Performance detection method for automobile air purification filter element

Abstract

The invention relates to a method for detecting the performance of an automobile air purification filter element. The method is characterized by comprising the following steps: detecting the filtering efficiency of the filter element on particulate matters through a multi-stage particulate matter filtering efficiency test module; detecting the formaldehyde decomposition rate of the filter element through a formaldehyde decomposition rate test module; detecting the VOC removal rate of the filter element through a volatile organic compound (VOC) removal rate test module; and carrying out weighted fusion processing on the data of the particulate matter filtering efficiency, the formaldehyde decomposition rate and the VOC removal rate to generate a comprehensive purification score so as to realize quantitative evaluation on the performance of the filter element. Comprehensive evaluation on the performance of the filter element is realized through a multi-dimensional comprehensive detection system; through weighted fusion processing, misjudgment caused by a single material parameter is overcome; through the dynamic airflow simulation module, a real driving environment can be simulated, and the practicability of a detection result is improved; through performance attenuation modeling, the actual purification capacity and residual life of the filter element can be scientifically reflected, and reliable technical support is provided for filter element replacement decision and maintenance.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automobile air filter element, and particularly relates to a performance detection method of an automobile air purification filter element. BACKGROUND

[0002] The automobile air purification filter element is a core component of an automobile air purifier, filters air, and blocks or adsorbs fine dust particles.

[0003] The filtering capacity of the filter element in the automobile air purifier is generally determined according to the performance of the filter paper. There are certain differences in the actual filtering performance and the filtering performance of the filter paper itself due to different manufacturing environments and product structures in the manufacturing process, thereby causing the filter element to be overloaded or supersaturated when replaced, or the filter element to be able to filter out particles of a corresponding size. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a performance detection method of an automobile air purification filter element, which solves the problem that the actual filtering performance and the filter paper material performance deviate, and the use state and replacement timing cannot be scientifically evaluated.

[0005] To solve the above technical problems, the technical scheme of the present application is as follows: a performance detection method of an automobile air purification filter element, which is characterized by comprising the following steps: detecting the filtering efficiency of the filter element on particulate matter through a multi-stage particulate matter filtering efficiency test module; detecting the decomposition rate of the filter element on formaldehyde through a formaldehyde decomposition rate test module; detecting the removal rate of the filter element on volatile organic compounds (VOC) through a VOC removal rate test module; and performing weighted fusion processing on the data of the particulate matter filtering efficiency, the formaldehyde decomposition rate and the VOC removal rate to generate a comprehensive purification score, so as to realize quantitative evaluation of the performance of the filter element.

[0006] Further, the multi-stage particulate matter filtering efficiency test module uses a laser particle size analyzer to detect particulate matter, and the detected particulate matter particle size range is 0.3-10 μm. This particle size range covers the main types of suspended particulate matter in the air inside the automobile, and the laser particle size analyzer can realize accurate detection of particulate matter of different particle sizes, ensuring that the filtering efficiency of the filter element on various types of particulate matter is accurately evaluated.

[0007] Further, the volatile organic compound (VOC) removal rate test module uses a gas chromatograph mass spectrometer to detect VOC, and the detected VOC types include one or more of benzene series, aldehydes and ketones. This detection method can comprehensively analyze harmful gases in the air inside the automobile, improve detection accuracy, and ensure that the removal effect of the filter element on VOC is accurately evaluated.

[0008] Further, in the weighted fusion processing, the weight coefficients of the particulate matter filtration efficiency, the formaldehyde decomposition rate and the VOC removal rate are respectively , , , and satisfy , wherein .

[0009] This weighting method ensures priority consideration of particulate matter filtration efficiency, while taking into account the removal capacity of harmful substances such as formaldehyde and VOC, forming a scientific and reasonable comprehensive scoring system.

[0010] Further, a dynamic air flow simulation module is introduced to simulate the air flow rate change under real driving scenarios and record the performance decay curve of the filter element under different working conditions in real time, which is used to predict the service life of the filter element. By simulating the air volume change under different driving environments, the performance of the filter element in actual use can be more realistically reflected, and the practicality of the detection results can be improved.

[0011] Further, the performance decay curve includes the decay trend of the particulate matter filtration efficiency with time or cumulative air volume, the decline curve of the formaldehyde decomposition rate and the degradation model of the VOC removal rate. By establishing the performance decay model, the performance decline trend of the filter element during use can be quantified, providing a scientific basis for filter element replacement.

[0012] Further, a life prediction model is established based on the performance decay curve to output a filter element replacement warning signal. The model can combine the use time and cumulative processing air volume of the filter element to predict the remaining life of the filter element, and issue a warning when the performance of the filter element decreases to a critical value, improving the user experience.

[0013] Further, the dynamic air flow simulation module is configured with a feedback control system to automatically adjust the air flow rate according to the measured pressure difference to maintain constant test conditions. The system can ensure that the detection environment of the filter element remains consistent under different test conditions, improving the accuracy and repeatability of the detection data.

[0014] Further, the comprehensive purification score is a percentage score, and the scoring formula is: , wherein is the comprehensive filtration efficiency of particulate matter, is the formaldehyde decomposition rate, is the VOC removal rate, is the corresponding weight. Through the scoring formula, the various performance indicators of the filter element can be integrated into a unified numerical value, making it easier for users to intuitively understand the overall purification capacity of the filter element.

[0015] The advantages of the present application are: 1) The comprehensive evaluation of the filter performance is realized by the multi-dimensional comprehensive detection system in the application; the misjudgment caused by a single material parameter is overcome by the weighted fusion processing; the real driving environment can be simulated by the dynamic airflow simulation module, and the practicality of the detection result is improved; the actual purification capacity and the remaining life of the filter can be scientifically reflected by the performance attenuation modeling, and reliable technical support is provided for the filter replacement decision and maintenance. BRIEF DESCRIPTION OF DRAWINGS

[0016] The application will be described in further detail below with reference to the drawings and specific embodiments.

[0017] Fig. 1 It is a filter three performance detection and scoring process overview schematic diagram of the filter performance detection method of the automobile air purification filter core of the application.

[0018] Fig. 2 It is a filter core attenuation and life prediction logic schematic diagram under the dynamic airflow environment of the filter performance detection method of the automobile air purification filter core of the application.

[0019] Fig. 3 It is a feedback control guarantee test condition stability principle diagram of the filter performance detection method of the automobile air purification filter core of the application.

[0020] Fig. 4 It is a performance index scoring weight distribution schematic diagram of the filter performance detection method of the automobile air purification filter core of the application. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical scheme and advantages of the embodiments of the application clearer, the technical scheme in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are part of the embodiments of the application, rather than all the embodiments. The components of the embodiments of the application described and shown in the drawings can be arranged and designed in various different configurations.

[0022] Therefore, the detailed description of the embodiments of the application provided in the drawings below is not intended to limit the scope of the claimed application, but only represents selected embodiments of the application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the application without creative labor are within the scope of protection of the application.

[0023] As Figs. 1 to 4The automobile air purification filter element performance detection method shown comprises the following steps: detecting the filtration efficiency of the filter element on particulate matter through a multi-stage particulate matter filtration efficiency test module; detecting the decomposition rate of the filter element on formaldehyde through a formaldehyde decomposition rate test module; detecting the removal rate of the filter element on VOC through a volatile organic compound (VOC) removal rate test module; and performing weighted fusion processing on the data of the particulate matter filtration efficiency, the formaldehyde decomposition rate, and the VOC removal rate to generate a comprehensive purification score, so as to realize quantitative evaluation of the performance of the filter element.

[0024] The multi-stage particulate matter filtration efficiency test module adopts a laser particle size analyzer to detect particulate matter, and the detected particulate matter particle size interval is 0.3-10 μm. This particle size range covers the main types of suspended particulate matter in the air inside the automobile, and the laser particle size analyzer can realize accurate detection of particulate matter of different particle sizes, ensuring that the filtration efficiency of the filter element on various types of particulate matter is accurately evaluated.

[0025] The volatile organic compound (VOC) removal rate test module adopts a gas chromatograph-mass spectrometer to detect VOC, and the detected VOC types include one or more of benzene series, aldehydes, and ketones. This detection means can comprehensively analyze the harmful gases in the air inside the automobile, improve the detection accuracy, and ensure that the removal effect of the filter element on VOC is accurately evaluated.

[0026] In the weighted fusion processing, the weight coefficients of the particulate matter filtration efficiency, the formaldehyde decomposition rate, and the VOC removal rate are,, and, respectively, and satisfy,, and, wherein. This weighting method ensures that the filtration efficiency of particulate matter is given priority, while taking into account the removal ability of harmful substances such as formaldehyde and VOC, forming a scientific and reasonable comprehensive scoring system.

[0027] A dynamic air flow simulation module is introduced to simulate the air flow rate change under real driving scenarios and record the performance decay curve of the filter element under different working conditions in real time, which is used to predict the service life of the filter element. By simulating the air volume change under different driving environments, the performance of the filter element in actual use can be more realistically reflected, and the practicality of the detection results can be improved.

[0028] The performance decay curve includes the decay trend of the particulate matter filtration efficiency with time or cumulative air volume, the decline curve of the formaldehyde decomposition rate, and the degradation model of the VOC removal rate. By establishing the performance decay model, the performance decline trend of the filter element during use can be quantified, providing a scientific basis for filter element replacement.

[0029] Based on the performance decay curve, a life prediction model is established to output a filter element replacement warning signal. This model can predict the remaining life of the filter element in combination with the use time and cumulative processing air volume of the filter element, and issue a warning when the performance of the filter element decreases to a critical value, improving the user experience.

[0030] The dynamic air flow simulation module is configured with a feedback control system, which automatically adjusts the air flow rate according to the measured pressure difference to maintain constant test conditions. The system can ensure that the detection environment of the filter element remains consistent under different test conditions, improving the accuracy and repeatability of the test data.

[0031] The comprehensive purification score is a percentage score, and the score formula is: wherein is the comprehensive filtration efficiency of particulate matter, is the formaldehyde decomposition rate, is the VOC removal rate, and is the corresponding weight. Through the score formula, the various performance indicators of the filter element can be integrated into a unified numerical value, facilitating the user's intuitive understanding of the overall purification capacity of the filter element.

[0032] Embodiment 1: The present application provides a method for detecting the performance of an automobile air purification filter element, which relates to the field of air purification and is particularly suitable for the scientific detection and life management of filter elements in automobile air conditioning and air purification systems. The specific implementation process is as follows: I. Structure design and module integration The core structure of the present application is composed of the following functional modules: 1) Multi-stage particulate matter filtration efficiency test module. A high-precision laser particle size analyzer is used to collect and analyze the content of suspended particulate matter in the air before and after passing through the filter element in real time within the particle size range of 0.3-10 pm. The sampling ports of the instrument are located upstream and downstream of the filter element, respectively, and are connected with a calibrated flowmeter and a high-sensitivity sampling pump to ensure that the particulate matter test results are true and reproducible.

[0033] 2) Formaldehyde decomposition rate test module. A dedicated formaldehyde analyzer (such as electrochemical or phenol reagent spectrophotometer) is selected and connected with the exhaust pipe downstream of the filter element to detect the change in formaldehyde content in the air in real time, and the initial formaldehyde concentration upstream of the filter element is combined to automatically record and store the formaldehyde removal amount and decomposition rate.

[0034] 3) VOC removal rate test module. A gas chromatograph-mass spectrometer (GC-MS) is introduced to quantitatively analyze volatile organic compounds represented by benzene series (such as benzene, toluene, xylene), aldehydes (acetaldehyde, propyl aldehyde), and ketones (acetone, etc.), and gases are collected at both ends of the filter element inlet and outlet to determine the specific removal efficiency data.

[0035] 4) Dynamic air flow simulation and feedback control module. It includes a high-precision fan set, a differential pressure sensor, and an electronic control system, which can simulate the real air flow under different driving conditions of the automobile (such as idle speed, uniform speed, high speed, etc.), and automatically adjust the wind speed or flow rate through the feedback loop to maintain the constant pressure difference between the two ends of the filter element, ensuring the stability of the test results (see the feedback control ensures the stability of the test conditions principle diagram).

[0036] 5) Data acquisition processing and scoring module. The above-mentioned sensors and analytical instruments are uniformly managed by an industrial control computer, and the data is sent to a weighted fusion module after being processed by a digital signal processor (DSP), and finally a comprehensive purification performance score of the filter element is generated (see filter three performance detection and scoring process overview). The weight distribution of the score is shown in the performance index score weight distribution diagram (particulate matter filtration efficiency 50%, formaldehyde decomposition rate 30%, VOC removal rate 20%).

[0037] 6) Performance attenuation modeling and life prediction module. After the system automatically collects the data of the changes of the purification performance of the filter element with time or cumulative air volume (volume), it uses mathematical models (such as exponential decay, linear degradation, and piecewise function) to automatically fit the performance curves. When the predicted value is lower than the set threshold, a replacement warning is issued (see filter attenuation and life prediction logic under dynamic airflow environment).

[0038] II. Material selection and process implementation 1) Laser particle size analyzer: high-resolution type with multi-channel detector, measuring particle size covering 0.2-10 pm, sensitivity higher than 0.01 pg / m3.

[0039] 2) Formaldehyde detector: electrochemical module or phenol reagent spectrophotometry, supporting ppm-level resolution, data output with real-time curve and cumulative statistics function.

[0040] 3) GC-MS: full-automatic sampling, wide linear response range, and target substance collection tube made of anti-adsorption material (such as Tenax tube).

[0041] 4) Fan: high-efficiency brushless DC motor, flow regulation range covering 50-1000 m3 / h, capable of simulating various actual vehicle operating conditions.

[0042] 5) Differential pressure sensor: 0-1000 Pa range, resolution less than 0.5 Pa, response time less than 0.1 s.

[0043] 6) All airflow pipelines are made of PTFE or high-inertness silica gel material to avoid adsorption reaction between sample gas and pipeline wall, affecting detection accuracy.

[0044] III. Process steps and operation flow 1) Initial preparation: place the filter element to be tested in the test station sealed cavity, connect the upstream and downstream sampling ports to the dynamic airflow path, and check the normal sealing; 2) System calibration: a. Laser particle size analyzer, formaldehyde analyzer, and GC-MS perform self-calibration and zeroing operation; b. Fan and pressure difference sensor cooperate to set standard flow (such as 300 m3 / h) and standard pressure difference (such as 200 Pa).

[0045] 3) Baseline data collection: a. Send in standard particulate matter aerosol to measure the filtration efficiency of the filter core without load; b. Introduce a certain initial concentration of formaldehyde and VOC standard gas, and record the initial decomposition and removal rate.

[0046] 4) Multi-condition performance detection: a. Adjust the air volume according to the actual common working conditions of the automobile (such as low wind, medium wind, and high wind); b. Continuously collect the filtration efficiency of 0.3-10 μm classification, formaldehyde decomposition rate, and VOC removal rate under each working condition.

[0047] 5) Data weighted fusion and score formation: a. Use the scoring formula , where is the particulate matter filtration efficiency, is the formaldehyde decomposition rate, is the VOC removal rate, and the weights are 0.5, 0.3, and 0.2, respectively; b. Automatically output the percentage score and archive it.

[0048] 6) Performance attenuation and life prediction: a. The system automatically records the change of test data with cumulative air volume or time, and fits the attenuation curve of each performance (commonly used such as , is the corresponding performance index, and is the attenuation constant); b. When a certain performance or comprehensive score attenuates to the warning threshold (such as 70 points, or a certain performance is lower than the regulatory requirement), an automatic replacement prompt is issued.

[0049] c. The filter core life prediction report and historical performance change curve can be exported.

[0050] Four, Key technical details and innovation point analysis 1) Multiple detection modules in parallel and complementary, ensuring multi-dimensional scientific evaluation of filter core comprehensive performance, overcoming the evaluation error caused by filter paper parameters or single standard experiment.

[0051] 2) The scoring mechanism of data weighted fusion can flexibly adjust the weight coefficient according to the actual application requirements, suitable for differentiated management of different types of filter cores or key purification targets.

[0052] 3) Dynamic air flow and feedback control avoid parameter drift in the test process, improve the repeatability and reliability of the detection.

[0053] 4) Performance degradation modeling combined with real working conditions, life prediction results can provide scientific core replacement cycle judgment for vehicle manufacturers and users, reduce unnecessary maintenance and potential air conditioner odor health risks.

[0054] The effect of embodiment 1: through the above-mentioned comprehensive detection and life prediction method, the following remarkable effects are obtained: (1) effectively overcome the defect that the traditional filter core detection only relies on material parameters to cause the inaccuracy of purification performance evaluation, through full working condition simulation and multiple project index detection, ensure that the purification capacity truly reflects the actual environment of the automobile; (2) The weighted score percentage result of the three performances of the filter core is convenient for terminal users and automobile manufacturers to quickly read and intuitively compare the comprehensive strength of different brands, different batches, different material filter cores; (3) The life curve modeling and early warning function solves the long-term problem of when to replace the filter core, avoids the economic waste and health hazards caused by over-conservative / over-period use; (4) Feedback control dynamic pressure difference, constant air flow standard, avoids the influence of previous test results caused by accidental conditions such as temperature and humidity, filter resistance change, etc. leading to judgment error; (5) Provide targeted VOC quantitative evaluation, help new car VOC limit regulation accurate adaptation, facilitate high-end automobile air purification scheme iteration optimization; (6) The system modules are highly integrated, supporting standardized factory batch detection or pre-installation factory quality control, or providing 4S shop after-market equipment quality inspection, improving the level of service specialization. From the user experience point of view: (1) Output simple and clear purification score guide, novice users can easily understand the filter core condition; (2) Life countdown and visual curve help 4S shop or car owner to make filter replacement plan; (3) Advanced functions such as device self-calibration, self-diagnosis, data remote export, etc. reduce the operation threshold, improve the detection efficiency and accuracy; (4) The same platform can adapt to multiple specifications of vehicle models, has strong compatibility, is convenient for subsequent upgrading and expansion.

[0055] The working principle of the present application is: the present application is based on the principles of aerodynamics, filter material technology, chemical detection and automatic control, etc. The multi-stage particulate monitoring module realizes quantitative counting of dust of different particle sizes through the principle of laser light scattering. The functional relationship between light scattering intensity and particle size and particle number density can be simplified as (Mie theory approximation), so that the collection efficiency of small particles can be accurately quantified. The removal rate test of formaldehyde and VOC depends on the release signal of quantitative chemical reaction and chromatographic peak area integration respectively, and all signals are calibrated and referenced upstream to obtain accurate purification rate.

[0056] The online monitoring and pressure difference self-feedback link is based on the PID closed-loop control algorithm: the pressure difference As input, the target pressure difference Real-time comparison, after the error is generated by the controller to dynamically adjust the fan speed The adjustment rule meets To ensure that the flow and load are stable during the test of the filter element.

[0057] The comprehensive score formed after the weighted fusion of multi-dimensional data is essentially subjected to mathematical processing such as performance normalization and weighted accumulation, ensuring that the purification capacity of multiple types of pollutants such as particulate matter, formaldehyde, and VOC is comprehensively reflected in the same comparable scale. The performance decay modeling over time / air volume uses an exponential function, a linear function, or an adaptive algorithm to capture the dynamic trend of the decline in purification performance in actual use. The relevant formula is as follows: , is the performance decay rate constant. Life prediction is based on cumulative running time, cumulative air volume, and curve extrapolation theory. When , it is determined that the filter element is due for replacement, and a replacement prompt is output.

[0058] The overall working mechanism integrates particle physics (light scattering, filter medium resistance), chemical metrology (chromatographic separation and quantification of volatile organic compounds), automatic control (constant air flow and pressure difference guarantee), statistical model (multi-parameter weighted fusion), and engineering reliability theory (life prediction, early warning mechanism). The above highly integrated and innovative combination realizes the full-linkage technical closed loop of the automobile air purification filter element from material detection, efficiency scoring to dynamic life management, ensuring the scientific nature of the evaluation of the final product and the practicality of the application.

[0059] Those skilled in the art should understand that the present application is not limited to the above embodiments, and the above embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application.

Claims

1. A method for testing the performance of an automotive air purification filter, characterized in that, Includes the following steps: The filter cartridge's filtration efficiency for particulate matter is tested using a multi-stage particulate matter filtration efficiency testing module; the formaldehyde decomposition rate is tested using a formaldehyde decomposition rate testing module; and the VOC removal rate is tested using a volatile organic compound (VOC) removal rate testing module. The data on particulate matter filtration efficiency, formaldehyde decomposition rate, and VOC removal rate are weighted and fused to generate a comprehensive purification score, thereby achieving a quantitative evaluation of the filter cartridge's performance.

2. The method for testing the performance of an automotive air purification filter element according to claim 1, characterized in that, The multi-stage particulate matter filtration efficiency testing module uses a laser particle size analyzer to detect particulate matter, and the detected particulate matter size range is 0.3–10 μm.

3. The method for testing the performance of an automotive air purification filter element according to claim 1, characterized in that, The volatile organic compound (VOC) removal rate testing module uses gas chromatography-mass spectrometry (GC-MS) to detect VOCs, including one or more of benzene compounds, aldehydes, and ketones.

4. The method for testing the performance of an automotive air purification filter element according to claim 1, characterized in that, In the weighted fusion process, the weighting coefficients for particulate matter filtration efficiency, formaldehyde decomposition rate, and VOC removal rate are respectively... , , And satisfy ,in .

5. The method for testing the performance of an automotive air purification filter element according to claim 1, characterized in that, A dynamic airflow simulation module is introduced to simulate changes in airflow velocity under real driving scenarios and record the performance degradation curve of the filter element under different operating conditions in real time, which is used to predict the service life of the filter element.

6. The method for testing the performance of automotive air purification filters according to claim 5, characterized in that, The performance degradation curves include the degradation trend of particulate matter filtration efficiency over time or cumulative air volume, the decrease curve of formaldehyde decomposition rate, and the degradation model of VOC removal rate.

7. The method for testing the performance of an automotive air purification filter element according to claim 5, characterized in that: A lifespan prediction model is established based on the performance degradation curve, and a filter element replacement warning signal is output.

8. The method for testing the performance of an automotive air purification filter element according to claim 5, characterized in that, The dynamic airflow simulation module is equipped with a feedback control system that automatically adjusts the airflow rate based on the measured pressure difference to maintain constant test conditions.

9. The method for testing the performance of an automotive air purification filter element according to claim 1, characterized in that, The comprehensive purification score is based on a 100-point scale, and the scoring formula is as follows: ,in For overall particulate matter filtration efficiency, Formaldehyde decomposition rate VOC removal rate For the corresponding weights.

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