Intelligent power management based on multi-objective cost function for plug-in biogas hybrid vehicles under uncertain driving conditions

Abstract This paper presents a new intelligent power management strategy based on multi-objective cost function for plug-in biogas hybrid vehicles (PBHVs). consists of long-term and short-term controller. The depends an improved generalized particle swarm optimization algorithm (IGPSO) to obtain the globally optimal values motor engine torques. To reduce computation time, five-mode rule-based control is used, where IGPSO estimates torques in mode depending function. aims fuel consumption drawn current from battery takes into consideration ageing. controller designed using interval type-2 Takagi–Sugeno-Kang (IT2TSK) fuzzy algorithm, which human experts overcome uncertainties driving conditions. Lyapunov stability theory online proved. proposed technique improves energy compared other techniques. simulation results real data engine, illustrate feasibility effectiveness approach with comparative results.