The growing demand for reducing greenhouse gas emissions is driving the development of intelligent electric vehicles and strategies for optimizing energy consumption. However, challenges such as limited driving range, scarce charging infrastructure, and traffic uncertainties impact the acceptance of these vehicles. In this context, this study analyzes the application of Digital Twins (DTs) as a tool for optimized route planning and real-time monitoring of energy consumption in electric vehicles.
Through a bibliometric analysis, recent trends and applications that interconnect DTs, energy efficiency, and trajectory planning are 
identified.
The analysis of the Web of Science database resulted in 4,209 documents, of which 206 included the term ``digital twin'' as a keyword. The construction of the bibliometric map reveals five main clusters, with the terms ``electric vehicles'', ``energy efficiency'', ``autonomous vehicles'', and ``digital twin'' as central topics. The data show that, although the term "digital twin" still has a lower frequency of co-occurrence, it has emerged as a growing trend with strong potential for practical application in the analyzed subjects.