电动力车等新能源汽车技术在我国日渐受到广泛关注的同时，针对其生命周期内的能耗和排放影响亟需进行科学评估。本研究采用燃料生命周期分析（WTW）的方法，应用GREET模型对全国和京津冀、长三角、珠三角三个地区的传统混合动力车（HEV）、插电式混合动力车（PHEV）和纯电动车（EV）相比传统汽油轿车（ICEV）的WTW单车节能和CO2减排效果进行评估；在此基础上结合全国和三个地区轻型乘用车（LDPV）保有量和电动汽车增长趋势的预测，对电动力车队WTW节能和CO2减排效益进行分析；本研究还评估了不同电动力车充电模式对平抑电网昼夜负荷峰谷差的影响。不论是全国平均水平还是典型地区，HEV、PHEV和EV都能够大幅度降低WTW单车石油消耗，与ICEV相比削减幅度分别为29%、50%和99%。PHEV和EV单车WTW化石能耗的削减效益显著低于石油消耗的削减幅度，2030年削减幅度分别为28%和51%。由于上游电力构成中煤电占据主导地位和煤的高碳含量特征，单车WTW CO2排放削减效益进一步弱化于化石能耗的削减，2030年PHEV和EV的削减幅度分别为21%和35%。三个地区（京津冀、长三角和珠三角）电动力车单车WTW化石能耗和CO2排放削减的不同主要源于地区电力构成的差异，在煤电比例很高的地区如京津冀地区，HEV在WTW CO2减排方面近中期内会比PHEV和EV更有优势。电动力车的推广可以显著削减我国LDPV的能耗和CO2排放。2030年设定的4种电动力车情景下车队TTW汽油消耗、WTW化石能耗和CO2排放分别比高增长情景低20%-36%、20%-30%和20%-26%。由于我国LDPV保有量基数大和增长率高，电动汽车推广所带来的节能和CO2减排效益的显著体现具有时间滞后性。在清洁电力比例高的地区（例如珠三角），电动力车的推广能达到更好的车队WTW节能和CO2削减效果。此外推动积极的电动汽车增长模式，可以使车队能耗和CO2排放的峰值年限明显提前。不同充电模式会对电网负荷产生不同的影响。智能填充模式下，电动力车对全国电网的“填充”发生在电网负荷的最低谷；而在北京采用电动车情景4则几乎填满了低谷。分时段填充对电网负荷的影响较智能填充更为显著，尤其在北京等大城市，可能会显著增加峰值负荷，并形成新的负荷峰。

With increasing concern on energy consumption and environmental impact of transportation in China, vehicle electrification has been seriously considered as an industry revolution to sustainable transportation. It is essential to evaluate the energy consumption and CO2 emissions of the advanced power/fuel technologies such as hybrid electric vehicle (HEV), plug-in hybrid electric vehicle (PHEV) and pure electric vehicle (EV) at the life-cycle basis. In this study, GREET model was used to calculate per-kilometre well-to-wheels (WTW) energy consumption and CO2 emission benefits of HEV, PHEV and EV compared to internal combustion engine vehicle (ICEV) in national level and three well-developed regions (Jing-Jin-Ji, Yangtze-River-Delta and Pearl-River-Delta) in China. Furthermore, assoicated with the projection of light-duty passenger vehicle (LDPV) and the four scenarios of HEV/PHEV/EV growth, fleet WTW energy use and CO2 emissions were evaluated and compared among various technology options. The impact of different charging modes of electric powered vehicles to power grid load was further assessed. Promotion of HEV, PHEV and EV (especially the latter two) could help cut per-kilometre WTW petroleum use to a great extent, 29%, 50% and 99% lower than that of ICEV, respectively. The reduction potential in WTW fossil energy consumption of PHEV and EV is significantly lower than that of petroleum energy use, with the WTW fossil energy use reduction by 28% (PHEV) and 51% (EV) in 2030. Due to the overwhelming share of coal power and the highest C content per unit of energy generation in coal among the three major fossil fuels, the WTW CO2 emission reduction benefits with promotion of PHEV and EV will be even worse than the reduction potential for fossil fuels, and the WTW CO2 reduction is 21% (PHEV) and 35% (EV) by 2030. In the three regions, the difference in generation mix leads to the different results for per-kilometre WTW fossil fuel use and CO2 emissions. HEV is a better solution than PHEV and EV to mitigate WTW CO2 emissions in all three regions in the near and mid-term future (especially in Jing-Jin-Ji region). For LDPV fleet, the promotion of HEV, PHEV and EV could help cut fleet energy use and CO2 emisions. By 2030, for HEV/PHEV/EV penetration scenarios 1-4, the reduction rate in fleet TTW gasoline consumption, WTW fossil fuel use and WTW CO2 emisions relative to the high LDPV scenario is 20%-36%, 20%-30% and 20%-26%, respectively. In addition, because of China's huge LDPV stock and rapid growth trend, a significant reduction in energy and CO2 with the promotion of electric vehicles will not come any time soon. The promotion of electric vehicles could achieve significant benefits of energy-saving and CO2 reduction in the region with a much cleaner electricity generation mix (e.g., Pearl-River Delta region). To promote electric vehicles in an aggressive way might advance the peak-year of energy consumption and CO2 emissions in all three regions. Different electricity filling patterns for PHEV and EV affect the power grid load in different ways. For the “Smart-filling”, the filling almost occurs in the bottom of power grid load in China; however, the electricity consumption of HEV/PHEV/EV penetration scenario 4 could make the power grid operate in the hightest load during all the day in Beijing. The “Time series-filling” have more significant impact than smart-filling, which is especially true for big cities like Beijing. It may increase the peak load of power grid, or even form another new peak load.