CN113962022A - Passenger experience-based intelligent cabin comfort evaluation method - Google Patents
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Abstract
The invention discloses an intelligent cabin comfort evaluation method based on passenger experience, which relates to the technical field of automobile cabins, and adopts the technical scheme that: 1) setting a first-level index for evaluating the comfort level of the intelligent cabin of the automobile, testing the automobile under three working conditions of static, constant speed and acceleration under the first-level index respectively, and obtaining the evaluation scores of passengers on the comfort levels under different first-level indexes after the test of each group of working conditions is finished; 2) obtaining a plurality of secondary evaluation factors corresponding to the primary indexes based on the primary index analysis; 3) calculating the weight scores of the first-level index and the second-level index; 4) obtaining a comfort level score of a first-level index; 5) and obtaining an expression of the intelligent cabin comfort comprehensive evaluation model according to the step 2), the step 3) and the game theory combination principle. From the specific comfort experience of passengers, the comfort of the intelligent passenger cabin is evaluated by a scientific and systematic evaluation method, and the passenger comfort evaluation values under different conditions of the intelligent passenger cabin of the automobile are predicted and simulated.
Description
Technical Field
The invention relates to the technical field of automobile cabins, in particular to an intelligent cabin comfort evaluation method based on passenger experience.
Background
At present, for the evaluation of an intelligent cabin, most of the intelligent cabins only have the objective evaluation of the whole cabin to the vehicle itself, and aim at the feeling of a specific component device, or only have the rough theoretical analysis of the cabin, and a cabin evaluation system aiming at the comfort degree of passengers of a set of system is hardly formed. Currently, the comfort evaluation of the conventional vehicle generally adopts an objective evaluation method. Since the vibration comfort is a narrow comfort, the train comfort can be measured under the condition that the requirement of the passengers is not high in the past.
The intelligent cockpit is still a relatively new concept at present. With the advent of numerous intelligent cabins, no evaluation mode for a comparison system exists for evaluating the quality of different intelligent cabins of automobiles, and therefore the difference among the intelligent cabins cannot be effectively compared.
Disclosure of Invention
The invention aims to provide an intelligent cabin comfort evaluation method based on passenger experience, so that various intelligent cabins of automobiles in the market are respectively researched, and a comprehensive comfort evaluation score is finally obtained. The evaluation result can provide directions for improving and improving the comfort of the passenger cabin and can also provide reference for automobile consumers.
The technical purpose of the invention is realized by the following technical scheme: an intelligent cabin comfort evaluation method based on passenger experience specifically comprises the following steps:
1) setting a first-level index for evaluating the comfort degree of the intelligent automobile cabin, wherein the first-level index comprises a light environment, a temperature, a noise level and a human-computer interaction environment; then, selecting 100 passengers, dividing the passengers into 25 groups, wherein each group comprises 4 passengers, each group of passengers sequentially enters the same common three-box four-seat car, controlling a primary index through a single variable, testing the cars under three working conditions of static, constant speed and acceleration respectively under the primary index, and obtaining the evaluation scores of the passengers on the comfort levels under different primary indexes after the testing of each group of working conditions is completed;
2) obtaining a plurality of secondary evaluation factors corresponding to the primary indexes based on the primary index analysis;
3) calculating the weight scores of the first-level index and the second-level index;
4) obtaining a comfort level score of a first-level index;
5) and obtaining an expression of the intelligent cabin comfort comprehensive evaluation model according to the step 2), the step 3) and the game theory combination principle.
Further, in the step 1), the method for testing the light environment index in the primary index comprises the following steps: the influence of the external light environment is eliminated, the thermal environment, the noise level and the human-computer interaction environment are controlled to be unchanged, and only the color temperature and the illumination are changed.
Further, in the step 1), the method for testing the thermal environment index in the primary index comprises the following steps: under the condition of constant external temperature, the temperature in the cabin is adjusted through the air conditioner in the vehicle.
Further, in the step 1), a method for testing a noise level index in the first-level index includes: noise environments with different frequencies and different decibels are arranged in the vehicle.
Further, the method for testing the human-computer interaction environment index of the primary index in the step 1) comprises the following steps: experience is carried out on human-computer interaction projects in different aspects in the vehicle.
Further, the specific method for calculating the first-level index and the second-level index in step 3) is to collect comfort evaluation scores in step 1), obtain objective weights through a quotient weight method based on the weight scores of different modules, obtain combined weights through a game theory, and finally obtain the weight scores of each first-level index and each second-level index.
Further, the specific method for obtaining the comfort level score in the step 4) is to perform effectiveness screening on comfort level experimental data, substitute dimensionless functions obtained from the noise and vibration environment, the light environment, the thermal environment and the human-computer interaction environment and weights of the primary evaluation index factors according to a punishment type substitution synthesis principle to obtain an expression of the intelligent cabin comfort comprehensive evaluation model, and obtain the corresponding comfort level score by taking the light environment, the temperature, the noise level and the human-computer interaction environment as independent variables.
In conclusion, the invention has the following beneficial effects: the comfort level test and the scoring are carried out on four indexes of the luminous environment, the temperature, the noise level and the human-computer interaction environment of each group of passengers through the same car, and the expression of the comprehensive evaluation model of the comfort of the intelligent passenger cabin is obtained through weight calculation, so that the effect of carrying out rigorous evaluation on the comfort of the intelligent passenger cabin is achieved, and the comfort evaluation values of passengers under different car intelligent passenger cabin conditions can be predicted and simulated.
Drawings
FIG. 1 is a flow chart of a method for evaluating comfort of an intelligent cabin based on passenger experience according to an embodiment of the present invention;
fig. 2 is a passenger comfort degree scoring index diagram of an intelligent cabin comfort degree evaluation method based on passenger experience in the embodiment of the invention.
Detailed Description
The present invention is described in further detail below with reference to fig. 1 and 2.
Example (b): an intelligent cabin comfort evaluation method based on passenger experience is disclosed, as shown in fig. 1 and fig. 2, and specifically includes the following steps:
1) setting a first-level index for evaluating the comfort degree of the intelligent automobile cabin, wherein the first-level index comprises a light environment, a temperature, a noise level and a human-computer interaction environment; then, selecting 100 passengers, dividing the passengers into 25 groups, wherein each group comprises 4 passengers, each group of passengers sequentially enters the same common three-box four-seat car, controlling a primary index through a single variable, testing the cars under three working conditions of static, constant speed and acceleration respectively under the primary index, and obtaining the evaluation scores of the passengers on the comfort levels under different primary indexes after the testing of each group of working conditions is completed;
2) obtaining a plurality of secondary evaluation factors corresponding to the primary indexes based on the primary index analysis;
3) calculating the weight scores of the first-level index and the second-level index;
combining the step 2) and the step 3) to obtain an intelligent cabin evaluation factor weight table;
intelligent cabin evaluation factor weight table
4) Obtaining a comfort level score of a first-level index;
5) and obtaining an expression of the intelligent cabin comfort comprehensive evaluation model according to the step 2), the step 3) and the game theory combination principle.
In step 5), when synthesizing the intelligent cabin comfort comprehensive evaluation model, because a plurality of evaluation factors are involved, boundary values of each evaluation value need to be considered. By combining the evaluation idea of punishment type substitution synthesis, when the comfort evaluation value of any single factor is the lowest, the evaluation value of the comprehensive comfort is also the lowest, and when the evaluation value of any one of four primary evaluation indexes, namely noise and vibration, a light environment, a thermal environment and a human-computer interaction environment, for evaluating the comfort of the intelligent cabin is 0, the evaluation result of the comprehensive comfort is 0. When y isiWhen the value is 0, the evaluation value of the comprehensive comfort degree of the intelligent cabin
Should be the minimum value, i.e. Y ═ 0. Thus, the dimensionless function of a single factor ranges from [0,10 ]]. The processing can be performed by adopting a mathematical function max, so that the evaluation value of each first-level evaluation index comfort degree after correction is in [0,10 ]]As shown in formula (5).
Yi＝max(yi，0) (5)
According to the punishment type substitution synthesis principle, dimensionless functions and weights of all primary evaluation index factors obtained by the noise and vibration environment, the luminous environment, the thermal environment and the human-computer interaction environment are substituted, and then an expression of the intelligent cabin comfort comprehensive evaluation model can be obtained, and the expression is shown in the following formula (6).
Y＝L+[max(0，y1)-L]0.2344[max(0，y2)-L]0.2079[max(0，y2)-L]0.2557[max(0，y4)-L]0.3020 (6)
In the above formula (6), L is 0.
In the step 1), the method for testing the light environment index in the primary index comprises the following steps: the influence of the external light environment is eliminated, the thermal environment, the noise level and the human-computer interaction environment are controlled to be unchanged, and only the color temperature and the illumination are changed.
In the step 1), the method for testing the thermal environment index in the first-level index comprises the following steps: under the condition of constant external temperature, the temperature in the cabin is adjusted through the air conditioner in the vehicle.
In the step 1), the method for testing the noise level index in the first-level index comprises the following steps: noise environments with different frequencies and different decibels are arranged in the vehicle.
The testing method of the human-computer interaction environment index of the primary index in the step 1) comprises the following steps: experience is carried out on human-computer interaction projects in different aspects in the vehicle.
The specific method for calculating the first-level indexes and the second-level indexes in the step 3) is to collect comfort evaluation scores in the step 1), obtain objective weights through a quotient weight method based on weight scores of different modules, obtain combined weights through a game theory, and finally obtain the weight scores of all the first-level indexes and the second-level indexes.
The specific method for obtaining the comfort level score in the step 4) is to carry out effectiveness screening on comfort level experimental data, substitute dimensionless functions and weights of primary evaluation index factors obtained from the noise and vibration environment, the luminous environment, the thermal environment and the human-computer interaction environment according to a punishment type substitution synthesis principle to obtain an expression of the intelligent cabin comfort comprehensive evaluation model, and obtain the corresponding comfort level score by taking the luminous environment, the temperature, the noise level and the human-computer interaction environment as independent variables.
Noise level environment expression:
because the automobile vibration belongs to low-frequency vibration, the selected noise level environment dimensionless function is a low-frequency constant-speed working condition linear fitting function under the experimental condition, as shown in formula (1):
y1＝-0.150N+16.795 (1)
wherein, y1Representing evaluation values of cabin noise and vibration comfort; n represents the evaluation value of noise obtained by using the a sound level as an evaluation method, and the unit is dB. The test is carried out on data with 50-90dB of noise, the 50dB sound comfort is the best, and the highest value (50dB, 9.295) is obtained;
a light environment expression:
the cabin luminous environment dimensionless function selects a quadratic function fitting function of cabin experimental data under the working conditions of 3500K color temperature and uniform speed, as shown in formula (2):
y2＝-0.000031C2+0.033C+0.597 (2)
wherein, y2Representing a cabin light environment comfort evaluation value; c represents the illuminance in the cabin, in lx. The test is carried out on data of illumination of 50-1000lx, the comfort of light is the best around 532lx, and the highest value can be obtained by drawing. Highest value (532lx, 9.379);
expression of temperature environment:
a cabin experimental data quadratic function fitting function under the constant-speed working condition is selected according to a dimensionless function of the thermal environment of the cabin, and is shown in a formula (3):
y3＝-0.054T2+2.649T-22.856 (3)
wherein, y3Representing the evaluation value of the comfort degree of the thermal environment of the cabin; t represents the in-cabin temperature in degrees C. The test is carried out by data experiment at the temperature of 17-31 ℃, the thermal comfort is the best around 24.5 ℃, and the highest value can be obtained by drawing. Maximum (24.5 ℃, 9.63);
expression of human-computer interaction environment:
selecting a fitting function of a quadratic function of the human-computer experimental data by the dimensionless function of the human-computer interaction environment of the cabin, wherein the fitting function is shown in formula (4):
y4＝-0.001P2+0.163P+1.398 (4)
wherein, y4Representing a cabin human-computer interaction environment comfort evaluation value; p represents the price of the automobile in ten thousand yuan. The test is carried out on 0-100 ten thousand man-machine data, about 81.5 ten thousand man-machine comfort is the best, and the highest value can be obtained by drawing. The highest value (81.5 ten thousand, 8.04025).
In the embodiment of the invention, the comfort level test and the scoring are carried out on four indexes of the luminous environment, the temperature, the noise level and the human-computer interaction environment of each group of passengers by the same car, and the expression of the comprehensive comfort evaluation model of the intelligent cabin is obtained through weight calculation, so that the effect of strictly evaluating the comfort of the intelligent cabin is achieved, and the comfort evaluation values of passengers under different intelligent cabin conditions of the car can be predicted and simulated.
The present embodiment is only for explaining the present invention, and it is not limited to the present invention, and those skilled in the art can make modifications of the present embodiment without inventive contribution as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present invention.
Claims (7)
1. An intelligent cabin comfort evaluation method based on passenger experience is characterized in that: the method specifically comprises the following steps:
1) setting a first-level index for evaluating the comfort degree of the intelligent automobile cabin, wherein the first-level index comprises a light environment, a temperature, a noise level and a human-computer interaction environment; then, selecting 100 passengers, dividing the passengers into 25 groups, wherein each group comprises 4 passengers, each group of passengers sequentially enters the same common three-box four-seat car, controlling a primary index through a single variable, testing the cars under three working conditions of static, constant speed and acceleration respectively under the primary index, and obtaining the evaluation scores of the passengers on the comfort levels under different primary indexes after the testing of each group of working conditions is completed;
2) obtaining a plurality of secondary evaluation factors corresponding to the primary indexes based on the primary index analysis;
3) calculating the weight scores of the first-level index and the second-level index;
4) obtaining a comfort level score of a first-level index;
5) and obtaining an expression of the intelligent cabin comfort comprehensive evaluation model according to the step 2), the step 3) and the game theory combination principle.
2. The intelligent cabin comfort evaluation method based on passenger experience according to claim 1, characterized in that: in the step 1), the method for testing the light environment index in the primary index comprises the following steps: the influence of the external light environment is eliminated, the thermal environment, the noise level and the human-computer interaction environment are controlled to be unchanged, and only the color temperature and the illumination are changed.
3. The intelligent cabin comfort evaluation method based on passenger experience according to claim 1, characterized in that: in the step 1), the method for testing the thermal environment index in the first-level index comprises the following steps: under the condition of constant external temperature, the temperature in the cabin is adjusted through the air conditioner in the vehicle.
4. The intelligent cabin comfort evaluation method based on passenger experience according to claim 1, characterized in that: in the step 1), the method for testing the noise level index in the first-level index comprises the following steps: noise environments with different frequencies and different decibels are arranged in the vehicle.
5. The intelligent cabin comfort evaluation method based on passenger experience according to claim 1, characterized in that: the testing method of the human-computer interaction environment index of the primary index in the step 1) comprises the following steps: experience is carried out on human-computer interaction projects in different aspects in the vehicle.
6. The intelligent cabin comfort evaluation method based on passenger experience according to claim 1, characterized in that: the specific method for calculating the first-level indexes and the second-level indexes in the step 3) is to collect comfort evaluation scores in the step 1), obtain objective weights through a quotient weight method based on weight scores of different modules, obtain combined weights through a game theory, and finally obtain the weight scores of all the first-level indexes and the second-level indexes.
7. The intelligent cabin comfort evaluation method based on passenger experience according to claim 1, characterized in that: the specific method for obtaining the comfort level score in the step 4) is to carry out effectiveness screening on comfort level experimental data, substitute dimensionless functions and weights of primary evaluation index factors obtained from the noise and vibration environment, the luminous environment, the thermal environment and the human-computer interaction environment according to a punishment type substitution synthesis principle to obtain an expression of the intelligent cabin comfort comprehensive evaluation model, and obtain the corresponding comfort level score by taking the luminous environment, the temperature, the noise level and the human-computer interaction environment as independent variables.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114878122A (en) * | 2022-07-12 | 2022-08-09 | 中国飞机强度研究所 | Vibration evaluation method for aircraft cabin environment test |
| CN116594858A (en) * | 2022-12-30 | 2023-08-15 | 北京津发科技股份有限公司 | Intelligent cabin man-machine interaction evaluation method and system |
| CN117934065A (en) * | 2023-11-29 | 2024-04-26 | 山东大学 | Intelligent cabin selection method and system based on multi-source information driving |
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2021
- 2021-09-30 CN CN202111159494.4A patent/CN113962022A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114878122A (en) * | 2022-07-12 | 2022-08-09 | 中国飞机强度研究所 | Vibration evaluation method for aircraft cabin environment test |
| CN114878122B (en) * | 2022-07-12 | 2022-09-13 | 中国飞机强度研究所 | Vibration evaluation method for aircraft cabin environment test |
| CN116594858A (en) * | 2022-12-30 | 2023-08-15 | 北京津发科技股份有限公司 | Intelligent cabin man-machine interaction evaluation method and system |
| CN117934065A (en) * | 2023-11-29 | 2024-04-26 | 山东大学 | Intelligent cabin selection method and system based on multi-source information driving |
| CN117934065B (en) * | 2023-11-29 | 2024-08-30 | 山东大学 | Intelligent cabin selection method and system based on multi-source information driving |
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