研究目的
To address the harmonization of visual quality and appearance of in-vehicle displays by optimizing white-point adjustment, color adjustment, and black uniformity for single and multiple display applications.
研究成果
The end-of-line adjustment processes for white point, color, and black uniformity are mature and effective in meeting OEM specifications, but they incur performance losses. Advances in intrinsic display matching by manufacturers could reduce these losses. System integrators must manage tolerance chains and optimize designs to ensure seamless integration and high-quality appearance in automotive interiors.
研究不足
The adjustment processes lead to luminance and contrast losses (e.g., 10-30% for white-point adjustment). The methods are specific to automotive applications and may not generalize to other display types. The reliance on end-of-line adjustments indicates intrinsic display variations that could be improved at the manufacturer level.
1：Experimental Design and Method Selection:
The study uses algorithm-based processes for end-of-line measurement and adjustment of key parameters such as white point, primary colors, and black uniformity. Proprietary measurement methods are employed for assessing mura effects due to mechanical stress.
2：Sample Selection and Data Sources:
Samples include over 100,000 in-plane switching-based LCD displays of different sizes from various suppliers, measured for parameters like color coordinates, luminances, and black uniformity.
3：List of Experimental Equipment and Materials:
Equipment includes measurement jigs for displacement testing, CIE 1931 color space tools, and algorithms for data recalculation. Materials involve automotive-grade LCD panels with backlights, touch layers, and cover glasses.
4：Experimental Procedures and Operational Workflow:
Displays are measured from specific viewing angles (e.g., perpendicular for clusters, 30° for center stacks). White-point and color adjustments are performed by recalculating image data at runtime. Black uniformity is tested using a jig that applies controlled displacement to measure mura effects.
5：Data Analysis Methods:
Data is analyzed using iterative algorithms to calculate target parameters. Statistical methods are applied to large populations of displays to assess scatter and adjustment effectiveness.
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