Machine learning and whale optimization algorithm based design of energy management strategy for plug?in hybrid electric vehicle

In this paper, a novel energy management strategy with the improved adaptability to various conditions for plug-in hybrid electric vehicle (PHEV) is proposed. The control parameters, derived from benchmark test, are optimized offline different driving conditions. parameters implemented according behaviours identified online. and online cooperation improves performance of in Three main efforts have been made: Firstly, valuable features that describe extracted by random forest (RF) used determining condition categories, utilized identification support vector machine (SVM). Secondly, thresholds developed whale optimization algorithm (WOA) under optimal will be called after certain traffic categorized. At last, simulation-based evaluation performed, validating enhanced proposed methods energy-saving