A Comparison of Parallel Gaussian Elimination Solvers for the Computation of Electrochemical Battery Models on the Cell Processor
Name
James R. Geraci-TR726.pdf
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19.97 MB
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Author(s)
Geraci, James R.
Date Issued
August 5, 2008
Series/Report no.
Technical Report (Massachusetts Institute of Technology, Research Laboratory of Electronics);#726
Abstract
The rising cost of fossil fuels, together with a push for more eco-friendly methods of transportation,
has increased interest in and demand for electrically powered or assisted vehicles. The majority of these
electric or hybrid electric vehicles will be, for the foreseeable future, powered by batteries.
One of the major problems with batteries is their aging. For batteries, aging means that the maximum
charge they can store decreases as number of charge/discharge cycles increases. Aging also means
that after a certain number of charge/discharge cycles, the battery will fail. In lead-acid batteries, one
of the major phenomenon that promotes battery failure is the development of a non-uniform concentration
gradient of electrolyte along the electrodes’ height. This phenomenon is known as electrolyte
stratification.
This thesis develops a simple two-level circuit model that can be used to model electrolyte stratification.
The two-level circuit model is justified experimentally using digital Mach-Zehnder interferometry
and is explained theoretically by means of two different electrochemical battery models. The experiments
show how the usage of the electrode varies along its height while the simulations indicate that the high
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resistivity of the lead dioxide electrode plays a major role in the development of a stratified electrolyte.
Finally, computational issues associated with the computation of a sophisticated two dimensional
electrochemical battery model on the multicore Cell Broadband Engine processor are addressed in detail.
In particular, three different banded parallel Gaussian elimination solvers are developed and compared.
These three solvers vividly illustrate how performance achieved on the new multicore processors
is strongly dependent on the algorithm used.
Description
Thesis Supervisor: John L. Wyatt, Jr.
Title: Professor
Thesis Supervisor: Thomas A. Keim
Title: Principal Research Engineer
MIT Department
Massachusetts Institute of Technology. Research Laboratory of Electronics
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