Performance Study of a Developed Rule-Based Control Strategy with Use of an ECMS Optimization Control Algorithm on a Plug-In Hybrid Electric Vehicle

Abstract Greenhouse gases jeopardize world’s climate. A significant amount of these pollutants is produced by road vehicles, so their producers are forced to reduce emissions significantly. This means that every car manufacturer expanding electrified vehicle range. Fully electric vehicles the best way for long-term elimination greenhouse production in transport. However, short term it not possible switch all EVs. Temporary solutions hybrid which offer a compromise between conventional and vehicles. In addition right choice powertrain correct scaling its components, also important develop suitable control strategy energy management. The main goal this work compare performance rule-based with built-in local optimization algorithm ECMS GT-SUITE TM software. Equivalent Consumption Minimization Strategy based on an selected parameters each time step driving cycle simulation. fuel efficiency improvement assessed plug-in vehicle. Results WLTC simulations charge sustaining mode (state battery at beginning end simulation same) shows consumption 5 l/100km rule 4.2 algorithm. can achieve more than 16% particular