Dissertation > Industrial Technology > Electrotechnical > Independent power supply technology (direct power) > Battery

Based of Fuzzy Control Communication Power Battery Testing System Design and Research

Author DengYing
Tutor YeQingYun
School Wuhan University of Technology
Course Communication and Information System
Keywords Valve Regulated Lead Acid-battery (VRLA) SOC (State Of Charge) SOH (State Of Health) Digital filter Adaptive-Network-based Fuzzy Inference System (ANFIS)
Type Master's thesis
Year 2008
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This dissertation mainly studies intelligent on-line monitoring technologies and System design for predicting state of health and calculating state of charge of valve regulated acid battery (VRLA) which working in back-up mode.Valve regulated lead acid batteries are widely used in back-up power supply systems. The reliability of battery plays an important role in the safety and stability of computer systems, telecommunication systems, electric power systems, petrochemical reaction equipment and other important situation. As the VRLA is a complex electrochemical system with sealed technologies, it is impossible to test directly by observing the plate and the electrolyte density, or to calculate the accurate state by normal data analysis method. So, the VRLA on-line monitoring technologies are crucial technology for improving the power systems reliability. How to develop valid intelligent monitoring system becomes a focused project for worldwide researchers and famous power supply systems manufactures.In this paper, firstly, we build the platform for data collection which based on the VRLA characteristics and the main technological parameter, and analysis the design process of the software and hardware platform in detail which contains the PIC24H controller, the testing module for internal resistance, temperature, voltage and current, the ideal of the software, the procedure structure and also the solution of the system debug.Secondly, through the analysis of the VRLA testing technology, elaborating the testing principle, module and the accurate method of measuring the VRLA internal resistance, I engaged in the battery health research which based on the internal resistance testing technology, and we also advance the method collecting IIR filter to accomplish the internal resistance testing on line, as we use MATLAB software to training the IIR digital filter and achieve the filter algorithm in PIC24HJ embedded software, then analysis the correlative between the internal resistance and the VRLA SOH (State Of Health)、SOC (State of Charge). Basing on the field data analysis and the characteristic of VRLA electrochemistry, the system module fixes the adaptive neural fuzzy inference system used for battery SOC and SOH modeling and the imports. Simulated results had been tested by MATLAB and experimental results are all under our expectation. The paper of VRLA technique research and design achieved our goal.

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