Biomechanical optimization of RGB LED systems: Temperature prediction model and optical compensation algorithm based on built-in constant current source chip
Abstract
In the realm of modern applications, especially those related to human - involved scenarios such as vehicles and medical or wearable devices, the performance of RGB LED lights is of great significance. Beyond the traditional concerns of electronic - optical properties, the integration of biomechanics - related factors can bring new perspectives and optimizations. In vehicles, during prolonged illumination, the color shifts of various LED lights not only affect driving comfort but also have potential implications for driving safety from a biomechanical perspective. The human body’s visual and psychological responses to these color and luminance changes are complex. For example, sudden or inconsistent color changes can cause visual fatigue and distraction, which may impact a driver’s reaction time and decision - making ability, all of which are related to biomechanical aspects of human - machine interaction. Each LED shows deviations in wavelength and luminous intensity, and the light decay of RGB chips is inconsistent. To address these issues and ensure consistent color and luminance of all RGB ambient lights during use, this paper proposes a temperature prediction model (PT - model) based on constant current source output PWM. This model takes into account the impact of temperature changes on the color coordinates and luminous flux of LED lights. Moreover, considering the potential applications in medical and wearable devices, the model’s performance becomes even more crucial. In medical light - based treatment devices, the precise control of RGB LED temperature and light output is essential for ensuring the effectiveness of treatment while minimizing potential harm to human tissues. Biomechanics research can provide insights into how different tissues respond to light - induced heat and mechanical stress. Similarly, in wearable devices for health monitoring, the stability of RGB LED performance is related to the comfort and accuracy of the device’s operation on the human body. Experimental results show that compared to traditional models, the prediction accuracy of this model is significantly improved, with errors reduced to within 4.3%. The model’s effectiveness is verified under different ambient temperatures ranging from −40 ℃ to 120 ℃, which is crucial for ensuring its reliability in various real - world applications, especially those related to human - centered scenarios influenced by biomechanical factors.
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