2014 IEEE/ACM International Conference on Computer-Aided Design (ICCAD) 2014
DOI: 10.1109/iccad.2014.7001349
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Power consumption characterization, modeling and estimation of electric vehicles

Abstract: Rapid electric vehicle (EV) penetration gives a threatening challenge in electric energy generation. An 1,814 kg curb weight full electric vehicle driving 18,129 km/year consumes electricity energy equivalent to 74% of the total residential electricity use per person in the US. This implies that 27% more nationwide electricity generation is needed when 70% of passenger vehicles are replaced with EVs. This paper is the first step toward systematic EV design-time and runtime optimization. We introduce instantane… Show more

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Cited by 31 publications
(23 citation statements)
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(6 reference statements)
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“…where F R , F G , F I , F A , θ, m, v, and a are the rolling resistance, gradient resistance, inertia resistance, aerodynamic resistance, road slope, vehicle curb weight, velocity, and acceleration, respectively [1]. The model coefficients α, β, γ, and A represent rolling resistance, gradient resistance, inertia resistance, and aerodynamic resistance, respectively.…”
Section: A Conventional Physics Equation Based Modelmentioning
confidence: 99%
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“…where F R , F G , F I , F A , θ, m, v, and a are the rolling resistance, gradient resistance, inertia resistance, aerodynamic resistance, road slope, vehicle curb weight, velocity, and acceleration, respectively [1]. The model coefficients α, β, γ, and A represent rolling resistance, gradient resistance, inertia resistance, and aerodynamic resistance, respectively.…”
Section: A Conventional Physics Equation Based Modelmentioning
confidence: 99%
“…5. Velocity versus regenerative braking power [1]. where δ is the coefficient corresponding to the regenerative force, and ε to be the minimum power to generate the regenerative braking power.…”
Section: A Power Consumption and Harvesting Estimationmentioning
confidence: 99%
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