A system and method for self-diagnosis and service prompting of an active automotive glazing

Abstract

Disclosed herein is a self-diagnosis and service prompting system (100) and a method (300) for an automotive glazing The system comprises one or more acquisition units (101, 102) to obtain static parameters and dynamic parameters with respect to the PDLC assembly (103) and a control unit (104) operably configured with the PDLC assembly (103) to identify the pre-mature aging of said PDLC assembly (103) by identifying critical deviations from performance based on the differences obtained from an ideal state and a present state at a preferred time. The system has a user interface (108) configured with the control unit (104) to receive alerts for service prompts, upon identification of a critical deviation. The disclosed invention provides prompt for service for a PDLC glazing, if a probable fault, failure, or pre-matured end of life is predicted by the self-diagnosis system.

Description

[0001] A SYSTEM AND METHOD FOR SELF-DIAGNOSIS AND SERVICE PROMPTING OF AN ACTIVE AUTOMOTIVE GLAZING

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to active glazing including a switchable automotive glazing in general. Particularly, it relates to a solution for diagnosis of the condition of an active switchable automotive glazing. More particularly, it relates to a solution of self-diagnosis and service prompting for polymer-dispersed liquid crystals (PDLC) based automotive glazing.

[0004] BACKGROUND

[0005] Background description includes information that may be useful in understanding the present disclosure. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed disclosure, or that any publication specifically or implicitly referenced is prior art.

[0006] It is known to one skilled in the art that glazing refers to any and all the glass or similar material within a structure or the installation of any piece of glass or the similar material within a sash or frame. The glass windows of an automobile are referred to as glazing. For laminated glazing, two or more layers of glass or a similar material, are fused together with an interlayer in the middle. The fusion is completed with pressure and heat, and it prevents the sheets of glass or the similar material from breaking. While some pieces of glass or the similar material might end up breaking into larger pieces, those pieces will stay together with the help of the interlayer, making it shatterproof. Windshield or windscreen, backlite, sidelite, quaterlite, sunroof etc., are regarded as some instances of glazing in a vehicle.

[0007] It is known that Polymer Dispersed Liquid Crystal (PDLC) based glazing are a type of smart glazing that includes a film which enables the transparency of the glazing in response to an electrical impulse or a voltage. When no voltage is supplied to the PDLC based glazing the liquid crystals are randomly arranged, and thus scattering the light as it permeates the screen. This results in an opaque appearance with haze and whenever, a voltage is applied, an electrical field is created between the connectors of the film causing the liquid crystals to align, thereby allowing light to pass through consequently turning the screen transparent. Such a PDLC film could be integrated in an automotive glazing (having laminated glass) to provide active glazing or active sunroof. These PDLC based glazing (like an active sunroof) switches from opaque or to transparent (tinted or non-tinted) in a very sophisticated manner, modulating light ambience and increasing comfort for the passengers in the vehicle. It is desirable for such active glazing to perform consistently to ensure user satisfaction and better experience. Accordingly, it would be desirable to have a regular or prompt servicing of such glazing.

[0008] Reference is made to CN107290884A that discloses a kind of comfort level self-adapting intelligent PDLC dimming glass control system. The PDLC dimming glass has a controller that controls the switch operating state of PDLC dimming glass according to the lookup result in a disclosed method. The system and method realize the transmittance that dimming glass is adaptively adjusted according to ambient brightness and without manual intervention. This solution is directed at a self-adapting intelligent PDLC dimming glass control, however, it does not disclose or suggest any features a service prompting feature or a self-diagnosis feature.

[0009] Another reference is made to US20210088867A1 that aims to providing a solution for the quality control of an electrochromic device. This solution is a subsequent to a stage of manufacturing of an electrochromic device. This disclosure talks about method may include directing a current tinting state of the electrochromic device to correspond to a first tinting state and receiving sensor data associated with the directing of the current tinting state of the electrochromic device to correspond to the first tinting state. The method may further include determining, based on the sensor data, whether a corrective action is to be performed for the electrochromic device and, responsive to determining the corrective action is to be performed, cause the corrective action to be performed. This solution does not talk about the self-diagnosis in manufacturing stage. However, this solution is unsuitable for scenarios where the active glazing is installed in a vehicle.

[0010] A further reference is made to US9360731B2 that provides an automated shade systems having controllers that use algorithms to control operation of the automated shade control system and components thereof. These algorithms may include information such as: 3-D models of a building and surrounding structures, shadow information, reflectance information, lighting and radiation information, information regarding one or more variable characteristics of glass, clear sky algorithms, log information related to manual overrides, occupant preference information, motion information, real-time sky conditions, solar radiation on a building, a total foot-candle load on a structure, brightness overrides, actual and / or calculated BTU load, time-of-year information, and microclimate analysis. However, this prior art document is also silent on how to deal with service prompting for the shade control system.

[0011] Thus, insofar, there are no solutions that are directed at monitoring the condition of a PDLC switchable glazing, to predict any malfunction or pre-matured end of its life (i.e. the PDLC based switchable glazing or assembly being completely non-functioning) or make such observation to predict service prompt to the user. In view of the prior art solutions disclosed hitherto, it has been observed that there is a dire requirement of a solution that provides features of self-diagnosis and service prompting in an active glazing, especially PDLC based glazing.

[0012] SUMMARY OF THE DISCLOSURE

[0013] An object of the present invention is to provide a solution for overcoming the drawbacks of the prior art solutions.

[0014] Another object of the present invention is to provide a solution for self-diagnosis and service prompt in a PDLC switchable glazing.

[0015] Yet another object of the present invention is to provide a solution to preventively provide the probability of any fault, failure, or pre-matured end of life of the PDLC switchable glazing.

[0016] Still another object of the present invention is to provide a solution to prompt the user for servicing the PDLC switchable glazing before it failing to perform.

[0017] These and other objects of the invention are achieved by the following aspects of the invention. The following disclosure presents a simplified summary of the invention in order to provide a basic understanding of some aspects of the invention. This presents some concept of the invention in a simplified form to a more detailed description of the invention presented later. It is a comprehensive summary of the disclosure, and it is not an extensive overview of the present invention. The intend of this summary is to provide a fundamental understanding of some of the aspects of the present invention. In an aspect of the present invention is provided a self-diagnosis and service prompting system for an automotive glazing. The system comprises a laminated glazing having a first substrate a of glass or polymer, a second substrate b of glass or polymer, one or more interlayers, and an electrically switchable Polymer Dispersed Liquid Crystals PDLC assembly disposed between said first and second substrates. It further includes one or more acquisition units, to obtain static parameters and dynamic parameters with respect to the PDLC assembly. It has a control unit operably configured with the PDLC assembly to identify the pre-mature aging of said PDLC assembly by identifying critical deviations from performance based on the differences obtained from an ideal state and a present state at a preferred time; wherein said present state is determined by said static and dynamic parameters obtained from one or more acquisition units. It has a user interface configured with the control unit to receive alerts for service prompts, upon identification of a critical deviation. The static parameters include the specification data of the PDLC assembly. The system comprising a storage unit to configured to store said specification data defining the physics model of the PDLC assembly. Said dynamic parameters include at least measured electrical data and ambience data of the PDLC assembly and the control unit is operably coupled with one or more acquisition units to obtain said dynamic parameters. The control unit is configured to determine the pre-mature aging based on a change in physics model of the PDLC assembly, wherein said change in physics model may be obtained as function of present state and input voltage applied, for given input voltage. The one or more acquisition units includes an electrical module of the control unit to obtain voltage applied, current drawn and power data. The one or more acquisition units comprises a camera unit to obtain the ambient light measure and a positioning device to obtain the location details of the vehicle, wherein said ambience data include light intensity data, transparency data, temperature data, and sun angle. The one or more acquisition units comprises a temperature sensor, disposed between first and second substrates a, b of the glazing, configured to obtain the Joule heating effect on the PDLC assembly. The control unit is configured to obtain the difference between the ideal state and the present state for a same input voltage at a preferred time, said preferred time being identified during instances of a state of transient change in transparency. The system further comprises a remote computing unit configured with the control unit via a network. The computing unit is configured to monitor the physics model at one or more pre-determined conditions, and to record it over a period, wherein said predetermined conditions include at least -state of being ‘ON’, a state of being ‘OFF’ and a state being in transient change in transparency, on state, off state and change in transparency level of PDLC. The computing unit is further configured to estimate the physics model change, analyse said estimated physical model using a machine learning module to predict the prematured aging of the PDLC film, said pre-mature aging being provided by an estimate time to failure of performance of the PDLC film. The computing unit and the control unit are operably configured to a vehicle electronic control unit to securely communicate a service prompt of the PDLC assembly based on the prediction on pre-mature aging of the PDLC assembly.

[0018] In another aspect of the present invention is provided, a method for self-diagnosis and service prompting for a Polymer Dispersed Liquid Crystal PDLC assembly in an automotive glazing. Said method comprises the steps of obtaining, by one or more acquisition units, one or more static and dynamic parameters to determine a state of a glazing, detecting, by a control unit, for deviation in the state of the glazing for obtaining an impact level and conditionally triggering, by the control unit or computation unit, a master control unit for obtaining a risk factor on the state of the glazing, wherein the master control unit is triggered, if an obtained impact level is more than a set threshold value. It further includes the step of communicating, by the master control unit, a cautionary message indicating the risk of the glazing. The method further includes detecting for deviation in the state of the glazing comprises obtaining, by the control unit, amplitude and frequency of signal sensed through the material of the glazing and comparing, by the control unit, the changes in obtained amplitude and frequency of signal with pre-determined values. The step of determining, by the control unit, a state of the glazing, wherein the said state is obtained by determining the impact level and one or more parameters of glazing, for communicating to the user interface the cautionary message and a service prompt.

[0019] The present invention provides a solution for monitoring of PDLC switchable glazing, predict any malfunction or pre-matured end of its life against pre-defined conditions. The target of the invention is to prompt for service preventively in case of probable fault, failure, or pre-matured end of life. The invention is directed towards identifying the maximum change in the output of PDLC switchable glazing at pre-determined states. The pre-determined states include switching of one or more PDLC glazing, switching of one or more PDLC glazing. The selfdiagnosis solution proposes to execute at pre-determined state only to save power in the controller. The significant features of the present invention and the advantages of the same will be apparent to a person skilled in the art from the detailed description that follows in conjunction with the annexed drawings.

[0020] BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The following briefly describes the accompanying drawings, illustrating the technical solution of the embodiments of the present invention or the prior art, for assisting the understanding of a person skilled in the art to comprehend the invention. It would be apparent that the accompanying drawings in the following description merely show some embodiments of the present invention, and persons skilled in the art can derive other drawings from the accompanying drawings without deviating from the scope of the disclosure.

[0022] FIG. 1 illustrates a block diagram of the system according to an embodiment of the present invention.

[0023] FIG. 2 illustrates a graphical representation of the deviation observed in the functioning of the PDLC assembly according to an embodiment of the present invention.

[0024] FIGs. 3A-3B illustrate graphical representations of the sampling data deviation in the PDLC assembly according to an embodiment of the present invention.

[0025] FIG. 4 illustrates another block diagram of the system according to an embodiment of the present invention.

[0026] FIG. 5 illustrates a schematic diagram of a switchable glazing according to an embodiment of the present invention.

[0027] FIG. 6 illustrates a block diagram of the method according to an embodiment of the present invention.

[0028] Persons skilled in the art will appreciate that elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of embodiments of the disclosure.

[0029] DETAILED DESCRIPTION

[0030] The present disclosure is now discussed in more detail referring to the drawings that accompany the present application. It would be appreciated by a skilled person that this description to assist the understanding of the invention, but these are to be regarded as merely exemplary.

[0031] The terms and words used in the following description are not limited to the bibliographical meanings and the same are used to enable a clear and consistent understanding of the invention. Accordingly, the terms / phrases are to be read in the context of the disclosure and not in isolation. Additionally, descriptions of well-known functions and constructions are omitted for clarity and conciseness.

[0032] The present invention is directed towards a solution for monitoring the condition a PDLC switchable glazing to predict its malfunction or pre-matured end of its life, such a prediction is being performed with pre-defined conditions. The disclosed solution provides the features to prompt for service preventively. The monitoring feature may be regarded as self-diagnosis technique. The system depends its diagnosis analysis on available measurements at an electronic control unit (or simply referred as control unit) of the PDLC. Such measurements include but not limited to current and voltage. Additionally, the control unit may take into account other optional parameters as well such as light intensity from a camera. Said camera may be disposed at a suitable place in the vehicle and may be used for purposes like detection of driver drowsiness. The control unit is advantageously configured to identify the maximum change in the output of the PDLC switchable assembly at pre-determined states. The predetermined states include switching of one or more PDLC switchable assembly.

[0033] In an embodiment of the present invention is disclosed a self-diagnosis and service prompting system (100) for an automotive glazing. Reference is made to FIG. 1 that depicts a block diagram of the said system. The system (100) comprises a laminated glazing (200). A laminated glazing, usually, has a first substrate (201a) of glass or polymer, a second substrate (201b) of glass or polymer and one or more interlayers (202, 203). The disclosed glazing (200) further includes an electrically switchable PDLC assembly (103) disposed between said first and second substrates (201a, 201b). In a preferred embodiment, there may be at least two interlayers and the PDLC assembly is disposed between said interlayers. The system (100) comprises a control unit (104) operably configured with the PDLC assembly. The control unit (104) is configured to identify the pre-mature aging of said PDLC assembly (103) by identifying critical deviations from performance. For the evaluation of the same, the control unit is configured with one or more acquisition units (101, 102). The one or more acquisition units (101, 102) are configured to obtain static parameters and dynamic parameters with respect to the PDLC assembly (103). The control unit (104) is configured to provide the service prompt based on evaluation on the differences obtained from an ideal state and a present state at a preferred time. The present state may be determined by said static and dynamic parameters obtained from one or more acquisition units. The system further includes a user interface (108) configured with the control unit (104) to receive alerts for service prompts, upon identification of a critical deviation.

[0034] The static parameters refer to those numerical or other measurable factor that do not change for a given PDLC assembly. For instance, the static parameters include the physics of the PDLC assembly or film. This may be acquired via the specification of PDLC film, that contain information such as the dimensions of the film, the temperature tolerances, voltage, energy use and the like. Dynamic parameters refer to those numerical or other measurable factor that changes for a given PDLC assembly. This may include measured current at a given instance of time. In an embodiment of the present invention, the system includes a remote computing unit (105) configured with the control unit (104) via a network. The computing unit (105) is configured to monitor the physics model at one or more pre-determined conditions, and to record it over a period. The computing unit (105) may be and not limited to a cloud-based server.

[0035] In an embodiment of the present invention, the static parameters may include the specification data of the PDLC assembly (103) which may be stored in a storage unit (1041) of the selfdiagnosis system. Said storage unit (1041) is configured to store said specification data defining the physics model of the PDLC assembly. The dynamic parameters may include at least measured electrical data and ambience data of the PDLC assembly (103). The control unit (104) may be operably coupled with one or more acquisition units to obtain said dynamic parameters. In an embodiment of the present invention, the computing unit (105) is configured identify the any state change of PDLC assembly that leads to pre-matured end of life of it. FIG. 2 provides a graphical representation of how the deviation from normal behaviour may be observed in a PDLC assembly. Once the computing unit (105) identifies the deviation as critical, signal is provided to a user interface (108) for intimating the user for service of the PDLC assembly.

[0036] In an implementation, if the computing unit (105) determines, change in PDLC electrical characteristics, self-correction in the control of voltage current of PDLC, it performs the verification to determine if it falls within a predefined tolerance. If the observed changes fall within said tolerance, the desired transparency would be achieved and the PDCL may function fine. However, if it does not fall within the predefined tolerance, it is identified as a critical deviation. In an implementation, the self-diagnosis by the computing unit (105) is configured to be executed at a pre-determined state to advantageously save power in the controller. The computing unit (105) is further configured to estimate the physics model change, analyse said estimated physical model using a machine learning module to predict the pre-matured aging of the PDLC film, said pre-mature aging being provided by an estimate time to failure of performance of the PDLC film. In an implementation, said pre-determined conditions may include at least state of being ‘ON’, a state of being ‘OFF’ and a state being in transient change in transparency, on state, off state and change in transparency level of PDLC.

[0037] In an embodiment of the present invention is disclosed that the prediction of the self-diagnosis system of PLDC assembly may be made effective, and accurate when control unit (104) acquires different available and relevant sensor data. The so acquired data may be provided to the computing unit (105) to ensure accurate prediction. Such data may include sun angle obtained from a positioning device (like a global positioning system, GPS), transparency level, current, or voltage besides the ADAS camera sensing data. In an implementation, said one or more acquisition units (101, 102,...) may be an electrical module of the control unit (104) to obtain voltage applied, current drawn and power data. In another instance, the acquisition units (101, 102,...) comprises a camera unit to obtain the ambient light measure and a positioning device to obtain the location details of the vehicle, wherein said ambience data include light intensity data, transparency data, temperature data, and sun angle. The acquisition units (101, 102,...) may comprise a temperature sensor, disposed between first and second substrates (201a, 201b) of the glazing, configured to obtain the Joule heating effect on the PDLC assembly (103).

[0038] In embodiment of the present invention, the control unit (104) is configured to obtain the difference between the ideal state and the present state for a same input voltage at a preferred time, said preferred time being is identified during instances of a state of transient change in transparency. The difference in any change in physics of the PDLC model advantageously at state change or transient state. Example of state change are turning-on or turning-off by applying or removing input voltage. This may be attributed to change being identifiable in the measurement at the transient state, otherwise at steady state, change in the model is not identifiable in the measurement signature. Thus, for self-diagnosis, the control unit is configured to consider the effect of different available parameters for accurate prediction of the abnormalcy.

[0039] In an embodiment of the present invention, the control unit (104) is configured to determine the pre-mature aging based on a change in physics model of the PDLC assembly (103), wherein said change in physics model may be obtained as function of present state and input voltage applied, for given input voltage. The computing unit (105) is further configured to estimate the physics model change, analyse said estimated physical model using a machine learning module to predict the pre-matured aging of the PDLC film, said pre-mature aging being provided by an estimate time to failure of performance of the PDLC film.

[0040] The change in transparency level (in %) with the time when it turned on or off by the voltage is shown in FIGs. 3 A and 3B respectively. The objective disclosed herein to identify a change in physics Model of the PDLC assembly for same input voltage applied. Identifying the change in the physics advantageously facilitates to check if there is any deterioration of PDLC characteristics or if there are any loose electrical connections or any change in other optical properties of the PDLC glass. The monitoring of the state change is identified in the physics model at pre-determined conditions, and it is recorded over a period, to estimate the model changes predict the pre-matured state of failure.

[0041] In an embodiment of the present invention, the computing unit (105) is configured to include a machine learning model that takes in to account all measurable parameters (electrical - current, voltage, ambient- temperature, transparency, light intensity and the like) and the PDLC properties and determine change of PDLC physics and estimate remaining useful and time to failure of performance of the PDLC film. The computing unit (105) and control unit (104) are configured to a vehicle electronic control unit (106). The control unit (104) may adjust the input (voltage) to get the desired output (optical properties) desirable for the user, technical steps to confirm and inform the user for service options and improve user experience. The disclosed features provide an indication to the user on preventive severability options through different (SMS, HUD) notifications.

[0042] In an embodiment of the present invention is provided an embodiment of how the temperature sensor (110) is disposed within the laminated glazing as shown in FIG. 4. The measurement of surface temperature on PDLC glazing is either on / face 2 / face 3 (faces are sequentially numbered from 1 from substrate 201a for the side facing outside of glass laminate) of the sunroof. This is configured to function as the representative of solar heat load and Joule’s effect of the device. In an implementation, arriving at an estimated (lab-scale) measure as compared to a real lifetime dependent measure, indicates the accelerated failure curve of PDLC. The dynamic parameter thus obtained may be a representative measure of ambient and Joule’s effect from the PDLC assembly. In a preferred embodiment, sensing element are provided outside (face 1) and in face 2 to segregate solar heating load and Joule’s heating loading. Joule's heating is indicative of failure. In embodiment, the measure of temperature or heat flux between face 2 and face adjacent to connectors and adjacent to PDLC film, consisting of sensing element suitable thereof could be obtained as one of the parameters.

[0043] In an embodiment of the present invention is provided the self-diagnosis with the control unit (104), the computing unit (105) being configured with the vehicle electronic control unit (106). The control unit (104) may be an edge computing device and is powered by the vehicle power supply (109) as shown in FIG. 4. The computing unit (105) and the control unit (104) are operably configured to a vehicle electronic control unit to securely communicate a service prompt of the PDLC assembly based on the prediction on pre-mature aging of the PDLC assembly. The control unit (104) identifies the best measurement of dynamic parameters available. This may include measuring change in the response (like current, voltage, temperature, image quality at very start is first indication. The change is response at different transient state are obtained by the control unit (104). The control unit (104) further obtains the change in transient characteristics over a period. The computing unit uses machine learning module to identify this and is further configured to identify whether the change in the ECU is feasible with processing capacity and memory. The computing unit further configured to take preventive action by sending information to user via a user interface (108). FIGs. 3A-3B represents the sampling data.

[0044] In an embodiment of the present invention is provided a method for self-diagnosis and service prompting for a Polymer Dispersed Liquid Crystal (PDLC) assembly in an automotive glazing. The disclosed method, depicted in FIG. 6, comprises the steps of obtaining (S301), by one or more acquisition units, one or more static and dynamic parameters to determine a state of a glazing, detecting (S302), by a control unit, for deviation in the state of the glazing for obtaining an impact level and conditionally triggering (S303), by the control unit or computation unit, a master control unit for obtaining a risk factor on the state of the glazing, wherein the master control unit is triggered, if an obtained impact level is more than a set threshold value. The method further includes the step of communicating (S304), by the master control unit, a cautionary message indicating the risk of the glazing. The step of detecting (S302) for deviation in the state of the glazing comprises obtaining (S3021), by the control unit, amplitude and frequency of signal sensed through the material of the glazing and comparing (S3022), by the control unit, the changes in obtained amplitude and frequency of signal with pre-determined values. It further includes step of determining (S3023), by the control unit, a state of the glazing, wherein the said state is obtained by determining the impact level and one or more parameters of glazing. If a critical impact is detected it is communicated to the user interface as cautionary message and / or service prompt.

[0045] The disclosed system is configured to monitor the physics model at pre-determined conditions, state change for example and record over a period, estimate the model changes, extend the estimate with machine learning model changes to predict the pre-matured state of failure and finally inform the use through reliable channel of communication. The system uses available measurements (current, voltage, temperature, or image) and identify the best time to perform diagnosis. It involves identifying noticeable change in one or more outputs of PDLC switchable glass at the pre-determined state (turn on / tum off time for example) and decide whether to execute diagnosis algorithm or not based on amount of change in the measurement identified. In an implementation, the computing unit is configured to store state physics of PDLC glass at different pre-determined operating states, uses statistical data to differentiates healthy state and deteriorated state of PDLC. This helps in obtaining the historical data for training and improving the Al module. The disclosed solution adaptively adjusts input variables to get the desired output (optical output). It is executed in the control unit and is configured to initiate precautionary, preventive action, message to the user (either a display or a voice alert). The disclosed solution advantageous improves life, and serviceability of the active glazing.

[0046] Example Embodiments: In an exemplary embodiment of the present invention, the disclosed system may include the control unit being implemented as sensor / edge level ECU data processor. The computing unit being implemented as a remote or computing module configured to implement a machine learning module to analyse and provide the self-diagnosis of a state of the PDLC assembly. The data from the different sensors (like temperature data, electrical signals) may be obtained by said control unit for further processing. The control unit may be connected to the vehicle electronic control unit via a local area network (LAN) or controller area network (CAN). The vehicle power supply may be provided to the Control unit. The control unit is configured to the remote computing unit in a wireless manner. The computing unit in turn is configured with the vehicle control unit and an user interface for service prompting.

[0047] In an exemplary embodiment of the present invention, the control unit is configured to obtain measured signals data (current, voltage, temperature) and ambient data which include sun angle / GPS, temperature, light intensity. The control unit is further configured to identify a right state or time based on predetermined conditions like turn on, turn off, peak, dip, and not necessarily steady state. The control unit is further to obtain a data sheet or initial PDLC parameters (which include number of PDLC, length, width and the like). The control unit is further configured to determine parameters that impact the dynamics of PDLC (such as maximum current per maximum transparency, time to settle transparency and the like). All required sensor data, inherent PDLC properties and the monitored the condition of PDLC assembly data are collected by the control unit and provided to the computing unit. The computing unit is a remote computing engine. The computing unit or the control unit is configured to estimate the deviation in output response for given same input with the present conditions. The computing is then configured to analyse the deviation with all historical data, events, changes. The computing unit includes a machine learning module to identify condition of PDLC assembly and extend the model prediction. The computing unit is configured to check the deviation from a pre-defined optical performance per given electrical inputs. If there is no deviation, the regular checks are repeated for self-diagnosis. But if there is a deviation, computing unit is configured to identify the percentage of deviation of optical performance to adjust electrical input to get desired optical performance. Additionally, the computing unit is configured to predict the remaining useful time and send a short message service to vehicle owner and prompt for service with time to service. The obtained data, prediction is pushed into a cloud storage for training the machine learning module.

[0048] Industrial Applicability: The disclosed solution finds several use cases of self-diagnosis of PDLC based active glazing and it improves the thermal comfort of users, the serviceability of glass, user experience and the life expectancy of the glass and the energy efficient of the entire system.

[0049] Some advantages of the present invention are enlisted in the following:

[0050] • The self-diagnosis, and service prompting feature as per the present invention provides users to pro-actively plan for preventive maintenance.

[0051] • The disclosed solution is proposing to execute at pre-determined state only to save power in the controller.

[0052] • It provides better user-experience and energy efficiency.

[0053] Many alterations and modifications of the present invention will no doubt become apparent to a person skilled in the art after having read the foregoing description. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. It is to be understood that the description above contains many specifications, these should not be construed as limiting the scope of the invention but as merely providing illustrations of some of the personally preferred embodiments of this invention. Thus, the scope of the invention should be determined by the appended claims and their legal equivalents rather than by the examples given. Features that are described and / or illustrated with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments and / or in combination with or instead of the features of the other embodiments.

[0054] List of reference numerals appearing in the accompanying drawings and the corresponding features:

[0055] 200: glazing

[0056] 201a: first substrate

[0057] 201b: second substrate 02: interlayer

[0058] 100: system

[0059] 101, 102: acquisition unit

[0060] 103: PDLC unit

[0061] 104: control unit

[0062] 105: computational unit

[0063] 106: Vehicle Electronic control unit

[0064] 108: user interface

[0065] 110: temperature sensor

[0066] 300: method

[0067] S301 -S304: method steps

Claims

CLAIMS1. A self-diagnosis and service prompting system (100) for an automotive glazing, wherein said system comprises: a laminated glazing (200) having a first substrate (201a) of glass or polymer; a second substrate (201b) of glass or polymer; one or more interlayers (202, 203) and an electrically switchable Polymer Dispersed Liquid Crystals (PDLC) assembly (103) disposed between said first and second substrates (201a, 201b); one or more acquisition units (101, 102) to obtain static parameters and dynamic parameters with respect to the PDLC assembly (103); a control unit (104) operably configured with the PDLC assembly (103) to identify the pre-mature aging of said PDLC assembly (103) by identifying critical deviations from performance based on the differences obtained from an ideal state and a present state at a preferred time; wherein said present state is determined by said static and dynamic parameters obtained from one or more acquisition units; and a user interface (108) configured with the control unit (104) to receive alerts for service prompts, upon identification of a critical deviation.

2. The system (100) as claimed in claim 1, wherein said static parameters include the specification data of the PDLC assembly (103); said system comprising a storage unit (1041) to configured to store said specification data defining the physics model of the PDLC assembly.

3. The system (100) as claimed in any one of the preceding claims, wherein said dynamic parameters include at least measured electrical data and ambience data of the PDLC assembly (103); and the control unit (104) is operably coupled with one or more acquisition units to obtain said dynamic parameters.

4. The system (100) as claimed in any one of the preceding claims, wherein said control unit (104) is configured to determine the pre-mature aging based on a change in physics modelof the PDLC assembly (103), wherein said change in physics model may be obtained as function of present state and input voltage applied, for given input voltage.

5. The system (100) as claimed in any one of the preceding claims, wherein said one or more acquisition units includes an electrical module of the control unit (104) to obtain voltage applied, current drawn and power data.

6. The system (100) as claimed in any one of the preceding claims, wherein said one or more acquisition units comprises a camera unit to obtain the ambient light measure and a positioning device to obtain the location details of the vehicle, wherein said ambience data include light intensity data, transparency data, temperature data, and sun angle.

7. The system (100) as claimed in any one of the preceding claims, wherein said one or more acquisition units comprises a temperature sensor, disposed between first and second substrates (201a, 201b) of the glazing, configured to obtain the Joule heating effect on the PDLC assembly (103).

8. The system (100) as claimed in any one of the preceding claims, wherein the control unit (104) is configured to obtain the difference between the ideal state and the present state for a same input voltage at a preferred time, said preferred time being identified during instances of a state of transient change in transparency.

9. The system (100) as claimed in any one of the preceding claims, further comprises a remote computing unit (105) configured with the control unit (104) via a network; wherein said computing unit (105) is configured to monitor the physics model at one or more pre-determined conditions, and to record it over a period, wherein said pre-determined conditions include at least -state of being ‘ON’, a state of being ‘OFF’ and a state being in transient change in transparency, on state, off state and change in transparency level of PDLC.

10. The system (100) as claimed in any one of the preceding claims, wherein the computing unit (105) is further configured to estimate the physics model change, analyse said estimated physical model using a machine learning module to predict the pre-matured aging of the PDLC film, said pre-mature aging being provided by an estimate time to failure of performance of the PDLC film.

11. The system (100) as claimed in any one of the preceding claims, wherein the computing unit (105) and the control unit (104) are operably configured to a vehicle electronic control unit to securely communicate a service prompt of the PDLC assembly based on the prediction on pre-mature aging of the PDLC assembly.

12. A method for self-diagnosis and service prompting for a Polymer Dispersed Liquid Crystal (PDLC) assembly in an automotive glazing, wherein said method comprises the steps of: obtaining (S301), by one or more acquisition units, one or more static and dynamic parameters to determine a state of a glazing; detecting (S302), by a control unit, for deviation in the state of the glazing for obtaining an impact level; conditionally triggering (S303), by the control unit or computation unit, a master control unit for obtaining a risk factor on the state of the glazing, wherein the master control unit is triggered, if an obtained impact level is more than a set threshold value; and communicating (S304), by the master control unit, a cautionary message indicating the risk of the glazing.

13. The method (300) as claimed in claim 12, wherein detecting (S302) for deviation in the state of the glazing comprises: obtaining (S3021), by the control unit, amplitude and frequency of signal sensed through the material of the glazing; and comparing (S3022), by the control unit, the changes in obtained amplitude and frequency of signal with pre-determined values.

14. The method (300) as claimed in claim 12, comprises determining (S3023), by the control unit, a state of the glazing, wherein the said state is obtained by determining the impact level and one or more parameters of glazing, for communicating to the user interface the cautionary message and a service prompt.

Images