Key points are not available for this paper at this time.
In light of increasing demands on decarbonized transportation systems, it became increasingly necessary to meet performance and environmental requirements for electromobility. Major challenges of electrified transportation can be pointed out as: rapid degradation of batteries, limited driving range and performance, and charging scheduling within infrastructural capabilities. Intelligent power management systems (I-PMSs), providing optimal energy handling decisions for electrified drivelines, have been increasingly the focus of electrification efforts, due to their significant potential to tackle the aforementioned challenges despite existing technological limitations. This contribution presents a comparative evaluation of recent advances in predictive and cognitive PMS with a particular focus on problem formulation, solving techniques, and practical examples of each method. Moreover, the evolving role of I-PMS in light of emerging intelligent transportation systems (ITSs) and connected vehicles technologies (CVTs) is discussed, to point out the ability of I-PMS to bridge the gap toward smart electromobility. This comprehensive overview of I-PMS aims at providing useful insights into the pros and cons of each method and puts forward potential outcomes for electrified transportation.
Ali et al. (Mon,) studied this question.