Backlight energy efficiency optimization method for liquid crystal display screen of mobile phone

Abstract

The invention relates to the technical field of liquid crystal display screens, in particular to a mobile phone liquid crystal display screen backlight energy efficiency optimization method, which comprises the following steps of: dynamically adjusting backlight brightness according to ambient light intensity and characteristics of display contents; a local dimming technology is adopted in different areas of the display screen, and backlight brightness of each area is adjusted according to brightness distribution of display content; a quantum dot material is introduced into the backlight source, so that the lighting effect of backlight is optimized; preparing a quantum dot-polymer composite film; regulating and controlling the thickness and the uniformity of the film; the thin film is integrated on a mobile phone LCD backlight module; optimizing the emission spectrum to match the transmission efficiency of the LCD and the color filter; local dimming is combined, and backlight brightness is dynamically adjusted; and designing an intelligent optimization control algorithm, and automatically adjusting the working mode of the backlight system according to the use state of the mobile phone and the environment change. Compared with the prior art, the method for optimizing the backlight energy efficiency of the liquid crystal display screen of the mobile phone has the advantages that the backlight brightness and the color temperature are accurately adjusted by introducing a quantum dot film technology and an intelligent control algorithm, the lighting effect of a backlight system is optimized, the display effect is improved, the energy consumption is reduced, the battery life is prolonged, and more comfortable user experience is provided.

Description

The present application relates to the technical field of liquid crystal display screens, and in particular to a mobile phone liquid crystal display screen backlight energy efficiency optimization method. With the popularization of smart phones, the energy efficiency of liquid crystal display screens as the main display device has attracted increasing attention. The backlight system of a liquid crystal display screen is usually composed of multiple LED light sources, and the display effect is achieved by adjusting the backlight brightness. However, in the traditional backlight adjustment scheme, the backlight brightness is usually simply adjusted according to the user's ambient brightness or the set display mode, and this method does not fully consider the optimal configuration and intelligent adjustment strategy of the backlight light source, and therefore has problems such as low energy efficiency utilization rate and poor brightness uniformity. In order to overcome the above problems, the present application provides a mobile phone liquid crystal display screen backlight energy efficiency optimization method which can effectively solve the above problems.

[0001] A technical solution provided by the present application to solve the above technical problems is to provide a mobile phone liquid crystal display screen backlight energy efficiency optimization method, comprising the following steps: Step S1, dynamically adjusting the backlight brightness according to the ambient light intensity and the characteristics of the display content; Step S2, using local dimming technology in different areas of the display screen, and adjusting the backlight brightness of each area according to the brightness distribution of the display content; Step S3, introducing quantum dot materials in the backlight source to optimize the light efficiency of the backlight; In the step S3, the following steps are included: Step S31, preparation of a quantum dot-polymer composite film; Step S32, controlling the film thickness and uniformity; Step S33, integrating the film in the mobile phone LCD backlight module; Step S34, optimizing the emission spectrum to match the transmission efficiency of the LCD and the color filter; Step S35, combining local dimming and dynamic adjustment of the backlight brightness; Step S4, designing an intelligent optimization control algorithm to automatically adjust the working mode of the backlight system according to the mobile phone usage state and environmental changes. Preferably, in the step S31, quantum dots with high photoluminescence efficiency are synthesized in advance; then they are dispersed in an optically transparent high-transparency polymer resin to form a composite material that is uniformly dispersed, has no aggregation, and is suitable for large-area coating; and the composite film is packaged and sealed.

[0002] ​​​Preferably, in step S33, the prepared quantum dot film is placed in the backlight module of the mobile phone LCD, preferably between the blue LED excitation source and the light guide plate, or as part of the light guide plate, so as to achieve efficient down-conversion of blue light to red, green and blue primary color light.

[0003] Preferably, in step S34, a multi-objective optimization method is used to optimize the red and green QD ratio, film thickness, blue light excitation wavelength, and quantum dot concentration parameters of the quantum dot film, so that the emission spectrum matches the color filter band of the mobile phone LCD panel as closely as possible, thereby reducing the light absorption loss of the color filter and improving the transmission efficiency.

[0004] Preferably, step S4 includes the following steps: Step S41: Multi-dimensional perception data acquisition and processing; Step S42, Intelligent optimization control algorithm design; Step S43, Dynamic backlight mode adjustment; Step S44, User Behavior Analysis and Adaptive Optimization; Step S45, Intelligent Feedback and Optimization; Step S46, Energy Efficiency Management and Optimization.

[0005] Preferably, step S41 includes the following steps: Step S411: Ambient light sensor data acquisition; Step S412, mobile phone usage status and scene detection; Step S413: Display content feature extraction.

[0006] Preferably, step S42 includes the following steps: Step S421, Data fusion and multi-dimensional input analysis; Step S422, Scene Adaptive Algorithm Design.

[0007] Preferably, step S43 includes the following steps: Step S431: Adjust backlight brightness based on ambient light and usage status; Step S432: Joint adjustment of color temperature and brightness.

[0008] Preferably, step S44 includes the following steps: Step S441, User behavior analysis and prediction model; Step S442, Personalized brightness adjustment.

[0009] Preferably, step S45 includes step S451, a real-time feedback and optimization mechanism; and step S46 includes step S461, energy efficiency optimization control.

[0010] Compared with existing technologies, the mobile phone LCD screen backlight energy efficiency optimization method of the present invention introduces quantum dot thin film technology and intelligent control algorithm to precisely adjust the backlight brightness and color temperature, optimize the light efficiency of the backlight system, improve the display effect, reduce energy consumption, extend battery life, and provide a more comfortable user experience. [Attached Image Description] Figure 1 This is a flowchart of the method for optimizing the backlight energy efficiency of a mobile phone LCD screen according to the present invention; Figure 2 This is a flowchart of step S3 of the method for optimizing the backlight energy efficiency of a mobile phone LCD screen according to the present invention.

Detailed Implementation Methods

[0011] It should be noted that in the embodiments of the present invention, all directional indications (such as up, down, left, right, front, back, etc.) are limited to relative positions on the specified view, rather than absolute positions.

[0012] Furthermore, in this invention, descriptions involving "first," "second," etc., are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0013] Please see Figure 1 and Figure 2 The method for optimizing the backlight energy efficiency of a mobile phone LCD display according to the present invention includes the following steps: Step S1: Dynamically adjust the backlight brightness based on the ambient light intensity and the characteristics of the displayed content.

[0014] Step S2: Use local dimming technology in different areas of the display screen to adjust the backlight brightness of each area according to the brightness distribution of the displayed content.

[0015] Step S3: Introduce quantum dot materials into the backlight to optimize the backlight's luminous efficiency.

[0016] Step S4: Design an intelligent optimization control algorithm to automatically adjust the working mode of the backlight system according to the phone's usage status and environmental changes.

[0017] Step S1 includes the following steps: Step S11: Multi-dimensional perception and data collection; Step S12, Intelligent optimization control algorithm design; Step S13: Dynamic backlight brightness and color temperature adjustment; Step S14, Personalized and intelligent optimization feedback mechanism; Step S15, Energy Efficiency Optimization and Battery Management; Step S16: Comprehensive adjustment and system adaptive optimization.

[0018] Step S11 includes the following steps: Step S111: Ambient light sensor data acquisition. The ambient light sensor collects real-time light intensity data of the surrounding environment. The intensity of ambient light affects the basic adjustment of the backlight brightness. Based on the current ambient light intensity, the system initially determines the backlight brightness range. Most existing technologies use a single ambient light intensity sensor for simple brightness adjustment, while this invention utilizes more precise ambient light data acquisition technology to provide more detailed ambient light feedback.

[0019] Step S112: Display content analysis and brightness feature extraction. Using image recognition technology and content analysis algorithms, the brightness distribution, color features, and contrast of the displayed content are analyzed in real time. For example, for bright images or video content, the system identifies bright areas and adjusts the backlight brightness according to the content requirements. Existing technologies typically adjust only based on the overall average brightness. This invention, through detailed analysis of the local brightness characteristics of the displayed content, performs precise adjustments, providing a more natural brightness transition.

[0020] Step S113, User visual comfort monitoring. By monitoring biosignals such as eye trackers or blink frequency, the system assesses the user's visual fatigue level in real time. Based on this data, the system dynamically adjusts the speed and magnitude of brightness changes to reduce visual fatigue and optimize the user's visual experience. Existing technologies typically lack consideration for user visual comfort; this invention, through bio-monitoring and visual comfort optimization, ensures that brightness adjustment is not only based on the environment and content but also fully considers the user's physiological perception.

[0021] Step S12 includes the following steps: Step S121, Data Fusion and Weighted Analysis. A data fusion algorithm is used to integrate multi-dimensional information such as ambient light data, display content features, and user behavior data. A weighted algorithm is then used to calculate the optimal backlight brightness adjustment scheme by combining the importance and real-time changes of each input source. In existing technologies, backlight brightness adjustment typically relies on a single data input source (such as considering only ambient light intensity or display content), while this invention, through multi-dimensional data fusion, makes backlight brightness adjustment more intelligent and precise.

[0022] Step S122, Scene-Adaptive Brightness Adjustment. Based on different usage scenarios (such as text browsing, video playback, game operation, etc.), this invention designs a scene-adaptive adjustment algorithm. The system dynamically adjusts the backlight brightness and color temperature according to the characteristics of the current scene. For example, the backlight brightness is increased when playing videos, and the brightness is appropriately reduced when reading text to reduce eye fatigue. Most existing technologies fix the brightness adjustment under a fixed scene setting, while the dynamic scene perception and adaptive adjustment of this invention can automatically optimize the backlight brightness and color temperature settings according to scene changes.

[0023] Step S13 includes the following steps: Step S131: Content-based brightness area optimization. This invention employs a local brightness optimization algorithm to independently adjust the backlight brightness of different areas based on the local brightness characteristics of the displayed content. For bright areas (such as bright white areas), the backlight brightness is increased; while for dark areas (such as black or dark areas), the backlight brightness is decreased to improve energy efficiency. Existing technologies typically unify brightness through global adjustment, while this invention, through local area optimization, adjusts the backlight according to the brightness distribution of the content, further improving display quality and energy efficiency.

[0024] Step S132, Adaptive Color Temperature Adjustment. This invention designs an automatic color temperature adjustment mechanism that adjusts the backlight color temperature based on ambient light and the color characteristics of the displayed content. For example, in low-light environments, the color temperature is automatically adjusted to a warm tone to reduce eye strain; while in bright environments, a cool tone is used to improve display clarity. Existing technologies typically only focus on brightness adjustment, while this invention considers color temperature adjustment simultaneously, providing dual optimization of brightness and color temperature to enhance the user's visual experience.

[0025] Step S14 includes the following steps: Step S141, User Behavior Analysis and Preference Learning. This invention uses deep learning algorithms to automatically learn user habits, such as device usage time and screen brightness preferences. The system dynamically optimizes based on the user's historical behavior and preferences, providing personalized backlight adjustment solutions. Existing technologies typically lack personalized learning capabilities, while this invention, through deep learning and behavior analysis, makes backlight adjustment more tailored to each user's needs.

[0026] Step S142, Intelligent Feedback and Real-time Adjustment. This invention uses an intelligent feedback system to monitor the phone's backlight brightness and ambient light changes in real time, ensuring that the backlight brightness matches the content, environment, and user needs. Whenever the ambient light or content changes, the system automatically adjusts the backlight brightness to ensure an optimal balance between display effect and battery life. Existing backlight adjustment technologies often rely on preset rules or static algorithms; this invention, through a real-time feedback and optimization mechanism, makes the adjustment more flexible and intelligent.

[0027] Step S15 includes the following steps: Step S151, Intelligent Energy Efficiency Management. This invention combines multiple factors such as ambient light intensity, displayed content, and usage scenario for energy efficiency management, minimizing battery consumption while maintaining good display performance. For example, when the ambient light intensity is high, the backlight brightness will automatically decrease, reducing unnecessary energy consumption. In existing technologies, energy efficiency management is often performed separately from brightness adjustment, while this invention combines energy efficiency with brightness adjustment, providing more efficient battery management and extending the phone's usage time.

[0028] Step S152, Battery Status Sensing and Adjustment. This invention designs a battery status sensing mechanism that monitors the remaining battery power in real time and optimizes backlight brightness based on battery status. When the battery is low, it automatically reduces backlight brightness or switches to power-saving mode to maximize battery life. Existing technologies typically manage batteries independently of brightness adjustment, while this invention achieves an optimal balance between battery life and display performance through joint optimization of battery and brightness adjustment.

[0029] Step S16 includes the following steps: Step S161, Comprehensive Adjustment and Adaptive Optimization. This invention utilizes a comprehensive adjustment system to intelligently adjust backlight brightness, color temperature, and energy efficiency based on real-time data from ambient light, display content, user behavior, usage scenarios, and battery status. This ensures adaptive optimization under various usage conditions. Existing technologies typically adjust each factor individually; this invention achieves more intelligent and efficient backlight management through multi-factor comprehensive adjustment.

[0030] Step S2 includes the following steps: Step S21: Real-time analysis of displayed content and detection of brightness distribution.

[0031] Step S22: Optimize the user visual perception model and brightness sensitivity.

[0032] Step S23: Dynamic area optimization and intelligent brightness adjustment algorithm.

[0033] Step S24: Intelligent feedback and real-time optimization.

[0034] Step S25: Comprehensive dimming optimization and energy efficiency improvement.

[0035] Step S21 includes the following steps: Step S211, Content Type Identification and Classification. Using image processing technology, the currently displayed content is analyzed to identify brightness features and color distribution in the image in real time. Through a content classification algorithm, the brightness distribution of the displayed content is preprocessed according to its type (e.g., video, image, text, webpage, etc.). Existing technologies typically only focus on the average distribution of overall brightness, while this invention further analyzes the local brightness features of the content, identifying bright and dark areas and optimizing local dimming.

[0036] Step S212: Generation of regional brightness distribution map. Based on the content type identification result, an image processing algorithm is used to generate a display area brightness distribution map, dividing the screen into several dynamically adjustable areas. The brightness value of each area is determined according to the brightness characteristics of the image content in that area. This invention introduces dynamic area division technology, which automatically adjusts the size and distribution of areas according to the actual brightness characteristics of different display content to achieve more precise local dimming.

[0037] Step S22 includes the following steps: Step S221, User Perception Difference Modeling. Based on the human visual perception characteristics (HVS), the impact of different brightness areas on the user's vision is analyzed. Using a visual perception model (such as the human eye's sensitivity to different brightness and color), the amplitude and speed of local brightness adjustment are optimized to ensure that the adjustment process has minimal impact on the user's visual experience. Existing technologies typically adjust backlighting through simple brightness changes, while this invention introduces a visual perception optimization model that adaptively adjusts brightness according to the user's visual sensitivity differences, making brightness changes more consistent with the natural perception patterns of the human eye.

[0038] Step S222: Adaptive control of brightness adjustment amplitude and speed. The adjustment speed and amplitude of the backlight brightness are adjusted according to the user's usage scenario (such as prolonged static reading, short video viewing, etc.). For example, in a static scenario, the backlight brightness adjustment amplitude is smaller and the transition speed is slower; while in a dynamic scenario, the backlight adjustment amplitude increases and the transition speed is faster. This invention can adjust the rate and amplitude of brightness adjustment according to scene changes, optimizing the user's visual experience, while existing technologies typically lack scene adaptability and have relatively simple backlight adjustment.

[0039] Step S23 includes the following steps: Step S231, Adaptive Brightness Adjustment Algorithm Design. Based on the local brightness distribution map and visual perception model, this invention designs an adaptive brightness adjustment algorithm to personalize the brightness of each area. The algorithm automatically selects different adjustment strategies according to different content (such as bright areas, dark areas, transition areas, etc.) to maintain the uniformity of the display effect and improve energy efficiency. Existing technologies typically use static brightness curves or simple local dimming strategies, while this invention, through an adaptive optimization algorithm, dynamically adjusts the backlight brightness under different content and environments, improving the accuracy and adaptability of the adjustment.

[0040] Step S232: Joint adjustment of local and global dimming. Based on multi-zone dimming, this invention proposes a joint adjustment mechanism of local and global dimming, automatically selecting either a local or global dimming strategy according to the displayed content and user needs. For relatively uniform display content (such as web pages, documents, etc.), global dimming is used; for display content with significant brightness differences (such as movies, games, etc.), local dimming technology is used to finely adjust the brightness of different areas. Most existing technologies only use one of local or global dimming, while this invention, through a joint adjustment mechanism, automatically selects the most suitable dimming mode based on the characteristics of the displayed content, avoiding unnecessary energy waste and improving the display effect.

[0041] Step S24 includes the following steps: Step S241, Real-time Feedback and Adjustment Optimization. This invention introduces a real-time feedback mechanism, using sensors to monitor changes in the display screen's brightness in real time and adjust backlight adjustment parameters accordingly. Based on changes in displayed content and ambient light, the system can provide real-time feedback on whether the current backlight brightness adjustment is reasonable and optimize the adjustment strategy based on the feedback data. Existing backlight adjustments mostly rely on preset modes, while this invention, through real-time feedback, ensures that each brightness adjustment is optimized based on actual conditions, providing higher accuracy and response speed.

[0042] Step S242, User-defined optimization mode. This invention supports user-defined backlight adjustment modes, such as adjusting the backlight brightness sensitivity according to the user's visual preferences and usage habits. The system analyzes the user's operating habits through machine learning and automatically adjusts the dimming strategy to adapt to the user's needs. Unlike the single-mode adjustment of existing technologies, this invention can dynamically adjust according to the user's personalized needs, further optimizing the user experience.

[0043] Step S25 includes the following steps: Step S251, Energy Efficiency Optimization Control. Building upon dimming optimization, this invention also considers energy efficiency optimization of the backlight system. By reducing ineffective brightness adjustments, the efficiency of the light source is optimized, achieving efficient energy management. For example, in low-brightness scenarios, local dimming reduces power consumption, while in high-brightness scenarios, backlight brightness is increased to meet display requirements, ensuring long battery life. Existing technologies largely focus on brightness optimization, while this invention incorporates energy efficiency optimization strategies alongside brightness optimization, improving the overall system's energy efficiency and extending battery life.

[0044] Step S4 includes the following steps: Step S41: Multi-dimensional perception data acquisition and processing.

[0045] Step S42, Intelligent optimization control algorithm design.

[0046] Step S43, Dynamic backlight mode adjustment.

[0047] Step S44, User Behavior Analysis and Adaptive Optimization.

[0048] Step S45, Intelligent Feedback and Optimization.

[0049] Step S46, Energy Efficiency Management and Optimization.

[0050] Step S41 includes the following steps: Step S411, Ambient light sensor data acquisition. The ambient light sensor collects the light intensity of the environment surrounding the mobile phone in real time. The intensity of ambient light is one of the fundamental bases for backlight adjustment and can affect the brightness adjustment range of the backlight system. In existing technologies, ambient light sensors are usually only used for basic brightness adjustment, while this invention improves sensing accuracy and adaptability by combining multiple sensor inputs.

[0051] Step S412, Phone Usage Status and Scene Detection. The phone's usage status and scene are detected using accelerometers, gyroscopes, and touch sensors. The current usage scene is determined by analyzing user actions (e.g., whether playing games, browsing web pages, reading documents, watching videos, etc.) and the phone's physical state (e.g., whether it is stationary or moving). Existing technologies often categorize usage scenes into static and dynamic scenes, resulting in relatively simple adjustment modes. This invention, through more refined status recognition (e.g., refined to specific application scenarios, such as games, video playback, etc.), can more accurately adjust the backlight.

[0052] Step S413, Feature Extraction of Display Content. Image processing algorithms are used to analyze the features of the currently displayed content, identifying factors such as brightness distribution, contrast, and color type in the image. These features help the control system determine whether backlight brightness or color temperature needs adjustment. Most existing technologies only focus on adjusting the brightness of the display screen, while this invention, through image analysis technology combined with the characteristics of the displayed content, adjusts the backlight brightness, color temperature, and contrast to optimize the visual effect.

[0053] Step S42 includes the following steps: Step S421, Data Fusion and Multi-Dimensional Input Analysis. Data fusion technology is employed to integrate and analyze multi-dimensional information such as ambient light data, mobile phone usage status, and display content characteristics. A weighted algorithm is used to calculate the optimal backlight adjustment scheme based on the weight of each input source. Specifically, in a bright environment with highly highlighted content, the system automatically lowers the backlight brightness; in a dim environment with relatively dim content, the system increases the backlight brightness. Existing brightness adjustment technologies typically rely on a single data input source (such as ambient light or content brightness), while this invention, through multi-dimensional fusion and weighted analysis, makes backlight adjustment more intelligent and precise.

[0054] Step S422, Scene Adaptive Algorithm Design.

[0055] This invention designs a scene-adaptive algorithm that can dynamically adjust the backlight's operating mode according to different usage scenarios. For example: In reading mode, the backlight brightness will be reduced appropriately and the color temperature will be adjusted to a warm tone to reduce eye fatigue; In video playback mode, the backlight brightness will be increased to enhance color performance; In game mode, the backlight brightness is adjusted according to changes in dynamic scenes, and the contrast is optimized to enhance the visual effect.

[0056] In existing technologies, scene switching typically relies on hard-coded modes (such as only "reading mode" and "video mode"). This invention, through an intelligent scene switching algorithm, can make various adjustments according to the complexity of the usage scenario.

[0057] Step S43 includes the following steps: Step S431: Backlight brightness adjustment based on ambient light and usage status. A real-time feedback mechanism is employed to dynamically adjust the backlight brightness according to changes in ambient light and usage status. For example, in bright light environments, the system automatically reduces the backlight brightness; while in dark environments, the backlight brightness automatically increases to improve display quality and save power. Existing technologies are mostly based on fixed ambient light and brightness adjustment logic, while this invention dynamically adjusts the backlight system according to usage status and content requirements, ensuring that the backlight system can cope with complex environmental changes.

[0058] Step S432: Joint adjustment of color temperature and brightness. This invention proposes a joint adjustment mechanism for color temperature and brightness. Through algorithmic optimization, the color temperature and brightness of the backlight are adjusted to better suit the needs of the displayed content. For example, when watching videos, the backlight brightness is increased, and the color temperature is adjusted to a cool tone; when reading or browsing web pages, the backlight brightness is moderate, and the color temperature is adjusted to a warm tone to reduce eye fatigue. In existing technologies, color temperature adjustment is usually separate from brightness adjustment, lacking coordination. This invention, through a joint adjustment mechanism, allows color temperature and brightness to work more collaboratively, improving the visual experience.

[0059] Step S44 includes the following steps: Step S441, User Behavior Analysis and Prediction Model. This invention uses a machine learning model to analyze user behavior, including touch habits, operation frequency, and content browsing type, to predict user needs. For example, if a user frequently reads at night, the system will automatically adjust to low brightness and a warm color temperature; if the user frequently plays games, the system will automatically increase brightness and enhance contrast. Existing technologies typically lack the ability to automatically adjust backlight based on user habits. This invention achieves automatic adjustment based on user preferences through user behavior learning and prediction.

[0060] Step S442, Personalized Brightness Adjustment. This invention allows users to fine-tune the sensitivity and adjustment range of the backlight through personalized settings. Using a deep learning algorithm, the system automatically adjusts parameters based on user habits, ensuring that each user's operation matches their individual preferences. For example, some users may prefer a brighter backlight, while others may prefer a dimmer display. Existing technologies mostly offer uniform adjustment methods, lacking personalized settings for different users. This invention provides a personalized backlight adjustment solution through personalized adjustment and a self-learning algorithm.

[0061] Step S45 includes the following steps: Step S451, Real-time Feedback and Optimization Mechanism. This invention utilizes a real-time feedback mechanism to evaluate and adjust the backlight adjustment effect in real time. Based on data from sensors (such as changes in ambient light and displayed content), the system instantly adjusts the backlight brightness and color temperature to ensure optimal display performance. Existing backlight adjustments are often based on preset modes, while this invention, through its real-time feedback and optimization mechanism, can make fine-tuned adjustments according to actual conditions, guaranteeing the best display effect.

[0062] Step S46 includes the following steps: Step S461, Energy Efficiency Optimization Control. This invention optimizes backlight energy efficiency management through intelligent control algorithms. For example, when ambient light intensity is high, the backlight brightness is reduced to decrease battery consumption; during nighttime use, the brightness is automatically lowered and the color temperature is optimized, thereby reducing unnecessary energy waste and extending the phone's battery life. Existing energy efficiency management technologies are relatively basic, typically relying on simple ambient light sensing to adjust brightness. This invention, however, achieves refined energy efficiency management through intelligent optimization control, based on multi-dimensional inputs, effectively improving battery life.

[0063] Step S3 includes the following steps: Step S31, Quantum dot-polymer composite film (QD) Preparation of polymer film.

[0064] In step S31, high photoluminescence efficiency (PLQY) quantum dots are synthesized in advance (II–VI QDs can be selected, or cadmium-free QDs / III–V QDs can be used to take into account environmental protection); then they are dispersed in an optically transparent high-transparency polymer resin (such as PMMA, PVDF, etc.) to form a uniformly dispersed, non-aggregated composite material suitable for large-area coating; the composite film is encapsulated / sealed (barrier film / multilayer polymer + oxide barrier layer encapsulation) to prevent the degradation of QDs by moisture and oxygen.

[0065] Step S32: Adjust the film thickness and uniformity.

[0066] Spraying coating, blade coating Coating) or printing (inkjet / slot) die / roll to Utilizing large-area, mass-producible processes such as roll-up (or similar technologies) suitable for mobile phone backlight modules, to ensure QD (Quality Demand) The film has uniform thickness and uniform light emission.

[0067] Step S33: Integrate the thin film into the mobile phone LCD backlight unit (BLU).

[0068] Prepared / packaged QD polymer quantum dot thin films (QD) The film (QDEF) is placed in the backlight module of the mobile phone LCD, preferably between the LED blue light (or near-UV) blue light excitation source and the light guide plate, or as part of the light guide plate, to achieve efficient down-conversion of blue light to red / green / blue (R / G / B) three primary colors. conversion).

[0069] Step S34: Optimize the emission spectrum to match the transmittance of the LCD + color filter.

[0070] Employing "multi-objective optimization (multi The "objective optimization" method is used to optimize quantum dot thin films (QDs). The parameters of the backlight film, such as the red / green QD ratio, film thickness, blue light excitation wavelength, and quantum dot concentration, are optimized to make the emission spectrum match the color filter band (R / G / B) of the mobile phone LCD panel as closely as possible. This reduces the light absorption loss of the color filter, improves transmission efficiency, and enhances the overall system efficiency. Through the above optimization, a higher light utilization rate (lower backlight power consumption to achieve the same front-end brightness) is achieved compared to traditional white LED backlights – which is "backlight energy efficiency optimization".

[0071] Step S35 combines local dimming and dynamic adjustment of backlight brightness.

[0072] QD has been integrated Based on the film's backlight system, and in conjunction with the intelligent adjustment algorithm for "content + environment + usage status" (such as local dimming + global dimming + content analysis + ambient light perception + user behavior prediction, etc.) in the aforementioned patent draft, the intensity of LED blue light excitation or regional light supply can be further adjusted to achieve the goal of both meeting display brightness / color gamut requirements and minimizing power consumption; due to QD The film's high luminous efficacy and high color purity allow it to maintain good color and contrast even when backlight brightness is reduced (e.g., in power-saving / low-brightness scenarios), resulting in higher fidelity and more significant energy efficiency advantages compared to traditional white LED backlight systems at low brightness.

[0073] Step S36 improves film reliability and lifespan.

[0074] A multilayer barrier film + polymer + / – oxide film encapsulation structure (such as that used in 3M QDEF) is adopted to protect against environmental factors such as water, oxygen, humidity, and photoaging, so as to ensure the stability and reliability of the QD film during the service life of mobile phones (usually required to be ≥ tens of thousands of hours); the encapsulation and sealing materials and interface engineering (surface treatment, adhesion layer) are optimized to prevent quantum dot aggregation, oxidation, and fluorescence decay, thereby maintaining good luminous efficiency and color gamut performance.

[0075] This invention employs quantum dot-polymer composite thin films (QD). Quantum dot film is a key material for backlighting. This quantum dot film is prepared by uniformly dispersing quantum dot materials and polymer resin through coating, casting, and other methods. Quantum dot materials (such as CdSe, InP, or cadmium-free quantum dots) possess excellent optical properties (high photoluminescence quantum efficiency PLQY), and their size and spectral characteristics can be customized to meet different display color gamut requirements based on specific application needs.

[0076] To improve the stability of quantum dot films, a multilayer barrier film encapsulation technology was employed. The barrier film layers, made of polymer and oxide materials, effectively prevent the oxidation and degradation of the quantum dot materials by moisture and oxygen, thereby improving their long-term reliability and luminous efficiency stability. This encapsulation technology references microstructure thin-film encapsulation methods in the literature, ensuring the long-term use of quantum dot films in backlight systems by improving encapsulation sealing and stability.

[0077] This invention combines quantum dot thin-film technology to achieve high-efficiency energy utilization of the backlight system by optimizing its operating mode. Specifically, the quantum dot thin film is applied to the backlight module (BLU) of a liquid crystal display screen, placed between the blue LED excitation source and the light guide plate (LGP). The quantum dot material is excited by the blue LED, and the quantum dot thin film converts the blue light into highly efficient red and green light, which, together with the transmitted blue light, form white light, thereby significantly improving the backlight's luminous efficiency.

[0078] To ensure the emission spectrum matches the display color filter, this invention employs a content-based optimized spectral adjustment method. By finely adjusting parameters such as the red-green quantum dot ratio, film thickness, and quantum dot concentration of the quantum dot film, the emission spectrum can be matched with the transmittance efficiency of the LCD color filter, reducing light absorption loss and improving overall optical efficiency. According to literature research, the optimized spectral adjustment can improve the backlight's color gamut and brightness while maximizing light utilization and reducing energy waste.

[0079] This invention combines the high luminous efficiency of quantum dot films with intelligent backlight control algorithms to further optimize the energy efficiency of the backlight system. The system dynamically adjusts the backlight brightness based on ambient light intensity, the brightness distribution of the displayed content, and the user's usage status. When the ambient light intensity is strong, the system automatically reduces the backlight brightness and performs fine-tuning of local areas according to the brightness requirements of the displayed content. For low-brightness content, the backlight brightness is reduced and automatically adjusted to a warm color temperature to reduce power consumption; while in high-brightness scenarios, the system enhances the display effect by increasing backlight brightness and adjusting the color temperature.

[0080] By leveraging the high luminous efficiency of quantum dot films, the backlight system not only maintains high color fidelity and contrast but also preserves good color saturation and brightness even at low brightness levels thanks to the high spectral efficiency of quantum dots. Therefore, the backlight energy efficiency optimization method of this invention can significantly reduce energy consumption, extend battery life, and achieve a more environmentally friendly display effect without sacrificing display quality.

[0081] Quantum dot thin films (QD) By combining quantum dot film with traditional LED backlight systems and precisely controlling the spectral conversion efficiency and energy output of the quantum dot film, the color performance and energy efficiency of mobile phone LCD displays are significantly improved. Specifically, by integrating quantum dot film into the backlight module of the mobile phone display, high brightness can be provided while maintaining low power consumption, and the backlight brightness can be automatically reduced when displaying static content to reduce unnecessary energy waste. By optimizing parameters such as the emission wavelength, film thickness, and light transmittance of the quantum dot film, high color gamut output at low brightness is achieved, improving the overall display effect and visual experience of the screen.

[0082] Furthermore, by incorporating an intelligent backlight control algorithm, this invention can automatically adjust the backlight brightness and color temperature according to the mobile phone's usage scenario. For example, in nighttime or low-light environments, the system will automatically reduce the brightness and adjust to a warm color temperature to avoid strong light stimulation; while in bright environments, the system will increase the backlight brightness and adjust to a cool color temperature to improve the readability and clarity of the display.

[0083] Compared with the prior art, the mobile phone LCD screen backlight energy efficiency optimization method of the present invention has the following beneficial effects: 1. Improve light efficiency and display effect: By adopting quantum dot thin film technology, the spectral characteristics of the backlight are optimized, improving the display color gamut and brightness performance, while reducing the energy consumption of the light source.

[0084] 2. Intelligent dimming and energy efficiency optimization: By combining ambient light, display content and user behavior, the backlight brightness and color temperature are dynamically adjusted to provide a more comfortable visual experience and significantly reduce energy consumption.

[0085] 3. Extend battery life: Through intelligent control algorithms and the high-efficiency light-emitting characteristics of quantum dot films, battery consumption is minimized while maintaining display quality, thus extending the device's usage time.

[0086] 4. Reliability and long lifespan: Quantum dot films effectively prevent the influence of the external environment on quantum dot materials through encapsulation technology, ensuring long-term stable use and improving the reliability and durability of the backlight system.

[0087] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any modifications, equivalent substitutions and improvements made within the concept of the present invention should be included within the patent protection scope of the present invention.

Claims

1. A method for optimizing the energy efficiency of a mobile phone LCD screen backlight, characterized in that, It comprises the following steps: Step S1, dynamically adjusting the backlight brightness according to the ambient light intensity and the characteristics of the display content; Step S2, using local dimming technology in different areas of the display screen, adjusting the backlight brightness of each area according to the brightness distribution of the display content; Step S3, introducing quantum dot material in the backlight source to optimize the light efficiency of the backlight; In step S3, it comprises the following steps: Step S31, preparation of quantum dot-polymer composite film; Step S32, controlling the thickness and uniformity of the film; Step S33, integrating the film into the LCD backlight module of the mobile phone; Step S34, optimizing the emission spectrum to match the transmission efficiency of the LCD and color filter; Step S35, combining local dimming and dynamic adjustment of backlight brightness; Step S4, designing an intelligent optimization control algorithm to automatically adjust the working mode of the backlight system according to the use state of the mobile phone and environmental changes.

2. The method for optimizing the energy efficiency of the backlight of the LCD screen of the handset according to claim 1, characterized in that, In step S31, high photoluminescence efficiency quantum dots are synthesized in advance; then they are dispersed in optically transparent high-transparency polymer resin to form a composite material that is uniformly dispersed, free of aggregation, and suitable for large-area coating; the composite film is packaged and sealed.

3. The method for optimizing the energy efficiency of the backlight of the LCD screen of the handset according to claim 1, wherein, In step S33, the prepared quantum dot film is placed in the backlight module of the mobile phone LCD, preferably between the blue LED excitation source and the light guide plate, or as part of the light guide plate, thereby realizing efficient down-conversion of blue light to red, green, and blue primary colors.

4. The method for optimizing the energy efficiency of the backlight of the LCD screen of the handset according to claim 1, wherein, In step S34, a multi-objective optimization method is used to optimize the red and green QD ratio, film thickness, excitation blue light wavelength, and quantum dot concentration parameters of the quantum dot film, so that the emission spectrum matches the color filter band of the mobile phone LCD panel as much as possible, thereby reducing the light absorption loss of the color filter and improving the transmission efficiency.

5. The method for optimizing the energy efficiency of the backlight of the LCD screen of the handset as claimed in claim 1, wherein, In step S4, it comprises the following steps: Step S41, multi-dimensional perception data acquisition and processing; Step S42, intelligent optimization control algorithm design; Step S43, dynamic backlight mode adjustment; Step S44, user behavior analysis and adaptive optimization; Step S45, intelligent feedback and optimization; Step S46, energy efficiency management and optimization.

6. The method for optimizing the energy efficiency of the backlight of the LCD screen of the handset according to claim 5, wherein, In step S41, it comprises the following steps: Step S411, ambient light sensor data acquisition; Step S412, mobile phone use state and scene detection; Step S413, display content feature extraction.

7. The method for optimizing the energy efficiency of the backlight of the LCD screen of the handset according to claim 5, wherein, In step S42, it comprises the following steps: Step S421, data fusion and multi-dimensional input analysis; Step S422, scene adaptive algorithm design.

8. The method for optimizing the energy efficiency of the backlight of the LCD screen of the handset according to claim 5, wherein, In step S43, it comprises the following steps: Step S431, backlight brightness adjustment based on ambient light and use state; Step S432, joint adjustment of color temperature and brightness.

9. The method for optimizing the energy efficiency of the backlight of the LCD screen of the handset according to claim 5, wherein, In step S44, it comprises the following steps: Step S441, user behavior analysis and prediction model; Step S442, personalized brightness adjustment.

10. The method for optimizing the backlight energy efficiency of a mobile phone LCD display as described in claim 5, characterized in that, In step S45, it comprises step S451, real-time feedback and optimization mechanism; in step S46, it comprises step S461, energy efficiency optimization control.

Images