期刊
JOURNAL OF POWER SOURCES
卷 275, 期 -, 页码 435-446出版社
ELSEVIER
DOI: 10.1016/j.jpowsour.2014.11.043
关键词
Electric vehicle; Driving strategy; Range prediction; Multi-objective optimization; Genetic algorithm
资金
- Department of Mechanical AMP
- Aerospace Engineering
- Indo-US Science and Technology Forum (IUSSTF), New Delhi, India [2013/40]
Due to the limited range and long charging time for electric vehicles, proper utilization of the stored battery energy is crucial. Current methods for electric vehicle range estimation do not help the driver to formulate a driving strategy based on trip parameters (e.g., trip speed) related to power savings. This can be done by predicting the driving range based on optimal trip parameters prior to the trip enabling the driver to formulate a suitable driving strategy. This study proposes a novel strategy that presents a number of optimal trip speeds to the driver, along with the total trip time corresponding to a predicted range. The optimal speeds were obtained by solving a multi-objective optimization problem that maximized electric motor efficiency and minimized power consumption. Two approaches to calculate the objective functions were considered: using constant battery voltage and using battery voltage as a function of the state-of-charge. Pareto-optimal fronts were obtained and a plot of the predicted range and trip times for optimal speeds was created. It was found that the shape of the fronts was not affected by the approach; however, the range was overestimated when a constant battery voltage was used. (C) 2014 Elsevier B.V. All rights reserved.
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