Research On The Remote Diagnosis And Maintenance Of Lead-Acid Battery

The valve regulated lead acid battery has been applied in different fields as an important energy storage and backup power, including in the automotive, electric power system, communication system, uninterruptable power supply(UPS) and so on. However, due to the lack of professional maintenance, the majority of VRLA batteries can’t reach the design life after they are into service, which will result in a large number of early retirement It will not just pollute the environment, but also increase the costs of enterprises. Therefore, to diagnose and maintain the batteries timely and effectively is of great importance.This paper focuses on the VRLA battery used as backup power. In order to improve the performance of battery, we pay our emphases on the principle of charge and discharge, the deterioration mechanism, health status prediction, capacity prediction and other aspects. Based on this,a remote diagnosis and maintenance system of VRLA battery is developed. This system will monitor and analyze the operation parameters of the battery in real time, and provide the automatic maintenance function, which all above will provide some reasonable proposal for maintenance of power supply to the staff, and improve the reliability of backup power at last The main contents are listed as follow:1. An overview on developing actuality of maintenance system of VRLA battery at home and abroad is discussed.2. After researching on the chemical reaction mechanism, the battery discharge process is simulated by Matlab/Simscape.3. Analyze the main factors that influence the health status of the battery, and research the battery deterioration mechanism.4. To verify the relationship between the internal resistance and battery capacity, some experiments are carried.5. Find out the bad battery of the battery group using the improved clustering procedures with the state parameters of the battery from the monitor system6. The application of support vector machine algorithm is to establish the model of the state parameter and battery remaining capacity, which is also compared with the traditional neural network algorithm7. The prototype development of the remote diagnosis and maintenance system is proposed, and its function and advantages are analyzed.The work of this paper has been applied in the backup power. In practice, this system can improve the battery maintenance capability and enhance the battery life effectively.