Extreme temperatures pose several limitations to electric vehicle (EV) performance and charging. To investigate these effects, we combine a hybrid artificial neural network-empirical Li-ion battery model with a lumped capacitance EV thermal model to study how temperature will affect the performance of an EV fleet. We find that at −10 °C, the self-weighted mean battery charging power (SWMCP) decreases by 15% compared to standard 20 °C temperature. Active battery thermal management (BTM) during parking can improve SWMCP for individual vehicles, especially if vehicles are charged both at home and at workplace; the median SWMCP is increased by over 30%. Efficiency (km/kWh) of the vehicle fleet is maximized when ambient temperature is close to 20 °C. At low (−10 °C) and high (+40 °C) ambient temperatures, cabin preconditioning and BTM during parking can improve the median efficiency by 8% and 9%, respectively. At −10 °C, preconditioning and BTM during parking can also improve the fleet SOC by 3–6%-units, but this also introduces a “base” load of around 140 W per vehicle. Finally, we observe that the utility of the fleet can be increased by 5%-units by adding 3.6 kW chargers to workplaces, but further improved charging infrastructure would bring little additional benefit.