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Perishable items like fresh food and life science products require efficient cold chain logistics, and using zero-emission electric vehicles offers an eco-friendly alternative but with operational challenges, particularly in energy efficiency and battery autonomy. The main aim of this research is to show that introducing temperature as a time-dependent variable in route design offers a more accurate approximation of energy consumption in a refrigerated fleet that is primarily influenced by the internal\u2013external temperature differential. Results show that considering time-dependent temperature variations provides more accurate refrigeration consumption estimates, with differences up to 16% compared to average temperature models. Refrigeration accounts for about 44% of total energy consumption, with product load and infiltration contributing 80% and 17%, respectively. 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