Research And Development Of Monitoring System For Storage Battery

The storage battery is an important part of DC system. It can provide uninterrupted power supply for communications and power equipment, which connects with the credible running of DC power system. It is very important to monitor the storage battery in time and credibly.The thesis introduces the basic principle of storage battery. The thesis analyzes the capability of storage battery, the factors that influence it and the methods to forecast it. The thesis researches a method to forecast the residual capability of battery by ANN (Artificial Neural Network). ANN has the powerful characteristics of non-linear mapping and information storage. Under the control of target precision we train the three-layer BP network by choosing LM algorithm that is one of the improved back-propagation (BP) learning algorithm. Then a model of forecasting the residual capability is realized. We test the capability of network by MATLAB emulation. The result of emulation indicates that it is feasible to forecast the residual capability of battery by ANN.The thesis designs a set of system for monitoring storage battery. This system based on AVR singlechip is exploited. It can detect the single voltage, the voltage of battery group, the current and actual temperature in real time. It also can detect the inner resistance of battery. There is a display that can help people to communicate with the system. The function of alarm help the user to locate the failure battery. The thesis analyzes the designs for hardware and software of the system detailedly, debugs the system and provides it an anti-jamming design. The system works normally after testing.