%0 Journal Article %A Sun, Weijun %A Yu, Yajuan %A Wang, Dong %A Wang, Xiang %A Liang, Yuhan %A Huang, Kai %D 2013 %I Begell House %K multiobjective optimization, secondary batteries, environmental impact %N 4 %P 241-256 %R 10.1615/InterJEnerCleanEnv.2014007911 %T MULTIOBJECTIVE FORECAST AND OPTIMIZATION FOR SECONDARY BATTERY PRODUCTION IN CHINA %U https://www.dl.begellhouse.com/journals/6d18a859536a7b02,61f50e2903edc7d4,280f3628188b704b.html %V 14 %X Currently in China, PbA, NiMH, and Li-ions have occupied the secondary battery market. However, the use of secondary batteries has severe environmental impact to humans, and the negative influences of different types are not the same. Therefore it is significant to build up yield optimization and adjust the industry structure for coordination of environmental and economic concerns. Yield structure is determined by policy, economic effect, environmental impact, and other factors, so this article sets up multiobjective goals and simulates three yield-optimization scenarios. "Business as usual" (BAU) focuses on policy direction, the "low-investment model" (LIM) takes economic effects into consideration, and the "environmental emphasis model" (EEM) focuses on the environment. The application of BAU, LIM, and EEM models, serving as tools to analyze the yield optimization and industry structure of secondary batteries, is helpful for decision makers and experts to put forward prospective policy for a sustainable society. Based on the three models, the results of secondary battery yield optimization are analyzed. Compared with total production, investment, and annual environmental impact from the three models, EEM has the lowest negative environmental impact, while investment and the annual production of the other two are within a reasonable range. That means EEM is an economical and environmentally friendly optimization model, balancing the high electrochemical performance and fast social development, while not sacrificing the environment. %8 2015-02-06