A method, device, and storage medium for predicting in-vehicle odor intensity

Abstract

The application discloses a method and device for predicting the intensity of odor in a vehicle, and a storage medium. The method comprises: obtaining a gas chromatography-olfactometry-mass spectrometry analysis result of vehicle gas, the gas chromatography-olfactometry-mass spectrometry analysis result comprising at least one odor substance in the vehicle and the concentration of the odor substance; determining the odor intensity of the odor substance according to the concentration of the odor substance; inputting the odor intensity of the at least one odor substance into a comprehensive odor intensity prediction model to obtain the odor intensity of the vehicle gas, the comprehensive odor intensity prediction model being used to predict the odor intensity of the vehicle gas by using the odor intensity of each odor substance.

Description

Technical Field

[0001] This application relates to the field of data processing technology, specifically to a method, apparatus, device, and storage medium for predicting the intensity of odors inside a vehicle. Background Technology

[0002] In-vehicle odor affects occupants' subjective experience and is a crucial indicator for evaluating passenger vehicle quality. Currently, automakers typically conduct odor intensity evaluations after new vehicles roll off the production line during the odor performance development phase. The most common evaluation method relies on subjective olfactory assessments by odor evaluators, a method directly related to their olfactory abilities. However, this method is susceptible to subjective influences (mood, environment, individual differences, etc.), lacking stability and consistency, leading to inaccurate predictions of in-vehicle odor intensity. Furthermore, odor evaluation depends on the human olfactory system, posing potential health hazards. Summary of the Invention

[0003] In view of this, embodiments of this application provide a method, apparatus, device, and storage medium for predicting the intensity of odors inside a vehicle, so as to more accurately assess the intensity of odors inside a vehicle.

[0004] To address the above problems, the technical solutions provided in this application are as follows:

[0005] In a first aspect, embodiments of this application provide a method for predicting the intensity of odors inside a vehicle, the method comprising:

[0006] The gas chromatography-olfactometry-mass spectrometry analysis results of the gas inside the vehicle are obtained, and the gas chromatography-olfactometry-mass spectrometry analysis results include at least one odor substance in the vehicle and the concentration of the odor substance.

[0007] The odor intensity of the odorant is determined based on its concentration.

[0008] The odor intensity of at least one of the odor substances is input into a comprehensive odor intensity prediction model to obtain the odor intensity of the gas inside the vehicle. The comprehensive odor intensity prediction model is used to predict the odor intensity of the gas inside the vehicle using the odor intensity of each of the odor substances.

[0009] In one possible implementation, determining the odor intensity of the odor substance based on its concentration includes:

[0010] The odor activity value of the odor substance is determined by the concentration of the odor substance and the odor threshold of the odor substance;

[0011] The odor intensity of the odor substance is determined using the Weber-Fechner law based on its odor activity value.

[0012] In one possible implementation, determining the odor intensity of the odor substance using the Weber-Fechner law based on its odor activity value includes:

[0013] Determine the odor activity value and odor intensity corresponding to different concentrations of the odorant;

[0014] Based on the odor activity values ​​and odor intensity corresponding to different concentrations of the odorant, the first and second coefficients of the Weber-Fechner law are obtained by fitting.

[0015] The odor intensity of the odor substance is determined based on its odor activity value, the first coefficient, and the second coefficient.

[0016] In one possible implementation, the integrated odor intensity prediction model is used for:

[0017] Calculate 10 to the power of x to obtain the first value, where x represents the odor intensity of each of the odor substances;

[0018] Calculate the sum of all the first values ​​to obtain the second value;

[0019] Taking the logarithm of the second value yields the odor intensity of the gas inside the vehicle.

[0020] In one possible implementation, the method further includes:

[0021] If the odor intensity of the gas inside the vehicle exceeds the odor intensity threshold, the target odor substance is determined based on the odor intensity of the odor substance.

[0022] Calculate the corrected odor intensity of the target odor substance.

[0023] In one possible implementation, calculating the corrected odor intensity of the target odor substance includes:

[0024] Calculate 10 to the power of y to obtain the third value, where y is the odor intensity threshold;

[0025] Calculate 10 to the power of z to obtain the fourth value, where z represents the odor intensity of each of the odor substances other than the target odor substance;

[0026] The sum of all the fourth values ​​is calculated to obtain the fifth value;

[0027] The corrected odor intensity of the target odor substance is obtained by subtracting the fifth value from the third value and taking the logarithm.

[0028] In one possible implementation, the method further includes:

[0029] The corrected concentration of the target odor substance is determined based on the corrected odor intensity of the target odor substance.

[0030] Secondly, embodiments of this application provide a device for predicting the intensity of odors inside a vehicle, the device comprising:

[0031] The first acquisition unit includes acquiring the gas chromatography-olfactometry-mass spectrometry analysis results of the gas inside the vehicle, wherein the gas chromatography-olfactometry-mass spectrometry analysis results include at least one odor substance inside the vehicle and the concentration of the odor substance;

[0032] The first determining unit is used to determine the odor intensity of the odor substance based on the concentration of the odor substance;

[0033] The second acquisition unit is used to input the odor intensity of at least one of the odor substances into a comprehensive odor intensity prediction model to obtain the odor intensity of the gas inside the vehicle. The comprehensive odor intensity prediction model is used to predict the odor intensity of the gas inside the vehicle using the odor intensity of each of the odor substances.

[0034] Thirdly, embodiments of this application provide a device for predicting the intensity of in-vehicle odor, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the method for predicting the intensity of in-vehicle odor as described in any of the preceding claims.

[0035] Fourthly, embodiments of this application provide a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to perform the in-vehicle odor intensity prediction method as described in any of the preceding claims.

[0036] Therefore, the embodiments of this application have the following beneficial effects:

[0037] This application first collects in-vehicle air samples and uses gas chromatography-olfactometry-mass spectrometry (GC-MS) to identify at least one odorant and its concentration. The concentration of each odorant determines its odor intensity. By inputting the odor intensities of each odorant into a comprehensive odor intensity prediction model, the overall odor intensity of the in-vehicle air can be obtained, achieving accurate determination of the mixed odor intensity of the entire vehicle. Attached Figure Description

[0038] Figure 1 A flowchart illustrating a method for predicting the intensity of in-vehicle odors provided in an embodiment of this application;

[0039] Figure 2 This is a schematic diagram of a vehicle interior odor intensity prediction device provided in an embodiment of this application. Detailed Implementation

[0040] To make the above-mentioned objectives, features and advantages of the embodiments of this application more apparent and understandable, the embodiments of this application will be further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0041] To facilitate understanding and explanation of the technical solutions provided in the embodiments of this application, the background technology of the embodiments of this application will be described first below.

[0042] The odor inside a vehicle affects people's subjective experience and is one of the important indicators for evaluating the quality of passenger vehicles. Currently, the following methods exist for evaluating in-vehicle odor:

[0043] (1) Subjective olfactory evaluation: Currently, the most common evaluation method used by automobile companies is subjective olfactory evaluation conducted by trained odor evaluators. Commonly used odor evaluation levels in the industry are shown in Table 1. This method is directly related to the olfactory evaluator's olfactory ability. However, this method is affected by the odor evaluator's subjectivity (mood, environment, individual differences, etc.), resulting in a lack of stability and consistency. Furthermore, odor evaluation relies on the human olfactory system, posing potential health hazards to the human body.

[0044] Table 1 Odor Intensity Levels

[0045] level Evaluation criteria level Evaluation criteria 1 Odorless 1.5 slight notice 2 You can feel it, and you feel comfortable. 2.5 It is clearly perceptible that there is no discomfort. 3 It is clearly perceptible that there is no interfering odor. 3.5 A slightly disturbing odor can be clearly detected. 4 There is a noticeable, unpleasant odor. 4.5 Strong, pungent odor, unpleasant. 5 Strong, pungent odor, intense discomfort 5.5 Strong, pungent odor, extremely unpleasant. 6 Unbearable, irritating, causes vomiting

[0046] (2) Electronic nose detection technology: Electronic nose is a device for odor detection. However, due to limitations in the cost of detection hardware, the accuracy of existing devices on the market is difficult to guarantee. They cannot trace the source of odors or effectively guide the rectification of odor exceeding standards. Furthermore, they increase the cost of equipment procurement. For these reasons, it is difficult for electronic noses to be widely used in the automotive industry.

[0047] (3) Odor chemistry theoretical model: This method refers to establishing a mathematical evaluation model based on the relationship between chemical substances and odors. However, this method can only assess the odor intensity of a single compound and cannot assess the overall odor intensity level of the vehicle.

[0048] Therefore, there is currently a lack of an accurate method to predict the intensity of odor in a vehicle, which means there is no effective way to guide the solution of excessive odors inside the vehicle.

[0049] Based on this, embodiments of this application provide a method, apparatus, device, and storage medium for predicting the intensity of in-vehicle odors, enabling rapid determination of the overall vehicle odor intensity and addressing the problem of existing research being unable to accurately predict the intensity of mixed odors. Furthermore, it can quickly pinpoint the direction for resolving odor exceeding standards, calculating the corrected odor intensity and concentration of substances with high odor intensity, thus efficiently guiding the resolution of in-vehicle odor exceeding standards.

[0050] See Figure 1As shown, this figure is a flowchart of a method for predicting the intensity of odor inside a vehicle according to an embodiment of this application. Figure 1 As shown, the method may include S101-S103:

[0051] S101: Obtain the gas chromatography-olfactometry-mass spectrometry analysis results of the gas inside the vehicle. The gas chromatography-olfactometry-mass spectrometry analysis results include at least one odorant in the vehicle and the concentration of the odorant.

[0052] The gas inside the vehicle is collected, and gas chromatography-olfactometry (GC-O-MS) is used to detect at least one odorant substance and quantify its concentration. The detected odorant substance can be a key odorant; for example, specific odorants can be pre-specified for detection, or odorants with concentrations exceeding a concentration threshold can be detected. Odorants can be odor compounds such as acetic acid, ethyl acetate, and toluene. In practical applications, dedicated instruments can be used to obtain the GC-O-MS analysis results of the gas inside the vehicle. In this embodiment, to predict the intensity of odors inside the vehicle, the GC-O-MS analysis results of the gas inside the vehicle can be obtained first.

[0053] S102: Determine the odor intensity of the odor substance based on its concentration.

[0054] The Weber-Fechner law can be used to calculate the odor intensity of a substance based on its concentration. This law, a psychophysical principle, is applied to the quantitative evaluation of odor perception, converting the concentration of an odor substance into odor intensity (OI).

[0055] For details on the specific implementation of S102, please refer to the description of the subsequent embodiments, which will not be repeated here.

[0056] S103: Input the odor intensity of at least one odorant into the comprehensive odor intensity prediction model to obtain the odor intensity of the gas inside the vehicle. The comprehensive odor intensity prediction model is used to predict the odor intensity of the gas inside the vehicle using the odor intensity of each odorant.

[0057] By substituting the odor intensity (OI) of the identified odor substances into the comprehensive odor intensity prediction model, the overall odor intensity (SOI) of the vehicle interior can be calculated. The comprehensive odor intensity prediction model is a model that predicts the odor intensity of a mixture from the odor intensities of multiple compounds, thereby deriving the odor intensity of the gas inside the vehicle. Its specific implementation can be found in the description of subsequent embodiments, and will not be elaborated upon here.

[0058] This application first collects in-vehicle air samples and uses gas chromatography-olfactometry-mass spectrometry (GC-MS) to identify at least one odorant and its concentration. The concentration of each odorant determines its odor intensity. By inputting the odor intensities of each odorant into a comprehensive odor intensity prediction model, the overall odor intensity of the in-vehicle air can be obtained, achieving accurate determination of the mixed odor intensity of the entire vehicle.

[0059] The specific implementations of S102 and S103 will be further explained below.

[0060] In one possible implementation, the specific implementation of S102, which determines the odor intensity of an odorant based on its concentration, may include:

[0061] A1: The odor activity value of an odor substance is determined by its concentration and odor threshold.

[0062] Odor Activity Value (OAV) is a parameter that characterizes the intensity of a compound's odor. It determines whether a compound produces an odor and the intensity of that odor by comparing the compound's concentration with the odor threshold.

[0063] The formulas for calculating the odor activity value of odor substances include: Among them, C i The concentration of odorant i (compound i) is expressed in μg / m³. 3 (micrograms per cubic meter); C Ti The odor threshold (i.e., odor threshold concentration) is the concentration of odorant i (compound i), expressed in μg / m³. 3 (micrograms per cubic meter); OAV i Let i be the odor activity value of odor substance i (compound i); odor substance i (compound i) is the i-th odor substance detected, where i is an integer from 1 to n, and n is the total number of odor substances detected in the gas chromatography-olfaction-mass spectrometry analysis results.

[0064] When OAV < 1, theoretically, the average person cannot perceive the odor produced by the compound. When OAV ≥ 1, the compound produces an odor that can be recognized by people at that concentration.

[0065] A2: Based on the odor activity value of the odor substance, the odor intensity of the odor substance is determined using the Weber-Fechner law.

[0066] The formula for the Weber-Fechner law includes: OI i =a i logOAV i +b i Among them, OI i Let a be the odor intensity of odor substance i (compound i). i b is the first coefficient of odorant i (compound i). i a is the second coefficient of odor substance i (compound i). i and b i Let OAV be a constant. Then, the odor activity value (OAV) of odor substance i (compound i) will be... i Substituting into the formula of the Weber-Fechner law, we can obtain the odor intensity OI of odor substance i (compound i). i .

[0067] In this embodiment of the application, the Weber-Fechner law can be used to accurately calculate the odor intensity of each odor substance included in the gas inside the vehicle, so as to achieve accurate prediction of the odor intensity of the gas inside the vehicle.

[0068] In one possible implementation, A2 determines the odor intensity of an odor substance based on its odor activity value using the Weber-Fechner law. This determination can include:

[0069] B1: Determine the odor activity value and odor intensity corresponding to different concentrations of odor substances.

[0070] In practical applications, the first coefficient α in the Weber-Fechner law... i and the second coefficient b i The first coefficient 'a' can be determined for each odor substance based on its specific characteristics. i Second coefficient b i .

[0071] Then, by preparing solutions of odorant i (compound i) at different concentrations C, the odor activity value of the odorant is calculated using the formula... It is possible to calculate the odor activity value of odor substance i (compound i) at different concentrations, and also to obtain the odor intensity of solutions of odor substance i (compound i) at different concentrations.

[0072] B2: Based on the odor activity value and odor intensity corresponding to different concentrations of odor substances, the first and second coefficients of the Weber-Fechner law are obtained by fitting.

[0073] Substituting the odor activity values ​​and odor intensities corresponding to different concentrations of odorant i (compound i) into the formula of the Weber-Fechner law, we can obtain the first coefficient 'a' corresponding to odorant i (compound i). i and the second coefficient b i In addition, in practical applications, data from relevant databases can be consulted to directly obtain the first coefficient 'a' corresponding to odor substance i (compound i). i and the second coefficient b i .

[0074] It is understood that the first and second coefficients corresponding to the odor substance can be predetermined before determining the odor intensity. This application does not impose limitations on the execution time and order of fitting the first and second coefficients.

[0075] B3: Determine the odor intensity of an odor substance based on its odor activity value, first coefficient, and second coefficient.

[0076] Finally, the odor activity value (OAV) of odor substance i (compound i) obtained in step A1 is calculated. i The first coefficient a corresponding to the odor substance i (compound i) obtained in step B2. i and the second coefficient b i Substituting this into the Weber-Fechner law formula, we can obtain the odor intensity OI of odor substance i (compound i). i .

[0077] In the embodiments of this application, the first coefficient and the second coefficient corresponding to each odor substance are obtained by fitting, which can make the determination of the odor intensity of the odor substance using the Weber-Fechner law more accurate.

[0078] In one possible implementation, the integrated odor intensity prediction model in S103 can be used for:

[0079] Calculate 10 to the power of x to obtain the first value, where x represents the odor intensity of each odor substance; calculate the sum of the first values ​​to obtain the second value; take the logarithm of the second value to obtain the odor intensity of the gas inside the vehicle.

[0080] The formulas for the comprehensive odor intensity prediction model include: Among them, OI i For each odor substance (compound i), the odor intensity is calculated separately. We obtain the first value. We then sum the sums of all the first values ​​to obtain... This is the second value. Final calculation. The odor intensity (SOI) of the gas inside the vehicle is obtained.

[0081] In this embodiment, a comprehensive odor intensity prediction model is used to calculate the overall odor intensity of the in-vehicle mixture. This solves the technical problem in the prior art that can only calculate the odor intensity of a single compound and cannot predict the odor intensity of the entire vehicle mixture.

[0082] Furthermore, existing technologies suffer from the following technical problems: if in-vehicle odor levels exceed standards, a step-by-step odor source tracing process is required, which is time-consuming and costly, and may make it difficult to pinpoint the cause of the exceedance, thus hindering the determination of rectification direction and objectives. Therefore, the industry currently lacks an efficient solution to the problem of excessive in-vehicle odor intensity. Based on this, the embodiments of this application can quickly identify the solution direction for the problem of excessive odor, calculate the target design odor intensity and concentration of high-odor substances, and efficiently guide the resolution of the problem of excessive in-vehicle odor.

[0083] In one possible implementation, the method for predicting the intensity of in-vehicle odor provided in this application embodiment may further include:

[0084] C1: If the odor intensity of the gas inside the vehicle exceeds the odor intensity threshold, the target odor substance is determined based on the odor intensity of the odor substance.

[0085] If the odor intensity inside the vehicle exceeds the odor intensity limit (i.e., odor intensity threshold), then the target odor substance with the highest odor intensity is determined based on the odor intensity of each odor substance. The target odor substance is the core substance causing the odor intensity to exceed the limit, and it is the object to be optimized. There can be one or more target odor substances. For example, the odor intensities of each odor substance can be sorted from high to low, and the odor substance with the highest ranking or the ranking within a preset range can be determined as the target odor substance.

[0086] C2: Calculate the corrected odor intensity of the target odor substance.

[0087] By decomposing the odor intensity threshold, the corrected odor intensity of the target odor substance is calculated. That is, when the odor intensity of the target odor substance is less than or equal to the corrected odor intensity, the odor intensity of the gas inside the vehicle will not exceed the odor intensity threshold. For example, if the odor intensity of odor substance m is 3.5, and the calculated corrected odor intensity of odor substance m is 3.0, then when the odor intensity of odor substance m is 3.0, the odor intensity of the gas inside the vehicle will not exceed the odor intensity threshold, thus meeting the restriction requirements.

[0088] In the embodiments of this application, by identifying the target odor substance and the corresponding corrected odor intensity, the direction for solving the problem of excessive odor can be quickly identified.

[0089] In one possible implementation, the specific implementation of C2 calculation of the corrected odor intensity of the target odor substance may include:

[0090] D1: Calculate 10 to the power of y to obtain the third value, where y is the odor intensity threshold.

[0091] D2: Calculate 10 to the power of z to obtain the fourth value, where z represents the odor intensity of each odor substance other than the target odor substance.

[0092] D3: Calculate the sum of all the fourth values ​​to obtain the fifth value.

[0093] D4: Subtract the fifth value from the third value and take the logarithm to obtain the corrected odor intensity of the target odor substance.

[0094] Perform inverse calculation on the formula of the comprehensive odor intensity prediction model Assuming that the highest SOI is the odor intensity threshold, the odor intensity of the target odor substance is deduced as the corrected odor intensity while keeping the odor intensities of other odor substances constant.

[0095] The formulas for calculating the corrected odor intensity of a target odor substance include: Among them, SOI Q Calculate the odor intensity threshold. The third value is obtained.

[0096] Assuming the target odor substance is the m-th odor substance, calculate the following for each odor substance other than the m-th odor substance: Even using the odor intensity OI of the 1st to the (m-1)th and (m+1)th to the nth odor substances. i Calculate separately The fourth value is obtained.

[0097] Recalculate That is, summing up each of the fourth values ​​yields the fifth value.

[0098] Subtracting the fifth value from the third value and taking the logarithm yields the corrected odor intensity (OI) of the target odor substance. ′ m .

[0099] In this embodiment of the application, by performing reverse calculation on the comprehensive odor intensity prediction model, the corrected odor intensity of the target odor substance can be accurately obtained in order to ensure that the odor intensity of the gas inside the vehicle does not exceed the odor emphasis threshold, thus efficiently guiding the solution of the problem of excessive odor inside the vehicle.

[0100] One possible implementation may also include:

[0101] C3: Determine the corrected concentration of the target odor substance based on the corrected odor intensity of the target odor substance.

[0102] After determining the corrected odor intensity of the target odor substance, the Weber-Fechner law OI can also be used. i =a i logOAV i +b i The corrected odor activity value of the target odor substance is obtained. Then, the formula for calculating the odor activity value of the odor substance is used. The corrected concentration of the target odor substance is then deduced.

[0103] Finally, optimization and control were implemented in terms of materials, processes, and warehousing to reduce the target odor substance to a corrected concentration, ensuring that the odor intensity inside the vehicle met the limit requirements. The corrected concentration of the target odor substance was calculated in reverse, quickly providing a solution to the problem of excessive odor intensity in the entire vehicle.

[0104] The following describes the method for predicting the intensity of in-vehicle odors provided in this application embodiment, with specific examples.

[0105] A vehicle of a certain brand was selected for high-temperature sealed sampling. After sampling the gas inside the vehicle, GC-O-MS analysis was performed. The identified odor substances (key odor compounds) are shown in Table 2.

[0106] Table 2 Examples of key odor compounds in a car interior

[0107] Odor compounds molecular weight Odor type <![CDATA[Concentration (μg / m 3 )]]> <![CDATA[Odor threshold value (μg / m 3 )]]> Odor activity value Odor intensity Acetic acid 60 sour 57 16 3.52 2.5 Ethyl acetate 88 Fruity aroma 3418 3420 1.00 1.8 Toluene 92 Aromatic hydrocarbon flavor 443 369 1.20 1.2 phenol 94 rubber smell 20 24 0.84 3.6 Hexanal 100 grassy flavor 71 71 1.00 2.8 xylene 106 Tar smell 550 2200 0.25 1.6 Nononal 142 Greasey smell 24 20 1.19 3.0 Undecane 156 solvent smell 5600 5600 1.00 1.8

[0108] Based on the odor threshold, the corresponding odor activity value can be calculated. Substituting this value into the Weber-Fechner law, the odor intensity of each odor substance can be calculated. Then, using the odor intensity prediction model, the SOI (Solar Odor Indication) of the in-vehicle gas is calculated to be 3.8. The odor intensity exceeds the odor intensity threshold of 3.5. Reviewing the odor intensities of individual odor substances, phenol, with an odor level of 3.6, is found to contribute the most to the overall odor intensity of the in-vehicle gas, thus being identified as the core substance causing the excessive odor. Through index decomposition calculations, when the corrected odor intensity of phenol is 3.1, the overall vehicle odor intensity is 3.5, meeting the limit requirements. The corrected concentration of phenol can also be calculated to be 8 μg / m³. 3The rectification goal is to reduce the concentration of phenol in the vehicle to 8 μg / m³. 3 It can predict the odor intensity of gases inside a vehicle, and when the odor intensity exceeds the standard, it can quickly locate the core substance causing the excessive odor and calculate the corrected concentration of the odor substance to provide a solution for the excessive odor.

[0109] Based on the method embodiment provided above for predicting the intensity of odor inside a vehicle, this application embodiment also provides a device for predicting the intensity of odor inside a vehicle, which will be described below with reference to the accompanying drawings.

[0110] See Figure 2 As shown, this figure is a structural schematic diagram of a vehicle interior odor intensity prediction device provided in an embodiment of this application. Figure 2 As shown, the in-vehicle odor intensity prediction device includes:

[0111] The first acquisition unit 201 includes acquiring the gas chromatography-olfactometry-mass spectrometry analysis results of the gas inside the vehicle, wherein the gas chromatography-olfactometry-mass spectrometry analysis results include at least one odor substance inside the vehicle and the concentration of the odor substance;

[0112] The first determining unit 202 is used to determine the odor intensity of the odor substance based on the concentration of the odor substance;

[0113] The second acquisition unit 203 is used to input the odor intensity of at least one of the odor substances into a comprehensive odor intensity prediction model to obtain the odor intensity of the gas inside the vehicle. The comprehensive odor intensity prediction model is used to predict the odor intensity of the gas inside the vehicle using the odor intensity of each of the odor substances.

[0114] In one possible implementation, the first determining unit includes:

[0115] The first determining subunit is used to determine the odor activity value of the odor substance based on the concentration of the odor substance and the odor threshold of the odor substance.

[0116] The second determining subunit is used to determine the odor intensity of the odor substance based on its odor activity value using the Weber-Fechner law.

[0117] In one possible implementation, the second determining subunit includes:

[0118] The third determining subunit is used to determine the odor activity value and odor intensity corresponding to different concentrations of the odor substance;

[0119] The fitting unit is used to fit the first and second coefficients of the Weber-Fechner law based on the odor activity value and odor intensity corresponding to different concentrations of the odor substance.

[0120] The fourth determining subunit is used to determine the odor intensity of the odor substance based on the odor activity value of the odor substance, the first coefficient, and the second coefficient.

[0121] In one possible implementation, the integrated odor intensity prediction model is used for:

[0122] Calculate 10 to the power of x to obtain the first value, where x represents the odor intensity of each of the odor substances;

[0123] Calculate the sum of all the first values ​​to obtain the second value;

[0124] Taking the logarithm of the second value yields the odor intensity of the gas inside the vehicle.

[0125] In one possible implementation, the device further includes:

[0126] The second determining unit is used to determine the target odor substance based on the odor intensity of the odor substance if the odor intensity of the gas inside the vehicle exceeds the odor intensity threshold.

[0127] The calculation unit is used to calculate the corrected odor intensity of the target odor substance.

[0128] In one possible implementation, the computing unit is specifically used for:

[0129] Calculate 10 to the power of y to obtain the third value, where y is the odor intensity threshold;

[0130] Calculate 10 to the power of z to obtain the fourth value, where z represents the odor intensity of each of the odor substances other than the target odor substance;

[0131] The sum of all the fourth values ​​is calculated to obtain the fifth value;

[0132] The corrected odor intensity of the target odor substance is obtained by subtracting the fifth value from the third value and taking the logarithm.

[0133] In one possible implementation, the device further includes:

[0134] The third determining unit is used to determine the corrected concentration of the target odor substance based on the corrected odor intensity of the target odor substance.

[0135] In addition, this application embodiment also provides a vehicle interior odor intensity prediction device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the vehicle interior odor intensity prediction method as described in any of the above claims.

[0136] This application also provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to perform the in-vehicle odor intensity prediction method as described in any of the preceding embodiments.

[0137] This application also provides a computer program product, including computer program instructions that, when executed on a computer, cause the computer to perform the method for predicting the intensity of in-vehicle odor as described in any of the preceding embodiments.

[0138] This application first collects in-vehicle air samples and uses gas chromatography-olfactometry-mass spectrometry (GC-MS) to identify at least one odorant and its concentration. The concentration of each odorant determines its odor intensity. By inputting the odor intensities of each odorant into a comprehensive odor intensity prediction model, the overall odor intensity of the in-vehicle air can be obtained, achieving accurate determination of the mixed odor intensity of the entire vehicle.

[0139] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems or apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and relevant parts can be referred to the method section.

[0140] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0141] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0142] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0143] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for predicting the intensity of odor inside a vehicle, characterized in that, The method includes: The gas chromatography-olfactometry-mass spectrometry analysis results of the gas inside the vehicle are obtained, and the gas chromatography-olfactometry-mass spectrometry analysis results include at least one odor substance in the vehicle and the concentration of the odor substance. The odor intensity of the odorant is determined based on its concentration. The odor intensity of at least one of the odor substances is input into a comprehensive odor intensity prediction model to obtain the odor intensity of the gas inside the vehicle. The comprehensive odor intensity prediction model is used to predict the odor intensity of the gas inside the vehicle using the odor intensity of each of the odor substances.

2. The method according to claim 1, characterized in that, Determining the odor intensity of the odorant based on its concentration includes: The odor activity value of the odor substance is determined by the concentration of the odor substance and the odor threshold of the odor substance; The odor intensity of the odor substance is determined using the Weber-Fechner law based on its odor activity value.

3. The method according to claim 2, characterized in that, The step of determining the odor intensity of the odor substance using the Weber-Fechner law based on the odor activity value of the odor substance includes: Determine the odor activity value and odor intensity corresponding to different concentrations of the odorant; Based on the odor activity values ​​and odor intensity corresponding to different concentrations of the odorant, the first and second coefficients of the Weber-Fechner law are obtained by fitting. The odor intensity of the odor substance is determined based on its odor activity value, the first coefficient, and the second coefficient.

4. The method according to any one of claims 1-3, characterized in that, The comprehensive odor intensity prediction model is used for: Calculate 10 to the power of x to obtain the first value, where x represents the odor intensity of each of the odor substances; Calculate the sum of all the first values ​​to obtain the second value; Taking the logarithm of the second value yields the odor intensity of the gas inside the vehicle.

5. The method according to any one of claims 1-4, characterized in that, The method further includes: If the odor intensity of the gas inside the vehicle exceeds the odor intensity threshold, the target odor substance is determined based on the odor intensity of the odor substance. Calculate the corrected odor intensity of the target odor substance.

6. The method according to claim 5, characterized in that, The calculation of the corrected odor intensity of the target odor substance includes: Calculate 10 to the power of y to obtain the third value, where y is the odor intensity threshold; Calculate 10 to the power of z to obtain the fourth value, where z represents the odor intensity of each of the odor substances other than the target odor substance; The sum of all the fourth values ​​is calculated to obtain the fifth value; The corrected odor intensity of the target odor substance is obtained by subtracting the fifth value from the third value and taking the logarithm.

7. The method according to claim 5, characterized in that, The method further includes: The corrected concentration of the target odor substance is determined based on the corrected odor intensity of the target odor substance.

8. A device for predicting the intensity of odors inside a vehicle, characterized in that, The device includes: The first acquisition unit includes acquiring the gas chromatography-olfactometry-mass spectrometry analysis results of the gas inside the vehicle, wherein the gas chromatography-olfactometry-mass spectrometry analysis results include at least one odor substance inside the vehicle and the concentration of the odor substance; The first determining unit is used to determine the odor intensity of the odor substance based on the concentration of the odor substance; The second acquisition unit is used to input the odor intensity of at least one of the odor substances into a comprehensive odor intensity prediction model to obtain the odor intensity of the gas inside the vehicle. The comprehensive odor intensity prediction model is used to predict the odor intensity of the gas inside the vehicle using the odor intensity of each of the odor substances.

9. A device for predicting the intensity of odors inside a vehicle, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method for predicting the intensity of in-vehicle odor as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform the method for predicting the intensity of in-vehicle odor as described in any one of claims 1-7.

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