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.
Personalized Mobile Sensing System Development for Emerging Electric-Drive Vehicles
2012
5 Seiten
Conference paper
English
Personalized Mobile Sensing System Development for Emerging Electric-Drive Vehicles
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