2026-09-18T20:50:15Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/816012022-01-13T07:54:05Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Sanjay E. Sarma.
Erb, Dylan C. (Dylan Charles)
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2013-10-24T17:33:48Z
2013-10-24T17:33:48Z
2013
2013
http://hdl.handle.net/1721.1/81601
858867922
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 87-91).
This thesis reviews the traditional battery pack design process for hybrid and electric vehicles, and presents a dynamic programming (DP) based algorithm that eases the process of cell selection and pack design, especially for blended battery packs (those containing two or more different energy sources). The proposed algorithm simultaneously optimizes the size of the battery pack while determining the ideal control strategy for the power split between the two sources. To test the algorithm, a simulation experiment is presented that compares the results of the DP based algorithm with single energy source options and a peak shaving heuristic strategy. The results of this experiment show that the algorithm reliably picks the lowest cost solution, and illustrates that blended battery packs have great potential for cost reduction in hybrid vehicles.
by Dylan C. Erb.
S.M.
91 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Optimization of blended battery packs
Thesis
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