Emerging green-energy cyber-physical systems (CPS), in particular electric-drive vehicles (PHEV, HEV, and EV), have demonstrated great potentials to significantly reduce greenhouse gas emissions and the ever-growing dependence on foreign oil. Few studies have focused on the user-specific driving behavior and its significant impact on electric-drive vehicles fuel efficiency, battery system life-cycle and the environment. This paper presents a personalized mobile sensing system development for the emerging green-energy CPS, which captures user’s run-time driving behavior and characterizes its impact on (P)HEV operations. The proposed sensing computing system has been deployed in a number of PHEVs and HEVs, with user studies of four different drivers and over 150 driving trips under various road and traffic conditions. Using the extracted real-world hybrid vehicle and user driving data, we have conducted detailed analytical studies of users’ specific driving patterns and their impacts on hybrid vehicle electric energy and fuel efficiency.