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The impending uptake of electric vehicles (EV) in worldwide car fleets is urging stakeholders to develop models that forecast impacts and risks of this transition. The most common modelling approaches rely on car movements provided in household travel surveys (HTS), despite their large data bias towards internal combustion engine vehicles. The scientific community has long wondered whether this characteristic of HTSs would undermine the conclusions drawn for EV mobility. This work applies state-of-the-art modelling techniques to the Swiss national HTS to conclusively prove, by means of validation, the reliability of these commonly used approaches. The cars tracked in the survey are converted to EVs, either pure battery or plug-in hybrids, and their performance is simulated over 4 consecutive days randomly sampled from the survey. EVs are allowed to charge at both residential and public locations at an adjustable charging power. Charging events are determined by a finely calibrated plugging-in decision scheme that depends on the battery’s state of charge. The resulting charging loads corroborate the validation, as these successfully compare with measurements obtained from several EV field tests. In addition, the study includes a sensitivity analysis that highlights the importance of accurately modelling various input parameters, especially EVs’ battery sizes and charging power. This work provides evidence that conventional HTSs are an appropriate instrument for generating EV insights, yet it adds guidelines to avoid modelling pitfalls and to maximise the simulation accuracy.
Pareschi et al. (Sat,) studied this question.