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Forecasting Cost Path of Electric Vehicle Drive System: Monte Carlo Experience Curve Simulation

UCD-ITS-RP-97-17

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Suggested Citation:
Lipman, Timothy E. and Daniel Sperling (1997) Forecasting Cost Path of Electric Vehicle Drive System: Monte Carlo Experience Curve Simulation. Transportation Research Record (1587), 19 - 26

The future costs of electric-drive vehicles, like those of any new technology, are uncertain. One method for forecasting cost reductions uses the concept of the experience curve. Experience curves take into account scale economies, technological improvements in production processes, improvements in product design, and improved efficiency of workers and production management. The future manufacturing cost of an innovative new technology—the synchronous, brushless permanent magnet electric vehicle drivetrain—is analyzed using experience curves and a Monte Carlo simulation technique. Based on experience curve theory and the assumptions used in the analysis, a drop in manufacturing cost is predicted—from today's $12,000 (with low-volume, hand-built production) to a cost of about $1,200 to $1,700 when full-scale economies and manufacturing experience have been realized. This cost range implies eventual high-volume prices of $1,500 to $2,100 once corporate profit and warranty costs are included. In an ongoing study at the University of California, Davis, experience curve analyses are being integrated with a detailed vehicle cost model to develop short- and long-term cost forecasts for complete electric vehicles.