The ability to accurately predict the energy consumption of electric vehicles (EVs) is important for alleviating the range anxiety of drivers and is a critical foundation for the spatial planning, operation and management of charging infrastructures. Based on the GPS observations of 68 EVs in Aichi Prefecture, Japan, an energy consumption model is proposed and calibrated through ordinary least squares regression and multilevel mixed effects linear regression. Specifically, this study focuses on how the ambient temperature affects electricity consumption. Moreover, the interactive effects of ambient temperature and vehicle auxiliary loads are explored. According to the results, the ambient temperature affects the energy efficiency significantly by directly influencing the output energy losses and the interactive effects associated with vehicle auxiliary loads. Ignoring the interactive effects between ambient temperature and vehicle auxiliary loads will exaggerate the energy consumption of the heater during warm conditions and underestimate the energy consumption of the air conditioner during cold conditions. The most economic energy efficiency was achieved in the range of 21.8–25.2 °C. The potential energy savings during proper usage of vehicle auxiliary loads is discussed later based on estimated parameters. As a result, a mean of 9.66% electricity will be saved per kilometre by eradicating unreasonable EV auxiliary loads.

准确预测电动汽车（EV）能耗的能力对于减轻驾驶员的行驶里程焦虑至关重要，并且是充电基础设施的空间规划，运营和管理的关键基础。基于日本爱知县对68辆电动汽车的GPS观测，提出了一种能耗模型，并通过普通最小二乘回归和多级混合效应线性回归进行了校准。具体而言，本研究着重于环境温度如何影响电力消耗。此外，探索了环境温度和车辆辅助负载的相互作用。根据结果​​，环境温度通过直接影响输出能量损失以及与车辆辅助负载相关的交互作用，极大地影响了能源效率。忽略环境温度和车辆辅助负载之间的交互作用会夸大在温暖条件下加热器的能耗，并低估了在寒冷条件下空调的能耗。在21.8–25.2°C的范围内实现了最经济的能源效率。稍后将基于估计的参数讨论在适当使用车辆辅助负载期间可能节省的能源。结果，通过消除不合理的EV辅助负载，每公里平均可节省9.66％的电力。忽略环境温度和车辆辅助负载之间的交互作用会夸大在温暖条件下加热器的能耗，并低估了在寒冷条件下空调的能耗。在21.8–25.2°C的范围内实现了最经济的能源效率。稍后将基于估计的参数讨论在适当使用车辆辅助负载期间可能节省的能源。结果，通过消除不合理的EV辅助负载，每公里平均可节省9.66％的电力。忽略环境温度和车辆辅助负载之间的交互作用会夸大在温暖条件下加热器的能耗，并低估了在寒冷条件下空调的能耗。在21.8–25.2°C的范围内实现了最经济的能源效率。稍后将基于估计的参数讨论在适当使用车辆辅助负载期间可能节省的能源。结果，通过消除不合理的EV辅助负载，每公里平均可节省9.66％的电力。稍后将基于估计的参数讨论在适当使用车辆辅助负载期间可能节省的能源。结果，通过消除不合理的EV辅助负载，每公里平均可节省9.66％的电力。稍后将基于估计的参数讨论在适当使用车辆辅助负载期间可能节省的能源。结果，通过消除不合理的EV辅助负载，每公里平均可节省9.66％的电力。