Optimal Selection of Navigation Modes of HEVs considering CO2 Emissions Reduction

Research output: Contribution to journalArticleScientificpeer-review


Research units

  • State University of Londrina (UEL)
  • University of Castilla-La Mancha


In this paper, a mixed-integer linear programming model is proposed to optimize hybrid electric vehicle (HEV) navigation modes on the city map, namely the problem of the optimal selection of navigation modes (OSNMs). The OSNMs problem of the HEV as part of the operating strategy is obtained considering a constraint set related to CO 2 emissions reduction, efficient battery charging, and the optimal scheduling of deliveries. Uncertainties in the HEV navigation on urban roads are modeled using probability values assigned to an established set of traffic density values according to the levels of service. The model is implemented in a mathematical programming language (AMPL) and solved using the commercial solver CPLEX. The case study considers real data related to the Prius Prime technology and shows the effectiveness of automating the HEV navigation modes considering CO 2 emissions reduction levels during an operating strategy.


Original languageEnglish
Article number8620548
Pages (from-to)2196-2206
Number of pages11
JournalIEEE Transactions on Vehicular Technology
Issue number3
Publication statusPublished - Mar 2019
MoE publication typeA1 Journal article-refereed

    Research areas

  • Efficient battery charging, Optimal selection navigation modes, optimal scheduling of deliveries, Operating strategy

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