Time-Varying and Asymmetric Relationship between Energy Use and Macroeconomic Activity

Transit bus passenger loading changes significantly over the course of a workday. Therefore, time-varying vehicle mass as a result of passenger load becomes an important factor in instantaneous energy consumption. Battery-powered electric transit buses have restricted range and longer “fueling” time compared with conventional diesel-powered buses; thus, it is critical to know how much energy they require. Our previous work has shown that instantaneous transit bus mass can be obtained by measuring the pressure in the vehicle’s airbag suspension system. This paper leverages this novel technique to determine the impact of time-varying mass on energy consumption. Sixty-five days of velocity and mass data were collected from in-use transit buses operating on routes in the Twin Cities, MN metropolitan area. The simulation tool Future Automotive Systems Technology Simulator was modified to allow both velocity and mass as time-dependent inputs. This tool was then used to model an electrified and conventional bus on the same routes and determine the energy use of each bus. Results showed that the kinetic intensity varied from 0.27 to 4.69 mi−1 and passenger loading ranged from 2 to 21 passengers. Simulation results showed that energy consumption for both buses increased with increasing vehicle mass. The simulation also indicated that passenger loading has a greater impact on energy consumption for conventional buses than for electric buses owing to the electric bus’s ability to recapture energy. This work shows that measuring and analyzing real-time passenger loading is advantageous for determining the energy used by electric and conventional diesel buses.

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Semi-synthetic Data and Testbed for Long-Distance E-Vehicle Routing

New Trends in Database and Information Systems - Communications in Computer and Information Science ◽

10.1007/978-3-030-85082-1_6 ◽

2021 ◽

pp. 61-71

Author(s):

Andrius Barauskas ◽

Agnė Brilingaitė ◽

Linas Bukauskas ◽

Vaida Čeikutė ◽

Alminas Čivilis ◽

...

Keyword(s):

Travel Time ◽

Energy Use ◽

Synthetic Data ◽

Route Planning ◽

Data Sets ◽

Time Varying ◽

Long Distance ◽

Elevation Data ◽

Autonomous Mobility ◽

Time And Energy

AbstractElectric and autonomous mobility will increasingly rely on advanced route planning algorithms. Robust testing of these algorithms is dependent on the availability of large realistic data sets. Such data sets should capture realistic time-varying traffic patterns and corresponding travel-time and energy-use predictions. Ideally, time-varying availability of charging infrastructure and vehicle-specific charging-power curves should be included in the data to support advanced planning.We contribute with a modular testbed architecture including a semi-synthetic data generator that uses a state-of-the-art traffic simulator, real traffic distribution patterns, EV-specific data, and elevation data to generate time-dependent travel-time and energy-use weights in a road-network graph. The experimental study demonstrates that the testbed can reproduce travel-time and energy-use patterns for long-distance trips similar to commercially available services.

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The Psychology of Energy Use

Contemporary Psychology ◽

10.1037/020669 ◽

1982 ◽

Vol 27 (10) ◽

pp. 768-770

Author(s):

Stuart Oskamp

Keyword(s):

Energy Use

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Adaptative Model of the Human Operator in a Time-Varying Control Task

PsycEXTRA Dataset ◽

10.1037/e506122009-008 ◽

1966 ◽

Author(s):

E. E. Gould ◽

K. S. Fu

Keyword(s):

Human Operator ◽

Time Varying ◽

Control Task

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Daily Occupant Behavior Pattern Affecting Energy Use in Residential Buildings

Construction Research Congress 2020 ◽

10.1061/9780784482865.055 ◽

2020 ◽

Author(s):

Yunjeong Mo ◽

Dong Zhao ◽

James Sorce

Keyword(s):

Energy Use ◽

Behavior Pattern ◽

Residential Buildings ◽

Occupant Behavior

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Local Policy for a Protected Environmental Area Management: The Case of Limiting Motorized Vehicles in Park of Canigou in Pyrenées Orientales

Advance in Environmental Waste Management & Recycling ◽

10.33140/aewmr.01.01.09 ◽

2018 ◽

Vol 1 (1) ◽

Keyword(s):

Climate Change ◽

Human Activities ◽

Energy Use ◽

Local Level ◽

Air Traffic ◽

Small Scale ◽

Individual Action ◽

Local Policy ◽

Motorized Vehicles ◽

Local Levels

“We regard the recent science –based consensual reports that climate change is, to a large extend, caused by human activities that emit green houses as tenable, Such activities range from air traffic, with a global reach over industrial belts and urban conglomerations to local small, scale energy use for heating homes and mowing lawns. This means that effective climate strategies inevitably also require action all the way from global to local levels. Since the majority of those activities originate at the local level and involve individual action, however, climate strategies must literally begin at home to hit home.”

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