Sensitivity Analysis of Environmental Factors for Electric Vehicles Energy Consumption

This paper provides a sensitivity analysis of the required EV propulsion power with respect to environmental factors such as wind speed, rolling resistance and temperature. The results obtained show the degree to which environmental factors affect overall battery power and energy usage for electric transportation. The paper provides analytical expressions as well as simulations to illustrate the key sensitivity results. The significance of our findings for vehicle range estimation is discussed and potential avenues to exploit the strong dependency between propulsion energy and environmental factors are proposed.

[1]  Paul Denholm,et al.  Emissions impacts and benefits of plug-in hybrid electric vehicles and vehicle-to-grid services. , 2009, Environmental science & technology.

[2]  Ingmar Posner,et al.  The Route Not Taken: Driver-Centric Estimation of Electric Vehicle Range , 2014, ICAPS.

[3]  T. Fuller,et al.  A Critical Review of Thermal Issues in Lithium-Ion Batteries , 2011 .

[4]  Xiaosong Hu,et al.  Charging time and loss optimization for LiNMC and LiFePO4 batteries based on equivalent circuit models , 2013 .

[5]  Mark A. Delucchi,et al.  Future Drive: Electric Vehicles And Sustainable Transportation , 1994 .

[6]  Xiaosong Hu,et al.  Comparison of Three Electrochemical Energy Buffers Applied to a Hybrid Bus Powertrain With Simultaneous Optimal Sizing and Energy Management , 2014, IEEE Transactions on Intelligent Transportation Systems.

[7]  A. Pesaran,et al.  Addressing the Impact of Temperature Extremes on Large Format Li-Ion Batteries for Vehicle Applications (Presentation) , 2013 .

[8]  Thomas H. Bradley,et al.  Design, demonstrations and sustainability impact assessments for plug-in hybrid electric vehicles , 2009 .

[9]  Ulrich Eberle,et al.  Sustainable transportation based on electric vehicle concepts: a brief overview , 2010 .

[10]  Ingmar Posner,et al.  Probabilistic attainability maps: Efficiently predicting driver-specific electric vehicle range , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

[11]  John G. Hayes,et al.  Simplified electric vehicle power train models and range estimation , 2011, 2011 IEEE Vehicle Power and Propulsion Conference.

[12]  Xiaosong Hu,et al.  Energy efficiency analysis of a series plug-in hybrid electric bus with different energy management strategies and battery sizes , 2013 .

[13]  C. Binding,et al.  Optimization Methods to Plan the Charging of Electric Vehicle Fleets , 2010 .

[14]  Peter H. Bauer,et al.  Spatio-Temporal Energy Demand Models for Electric Vehicles , 2014, 2014 IEEE Vehicle Power and Propulsion Conference (VPPC).

[15]  L. Dickerman,et al.  A New Car, a New Grid , 2010, IEEE Power and Energy Magazine.

[16]  K. S. Grewal,et al.  Model-based EV range prediction for Electric Hybrid Vehicles , 2013 .

[17]  Peter H. Bauer,et al.  Energy Consumption Model and Charging Station Placement for Electric Vehicles , 2014, SMARTGREENS.