GETTING SMART ER ON ENERGY & MOBILITY REUBEN SARKAR Department - PowerPoint PPT Presentation

GETTING SMART ER ON ENERGY & MOBILITY REUBEN SARKAR Department of Energy June 2 nd , 2016

THE OPPORTUNITY AND PROBLEM … . Massive wave of changes hitting our transportation system Megatrends Shared Mobility MaaS GPS/Map Services E-Retailing Master the wave or get washed out on GHG emissions 2

TODAY … .ADVANCED VEHICLES IN A SUB-OPTIMAL SYSTEM Efficient vehicles enter an CAVs technology targeting inefficient system safety is hitting the market. Designing for the nexus of safety, energy, and mobility 3

INTRODUCING TRANSPORTATION-AS-A-SYSTEM § Today: Explore untapped system- level efficiencies at − Vehicle-level focus planning and operations − Independent timescales − Unconnected − Subject to behaviors & decisions § Tomorrow: − System-level focus − Connected − Automated − In concert − Across modes − Managed behaviors & decisions 4

LARGE ENERGY AND GHG EMISSIONS IMPLICATIONS +200% Potential Increase in Energy Consumption 2050 Baseline Energy Consumption Potential Decrease in Energy Consumption -90% Vast range of energy implications … more research required 5 5

UNLOCKING VALUE MAY UNLEASH CONSUMPTION +200% Travel More Potential Increase in Energy Consumption Travel Faster Modal Shifting* Ship More Goods* * Not included in preliminary projections 2050 Baseline Energy Consumption Reduce Congestion Potential Decrease in Smooth Traffic Flow Energy Consumption Operate More Efficiently -90% Adopt More ZEVs Will new value creation drive unbridled consumption? 6

INCREASINGLY COMPLEX DECISION ENVIRONMENT Charging/Fueling Connected Infrastructure Travelers Cities and Regions Decisions Image by NREL Data Management CAVs Energy Infrastructure More Decisions 7 Transforming complexity into clarity for decision makers?

CONNECTED & AUTOMATED VEHICLES (CAVs) § Quantify the energy impacts § Identify CAV-enabled opportunities § Inform policy/research on CAVs § Address the barriers to CAVs EERE Incubator Award (U of M, ANL, INL) 500 Vehicle Fleet Improving our ability to predict the energy impact of CAV’s

URBAN MOBILITY SCIENCE § A new class of data science § City-scale computational mobility models § Revealing the previously unknown Providing scientific support to decision makers

MOBILITY DECISION SCIENCE § A science of decision making Transportation System Travel Driving § Increasingly complex decision Decision environment Points § Convergence of ICT, IOT, Shared Economy Lifestyle Technology and policy that anticipate how decisions are made

WORLD CLASS LABORATORY RESOURCES Massive data feeds Automation tools Multi-scale mobility models Propulsion / powertrain HPC architecture and systems Modeling systems Land use models and regional models 11

DOE SMART MOBILITY Multi-lab consortia exploring the nexus of energy and future mobility paradigms