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Research of VRLA Battery On-line Montoring and Contorl System

Author: GuoLiang
Tutor: DongYouEr
School: Shanxi University
Course: Physical Electronics
Keywords: battery internal resistance SOC Neural Network charge
CLC: TP277
Type: Master's thesis
Year: 2011
Downloads: 54
Quote: 0
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Abstract


As the communications, electronics, and energy technology develop, battery is more and more widespread in life and industrial production, and more important. Particularly in the energy depletion and environmental pollution a growing problem of today, new energy into the development of hot spots around the world eager.In the "Twelfth five years plan",wind power, photovoltaic power generation will be cheap, and new energy vehicles was listed as China’s auto industry development top priority the next 5 years. Batteries in photovoltaic and wind power plays a crucial role, both as an energy supplement inadequate, but also store excess energy, the energy source is the electric vehicle battery. Improper battery maintenance management will directly affect the efficiency and the use of battery life, and even damage the battery, severe cases can lead to security incidents, the reliability of many important occasions related to security and stability. Online monitoring of the operating parameters of the battery, you can keep abreast of the working status of the battery, and battery maintenance job characteristics, and to discharge its reasonable control, making it safe and effective operation. Therefore, the development of line battery monitoring system is imperative.Regarding the deficiency of battery online monitor at present,and solar independent power system in our laboratory, to explore and study parameter measurement of lead-acid battery, capacity estimates, the charge. Concrete experiments and work is shown as follows:(1) Analysis technical parameters and characteristics of the battery, and the current situation of battery monitoring system.(2) Research the monitoring method of Battery voltage, current and temperature, completed the design of hardware and software.(3) Design and complete a system of detecting internal resistance of battery on line was designed,which used four down-lead connect method,inject a alternating current with certain frequency into the battery.The accuracy to 0.1 Mohm.(4) Analysis the factors for SOC of battery,and the mathods of predict SOC. The neural network was used to predict SOC, and simulate in the MATLAB.The result showed that these methods can satisfy the requirement.(5) Compare the method of charge, use the IC named UC3906 to design the charger.Process divide into three stage,can safe and effective charge the battery.

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > Monitoring, alarm,fault diagnosis system
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