used as simulation test results.
5. The method of testing the running state of a motorcycle as claimed in claim 4, wherein the first test is a brake performance test, and the step S32 includes:
s321, setting a first test condition comprising an initial speed, a braking force and a test distance;
s322, according to the first test requirement, adjusting parameters of a test scene and a test environment;
s323 enables the field car model to run according to the current initial speed, alpha braking points are designated in the current testing distance, current braking force is applied to each braking point through a physical engine, a braking system of the field car model is triggered, and meanwhile, data in testing, including deceleration, braking time and braking distance in a braking process, are collected in real time by utilizing the first sensor model;
s324, when the on-site vehicle model reaches the end point of the current testing distance, after the testing is finished, obtaining first initial data;
s325, in the adjustment range of the first test condition, adjusting the initial speed, the braking force and the test distance to obtain N 1 A set of adjusted first test conditions, wherein each set of adjusted first test conditions meets a first adjustment constraint condition;
s326, repeating the testing process in the step S323 for each set of adjusted first testing conditions, and obtaining N altogether when the testing is completed 1 Group first adjustment data;
s327 combines the first initial data and the first adjustment data, and adds corresponding first test conditions as labels to obtain first data.
6. The method of claim 5, wherein in step S325, the first adjustment constraint includes:
F<μ×m×a
v 0 ≤(2×F max ×I) 0.5
wherein D is 1 For the test distance, F is the braking force, v 0 For initial speed F max Alpha is the number of braking points, mu is the friction coefficient, m is the mass of the field car, a is the acceleration of the field car, and I is the inertial tensor.
7. The method for testing the running state of a motor vehicle according to claim 4, wherein the second test is a hill climbing performance test, and the step S33 includes:
s331, setting second test conditions including a climbing gradient, a climbing speed and a climbing distance, and adjusting parameters of a test scene and a test environment according to second test requirements;
s332, enabling the field vehicle model to run at the current climbing speed and start climbing, designating beta detection points within the current climbing distance, and sequentially setting the battery power index of each detection point, wherein the battery power index is the first battery power indexAnd a second battery power indicator->
S333, acquiring the battery power when reaching each detection point in real time by using the first sensor model, and if the current battery power is lower than the first battery power index of the current detection point Triggering a braking system to charge the battery of the field vehicle model until the battery electric quantity of the field vehicle model reaches the second battery electric quantity index of the current detection point +.>Releasing the brake and enabling the field vehicle model to continuously climb the slope;
s334, when the on-site vehicle model reaches the end point of the current climbing distance, obtaining second initial data including speed, acceleration and battery electricity in the climbing process after the test is finished;
s335, adjusting the climbing gradient, the climbing speed and the climbing distance within the adjustment range of the second test condition to obtain N 2 A set of adjusted second test conditions, wherein each set of adjusted second test conditions meets a second adjustment constraint condition;
s336, repeating the testing process in the steps S323-S333 for each set of adjusted second testing conditions, and obtaining N altogether when the testing is completed 2 A second set of adjustment data;
s337, combining the second initial data and the second adjustment data, and adding corresponding second test conditions as labels to obtain second data.
8. The method for testing a state of operation of a motor vehicle according to claim 7, wherein in step S335, the second adjustment constraint includes:
v 1 ≤min(v maxpower ,v maxfriction )
wherein D is 2 V is the climbing distance 1 For climbing speed, θ is climbing gradient, g is gravitational acceleration, μ is friction coefficient, f represents the ratio of vertical force applied to the tire of the model of the motorcycle to the mass of the motorcycle, v maxpower Representing maximum ramp rate under dynamic constraints, v maxdriction Representing the maximum ramp rate under friction constraints;
wherein:
wherein P is max For maximum output power of the power system, m is mass of the field car, sqrt represents square root operation, mu max R is the tire radius and is the maximum coefficient of friction.
9. The method of claim 4, wherein the third test is a noise level test, and the step S34 includes:
s341 sets a third test condition comprising a running speed, a running acceleration, a running deceleration, a load amount and a test time;
s342, according to a third test requirement, parameters of a test scene and a test environment are adjusted;
s343, adding load to the field vehicle model according to the load quantity, setting a test stage, wherein the test stage is divided into three stages, namely an acceleration stage A, a uniform speed stage B and a deceleration stage C, and setting the acceleration starting speed of the acceleration stage according to the test stageAnd acceleration end speed->Constant speed driving speed in constant speed stage>Deceleration start speed in deceleration phase +.>And deceleration end speed +.>
S344, setting a test flow, wherein the test flow is a combination of test stages, the test flow is expressed as S= { A, B, C }, the field car model is subjected to a third test according to the test flow, and the data of each test stage in the test process, including sound level data, frequency data and noise change condition, are recorded by using a third sensor model;
S345, when the test time is reached, obtaining third initial data after the test is completed;
s346 is to the running speed, the running acceleration and the running subtraction in the adjustment range of the third test conditionSpeed, load capacity and test time are adjusted to obtain N 3 A set of adjusted third test conditions, wherein each set of adjusted third test conditions meets a third adjustment constraint condition;
s347 repeating the test procedure in steps S343-344 for each set of adjusted third test conditions, and obtaining N altogether when the test is completed 3 A third group of adjustment data;
s348, combining the third initial data and the third adjustment data, and adding corresponding third test conditions as labels to obtain third data;
wherein the third adjustment constraint comprises:
L≤L max
in the formula, v 2 For travelling speed, P max Is the maximum output power of the power system, mu is the friction coefficient, R is the tire radius, a 1 For acceleration of driving, T max For maximum traction, m is mass of the field car, L is load quantity, a 2 For the running deceleration, g is gravity acceleration, r is mass distribution coefficient of the field car, L max Is the maximum load of the field car.
10. A system for testing the running status of a field vehicle, wherein the system is configured to perform the method of any one of claims 1-9, the system having three-dimensional simulation software loaded therein, the system comprising:
The virtual simulation environment module is used for creating a test scene and a test environment;
the test project management module is used for setting test projects and test conditions, including a first test, a second test and a third test, and is connected with the virtual simulation environment module to adjust a test scene and a test environment;
the model construction module is used for constructing a field vehicle model according to actual structural parameters and motion parameters of the field vehicle, loading a physical engine in the field vehicle model, designing a corresponding sensor model according to specifications and performance parameters of an actual sensor required by a test project, and assembling the sensor model on a test point of the field vehicle model;
the test execution module is used for receiving a test instruction of the test project management module, testing the field car model according to the test instruction, and synchronously calling the sensor model to acquire test data so as to acquire a simulation test result;
the test result analysis module is used for receiving and analyzing the simulation test result transmitted by the test execution module, and evaluating the simulation test result according to the test index to obtain a test evaluation result of the field vehicle;
and the test display module is used for receiving the test evaluation result of the test result analysis module and performing visual display.
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| CN118565857A (en) * | 2024-07-30 | 2024-08-30 | 山东杨嘉汽车制造有限公司 | Performance detection system of low-bed semitrailer |
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