Research On Intelligent Power Management System For LED

Lighting technologies are now undergoing a revolution in lighting field. The countries at home and abroad have issued an announcement phasing out the production and sale of the traditional incandescent to save energy and protect the environment. As a new generation of "green light", LED has a development trend of moving into the fields of general illumination. In order to improve the utilization of energy and avoid the service disruptions from the unusual states of electric system, the power scheme which realized an uninterruptible power supply by batteries, has been widely used. Meanwhile, the battery management system is in a period of rapid growth. Therefore, a multi-function power management system that combines LED control with the battery management has wide development prospects.In the paper, the demand analysis is first carried on for LED power management system and the whole system architecture is established based on the functional requirements, and the management schemes of LED illume and the battery are designed according to the state of charge of the battery. Secondly, owing to VRLA batteries is a complex nonlinear system, it is difficult for the battery pack's remaining capacity to measure directly during operation of the system. Therefore, a new on-line SOC estimation algorithm is offerred and its model is built based on Ah estimation method, with the help of the curve fitting method, piecewise linearization method and look-up table method. Then, according to the established mathematical model of Ah method and the new method for SOC estimation, Simulink in Matlab is applied and simulated, and the effectiveness of the new method are confirmed through the simulation analysis results. Finally, based on the systematic performance requirements, the hardware circuit and software program are designed in accordance with the modular design concept. However, a structure of distributed type is adopted in the hardware design, and the charging circuit is simulated by the SABER; moreover, the software system is developed under the Keil C51 development environment, and on-line programming and debugging is proceeded through KeilμVision3.By experimental testing, it can be concluded that the power management system works stably and each module keeps in good condition, which gains the expected performance. And the new SOC estimation algorithm has showed a certain degree of adaptability and versatility.