文章基本信息

标题：A Computationally Efficient Predictive Cruise Control for Automated Electric Vehicles
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作者：Shiying Dong ; Bingzhao Gao ; Qifang Liu 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：14173-14178
DOI：10.1016/j.ifacol.2020.12.1037
语种：English
出版社：Elsevier
摘要：AbstractThis paper proposes an energy-efficient predictive cruise control (PCC) system to cope with range anxiety of automated electric vehicles. The proposed approach is formulated as an optimal control problem to realize better energy efficiency and ensure safe inter-vehicle distance. To improve computational efficiency, a fast algorithm combining Gauss pseudospectral method (GPM) and moving horizon control (MHC) is introduced to solve this nonlinear optimal problem. The comparative simulation results reveal that the energy economy of the PCC system is improved about 4.1%, and its computation time is reduced compared with the Euler method while ensuing the same accuracy.
关键词：KeywordsPredictive cruise controlRange anxietyAutomated electric vehiclesGauss pseudospectral methodMoving horizon control