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- W1995987913 abstract "For electric vehicle (EV) operation, a major concern is whether the available onboard battery charge could sustain a specific trip or not. It is of practical benefit for EV driver to predict the battery energy demand for a specific trip a prior. This paper presents a trip specific scheme for estimating the battery stateofcharge (SOC) change based on the trip modelling in a probabalistic fashion. Assuming an approximate constantacceleration model for trip segments, there are cases of accelerating, constant speed and decelerating segments. The distribution density functions of the segmental acceleration and mean speed are estimated from test driving cycle data. The stochastic characteristics of the SOC change for a specific trip is then obtained via a Monte Carlo type method. For an example trip in the greater Milwaukee area, simulation results show that for the example trip, the SOC change is 33.4% ? 6.4% with 95% confidence." @default.
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- W1995987913 date "2011-01-01" @default.
- W1995987913 modified "2023-09-24" @default.
- W1995987913 title "Trip-based stochastic prediction of battery state-of-charge for electric vehicles" @default.
- W1995987913 doi "https://doi.org/10.1504/ijehv.2011.044371" @default.
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