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- W1966482803 abstract "Vehicles with electric drive trains are currently the subject of intense discussion by society. The cost trends of the individual components in the electric drive train are a central aspect of the future market success of the different vehicle drive systems. An innovative two-factor experience curve approach was developed to facilitate the generation of the most meaningful cost forecasts for these components. This enables the creation of a flexible cost forecast model that supplements the two-factor experience curve approach by an analogous technology component. The performance of the model was demonstrated using alternative drive components, namely the proton exchange membrane (PEM) fuel cell stack, a high energy lithium-ion battery and a high power lithium-ion battery. A comparison of the forecast values calculated using this model with the industry targets determined by McKinsey in the study “A portfolio of power-trains for Europe” [1] shows that the realization of these targets for the fuel cell stack is possible if the product volume increases rapidly enough. For the high energy and high power lithium-ion battery targets, the product volume and research and development activity, measured here in terms of patent growth, need to grow compared to the trend of the last years. ► We developed a new two-factor experience curve approach for our cost forecast model. ► The model endogenous cost degression is driven by output and patent publications. ► For the fuel cell stack, 2020 costs of €36–€49/kW were calculated. ► For high energy Li-ion batteries, 2020 costs of €309–€408/kWh were calculated. ► For high power Li-ion batteries, 2020 costs of €38–€46/kW were calculated." @default.
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- W1966482803 date "2012-10-01" @default.
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- W1966482803 title "Feasibility study of 2020 target costs for PEM fuel cells and lithium-ion batteries: A two-factor experience curve approach" @default.
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- W1966482803 doi "https://doi.org/10.1016/j.ijhydene.2012.07.022" @default.
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