DocumentCode :
1787595
Title :
Power consumption characterization, modeling and estimation of electric vehicles
Author :
Naehyuck Chang ; Donkyu Baek ; Jeongmin Hong
Author_Institution :
Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea
fYear :
2014
fDate :
2-6 Nov. 2014
Firstpage :
175
Lastpage :
182
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 instantaneous power consumption modeling of an EV by the curb weights, speed, acceleration, road slope, passenger and cargo weights, motor capacity, and so on, as a battery discharge model. The model also considers the onboard charger, regenerative braking and so on, as a battery charge model. To insure model fidelity, we fabricate a lightweight custom EV, perform extensive measurement, and derive model coefficients using multivariable regression analysis. We estimate the EV instantaneous power consumption of a given speed and route profiles and verify the estimation fidelity with a real test run data.
Keywords :
battery powered vehicles; optimisation; power consumption; regenerative braking; regression analysis; road vehicles; secondary cells; EV passenger; battery charge model; battery discharge model; electric energy generation; electric vehicle driving; electric vehicle penetration; instantaneous power consumption model; multivariable regression analysis; onboard charger; regenerative braking; residential electricity; runtime optimization; systematic EV instantaneous power consumption; Batteries; Electricity; Petroleum; Power demand; Power generation; Traction motors; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Aided Design (ICCAD), 2014 IEEE/ACM International Conference on
Conference_Location :
San Jose, CA
Type :
conf
DOI :
10.1109/ICCAD.2014.7001349
Filename :
7001349
Link To Document :
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