A photothermal comprehensive performance test and evaluation system and method for an automobile window film

Abstract

The application relates to the field of optical material performance testing, and specifically discloses a light-heat comprehensive performance test and evaluation system and method for an automobile window film, which comprises the following steps: under the action of dynamic multi-field coupling, collecting transient polarization spectrum data, and constructing a multi-field coupling spectrum feature set; tracking a thermal absorption peak drift trajectory based on the multi-field coupling spectrum feature set, extracting a thermal red shift mutation temperature and a thermal response inertia index; simultaneously applying a pulse laser matching a sample polarization state, collecting near-field thermal radiation intensity and tracking plasma resonance thermal frequency shift, and extracting a transient response feature vector; measuring an irreversible red shift amount after cooling, calculating an entropy production rate and an irreversible degradation index, generating a light-heat comprehensive durability coefficient, and outputting service life prediction and climate adaptation grade. The application realizes multi-field coupling dynamic evaluation, reversible / irreversible damage separation and entropy production theory quantitative durability, and provides a scientific basis for long-term stability evaluation of the window film.

Description

Technical Field

[0001] This invention relates to the field of optical material performance testing technology, specifically to a system and method for testing and evaluating the comprehensive photothermal performance of automotive window films. Background Technology

[0002] As a multi-layered composite functional material integrating spectral selectivity control and thermal management, automotive window film's actual service performance directly determines driving comfort and energy consumption levels. Existing window film photothermal performance testing technologies are mainly based on steady-state spectral transmittance measurement and static heat insulation rate testing. In a standard laboratory environment, spectrophotometers and infrared thermal imaging equipment are used to acquire optical transmittance characteristics and steady-state thermal resistance data within specific wavelength ranges.

[0003] However, existing technologies have fundamental flaws: First, existing testing methods mostly use fixed geometric shapes and static environmental parameters, failing to simulate the dynamic thermal-humidity-mechanical multi-field coupling effects experienced by automotive window films after actual installation. In actual use, automotive window films are bonded to curved glass. During vehicle operation, vehicle vibration and temperature changes cause the glass surface to dynamically transform between convex and concave curvatures. At the same time, the thermal cycling and condensation-evaporation processes caused by the diurnal temperature difference cause the polymer substrate and functional coating of the window film to experience periodic expansion-contraction stress. This multi-field coupling effect can lead to microcracks in the functional layer, interface debonding, and irreversible degradation of optical performance. Existing static tests are completely unable to identify such service damage mechanisms.

[0004] Second, current technologies lack effective means to separate reversible thermal responses from irreversible structural damage. Window films exhibit a thermally induced redshift of the absorption peak under transient illumination excitation. This phenomenon is partly due to thermal modulation of the material's electronic band structure and partly due to the proliferation of lattice defects caused by accumulated thermal stress. Existing testing methods only record steady-state spectral data and cannot distinguish between the reversible and irreversible components of the redshift, making it impossible to accurately assess the actual service life of the window film.

[0005] Third, existing far-field thermal imaging technologies can only acquire the macroscopic temperature distribution on the surface of the window film, and cannot detect near-field evanescent wave thermal radiation and surface plasmon thermal frequency shift. In reality, there are nanoscale micro-gaps at the interface between the window film and the glass. The near-field heat transfer modes within these gaps significantly contribute to the thermal insulation performance. Furthermore, the real-time frequency shift of the surface plasmon resonance peak position of the metal oxide functional layer with increasing temperature directly reflects the carrier-phonon coupling strength and thermal response inertia. Existing far-field detection methods cannot obtain these microscopic physical parameters.

[0006] Fourth, existing evaluation methods do not incorporate non-equilibrium thermodynamics to quantify entropy production and irreversible degradation during photothermal conversion. Window films experience continuous energy dissipation and structural damage during dynamic service. Traditional steady-state thermal resistance evaluations cannot characterize this time-accumulated irreversible degradation trend, leading to a significant deviation between product classification and actual service life.

[0007] To address the aforementioned technical deficiencies, there is an urgent need for a comprehensive performance testing and evaluation method that can simulate dynamic thermal-humidity-mechanical multi-field coupling environments, separate reversible / irreversible damage mechanisms, detect near-field thermal radiation and plasma thermal frequency shift, and predict lifetime based on non-equilibrium entropy production theory. This method would enable accurate performance grading and reliability assessment of window film products under real service conditions. Summary of the Invention

[0008] The purpose of this invention is to provide a comprehensive photothermal performance testing and evaluation system and method for automotive window films, in order to solve the technical problem that existing testing methods only measure static instantaneous performance and ignore the thermal spectral drift and irreversible damage caused by multi-field coupling in real service scenarios.

[0009] To solve the above-mentioned technical problems, the present invention specifically provides the following technical solution: A method for testing and evaluating the comprehensive photothermal performance of automotive window film includes the following steps: S1. Under the dynamic thermal-humidity-mechanical multi-field coupling, the transient polarization spectrum data of the window film under test are collected, and the multi-field coupled spectral feature set is constructed. S2. Based on the multi-field coupled spectral feature set, track the thermal absorption peak drift trajectory, extract the thermal redshift abrupt change temperature and thermal response inertia index; simultaneously apply a pulsed laser matching the polarization state of the sample, collect the near-field thermal radiation intensity and track the plasma resonance thermal frequency shift, and extract the transient response feature vector; S3. After cooling, measure the irreversible redshift, calculate the entropy production rate and irreversible degradation index, and combine the thermally induced redshift abrupt change temperature, thermal response inertia index, irreversible redshift, and phase delay time to generate a photothermal integrated durability coefficient, outputting service life prediction and climate adaptability level.

[0010] As a preferred embodiment of the present invention, S1 specifically includes: S11. The window film sample to be tested is attached to the bidirectional curvature adjustment device of the controllable multi-field coupling test bench. The bidirectional curvature adjustment device cycles between convex curvature state and concave curvature state at a preset frequency to simulate the dynamic deformation of the glass surface when the actual vehicle is driving. S12. During the dynamic deformation process, a programmed temperature-controlled thermal cycling excitation and a pulsed humidity excitation are applied to the sample surface; S13. During the establishment of the dynamic thermal-humidity-mechanical multi-field coupling effect, multiple characteristic wavelengths are selected in the near-infrared band through the full Stokes polarization spectroscopy acquisition system, and transient polarization spectral data of the sample polarization state evolution over time are obtained at a set sampling interval. S14. Simultaneously record the real-time curvature radius data of the bidirectional curvature adjustment device, the real-time temperature data of thermal cycling excitation, and the real-time relative humidity data of pulse humidity excitation to construct a transient polarization spectral evolution feature set characterizing the mapping relationship between multi-field coupling parameters and polarization state evolution law.

[0011] As a preferred embodiment of the present invention, S12 specifically includes: S121. Place the bidirectional curvature adjustment device with the sample to be tested attached inside the controllable environment chamber, and apply periodic thermal cycling excitation to the sample surface through the program temperature control system. The heating rate and cooling rate of the thermal cycling excitation are independently adjustable. A single thermal cycle includes a complete process from heating from the initial temperature to the highest temperature, holding the temperature, and then cooling back to the initial temperature to simulate the diurnal temperature difference and the exposure-cooling cycle process. S122. While the thermal cycling excitation is running, a pulsed humidity excitation asynchronous with the thermal cycling cycle is applied to the sample surface through a pulsed humidification system. The humidity variation range of the pulsed humidity excitation covers a wide range from low humidity to high humidity. A single humidity pulse cycle includes a rapid humidification stage, a high humidity holding stage, and a rapid dehumidification stage to simulate the condensation-evaporation process in the real environment. S123. The asynchronous setting of the thermal cycling excitation and the pulsed humidity excitation includes making the ratio of the thermal cycling period to the humidity pulse period not an integer, or making there a fixed or random time offset between the phase of the thermal cycling and the phase of the humidity pulse, so as to simulate the natural state where temperature changes and condensation-evaporation processes are not synchronized in the real environment.

[0012] As a preferred embodiment of the present invention, S2 specifically includes: S21. Based on the transient polarization spectral evolution feature set, track the real-time drift trajectory of the characteristic absorption peak position at different temperature points, mark the temperature points where the drift rate changes significantly as thermally induced redshift abrupt change temperatures, and calculate the thermal response inertia index at the same time. S22. Transfer the sample that has completed the multi-field coupling test to the near-field photothermal test cavity. According to the polarization state evolution law of the feature set, adjust the incident polarization state of the tunable pulsed laser source to match the intrinsic polarization sensitive axis of the sample at the current temperature. Under the matching condition, apply transient pulsed photothermal excitation that matches the plasma resonance energy level on the surface of the metal oxide layer with photon energy. S23. Using a scanning near-field thermal radiation probe array, time-series data of evanescent thermal radiation intensity evolving over time are collected in the nanoscale air gaps on the sample surface, and real-time thermal frequency shift data of surface plasmon resonance caused by the accumulation of hot carriers are simultaneously tracked. S24. Perform phase coupling analysis on the evanescent wave thermal radiation intensity time series data and the surface plasmon resonance real-time thermal frequency shift data, and extract the phase relationship features between the two as transient response feature vectors.

[0013] As a preferred embodiment of the present invention, S21 specifically includes: S211. Based on the transient polarization spectral evolution feature set, select the characteristic absorption band of the window film to be tested in the near-infrared band, extract the characteristic absorption peak position in the band at different temperature points, and construct the real-time drift trajectory of the characteristic absorption peak position as the temperature changes. S212. After smoothing the real-time drift trajectory to remove noise interference, calculate its first derivative as the instantaneous redshift rate curve, and then calculate the second derivative to identify the rate of change of the redshift rate. S213. The temperature point at which the absolute value of the second derivative first exceeds a preset threshold is marked as the thermally induced redshift abrupt change temperature. The preset threshold is determined based on a reference sample without thermally induced drift. The physical meaning of the thermally induced redshift abrupt change temperature is the critical temperature point at which the window film begins to undergo significant thermally induced spectral drift. S214. Simultaneously, the absolute value of the instantaneous redshift rate over the entire temperature range is integrated to obtain the thermal response inertia index. The integration interval covers the entire heating process from the initial temperature to the preset maximum temperature. The magnitude of the thermal response inertia index characterizes the intensity of the window film's overall response to temperature changes. The larger the value, the more drastic the change in the absorption peak position of the window film during the heating process, and the worse the thermal stability.

[0014] As a preferred embodiment of the present invention, S24 specifically includes: S241. Perform time axis alignment preprocessing on the evanescent wave thermal radiation intensity time series data and the surface plasma resonance real-time thermal frequency shift data to eliminate the time delay introduced by the difference in data acquisition channels; S242. The two sets of time-series data after alignment are subjected to Fourier transform and converted to the frequency domain space. The phase angle information of the evanescent wave thermal radiation intensity spectrum and thermal frequency shift spectrum at the characteristic frequency is extracted. The characteristic frequency corresponds to the fundamental frequency and harmonic components of the transient pulsed photothermal excitation. S243. Calculate the phase difference between the evanescent wave thermal radiation intensity spectrum and the thermal shift spectrum at the characteristic frequency. The phase difference characterizes the time lag relationship between the near-field thermal radiation response and the plasma resonance thermal shift response. Simultaneously, calculate the coherence coefficient of the two sets of time series data in the characteristic frequency band. The coherence coefficient ranges from 0 to 1, characterizing the linear correlation between near-field thermal radiation and plasma resonance thermal shift. Combine the phase difference and the coherence coefficient to construct a two-dimensional transient response feature vector. This feature vector quantifies the intensity and phase relationship of the near-field thermal radiation-plasma-temperature three-field coupling effect of the window film under dynamic thermal-humidity-mechanical multi-field coupling.

[0015] As a preferred embodiment of the present invention, S3 specifically includes: S31. The window film to be tested is naturally cooled from the preset maximum temperature back to the initial temperature. The acquisition system obtains the recovered absorption spectrum after cooling, extracts the characteristic absorption peak position after recovery, and calculates the irreversible redshift. S32. Based on the transient polarization spectral evolution feature set, transient response feature vector, and irreversible redshift, calculate the photothermal conversion entropy yield of the sample under dynamic thermal-humidity-mechanical multi-field coupling. S33. Construct an irreversible degradation index based on the cumulative effect of the photothermal conversion entropy production rate over multiple thermal cycles, and integrate the thermally induced redshift abrupt change temperature, thermal response inertia index, irreversible redshift amount, and phase delay features in the transient response feature vector to generate an entropy production-weighted photothermal comprehensive durability coefficient. S34. Based on the combined distribution of the irreversible degradation index and the photothermal integrated durability coefficient, and by referring to the preset climate zone database, output the multi-field coupled service life prediction value of the sample and the corresponding extreme climate adaptability level label.

[0016] As a preferred embodiment of the present invention, S31 specifically includes: S311. After completing the transient pulsed photothermal excitation test in step S2, immediately shut down the tunable pulsed laser source and the heating system of the near-field photothermal test cavity, so that the window film sample under test can be slowly cooled back to the initial temperature from the preset maximum temperature at a natural cooling rate not exceeding 3℃ / min. During the cooling process, the ambient humidity in the test cavity is kept stable below 40% relative humidity to avoid additional condensation during the cooling process from interfering with the test results. S312. After the sample temperature stabilizes and drops back to the initial temperature and is kept constant for at least 10 minutes, restart the all-Stokes polarization spectroscopy acquisition system and, under the same test parameters as in step S1, obtain the recovery absorption spectrum curve of the test window film after cooling. S313. Perform peak analysis on the recovered absorption spectrum curve to extract the recovered characteristic absorption peak positions. The algorithm for extracting the characteristic absorption peak positions is completely consistent with the algorithm used in step S1 to determine the initial reference peak position, so as to ensure the comparability of the data before and after. Calculate the offset of the recovered characteristic absorption peak position relative to the initial reference peak position, and take its absolute value as the irreversible redshift. The irreversible redshift quantitatively characterizes the degree of permanent spectral damage caused by factors such as chemical degradation, interfacial diffusion or material aging after the test window film has undergone a complete thermal cycle.

[0017] As a preferred embodiment of the present invention, S32 specifically includes: S321. Based on the transient polarization spectral evolution feature set, extract the polarization state drift rate of the sample at different temperature points, and based on the transient response feature vector, extract the heat flux density change rate corresponding to the evanescent wave thermal radiation intensity time series data and the polarization state change rate corresponding to the real-time thermal frequency shift data; S322. According to the principle of non-equilibrium thermodynamics, the conjugate thermodynamic force corresponding to the heat flux density change rate is defined as the combination of the reciprocal of the temperature gradient and the local temperature fluctuation, and the conjugate thermodynamic force corresponding to the polarization state change rate is defined as the product of the chemical potential gradient and the polarization state coupling coefficient. S323. Within the near-field interaction region of the sample surface, the space is discretized into several nanoscale micro-elements. The instantaneous product of thermodynamic flow and corresponding thermodynamic force is calculated within each micro-element. The product is then integrated over all micro-elements in the spatial domain to obtain the instantaneous photothermal conversion entropy yield at a certain moment. S324. The instantaneous photothermal conversion entropy yield is integrated in the time domain over the entire period of transient pulsed photothermal excitation applied in step S2, and weighted and corrected in combination with the irreversible redshift obtained in step S31 to obtain the cumulative photothermal conversion entropy yield of the sample in the complete thermal cycle. The cumulative photothermal conversion entropy yield quantitatively characterizes the total energy dissipation of the window film due to irreversible thermodynamic processes under multi-field coupling.

[0018] A system for testing and evaluating the comprehensive photothermal performance of automotive window films, used to implement a method for testing and evaluating the comprehensive photothermal performance of automotive window films, including: The multi-field coupled environment simulation module includes a bidirectional curvature adjustment device, a programmed temperature control unit, and a pulsed humidification unit. The bidirectional curvature adjustment device is used to carry the window film sample under test and cyclically switch between convex and concave curvature states at a preset frequency. The programmed temperature control unit is used to apply periodic thermal cycling excitation with independently adjustable heating and cooling rates to the sample surface. The pulsed humidification unit is used to apply pulsed humidity excitation asynchronous to the thermal cycling period to the sample surface. The all-Stokes polarization spectroscopy acquisition module is used to acquire transient polarization spectral data of the polarization state of a sample at multiple characteristic wavelengths over time during dynamic thermal-humidity-mechanical multi-field coupling, with a preset sampling interval. The near-field photothermal testing module includes a built-in tunable pulsed laser source and a scanning near-field thermal radiation probe array. The tunable pulsed laser source is used to adjust the incident polarization state according to the polarization spectrum characteristics to match the intrinsic polarization sensitive axis of the sample and apply transient pulsed photothermal excitation. The scanning near-field thermal radiation probe array is used to acquire the evanescent wave thermal radiation intensity time series data in the nanoscale air gaps on the sample surface and simultaneously track the surface plasmon resonance thermal frequency shift data. The data processing and control module is connected to the multi-field coupled environment simulation module, the full Stokes polarization spectrum acquisition module, and the near-field photothermal testing module. It is used to synchronously record real-time curvature radius data, real-time temperature data, and real-time relative humidity data, construct a transient polarization spectral evolution feature set, extract the thermally induced redshift abrupt change temperature, thermal response inertia index, and transient response feature vector, calculate the irreversible redshift, photothermal conversion entropy yield, and irreversible degradation index, generate a photothermal comprehensive durability coefficient, and output the service life prediction value and climate adaptability level label.

[0019] Compared with the prior art, the present invention has the following advantages: 1. This invention breaks through the limitations of traditional static testing. It simulates glass surface deformation by dynamically switching bidirectional curvature and simulates the natural decoupling state of day-night temperature difference and condensation-evaporation process by asynchronous coupling of temperature and humidity. It can reproduce the multi-field synergistic effect actually experienced by the window film in the laboratory and accurately identify pseudo-high-performance films that perform well in static testing but whose performance drops sharply in dynamic service due to multi-field coupling.

[0020] 2. This invention extracts the thermally induced redshift abrupt change temperature and thermal response inertia index by tracking the real-time drift trajectory of the absorption peak, revealing the critical temperature point at which the window film performance begins to decline sharply and the severity of the thermal response; it calculates the irreversible redshift through cooling recovery tests, distinguishing between physically reversible changes and chemically irreversible damage, and quantifying the permanent material aging caused by thermal cycling; through near-field thermal radiation and thermal frequency shift phase coupling analysis, it reveals the intrinsic relationship between hot carrier accumulation and optical performance degradation at the nanoscale, enabling durability evaluation to move from empirical speculation to mechanism quantification.

[0021] 3. This invention calculates the photothermal conversion entropy production rate based on entropy production theory, quantifying the multi-field coupled degradation process into a measurable cumulative value; it integrates abrupt temperature, thermal response inertia index, irreversible redshift, phase delay characteristics, and cumulative entropy production rate to generate an entropy production-weighted photothermal comprehensive durability coefficient, achieving multi-parameter fusion evaluation; based on the joint distribution of the photothermal comprehensive durability coefficient and the irreversible degradation index, it outputs the predicted service life value and extreme climate adaptability level label, and can generate a heat map of expected service life in major cities across the country, transforming complex test data into intuitive purchasing guidance and marketing tools. Attached Figure Description

[0022] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating the method described in Embodiment 1 of the present invention.

[0024] Figure 2 This is a framework diagram of the system described in Embodiment 2 of the present invention. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] The concepts involved in this application will first be described with reference to the accompanying drawings. It should be noted that the following descriptions of various concepts are only for the purpose of making the content of this application easier to understand and do not constitute a limitation on the scope of protection of this application; furthermore, the embodiments and features in the embodiments of this application can be combined with each other unless otherwise specified. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0027] Example 1 like Figure 1 As shown, this invention provides a method for testing and evaluating the comprehensive photothermal performance of automotive window films, comprising the following steps: S1. Under dynamic thermal-humidity-mechanical multi-field coupling, transient polarization spectral data of the window film under test are acquired, and a multi-field coupled spectral feature set is constructed; specifically including: S11. Sample bonding and fixation and bidirectional dynamic deformation application, specifically: S111. The window film sample to be tested is attached to the bidirectional curvature adjustment device of the controllable multi-field coupling test bench using a standard mounting process. The bidirectional curvature adjustment device consists of a set of precision CNC driven punches and dies. The punches and dies are made of high-strength aluminum alloy or stainless steel, and the working surfaces are mirror polished. The geometry of the punch simulates the convex arc surface of the windshield of a car, and the geometry of the die simulates the concave arc surface of the side window of a car. The curvature radius of the punch and die is continuously adjustable in the range of 500mm to 2000mm, and each is equipped with an independent servo motor drive system and ball screw transmission mechanism.

[0028] The sample is fixed to the working surface of the punch or die using a vacuum adsorption device or a flexible pneumatic clamping device. The vacuum adsorption device connects to a vacuum pump through an array of micropores on the working surface of the die to ensure that there are no air bubbles left on the sample mounting surface and that the edges are well sealed. Alternatively, a flexible pneumatic clamping device can be used to apply a constant clamping force along the edge of the sample through evenly distributed silicone strips to simulate the edge constraint state during actual mounting.

[0029] S112. The servo motor drive system, according to a preset deformation control program, drives the punch and die to alternately press or draw in the sample at a preset frequency of 0.1–0.5 Hz / min, causing the sample to cycle between convex and concave curvature states. In the convex curvature state, the sample's mounting surface bends outwards with the center of curvature located on the outside of the sample; in the concave curvature state, the sample's mounting surface bends inwards with the center of curvature located on the inside of the sample. The cyclic switching process simulates the dynamic deformation of the glass surface caused by vehicle body torsion, suspension vibration, and temperature stress during actual vehicle operation, introducing periodic alternating tensile and compressive stresses between the polymer substrate layer and the inorganic functional coating layer of the sample, thereby establishing a dynamic mechanical field.

[0030] S12. During the dynamic deformation process, a programmed temperature-controlled thermal cycling excitation and a pulsed humidity excitation are applied to the sample surface; specifically: S121. Application of programmed temperature-controlled thermal cycling excitation, specifically: The programmed temperature control system includes a radiant heating array arranged above the surface of the sample to be tested and a forced convection cooling device arranged on the side wall of the environmental chamber. The radiant heating array consists of multiple sets of quartz halogen heating tubes or ceramic infrared heating plates. Each heating unit is equipped with an independent solid-state relay power adjustment module. The forced convection cooling device includes a combination of a variable frequency centrifugal fan and a cooling coil.

[0031] The thermal cycling program parameters are set using a PID closed-loop temperature controller. The heating rate is set to 2-5℃ / min, the cooling rate to 5-10℃ / min, the initial temperature to 23℃, and the maximum temperature to be no less than 80℃. When the thermal cycle starts, the PID closed-loop temperature controller adjusts the duty cycle of the solid-state relay power regulation module using pulse width modulation based on the real-time temperature signal fed back by the thin-film resistance temperature sensor attached to the sample surface. This allows the radiant heating array to linearly and programmatically raise the sample surface temperature from the initial temperature to the maximum temperature at the set heating rate, and maintain this temperature at the maximum temperature for a preset holding time, such as 30-60 minutes, to simulate the steady-state heat load of direct sunlight exposure.

[0032] Subsequently, the PID closed-loop temperature controller switches to cooling mode and starts the variable frequency centrifugal fan to deliver cooling airflow to the sample surface through the cooling coil at maximum airflow. The sample surface temperature is then linearly cooled back to the initial temperature at the set cooling rate, completing a single thermal cycle.

[0033] The independent adjustable characteristics of the heating and cooling stages are achieved by setting the upper limit of the power of the radiant heating array and the upper limit of the speed of the variable frequency centrifugal fan, thereby simulating different thermal shock modes caused by the diurnal temperature difference in the real environment, such as slow heating and rapid cooling or sudden rain cooling after exposure to the sun.

[0034] S122. Asynchronous coupling application of pulsed humidity excitation, specifically: The pulse humidification system includes an ultrasonic atomizing nozzle array located at the top of the controlled environment chamber and a vacuum dehumidification pipeline located at the bottom of the chamber. The ultrasonic atomizing nozzle array atomizes water into micron-sized water mist particles through high-frequency oscillation, while the vacuum dehumidification pipeline removes moisture from the chamber through a combination of a vacuum pump and a dehumidification membrane. The humidity range of the pulse humidity excitation covers a range from low humidity (30% relative humidity) to high humidity (95% relative humidity), and a single humidity pulse cycle includes a rapid humidification phase, a high humidity maintenance phase, and a rapid dehumidification phase.

[0035] During the rapid humidification phase, the control unit activates the ultrasonic atomizing nozzle array to continuously inject water mist into the chamber at maximum atomization volume, while simultaneously shutting off the vacuum dehumidification pipeline. This causes the relative humidity inside the chamber to rapidly increase from 30% to 95% within 10 minutes, inducing condensation on the sample surface. During the high humidity maintenance phase, the ultrasonic atomizing nozzle array is maintained at low power and intermittently to stabilize the relative humidity at 95% for a preset duration, such as 20-40 minutes, simulating the continuous effect of a high-humidity environment. During the rapid dehumidification phase, the ultrasonic atomizing nozzle array is shut off, and the vacuum dehumidification pipeline is activated at maximum dehumidification rate, causing the relative humidity to rapidly decrease from 95% to 30% within 15 minutes, simulating the evaporation process caused by sunlight.

[0036] S123. The period of thermal cycling excitation and pulsed humidity excitation is set asynchronously. The ratio of the thermal cycling period to the humidity pulse period is adjusted to be a non-integer value, such as 3:2 or 5:3, by programming. Alternatively, a fixed or random time difference offset is introduced between the phase of the thermal cycle and the phase of the humidity pulse. For example, the starting point of the thermal cycle is delayed by 15 min to 30 min relative to the starting point of the humidity pulse. This ensures that the peak temperature change and the peak humidity appear asynchronously in time, thereby simulating the natural state of asynchronous temperature change and condensation-evaporation process in the real environment and forming a complex stress field with multiple coupled thermal, humidity and force fields inside the sample.

[0037] S13. Acquisition of transient polarization spectral data, specifically: After the dynamic thermo-humidity-mechanical multi-field coupling effect is established and stabilized, the all-Stokes polarization spectral acquisition system is activated. The acquisition system consists of a broadband light source, a polarizer, a sample stage, an analyzer array, and a high-sensitivity infrared detector. The broadband light source uses a halogen tungsten lamp or a supercontinuum laser, covering the visible to near-infrared band, i.e., 400nm–2500nm; specifically: S131. In the near-infrared band, i.e., 780nm–2500nm, multiple characteristic wavelengths, such as 900nm, 1200nm, and 1600nm, are pre-selected that correspond to the surface plasmon resonance absorption peaks of the metal oxide functional layers in the test window film, such as indium tin oxide and titanium nitride, and the molecular vibration absorption peaks of the polymer substrate, such as polyethylene terephthalate. For each characteristic wavelength, the polarizer adopts a rotating waveplate type or liquid crystal variable retarder type structure to sequentially generate linearly polarized light with polarization directions of 0°, 45°, 90°, and 135°, as well as left-handed and right-handed circularly polarized light, which are incident on the sample surface.

[0038] S132. The analyzer array synchronously acquires the light intensity signal after transmission through the sample. Based on the four-beam method or Fourier transform method, it calculates the four components S0, S1, S2, and S3 of the Stokes parameter, thereby determining the polarization state parameters of the sample at the characteristic wavelength, including the degree of polarization, polarization ellipticity, and polarization azimuth angle. At a set sampling interval, such as every ten seconds or every degree Celsius temperature change interval, it continuously records the transient polarization spectrum data of the polarization state evolution over time, forming the time evolution trajectory of the polarization state. At the same time, it monitors the polarization degree decay rate and the polarization azimuth angle drift. When the polarization degree decay rate exceeds a preset threshold, the moment is marked as the polarization instability critical state.

[0039] S14. Synchronous recording and feature set construction of multi-field coupling parameters, specifically: S141. Simultaneously with S13, a strain gauge-type curvature sensor arranged on the back of the bidirectional curvature adjustment device records real-time curvature radius data of the punch or die with the same time resolution as polarization spectral sampling, such as every ten seconds; a thin-film resistance temperature sensor or infrared thermometer attached to the central and edge regions of the sample surface records real-time temperature data of thermal cycling excitation; and a capacitive humidity sensor arranged on the side wall of the environmental chamber records real-time relative humidity data of pulsed humidity excitation.

[0040] S142. Establish a unified data acquisition time series benchmark, align the real-time radius of curvature data, real-time temperature data, and real-time relative humidity data with the transient polarization spectral data acquired at the corresponding time points, and fuse the data to construct a transient polarization spectral evolution feature set that characterizes the mapping relationship between multi-field coupling parameters and polarization state evolution. The feature set is stored in the form of a time series data matrix, with each row corresponding to a sampling time point. The column fields include at least the timestamp, radius of curvature value, temperature value, humidity value, Stokes parameter at each characteristic wavelength, calculated degree of polarization, polarization ellipticity, and polarization azimuth angle index, providing a complete data foundation for the correlation between multi-field coupling state and optical response in subsequent steps.

[0041] S2. Based on the multi-field coupled spectral feature set, the thermally induced absorption peak drift trajectory is tracked to extract the thermally induced redshift abrupt change temperature and the thermal response inertia index; simultaneously, a pulsed laser matching the sample polarization state is applied to collect near-field thermal radiation intensity and track the plasma resonant thermal frequency shift, extracting the transient response feature vector; specifically including: S21. Extract thermally induced redshift characteristic parameters based on transient polarization spectral evolution feature set, specifically: S211. Extraction of characteristic absorption peak positions and construction of real-time drift trajectories, specifically: Based on the transient polarization spectral evolution characteristics, band selection was performed on the characteristic absorption properties of the window film under test in the near-infrared band. Specifically, multiple characteristic absorption bands corresponding to the surface plasmon resonance absorption peaks of the metal oxide functional layer and the molecular vibration absorption peaks of the polymer substrate were selected. The metal oxide functional layer includes indium tin oxide or titanium nitride nanoparticle layers, and the polymer substrate includes polyethylene terephthalate or polyethylene naphthalate. Its molecular vibrations include carbonyl stretching vibrations and benzene ring skeleton vibrations.

[0042] For each selected characteristic absorption band, spectral absorbance curves at different temperature points within that band are extracted from the transient polarization spectral evolution feature set. These temperature points are determined by the real-time temperature data recorded in step S14. Baseline correction is performed on the spectral absorbance curves at each temperature point, using an adaptive iterative penalized least squares method or a polynomial fitting baseline subtraction method to eliminate baseline fluctuations caused by scattering and drift. Subsequently, a nonlinear least squares fitting algorithm is used to accurately determine the characteristic absorption peak position at that temperature point. The fitting algorithm employs a Gaussian-Lorentz mixture function or a Voigt linear function under the Levenberg-Marquardt algorithm. The characteristic absorption peak position is the wavelength coordinate corresponding to the maximum point of the fitted curve, accurate to a resolution of 0.01 nm.

[0043] Using the real-time temperature data recorded in step S14 as the horizontal axis and the characteristic absorption peak position corresponding to each temperature point as the vertical axis, a continuous real-time drift trajectory curve of the characteristic absorption peak position with temperature change is constructed through cubic spline interpolation or moving average smoothing. The trajectory curve fully characterizes the real-time evolution law of the optical bandgap or plasma resonance frequency of the window film functional layer with temperature increase under dynamic thermal-humidity-mechanical multi-field coupling, providing a high-resolution data foundation for subsequent identification of thermally induced redshift abrupt temperature and calculation of thermal response inertia index.

[0044] S212. Differential dynamics processing of real-time drift trajectory, specifically: Digital signal processing was performed on the real-time drift trajectory curve to eliminate high-frequency noise interference and extract differential dynamic features. First, the Savitzky-Golay polynomial smoothing filter algorithm was used to smooth the real-time drift trajectory. The filter window width was set to 7-15 sampling points, corresponding to a temperature range of approximately 3-7℃. The polynomial fitting order was set to second or third order. This effectively preserved the long-term trend characteristics of the original data while suppressing high-frequency random noise introduced by electronic noise from the spectral acquisition system, light source intensity fluctuations, and environmental micro-vibrations.

[0045] Subsequently, numerical differentiation is performed on the smoothed trajectory curve. The central difference method is used, which utilizes the difference quotient between adjacent data points before and after the current sampling point, or the three-point Lagrange differential formula is used to calculate its first derivative. This yields the instantaneous redshift rate curve, which characterizes the instantaneous rate of change of the characteristic absorption peak position with temperature. The instantaneous redshift rate curve quantitatively reflects the nanometer-scale drift of the characteristic peak position caused by a unit temperature change of 1 degree Celsius. The positive or negative value indicates the peak position redshift (towards longer wavelengths) or blueshift (towards shorter wavelengths). The absolute value directly quantifies the severity of the thermally induced spectral drift.

[0046] Then, the instantaneous redshift rate curve is numerically differentiated again, and its second derivative is calculated using the same numerical differentiation algorithm to obtain the redshift acceleration curve, which characterizes the acceleration of the redshift rate with temperature change. The redshift acceleration curve reflects the increasing and decreasing trend and curvature characteristics of the peak position drift rate, and the magnitude of the absolute value of the second derivative indicates the nonlinearity of the thermally induced spectral drift process and the sensitivity to thermal shock. The first and second derivative data sequences are strictly time-stamp aligned with the real-time temperature data recorded in step S14, forming a complete differential feature dataset.

[0047] S213. Critical determination and labeling theory of thermo-induced redshift abrupt change temperature, specifically: Based on the redshift acceleration curve, automatic identification of thermally induced redshift abrupt change temperature and determination of critical phase transition are implemented. First, under standard environmental conditions, the same temperature scanning procedure as the test sample is performed on a standard reference sample without thermally induced drift. The standard reference sample includes a fused silica optical substrate or a vacuum-metallized standard mirror. The background spectral noise level of the sample is measured within the same temperature range. The statistical mean and standard deviation of the absolute value of the second derivative of the real-time drift trajectory of the reference sample are calculated. The mean plus three times the standard deviation is set as the preset threshold to ensure that the threshold can effectively distinguish between real physical signals and background noise.

[0048] Subsequently, during the temperature ascending scan of the redshift acceleration curve, a sliding window monitoring algorithm is used to calculate the average absolute value of the second derivative of three consecutive points: the current temperature point and one sampling point before and after it. When this average value first continuously exceeds a preset threshold and is maintained for at least three consecutive sampling points, the temperature point corresponding to the center of the window is precisely marked as the thermally induced redshift abrupt change temperature. The physical meaning of the thermally induced redshift abrupt change temperature is the critical temperature point at which the metal oxide functional layer or polymer substrate in the window film begins to undergo a significant thermally induced spectral drift. It characterizes the critical phase transition point where the internal stress relaxation, defect proliferation, microcrystalline melting, or phase transformation process of the material changes from the reversible thermoelastic response stage to the irreversible structural damage stage. The accurate identification of this temperature point has key engineering guiding significance for defining the reliability limit of the window film under actual high-temperature exposure service environment, predicting the initiation conditions of long-term thermal aging failure, optimizing the thermal stability formulation design of multilayer composite film systems, and distinguishing the applicability levels of different climate regions.

[0049] S214. Calculation of the definite integral of the thermal response inertia index, specifically: Based on the instantaneous redshift rate curve, the absolute value of the instantaneous redshift rate over the entire temperature range is calculated by definite integral to obtain the thermal response inertia index. In specific implementation: First, the integration interval is determined to be the entire heating process from the initial temperature of 23℃ at the start of the thermal cycle to the preset maximum temperature of no less than 80℃ set in step S121. The instantaneous redshift rate is obtained by performing a first-order numerical derivative operation on the real-time drift trajectory curve constructed in step S221. Its physical meaning is the amount of peak position drift caused by a unit temperature change.

[0050] Numerical integration methods are employed to accumulate the absolute value of the instantaneous redshift rate over the integration interval. These methods include the composite trapezoidal rule, the composite Simpson's rule, or the Gauss-Legendal numerical integration. Mathematically, the thermal response inertia exponent is expressed as the definite integral of the absolute value of the instantaneous redshift rate over the temperature variable within the integration interval. The magnitude of the thermal response inertia exponent quantifies the severity of the window film's overall response to temperature changes and its thermal inertia characteristics. A larger exponent indicates a more severe shift in the absorption peak position during heating, a faster rate of stress relaxation and defect proliferation within the functional layer, poorer thermal stability, and a greater susceptibility to irreversible spectral degradation and structural delamination during service. Conversely, a smaller exponent indicates a smoother thermal response, lower thermal inertia, more efficient internal energy dissipation mechanisms, and superior thermal stability. This exponent, along with parameters such as the irreversible redshift and phase delay time in subsequent step S3, constitutes the key input variable for the entropy-weighted photothermal comprehensive durability coefficient.

[0051] S22. Polarization matching and transient excitation application in the near-field photothermal test cavity are as follows: S221. The test window film sample, after completing the multi-field coupling test, is transferred from the controllable multi-field coupling test stage to the near-field photothermal test cavity. The test cavity is equipped with a high-precision temperature-controlled sample stage, a tunable pulsed laser source, and a scanning near-field thermal radiation probe array. Based on the polarization state evolution law recorded in the transient polarization spectrum evolution characteristics, especially the azimuth angle and ellipticity data of the intrinsic polarization sensitive axis of the sample at different temperature points, the polarization state of the emitted beam of the tunable pulsed laser source is adjusted by an electronically controlled liquid crystal phase delay device or a motorized rotating waveplate group, i.e., a combination of half-wave plates and quarter-wave plates, so that its polarization ellipticity and polarization azimuth angle are precisely matched with the intrinsic polarization sensitive axis of the sample at the current temperature state. This ensures that the incident light polarization state and the intrinsic polarization mode induced by the sample's stress birefringence are selectively coupled. The matching state can be confirmed by monitoring the change in the polarization state of the sample's reflected light or maximizing the intensity of the second harmonic signal.

[0052] S222. After confirming polarization matching, adjust the output wavelength of the tunable pulsed laser source, such as an optical parametric oscillator or a Ti:sapphire laser, to make its photon energy precisely match the surface plasmon resonance energy level of the metal oxide functional layer in the window film, and start the acousto-optic modulator or electro-optic modulator to convert the continuous laser into transient pulsed photothermal excitation. The pulse width is set to the nanosecond to microsecond range, and the pulse repetition frequency is set to an asynchronous frequency that is not an integer multiple of the bidirectional curvature switching frequency in step S11, so as to excite the transient accumulation and relaxation process of hot carriers in the functional layer, while avoiding interference caused by coupling with the mechanical deformation frequency, thereby establishing a non-equilibrium photothermal field in the near-field region.

[0053] S23. Synchronous acquisition of near-field evanescent wave thermal radiation and surface plasmon resonance thermal frequency shift, specifically: S231. During the application of transient pulsed photothermal excitation, a scanning near-field thermal radiation probe array, consisting of multiple sharp quartz tips coated with platinum-iridium alloy arranged at an air gap distance of 50-100 nm above the sample surface, is used to collect time-series data of evanescent wave thermal radiation intensity in the nanoscale air gap generated by photon absorption on the sample surface. The probe maintains a constant air gap distance between the tip and the sample surface through a shear force feedback control system. The near-field thermal radiation coupling occurring at the tip converts the local thermal signal into a detectable electrical signal, which is then processed by a low-temperature, low-noise preamplifier and a lock-in amplifier, and recorded at a sampling rate of 1,000 to 10,000 points per second.

[0054] S232. Simultaneously, scattered or transmitted light from the sample surface is collected by an optical fiber integrated into the probe arm and introduced into a high-resolution fiber optic spectrometer to track and monitor the real-time drift of the surface plasmon resonance absorption peak of the metal oxide functional layer as the temperature increases. This is the real-time thermal frequency shift data of surface plasmon resonance, which originates from the change in the real and imaginary parts of the dielectric function caused by the accumulation of hot carriers. The thermal frequency shift tracking is achieved by calculating the peak wavelength through real-time Gaussian fitting or Lorentz fitting algorithms.

[0055] The evanescent wave thermal radiation intensity time series data and the surface plasmon resonance real-time thermal frequency shift data are synchronously acquired through the same hardware trigger signal to ensure strict timestamp alignment, forming a dual-channel time series dataset with precise time correspondence, which is used for subsequent phase coupling analysis.

[0056] S24. Phase coupling analysis and transient response eigenvector construction, specifically: S241. Perform time axis alignment preprocessing, calculate the relative time delay offset between the two sets of data using a cross-correlation algorithm, and use the one with the smaller delay as the benchmark for time shift compensation to eliminate the system time delay introduced by differences in data acquisition channels, such as the difference between probe thermal response delay and spectrometer integration time, and ensure strict synchronization of the two sequences in physical time.

[0057] S242. Frequency domain transformation and phase angle information extraction, specifically: Frequency domain transformation was performed on the evanescent wave thermal radiation intensity time series data and the real-time thermal frequency shift data of surface plasmon resonance after time axis alignment. First, a window function was applied to the two sets of time series data to suppress spectral leakage. The Hanning window or Hamming window function was used, and the window width was consistent with the data length. By multiplying the time-domain data point by point with the window function weight, the spectral sidelobe interference caused by data truncation was reduced. Then, the fast Fourier transform algorithm was performed on the windowed data to transform the time-domain signal to the frequency domain space to obtain a complex spectrum data sequence, in which the real part and imaginary part represent the in-phase component and the quadrature component, respectively.

[0058] In the frequency domain, based on the fundamental frequency and its harmonic components of the transient pulsed photothermal excitation set in step S22, the characteristic frequency positions are accurately identified. The fundamental frequency is the pulse repetition frequency, and the harmonic components are integer multiples of the fundamental frequency. The phase angle information of the evanescent wave thermal radiation intensity spectrum and the thermal frequency shift spectrum at these characteristic frequencies is extracted. The phase angle information is obtained by calculating the argument of the complex spectrum data, that is, by taking the arctangent of the ratio of the imaginary part to the real part. The result is normalized to 0.2π radians or the range of -π to +π radians, which characterizes the initial phase state of the near-field thermal radiation response and the plasma resonant frequency shift response at their respective characteristic frequencies, providing basic data for subsequent phase difference calculations.

[0059] S243. Phase difference calculation and two-dimensional eigenvector construction, specifically: Based on the phase angle information extracted in step S242, the phase difference between the evanescent wave thermal radiation intensity spectrum and the thermal frequency shift spectrum at each characteristic frequency is calculated. The phase difference is obtained by subtracting the phase angle of the evanescent wave thermal radiation intensity spectrum from the phase angle of the thermal frequency shift spectrum. The numerical range is from -π to +π radians. This phase difference quantitatively characterizes the time lag relationship between the near-field thermal radiation response and the plasma resonant frequency shift response. The smaller the absolute value of the phase difference, the higher the synchronization of the two field responses. The larger the absolute value, the more significant the phase delay caused by thermal inertia.

[0060] Simultaneously, the coherence coefficients of the two sets of time-series data within the characteristic frequency band are calculated. The coherence coefficients are obtained by the geometric mean ratio of the cross power spectrum to the individual power spectrum. Specifically, the square of the cross power spectrum amplitude of the two signals is divided by the product of the individual power spectrum amplitudes of the two signals. The coherence coefficient ranges from 0 to 1. The closer the value is to 1, the higher the linear correlation and energy coupling efficiency between near-field thermal radiation and plasma resonant thermal frequency shift. The closer the value is to 0, the weaker the coupling effect or the presence of strong nonlinear interference.

[0061] A two-dimensional transient response feature vector is constructed by combining the phase difference and the coherence coefficient. The first component of the feature vector represents the phase lag relationship between the two field responses, and the second component represents the coupling strength between the two field responses. This two-dimensional vector quantifies the comprehensive dynamic characteristics of the three-field coupling effect of near-field thermal radiation, plasma resonance and temperature of the window film under dynamic thermal-humidity-mechanical multi-field coupling.

[0062] S3. After cooling, measure the irreversible redshift, calculate the entropy production rate and irreversible degradation index, and integrate the thermally induced redshift abrupt change temperature, thermal response inertia index, irreversible redshift, and phase delay time to generate a photothermal integrated durability coefficient, outputting service life prediction and climate adaptability level; specifically including: S31. Reversible / irreversible damage separation and irreversible redshift measurement, specifically: S311. Turn off the power switch of the tunable pulsed laser source and the heating system of the near-field photothermal test cavity, cut off the active heat source input, and allow the test window film sample to be slowly cooled from the preset maximum temperature set in step S1 back to the initial temperature of 23°C at a natural cooling rate not exceeding 3°C / min. The natural cooling process is achieved by opening the circulating cooling water path of the test cavity and natural convection with the external heat sink to avoid thermal shock caused by forced air cooling. During the entire cooling process, the ambient humidity in the test cavity is kept stable below 40% relative humidity through a closed-loop humidity control system to ensure that the dehumidification is greater than the possible condensation, so as to strictly avoid the introduction of interference hydration damage caused by water vapor on the sample surface during the cooling process.

[0063] S312. Once the sample temperature has been confirmed to have stabilized and dropped back to the initial temperature of 23°C by real-time temperature monitoring, and has been maintained at a constant temperature for at least 10 minutes to ensure thermodynamic equilibrium, the all-Stokes polarization spectroscopy acquisition system is restarted. Under the same test parameters as in step S1, including the same light source intensity, integration time, wavelength scanning range, polarization angle setting, and data acquisition frequency, the recovery absorption spectrum curve of the window film under test after cooling is obtained.

[0064] S313. The peak analysis algorithm used in step S1 to determine the initial reference peak position is completely consistent with that used to recover the absorption spectrum curve, including the same baseline correction parameters, fitting function type, and convergence accuracy threshold. The recovered characteristic absorption peak position is extracted. The wavelength shift of the recovered characteristic absorption peak position relative to the pre-determined initial reference peak position is calculated, and its absolute value is taken as the irreversible redshift. The irreversible redshift physically quantifies the degree of permanent spectral damage caused by irreversible factors such as chemical degradation of polymer substrate, proliferation of lattice defects in inorganic functional layer, interlayer diffusion, or microstructure aging after the window film under test has undergone a complete thermal-humidity-mechanical multi-field coupling cycle. This value is the core damage indicator for evaluating the long-term service reliability of the window film.

[0065] S32. Calculation of entropy yield of photothermal conversion based on non-equilibrium thermodynamics, specifically: S321. Extraction and calculation of thermodynamic flow parameters, specifically: From the transient polarization spectral evolution feature set, for the temperature data point corresponding to each sampling moment, the polarization azimuth angle and polarization ellipticity values ​​at that moment are extracted. The changes in polarization azimuth angle and polarization ellipticity between adjacent sampling moments are calculated. The changes are divided by the time interval between adjacent sampling moments to obtain the polarization state drift rate, including the azimuth drift rate and the ellipticity drift rate, which respectively characterize the rotational change rate and shape change rate of the polarization state under the dynamic thermal-humidity-mechanical multi-field coupling.

[0066] Extract the evanescent wave thermal radiation intensity time series data collected in step S23 from the transient response feature vector, multiply the evanescent wave thermal radiation intensity by the material emissivity correction coefficient and Stefan-Boltzmann constant, convert it into a near-field heat flux density value, perform time-domain numerical differentiation on the heat flux density value, and use the central difference method or the five-point cubic smoothing differentiation method to obtain the heat flux density change rate, which characterizes the degree of drastic change of heat flux in the near-field region over time.

[0067] The real-time variation curve of the surface plasmon resonance peak position over time is extracted from real-time thermal frequency shift data. The change in peak wavelength at adjacent moments is calculated and divided by the time interval to obtain the polarization state change rate caused by hot carrier accumulation and relaxation. This rate of change is directly related to the plasmon resonance frequency drift and reflects the dynamic characteristics of electron-phonon interaction in the metal oxide functional layer. The polarization state drift rate, the heat flux density change rate, and the polarization state change rate are used as thermodynamic flux parameters to provide basic variables for the subsequent definition of conjugate thermodynamic forces and entropy production calculations.

[0068] S322. Definition and construction of conjugate thermodynamic forces, specifically: Based on the principle of local entropy generation in non-equilibrium thermodynamics, corresponding conjugate thermodynamic forces are defined for the rate of change of heat flux density and the rate of change of polarization state, respectively. For the rate of change of heat flux density, its conjugate thermodynamic force is defined as a combination function of the reciprocal of the local temperature gradient and the deviation of the local temperature from the environmental equilibrium temperature. Specifically, by arranging a temperature sensor array in the near-field region or by using temperature field data inverted from evanescent wave thermal radiation intensity, the first-order gradient of the spatial temperature distribution is calculated to obtain the temperature gradient vector. The reciprocal of its magnitude is taken as the first term. At the same time, the difference between the local instantaneous temperature and the environmental set temperature is calculated as the temperature fluctuation. The two terms are linearly combined or multiplied by preset weighting coefficients to construct the conjugate thermodynamic force corresponding to the rate of change of heat flux density. This force characterizes the temperature non-equilibrium potential driving the change of heat flux.

[0069] For the rate of change of polarization state, its conjugate thermodynamic force is defined as the product of the chemical potential gradient and the polarization state coupling coefficient. The chemical potential gradient is calculated based on the rate of change of carrier concentration and the Fermi level shift in the functional layer of the metal oxide at high temperature. The polarization state coupling coefficient is pre-determined through calibration experiments and characterizes the coupling strength between the change of polarization state and the change of the material's chemical potential. Multiplying the two yields the conjugate thermodynamic force corresponding to the rate of change of polarization state. This force characterizes the non-equilibrium chemical potential driving the evolution of polarization state. Through the above definition, a phenomenological relationship between thermodynamic flux and thermodynamic force is established, satisfying the fundamental principle in non-equilibrium thermodynamics that the rate of entropy generation equals the sum of the products of the thermodynamic flux and the corresponding conjugate thermodynamic force.

[0070] S323. Spatial discretization and local entropy production integral, specifically: Within the near-field interaction region between the surface of the window film sample and the tip of the near-field thermal radiation probe, the continuous space is divided into several nanoscale cubic micro-elements using the finite element method or the finite difference mesh method. The side length of each micro-element is set to 10nm-50nm to match the spatial resolution of the near-field detection, ensuring that the physical parameters within each micro-element can be considered uniformly distributed. At the geometric center of each micro-element, based on the polarization state drift rate, heat flux density change rate, and polarization state change rate extracted in step S321, and the corresponding conjugate thermodynamic force defined in step S322, the instantaneous scalar product of the thermodynamic flux and the corresponding conjugate thermodynamic force is calculated to obtain the local entropy generation rate density of the micro-element at the current moment, expressed in watts per cubic meter per Kelvin.

[0071] The local entropy production rate density of all infinitesimal elements is integrally calculated in the three-dimensional spatial domain by multiplying the entropy production rate density of each infinitesimal element by its volume and then summing the results. Alternatively, Gaussian numerical integration can be used to integrate the results over the entire domain to obtain the instantaneous photothermal conversion entropy production rate in the near-field region at a specific moment. The instantaneous photothermal conversion entropy production rate characterizes the total entropy increase per unit time caused by the irreversible photothermal conversion process of the window film at that moment, reflecting the instantaneous growth rate of the system's disorder.

[0072] S324. Time-domain integration and irreversible redshift weighted correction, specifically: The instantaneous photothermal conversion entropy yield obtained in step S323 is subjected to time-domain definite integration over the entire duration of the transient pulsed photothermal excitation applied in step S22. Specifically, the integration interval is defined as the period from the start to the end of the pulse excitation. The composite trapezoidal rule or the composite Simpson rule is used to numerically integrate the curve of the instantaneous photothermal conversion entropy yield over time to obtain the preliminary cumulative photothermal conversion entropy yield.

[0073] The irreversible redshift measured in step S31 is introduced as a structural damage weighting factor to weight and correct the initial cumulative photothermal conversion entropy yield. The irreversible redshift is divided by the initial reference peak wavelength to obtain the relative redshift rate. This relative redshift rate is then used as a weighting coefficient and multiplied by the initial cumulative photothermal conversion entropy yield, or the additional entropy yield calculated based on the redshift is directly added. This yields the corrected cumulative photothermal conversion entropy yield of the sample over a complete thermal cycle. The cumulative photothermal conversion entropy yield comprehensively quantifies the total energy dissipation and accumulated structural disorder caused by irreversible thermodynamic processes such as near-field thermal radiation dissipation, plasmon resonance thermal frequency shift, and irreversible polarization state drift of the window film under multi-field coupling. This provides a core physical quantity for subsequently constructing the irreversible degradation index and assessing long-term durability.

[0074] S33. The irreversible degradation index is constructed and integrated with the durability coefficient, specifically as follows: S331. Based on the photothermal conversion entropy production rate calculated in step S32, cumulative tracking is performed over multiple consecutive thermal cycling test cycles to construct an irreversible degradation index that evolves over time. In specific implementation, the cumulative photothermal conversion entropy production rate is calculated for each thermal cycling cycle, and the entropy production rate values ​​of each cycle are summed to form a degradation trajectory curve showing the cumulative entropy production changing with the number of cycles. Linear regression or exponential fitting is performed on the degradation trajectory curve, and its growth rate constant is extracted as the irreversible degradation index. The larger the irreversible degradation index value, the faster the window membrane structure degrades and the shorter its service life.

[0075] S332. Simultaneously, the thermally induced redshift abrupt change temperature and thermal response inertia exponent calculated in step S2, the irreversible redshift measured in step S31, and the phase delay characteristics in the transient response feature vector obtained in step S24, including phase difference and coherence coefficient, are fused to generate an entropy-weighted photothermal comprehensive durability coefficient. The fusion process first normalizes each individual parameter: the thermally induced redshift abrupt change temperature is normalized using a ratio relative to 80℃; the thermal response inertia exponent is normalized using a reciprocal normalization to maximize the conversion; the irreversible redshift is normalized using a negative exponential mapping; the absolute value of the phase difference in the phase delay characteristics is negatively linearly mapped; and the coherence coefficient is directly used as its original value.

[0076] S333. Subsequently, the normalized thermally induced redshift abrupt change temperature, the response sensitivity factor (i.e., the reciprocal of the thermal response inertia index), the structural stability factor (i.e., the negative exponential mapping of the irreversible redshift), and the coupling efficiency factor (i.e., the combination function of phase delay and coherence coefficient) are weighted and geometrically averaged to obtain the comprehensive performance factor. Finally, the comprehensive performance factor is multiplied by the reciprocal of the irreversible degradation index to generate the entropy-weighted photothermal comprehensive durability coefficient. This coefficient comprehensively considers the transient thermal response characteristics of the window film, the degree of reversible / irreversible damage, and the long-term entropy production accumulation effect.

[0077] S34. Service life prediction and extreme climate adaptation level determination, specifically: S341. Based on the joint distribution of the irreversible degradation index and the photothermal comprehensive durability coefficient obtained in step S33, perform multi-field coupled service life prediction and extreme climate suitability classification of the window film under test. First, establish a mathematical model of the irreversible degradation index changing with the number of test cycles. A linear model or an Arrhenius-type exponential degradation model is usually adopted. The number of prediction cycles corresponding to when the irreversible degradation index reaches the preset performance failure threshold is calculated by extrapolation and used as the basic life prediction value.

[0078] S342. Based on the numerical range of the photothermal integrated durability coefficient, the basic life prediction value is corrected: when the photothermal integrated durability coefficient is higher than the preset high durability threshold, it indicates that the material has excellent resistance to multi-field coupling damage, and the basic life prediction value is multiplied by a correction factor greater than one; when the photothermal integrated durability coefficient is lower than the preset low durability threshold, it indicates that the material has poor thermal stability, and the basic life prediction value is multiplied by a correction factor less than one, and finally the multi-field coupling service life prediction value is generated.

[0079] S343. Simultaneously, based on the joint distribution status and the preset climate zone database, including environmental parameter thresholds for extremely cold regions, hot and humid regions, strong ultraviolet radiation regions, and ordinary climate zones, the corresponding extreme climate adaptability level identifier is output: when the thermal redshift abrupt change temperature is lower than the preset low temperature threshold and the thermal response inertia index is greater than the preset high inertia threshold, it is determined to be an extreme cold region applicable identifier; when the irreversible degradation index grows at a rate lower than the preset stability threshold over multiple test cycles and the photothermal comprehensive durability coefficient is higher than the preset high value threshold, it is determined to be a hot and humid region applicable identifier; when the transient response feature vector indicates a strongly coupled response and the thermal redshift abrupt change temperature is higher than the preset high temperature threshold, it is determined to be a strong ultraviolet radiation region applicable identifier; all other cases are determined to be ordinary climate zone applicable identifiers.

[0080] Example 2 like Figure 2 As shown, a photothermal comprehensive performance testing and evaluation system for automotive window films is used to implement a method for testing and evaluating the photothermal comprehensive performance of automotive window films, including: A. Multi-field coupling environment simulation module, which includes a bidirectional curvature adjustment device, a programmable temperature control unit, and a pulsed humidification unit; The bidirectional curvature adjustment device is used to carry the window film sample to be tested and to cycle between convex curvature state and concave curvature state at a preset frequency. The bidirectional curvature adjustment device includes a first curvature adjustment plate and a second curvature adjustment plate arranged opposite to each other. Both the first curvature adjustment plate and the second curvature adjustment plate are made of shape memory alloy or electrostrictive material. The continuous adjustable switching between convex curvature state and concave curvature state with curvature radius of 500mm to 2000mm is achieved by controlling the magnitude and direction of the applied voltage.

[0081] The programmed temperature control unit is used to apply periodic thermal cycling excitation to the sample surface with independently adjustable heating and cooling rates. The pulsed humidification unit is used to apply pulsed humidity excitation to the sample surface that is asynchronous with the thermal cycling cycle.

[0082] B. Stokes polarization spectroscopy acquisition module: The Stokes polarization spectroscopy acquisition module is used to acquire transient polarization spectral data of the polarization state of the sample at multiple characteristic wavelengths as a function of time during dynamic thermal-humidity-mechanical multi-field coupling. C. Near-field photothermal testing module, which includes a built-in tunable pulsed laser source and a scanning near-field thermal radiation probe array; Tunable pulsed laser sources are used to adjust the incident polarization state according to the polarization spectrum characteristics to match the intrinsic polarization sensitive axis of the sample and apply transient pulsed photothermal excitation; A scanning near-field thermal radiation probe array is used to acquire time-series data of evanescent wave thermal radiation intensity in nanoscale air gaps on the sample surface and simultaneously track surface plasmon resonance thermal frequency shift data.

[0083] The near-field photothermal testing chamber is also equipped with a temperature-controlled sample stage and a vacuum environment maintenance unit. The temperature-controlled sample stage is used to precisely control the sample temperature during near-field testing, and the vacuum environment maintenance unit is used to maintain the gas pressure inside the testing chamber below 10 during near-field thermal radiation testing. －3 Pascal, to eliminate the interference of air molecules on the propagation of evanescent waves.

[0084] D. Data Processing and Control Module: This module is connected to the multi-field coupled environment simulation module, the full Stokes polarization spectrum acquisition module, and the near-field photothermal testing module. It synchronously records real-time curvature radius data, real-time temperature data, and real-time relative humidity data; constructs a transient polarization spectral evolution feature set; extracts the thermally induced redshift abrupt change temperature, thermal response inertia index, and transient response feature vector; calculates the irreversible redshift, photothermal conversion entropy yield, and irreversible degradation index; generates a comprehensive photothermal durability coefficient; and outputs a predicted service life value and climate adaptability level identifier. Specifically, it includes: The feature extraction unit is used to extract the real-time drift trajectory of the characteristic absorption peak position from transient polarization spectral data and calculate the thermally induced redshift abrupt temperature and thermal response inertia index. The phase analysis unit is used to perform phase coupling analysis on the evanescent wave thermal radiation intensity time series data and real-time thermal frequency shift data, and extract the phase difference and coherence coefficient to form a transient response feature vector; Entropy production calculation unit, used to calculate the entropy production rate of photothermal conversion and the cumulative irreversible degradation index based on the principle of non-equilibrium thermodynamics; The fusion evaluation unit is used to fuse multiple characteristic parameters to generate a comprehensive photothermal durability coefficient, and output the service life prediction value and grade label by comparing it with the preset climate zone database.

[0085] E. Visualization output module: The visualization output module is connected to the data processing and control module. It is used to generate heat maps of the expected service life of the window film under test in major cities based on the service life prediction value. The heat map uses different colors to distinguish the recommended replacement cycle of different regions.

[0086] As can be seen from the above description, the embodiments of the present invention achieve the following technical effects: The bidirectional curvature adjustment device of this invention cycles between convex and concave curvature states at a preset frequency, realistically simulating the dynamic deformation of the glass surface caused by wind pressure and temperature changes during vehicle operation, revealing the evolution law of the optical performance of the window film under repeated bending. The asynchronous setting of the programmed temperature-controlled thermal cycling excitation and pulsed humidity excitation breaks through the distortion mode of synchronous temperature and humidity changes in traditional testing, and reproduces the natural state of asynchronous temperature changes and condensation-evaporation processes in the real world in a laboratory environment. By synchronously recording the curvature radius, temperature, humidity and polarization spectrum data through a full Stokes polarization spectral acquisition system, a four-field coupled mapping relationship feature set is constructed, providing a high-fidelity data foundation for subsequent thermal drift dynamic tracking. This enables window film testing to leap from static laboratory ideal conditions to dynamic real service scenarios, and can accurately identify pseudo-high-performance films that perform well in static testing but whose performance drops sharply in actual driving due to multi-field coupling.

[0087] This invention tracks the real-time drift trajectory of the characteristic absorption peak position with temperature using S21, extracting the thermally induced redshift abrupt change temperature and the thermal response inertia index. The thermally induced redshift abrupt change temperature is the critical temperature point at which the window film begins to experience a significant thermally induced spectral drift. When the actual operating temperature exceeds the thermally induced redshift abrupt change temperature, the barrier performance of the window film will drop sharply. The thermal response inertia index quantifies the severity of the window film's overall response to temperature changes. These two parameters provide a quantitative characterization of the thermal stability of the window film for the first time, filling a gap in the industry. Through S24, phase coupling analysis is performed on the evanescent wave thermal radiation intensity and thermal frequency shift data to extract the phase difference and coherence coefficient, achieving a quantitative characterization of the near-field thermal radiation-plasma-temperature three-field coupling effect. This eigenvector reveals the intrinsic relationship between hot carrier accumulation and optical performance degradation at the nanoscale, providing an unprecedented experimental means for understanding the microscopic mechanism of thermally induced failure of the window film. The irreversible redshift after cooling recovery is calculated using S31, which distinguishes between physically reversible changes and chemically irreversible damage in the field of window film testing. The irreversible redshift quantifies the degree of permanent damage to the window film caused by factors such as chemical degradation and interfacial diffusion after a complete thermal cycle, and is a core indicator for predicting the long-term service life of window films. The combination of these three methods enables the evaluation of window film durability to move from empirical speculation to mechanistic quantification.

[0088] This invention, based on the principles of nonequilibrium thermodynamics, calculates the photothermal conversion entropy production rate using evanescent wave thermal radiation intensity and thermal frequency shift data. It quantifies the complex multi-field coupled degradation process into a measurable cumulative entropy production rate. A higher entropy production rate indicates more irreversible energy dissipation during thermal cycling and faster performance degradation. This is the first application of entropy production theory in the field of window film durability evaluation, providing a solid theoretical foundation for lifetime prediction. By integrating thermally induced redshift abrupt change temperature, thermal response inertia index, irreversible redshift, phase delay characteristics, and cumulative entropy production rate, an entropy production-weighted photothermal comprehensive durability coefficient is generated. This coefficient is a comprehensive evaluation index that integrates multi-dimensional features, achieving a leap from single-index evaluation to multi-parameter fusion evaluation. The comprehensiveness and accuracy of the evaluation results far exceed existing technologies. Based on the joint distribution of the irreversible degradation index and the comprehensive durability coefficient, and in comparison with a pre-defined climate zone database, the system outputs multi-field coupled service life predictions and extreme climate adaptability level labels for the samples. This output can be directly converted into purchasing guidance for consumers—for example, EX-level extreme climate adaptability models are suitable for harsh regions such as deserts and tropics, while ST-level standard climate adaptability models are suitable for conventional regions. Simultaneously, based on this output, heat maps of expected service life for major cities can be generated, transforming complex test data into an intuitive commercial marketing tool.

[0089] The embodiments and / or implementation methods described above are merely preferred embodiments and / or implementation methods for implementing the technology of the present invention, and are not intended to limit the implementation methods of the technology of the present invention in any way. Any person skilled in the art may make some modifications or alterations to other equivalent embodiments without departing from the scope of the technical means disclosed in the present invention, but these should still be regarded as the technology or embodiments that are substantially the same as the present invention. This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. The above descriptions are only preferred embodiments of this application. It should be noted that due to the limitations of written expression, while there are objectively infinite specific structures, those skilled in the art can make several improvements, modifications, or changes without departing from the principles of this application, and can also combine the above technical features in an appropriate manner. These improvements, modifications, changes, or combinations, or the direct application of the inventive concept and technical solution to other situations without modification, should all be considered within the scope of protection of this application.

Claims

1. A method for testing and evaluating the comprehensive photothermal performance of automotive window film, characterized in that, include: Under dynamic thermal-humidity-mechanical multi-field coupling, transient polarization spectral data of the window film under test are collected, and a multi-field coupled spectral feature set is constructed. Based on the multi-field coupled spectral feature set, the thermally induced absorption peak drift trajectory is tracked, and the thermally induced redshift abrupt change temperature and thermal response inertia index are extracted; at the same time, a pulsed laser matching the polarization state of the sample is applied, the near-field thermal radiation intensity is collected, and the plasma resonance thermal frequency shift is tracked to extract the transient response feature vector; After cooling, the irreversible redshift is measured, the entropy production rate and irreversible degradation index are calculated, and the thermo-induced redshift abrupt change temperature, thermal response inertia index, irreversible redshift and phase delay time are integrated to generate a photothermal durability coefficient, and the service life prediction and climate adaptability level are output.

2. The method for testing and evaluating the comprehensive photothermal performance of automotive window film according to claim 1, characterized in that, The process of acquiring transient polarization spectral data of the window film under test under dynamic thermal-humidity-mechanical multi-field coupling and constructing a multi-field coupled spectral feature set specifically includes: The test window film sample is attached to the bidirectional curvature adjustment device of the controllable multi-field coupling test bench. The bidirectional curvature adjustment device cycles between convex curvature state and concave curvature state at a preset frequency to simulate the dynamic deformation of the glass surface when the actual vehicle is driving. During the dynamic deformation process, a programmed temperature-controlled thermal cycling excitation and a pulsed humidity excitation are applied to the sample surface; During the establishment of the dynamic thermal-humidity-mechanical multi-field coupling effect, multiple characteristic wavelengths are selected in the near-infrared band through a full Stokes polarization spectroscopy acquisition system, and transient polarization spectral data of the sample polarization state evolution over time are obtained at a set sampling interval. The real-time curvature radius data of the bidirectional curvature adjustment device, the real-time temperature data of thermal cycling excitation, and the real-time relative humidity data of pulse humidity excitation are recorded simultaneously to construct a transient polarization spectral evolution feature set that characterizes the mapping relationship between multi-field coupling parameters and polarization state evolution.

3. The method for testing and evaluating the comprehensive photothermal performance of automotive window film according to claim 2, characterized in that, During the dynamic deformation process, programmed temperature-controlled thermal cycling excitation and pulsed humidity excitation are applied to the sample surface, specifically including: The bidirectional curvature adjustment device with the sample to be tested attached is placed in a controllable environment chamber. Periodic thermal cycling excitation is applied to the sample surface through a programmed temperature control system. The heating rate and cooling rate of the thermal cycling excitation are independently adjustable. A single thermal cycle includes a complete process from heating from the initial temperature to the maximum temperature, holding the temperature, and then cooling back to the initial temperature. While the thermal cycling excitation is running, a pulsed humidity excitation asynchronous with the thermal cycling cycle is applied to the sample surface through a pulsed humidification system. The humidity variation range of the pulsed humidity excitation covers a wide range from low humidity to high humidity. A single humidity pulse cycle includes a rapid humidification phase, a high humidity holding phase, and a rapid dehumidification phase. The asynchronous setting of the thermal cycling excitation and the pulsed humidity excitation includes making the ratio of the thermal cycling period to the humidity pulse period not an integer, or making there a fixed or random time offset between the phase of the thermal cycling and the phase of the humidity pulse.

4. The method for testing and evaluating the comprehensive photothermal performance of automotive window film according to claim 3, characterized in that, Based on the multi-field coupled spectral feature set, the thermally induced absorption peak drift trajectory is tracked, and the thermally induced redshift abrupt change temperature and thermal response inertia index are extracted. Simultaneously, a pulsed laser matching the sample polarization state is applied, near-field thermal radiation intensity is acquired, and the plasma resonant thermal frequency shift is tracked to extract the transient response feature vector, specifically including: Based on the transient polarization spectral evolution feature set, the real-time drift trajectory of the characteristic absorption peak position at different temperature points is tracked, and the temperature points where the drift rate changes significantly are marked as thermally induced redshift abrupt temperature. At the same time, the thermal response inertia index is calculated. The sample that has completed the multi-field coupling test is transferred to the near-field photothermal test cavity. According to the polarization state evolution law of the feature set, the incident polarization state of the tunable pulsed laser source is adjusted to match the intrinsic polarization sensitive axis of the sample at the current temperature. Under the matching condition, a transient pulsed photothermal excitation that matches the plasma resonance energy level on the surface of the metal oxide layer is applied. Using a scanning near-field thermal radiation probe array, time-series data of evanescent thermal radiation intensity evolving over time are collected in the nanoscale air gaps on the sample surface, and real-time thermal frequency shift data of surface plasmon resonance caused by the accumulation of hot carriers are simultaneously tracked. Phase coupling analysis was performed on the evanescent wave thermal radiation intensity time series data and the surface plasmon resonance real-time thermal frequency shift data, and the phase relationship features between the two were extracted as transient response feature vectors.

5. The method for testing and evaluating the comprehensive photothermal performance of automotive window film according to claim 4, characterized in that, Based on the transient polarization spectral evolution feature set, the real-time drift trajectory of the characteristic absorption peak position at different temperature points is tracked. Temperature points where the drift rate changes significantly are marked as thermally induced redshift abrupt change temperatures. Simultaneously, the thermal response inertia index is calculated, specifically including: Based on the transient polarization spectral evolution feature set, the characteristic absorption bands of the window film under test in the near-infrared band are selected, the characteristic absorption peak positions in the bands at different temperature points are extracted, and the real-time drift trajectory of the characteristic absorption peak positions as temperature changes is constructed. After smoothing the real-time drift trajectory to remove noise interference, its first derivative is calculated as the instantaneous redshift rate curve, and then the second derivative is calculated to identify the rate of change of the redshift rate. The temperature point at which the absolute value of the second derivative first exceeds a preset threshold is marked as the thermally induced redshift abrupt change temperature, and the preset threshold is determined based on a reference sample without thermally induced drift. Meanwhile, the absolute value of the instantaneous redshift rate is integrated over the entire temperature range to obtain the thermal response inertia index. The integration interval covers the entire heating process from the initial temperature to the preset maximum temperature.

6. The method for testing and evaluating the comprehensive photothermal performance of automotive window film according to claim 5, characterized in that, Phase coupling analysis is performed on the evanescent wave thermal radiation intensity time series data and the real-time thermal frequency shift data of surface plasmon resonance. The phase relationship features between the two are extracted as transient response feature vectors, specifically including: The evanescent wave thermal radiation intensity time series data and the surface plasmon resonance real-time thermal frequency shift data are preprocessed with time axis alignment. The two sets of time-series data after alignment are subjected to Fourier transform and converted to the frequency domain space to extract the phase angle information of the evanescent wave thermal radiation intensity spectrum and thermal frequency shift spectrum at the characteristic frequency. Calculate the phase difference between the evanescent wave thermal radiation intensity spectrum and the thermal frequency shift spectrum at the characteristic frequency, and simultaneously calculate the coherence coefficient of the two sets of time series data in the characteristic frequency band. Combine the phase difference and the coherence coefficient to construct a two-dimensional transient response feature vector.

7. The method for testing and evaluating the comprehensive photothermal performance of automotive window film according to claim 6, characterized in that, The process involves measuring the irreversible redshift after cooling, calculating the entropy production rate and the irreversible degradation index, and integrating the thermally induced redshift abrupt change temperature, thermal response inertia index, irreversible redshift, and phase delay time to generate a photothermal integrated durability coefficient. This results in a service life prediction and climate adaptability rating, specifically including: The window film under test is naturally cooled from the preset maximum temperature back to the initial temperature. The acquisition system obtains the recovered absorption spectrum after cooling, extracts the characteristic absorption peak position after recovery, and calculates the irreversible redshift. Based on the transient polarization spectral evolution feature set, transient response feature vector, and irreversible redshift, the photothermal conversion entropy yield of the sample under dynamic thermal-humidity-mechanical multi-field coupling is calculated. Based on the cumulative effect of the photothermal conversion entropy production rate over multiple thermal cycles, an irreversible degradation index is constructed. The thermally induced redshift abrupt change temperature, thermal response inertia index, irreversible redshift amount, and phase delay features in the transient response feature vector are integrated to generate an entropy production-weighted photothermal comprehensive durability coefficient. Based on the combined distribution of the irreversible degradation index and the photothermal durability coefficient, and in accordance with the preset climate zone database, the multi-field coupled service life prediction value of the sample and the corresponding extreme climate adaptability level label are output.

8. The method for testing and evaluating the comprehensive photothermal performance of automotive window film according to claim 7, characterized in that, The test window film is naturally cooled from the preset maximum temperature back to its initial temperature. The acquisition system obtains the recovered absorption spectrum after cooling, extracts the characteristic absorption peak positions, and calculates the irreversible redshift, specifically including: After completing the transient pulsed photothermal excitation test, immediately shut down the tunable pulsed laser source and the heating system of the near-field photothermal test cavity, so that the window film sample under test can be slowly cooled back to the initial temperature from the preset maximum temperature at a natural cooling rate. After the sample temperature stabilizes and drops back to the initial temperature and is kept constant for at least 10 minutes, the full Stokes polarization spectroscopy acquisition system is restarted to obtain the recovery absorption spectrum curve of the window film after cooling. Peak analysis is performed on the recovered absorption spectrum curve to extract the recovered characteristic absorption peak positions. The offset of the recovered characteristic absorption peak positions relative to the initial reference peak positions is calculated, and its absolute value is taken as the irreversible redshift.

9. The method for testing and evaluating the comprehensive photothermal performance of automotive window film according to claim 8, characterized in that, Based on the transient polarization spectral evolution feature set, transient response feature vector, and irreversible redshift, the photothermal conversion entropy yield of the sample under dynamic thermal-humidity-mechanical multi-field coupling is calculated, specifically including: Based on the transient polarization spectral evolution feature set, the polarization state drift rate of the sample at different temperature points is extracted. Based on the transient response feature vector, the heat flux density change rate corresponding to the evanescent wave thermal radiation intensity time series data and the polarization state change rate corresponding to the real-time thermal frequency shift data are extracted. Based on the principle of non-equilibrium thermodynamics, the conjugate thermodynamic force corresponding to the rate of change of heat flux density is defined as the combination of the reciprocal of the temperature gradient and the local temperature fluctuation, and the conjugate thermodynamic force corresponding to the rate of change of polarization state is defined as the product of the chemical potential gradient and the polarization state coupling coefficient. Within the near-field interaction region of the sample surface, the space is discretized into several nanoscale micro-elements. The instantaneous product of thermodynamic flow and corresponding thermodynamic force is calculated within each micro-element. The product is then integrated over all micro-elements in the spatial domain to obtain the instantaneous photothermal conversion entropy yield at a certain moment. The instantaneous photothermal conversion entropy yield is integrated in the time domain over the entire duration of the transient pulsed photothermal excitation, and then weighted and corrected by the irreversible redshift to obtain the cumulative photothermal conversion entropy yield of the sample over the complete thermal cycle.

10. A comprehensive photothermal performance testing and evaluation system for automotive window films, characterized in that, A method for testing and evaluating the comprehensive photothermal performance of an automotive window film as described in any one of claims 1-9 includes: The multi-field coupled environment simulation module includes a bidirectional curvature adjustment device, a programmed temperature control unit, and a pulsed humidification unit. The bidirectional curvature adjustment device is used to carry the window film sample under test and cyclically switch between convex and concave curvature states at a preset frequency. The programmed temperature control unit is used to apply periodic thermal cycling excitation with independently adjustable heating and cooling rates to the sample surface. The pulsed humidification unit is used to apply pulsed humidity excitation asynchronous to the thermal cycling period to the sample surface. The all-Stokes polarization spectroscopy acquisition module is used to acquire transient polarization spectral data of the polarization state of a sample at multiple characteristic wavelengths over time during dynamic thermal-humidity-mechanical multi-field coupling, with a preset sampling interval. The near-field photothermal testing module includes a built-in tunable pulsed laser source and a scanning near-field thermal radiation probe array. The tunable pulsed laser source is used to adjust the incident polarization state according to the polarization spectrum characteristics to match the intrinsic polarization sensitive axis of the sample and apply transient pulsed photothermal excitation. The scanning near-field thermal radiation probe array is used to acquire the evanescent wave thermal radiation intensity time series data in the nanoscale air gaps on the sample surface and simultaneously track the surface plasmon resonance thermal frequency shift data. The data processing and control module is connected to the multi-field coupled environment simulation module, the full Stokes polarization spectrum acquisition module, and the near-field photothermal testing module. It is used to synchronously record real-time curvature radius data, real-time temperature data, and real-time relative humidity data, construct a transient polarization spectral evolution feature set, extract the thermally induced redshift abrupt change temperature, thermal response inertia index, and transient response feature vector, calculate the irreversible redshift, photothermal conversion entropy yield, and irreversible degradation index, generate a photothermal comprehensive durability coefficient, and output the service life prediction value and climate adaptability level label.

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