Application of S-Curve methodology for forecasting of V2X communications and autonomous vehicle research

Alankus, Orhan Behic

doi:10.1109/icves.2012.6294258

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Technology Forecasting Methodology1

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2017

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“…After investigation of different methodologies, Logistic Pearl and Gompertz seems to be best fitting methodology for technology forecasting of electric vehicle battery technology [8,9]. Logistic Pearl formula is…”

Section: Technology Forecasting Methodologymentioning

confidence: 99%

Technology Forecast for Electrical Vehicle Battery Technology and Future Electric Vehicle Market Estimation

Alankus¹

2017

Adv Automob Eng

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Electric Vehicle (EV) battery technologies is a limiting factor for the wide spread diffusion of electric vehicles. EV battery's energy density compared to fossil fuels is still very low, thus EV's have still stringent driving range with voluminous, heavy and high cost batteries. Automotive OEM's are trying to estimate the future of batteries to do their plans related to electric vehicle manufacturing. This article attempts to estimate the future of EV batteries and mainly that of Li_Ion, Li_S and Li_Air Technologies which seem to be the most promising Technologies as of today. The article explains in detail the methodology used, and the results with an estimation of future EV market as a result of the EV battery development time scale.

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Section: Technology Forecasting Methodologymentioning

confidence: 99%

Technology Forecast for Electrical Vehicle Battery Technology and Future Electric Vehicle Market Estimation

Alankus¹

2017

Adv Automob Eng

View full text Add to dashboard Cite

show abstract

Application of S-Curve methodology for forecasting of V2X communications and autonomous vehicle research

Cited by 1 publication

References 3 publications

Technology Forecast for Electrical Vehicle Battery Technology and Future Electric Vehicle Market Estimation

Technology Forecast for Electrical Vehicle Battery Technology and Future Electric Vehicle Market Estimation

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