Network computational analysis way for SOC estimation of lead acid

Student Poster Abstract for ASEE-NE’15 Conference
Network computational analysis way for SOC estimation
of lead acid rechargeable batteries
Wu Shi1,Linfeng Zhang1
Department of
Electrical Engineering,
University of Bridgeport, CT 06604, USA
Abstract: The state of charge (SOC) is a very useful index that can help to monitor and control
the working modes of the battery for optimizing storage power distribution and promoting the
storage power efficiency in the microgrid. Many techniques to estimate SOC has been
reported, and the nevus networks analysis method is one of the effective and popular way to
estimate SOC in dynamic mode. The network analysis algorithm can be described as a
discrete model always assembled by the derivative functions and the matrix, which can be
used for iterated operation process to calculate the estimate value of SOC in real time depend
on the collected samples.
In this poster, a network matrix model that permit manually modifying model factors
corresponding with the real test values as close as possible have been built. The results of
SOC values come from the intergradient way and network matrix way have been compared
and prove the later one is indeed functional for the dynamic working estimation. Then a battery
management strategy which combined this algorithm with the NI visa techniques in Labview
software has been introduced.
Keywords: Storage elements, State of charge, Power distribution, Microgrid, Networks analysis.
of Electrical and Computer Engineering, University of Bridgeport, 221 University
Avenue, Bridgeport, CT 06604. Email: [email protected]