Data-Driven Decision Aids for Purchasing Battery Electric Vehicles Based on PROMETHEE-II Methodology

Abstract

Considering the significant contribution of the transport sector to carbon emissions, the importance of battery electric vehicles (BEVs) as environmentally friendly vehicles is self-evident. Due to the rapid expansion of the BEV market in recent years, a comprehensive evaluation of BEV options from the consumer perspective has become an important issue. This paper proposes a data-driven decision aids for purchasing BEVs based on a multiple criteria decision-making methodology (i.e., PROMETHEE-II). A hierarchical evaluation criteria system of BEVs is constructed and correlation analysis between indicators is performed to eliminate duplicate indicators. Then, a comprehensive weighting method by integrating largescale group decision making method and the Entropy-based method is proposed to identify the weights of criteria. Based on which, the ranking of candidate BEVs can be obtained based on the PROMETHEE-II with a hierarchical evaluative criteria, which can help consumers make BEV purchase choices. Furthermore, the robustness and reliability of the results are tested by applying the sensitivity analysis and contrastive analysis.INDEX TERMS Multiple criteria decision-making, hierarchical decision modelling, battery electric vehicle, decision support, PROMETHEE II.

Functional Failure Criticality Assessment and Control of Power Distribution Systems: Failure Prioritization Using AHP

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