Eco-Drive Experiment on Rolling Terrain for Fuel Consumption Optimization

10422202032017PDFTech ReportFHWA-HRT-18-037DTFH6116D00030 Task Order 07Fuel conservationEcodrivingFuel consumptionUnited StatesUnited States. Federal Highway Administration. Office of Operations Research and DevelopmentMa, JiaqiHu, JiaLeslie, EdZhou, FangHuang, ZhitongLeidosUnited States. Federal Highway Administration. Office of Operations Research and DevelopmentTurner-Fairbank Highway Research CenterHuang, P. C.Bared, Joe G.Federal Highway AdministrationEco-drive is one of the many theoretical concepts that have been developed to increase vehicle fuel efficiency and improve the sustainability of the entire transportation system within the connected vehicle paradigm. This study proposes an eco-drive algorithm for vehicle fuel consumption optimization on rolling terrains, which frequently cause additional fuel waste because of inefficient transformation between kinetic and potential energy. The algorithm uses the Relaxed Pontryagin\u2019s Minimum Principle (RPMP), is computationally efficient, and is applicable in real time. While similar algorithms have proven effective in simulation with many assumptions, it is necessary to test these algorithms in the field to better understand the algorithm\u2019s performance and thus enable optimal vehicle control in support of eco-driving. Therefore, this study further tested and verified the newly developed algorithms on an innovative connected and automated vehicle (CAV) platform and quantified the fuel saving benefits of eco-drive. The proposed eco-drive system is compared against conventional constant-speed cruise control on a total of 7 road segments over 47 miles. Experimental data show that more than 20 percent of fuel consumption can be avoided on certain terrains. Detailed analysis through linear models also reveals the main geometrical contributors to eco-drive fuel savings. This conclusion can enable a rough estimate of fuel saving potential on given roadways and help State departments of transportation to identify roadways where eco-drive should be implemented. The algorithm and the experiment can also support original equipment manufacturers in developing and marketing this technology to reduce fuel consumption and emissions in the future