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It was recognised by ‘The Club of Rome’ in 1948 that the earth’s resources were limited and by 1971 in the book ‘Fundamentals of Exhaust Emissions’ I concluded that we should also have concern for CO2 levels in the air and consequent global warming caused by transport emissions. So what is the optimum strategy for minimizing energy use and emissions, recognizing that the car is the prime source of personal space for mobility, and that many governments support a focus as EVs as the solution for the future? To demonstrate how range capability has a significant influence on the optimum life for two classes of EVs and to identify the inter relationship with vehicle life. From this to forecast the optimum service life (before scrapping including recycling) against a back drop of steadily improving EV and battery manufacturing energy and efficiency, Using the best available energy production and usage data, life cycle analysis (more than ‘well-to-wheel’ as the energy content and manufacture of consumables and recycling/reuse is included) is performed for electric vehicles accounting for the change in vehicle use with age in vehicle fleets, in which new vehicles replace older, scrapped ones in the market with improvements in energy efficiency (and CO2 emissions). Depending on the vehicle size and configuration, the optimum vehicle life ranges from 17 years to more than thirty. The greater the installed battery kWh and hence range capability the longer is the optimum service life. As the energy efficiency trend for new vehicles entering the market reduces, as it must according to the law of diminishing returns, vehicles need to remain in use for longer to amortize the embedded energy in manufacturing which will also continue to improve. The analysis is only as reliable as the data. However the sensitivity analysis allows the results to remain useful as the user can adjust the scenario according to updated information. Moreover sensitivity analysis allows the reader to apply the results for regional variables such as the proportion of renewable energy in electricity generation and as a consequence of EVs reduced annual travel compared with conventional and hybrid light duty vehicles.. The application of the most recent input data is also novel. Finally, the author is not aware of analyses of this type that recognise reducing annual travel as vehicles age, rather constant km of travel per year has previously been assumed throughout the vehicle life. On the basis of the median results from the projections, short to moderate range EVs offer the path to minimizing CO2 emissions which conflicts with the general consumer desire for reduced ‘range anxiety’ and thus frequency of recharging. EVs life cycle emissions will be considerably worse than those from hybrid vehicles which use the least long term (several model change overs) energy and produce correspondingly low CO2. The sensitivity analysis allows for conclusions to be drawn about many alternative scenarios.
Prof. Harry Watson, University of Melbourne, AUSTRALIA