Research On The Optimization Of Remaining Cycle Life For Paralleled Li-ion Battery Pack

Energy Internet is one of the five basic points of the third industrial revolution, as well as the focus of the construction of energy and electric systems in the next phase of our nation, and in this context, the economic efficiency and cycle life for battery storage system is of vital importance as it is the essential facility for Energy Internet. Battery pack is the basic method for generating battery storage system, however the unit in which may fall into failure for various reasons and been replaced lately, which would enlarge the performance difference between units in the pack, and the equilibrium strategy used before could not improve the remaining cycle life of the pack because it could fulfill the whole potential of the new unit’s economic efficiency. Therefore, this thesis focuses on the optimization of remaining cycle life for battery pack whose unit has been exchanged as accidential failure. The major works include:Firstly, according to the analysis of remaining cycle life for paralleled battery pack under the common used equilibrium strategies, the shortage of the traditional strategies and the necessity of establishing the optimization model on remaining cycle life for the pack was given;Secondly, the optimization control system for paralleled Li-ion battery pack’s remaining cycle life was established, which was composed of the State of Charge estimation unit, the State of Health estimation unit, the signal processing unit, the current calculation unit, several current and internal resistance measurement instrument. Then the optimization model for paralleled Li-ion battery pack’s remaining cycle life was generated based on the control system, furthermore, the implementation steps of the optimization process was presented;Thirdly, the optimization model for Li-ion battery pack’s remaining cycle life was transformed into nonlinear equations as they had the same format, and the Genetic Annealing Algorithm was used to solve these equations, with whose fitness function, coding, genetic, annealing operation were defined, besides, the validity of the algorithm for this problem was verified with examples.Lastly, based on the actual data of a battery storage system, the system’s life was calculated with the optimization model and method for Li-ion battery pack’s remaining cycle life, and the applicability of the model and method was analyzed.Apart from the work presented above, the thesis was summarized with some points needed to be improved or researched was discussed.