Applying Probability Method for Battery Electric Vehicle Selection

The global automotive industry is actively transitioning to the production of battery electric vehicles (BEVs) to significantly reduce carbon emissions and contribute to a greener planet. The proliferation of BEVs is not only a trend but also an urgent solution to address climate change. In the context of a world striving for sustainable development, choosing the right electric vehicle becomes a crucial decision for consumers. This study, for the first time, applies the probability method to select an electric vehicle from ten available options. Each electric vehicle is described by 11 criteria, and the weights of these criteria have been calculated using three different methods: MEREC, CRITIC, and equal weights. This study found that regardless of the method used to weigh the criteria, the probabilistic method consistently identified the best BEV. Furthermore, the BEV identified as the best using the probabilistic method coincided with those found using the PIV, TOPSIS, and SAW methods. This research has pioneered in demonstrating the accuracy of the probability method when used to rank BEVs.