Optimization Model for Global Portfolio of Clean Energy Vehicles Considering Metal Resource

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Various types of clean energy vehicles (CEVs) have been developed to reduce CO2 emissions and move our economies away from petroleum in the transportation sector. To make an innovation of these technologies and introduce them into the market effectively, it is important to analyze an optimal portfolio of CEVs, CO2 reduction effects and total social cost in the future that can be used as a decision-making guideline for governments and companies. Meanwhile, CEVs contain some metals that have supply risks because of the reserves and political availability. However, previous researches have not taken the metal resource problems into account. In this paper, we develop the optimization model by linear programming for CEV portfolios by 6 regions of the world, considering metal resource usage of CEVs. As a case study, under the definition that the objectives are minimizing total social cost or copper resource usage, and the constraint is CO2 emission reduction target, we clarify an optimal CEV portfolio of the world. In case of minimizing total social cost, electric vehicle and plug-in hybrid electric vehicle were mainly selected. On the other hand, in case of minimizing copper usage, fuel cell vehicle and clean diesel vehicle are selected. The optimal portfolio is different for both cases. Moreover, the relationship between CO2 emission target and copper usage to achieve is clarified. Finally, we evaluate copper resource constrains. When achieving 15% reduction of CO2, about 1.7 million ton of copper (approximately equal to 33 million units of EV) might be in short supply.

Optimization Model for Global Portfolio of Clean Energy Vehicles Considering Metal Resource

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