Numerous technologies are available for developing and evaluating electric drives in terrestrial vehicles, encompassing the electric motor, electronic power stage, power source, and mechanical engine used to link the load torque in electric vehicles. These technologies are not solely focused on enhancing electric performance and efficiency. Expert designers typically delve into detailed considerations to evaluate this technology more comprehensively. This paper presents a framework based on the S5 (Sensing, Smart, Sustainable, Social, and Security) framework, which can be integrated with artificial intelligence methodologies to offer a holistic evaluation that incorporates decision-makers needs. Specifically, the paper proposes an evaluation framework that combines genetic algorithms and Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The results demonstrate the superiority of this approach over the sole utilization of electric variable evaluations for evaluating the performance of the electric drive in an electric robot under only one condition.