Effects of environmental factors on electric vehicle energy consumption: a sensitivity analysis

Abstract

Special section 'Design, modelling and control of electric vehicles') This study provides a detailed deterministic and stochastic sensitivity analysis of the propulsion energy cost of electric vehicles (EVs) with respect to environmental variables. In particular, the effects of wind speed, rolling resistance, parasitic power and temperature are highlighted. The study provides exact analytical expressions as well as simulations to illustrate the key results. It is shown that the sensitivity of energy consumption with respect to the four environmental variables greatly vary with operating conditions of the vehicle. These environmental effects can have a profound effect on the overall energy consumption of EVs and drastically affect range. The significance of the authors' findings for vehicle range estimation is discussed and potential avenues to exploit the strong dependency between propulsion energy and environmental factors are proposed.

Plug-in Hybrid Ecological Category in Real Driving Emissions

“…Under actual traffic conditions in sub-zero temperatures, the energy consumption in such a vehicle is greater by 14% compared to warm weather. Similar investigations were carried out by Yi et al [13], indicating that energy consumption in the electric vehicle (EV) may vary drastically depending on the driving conditions, which is extremely impactful on the vehicle range.…”

Data-driven optimal charging decision making for connected and automated electric vehicles: A personal usage scenario

“…In this equation, v is vehicle speed, C d denotes the air drag coefficient, A is the projected frontal area, w is the wind speed component in the direction of vehicle speed, ρ is the air density, M is the vehicle mass, C r is the coefficient of rolling resistance, α is the angle of road surface for the slope or grade,M is the equivalent mass considering the inertial mass factors and a is the vehicle acceleration. The detailed analysis of this equation can be found in Yi and Bauer (2017b). The longitudinal dynamical model describes tractive force coupled with a speed profile.…”

Influence Factors and Correction coefficient for Energy Consumption of Electric Vehicles

“…However, in the actual use process, there is a big gap between the energy consumption of pure electric vehicles and the laboratory environment. In order to analyze the actual operation process on the vehicle energy consumption rate, Yi et al analyzed the sensitivity of driving style to vehicles [3] . Li et al studied the classification and recognition methods of drivers' driving styles further [4] .…”