Parameter identification of BIPT system using chaotic-enhanced fruit fly optimization algorithm

摘要: Bidirectional inductive power transfer (BIPT) system facilitates contactless between two sides and across an air-gap, through weak magnetic coupling. Typically, this is nonlinear high order which includes switch components resonant networks, developing of accurate model a challenging task. In paper, novel technique for parameter identification BIPT presented by using chaotic-enhanced fruit fly optimization algorithm (CFOA). The (FOA) new meta-heuristic based on the swarm behavior fly. This paper proposes CFOA, employs chaotic sequence to enhance global capacity original FOA. formalized as multi-dimensional problem, objective function established minimizing errors estimated measured values. All 11 parameters (Lpi, LT, Lsi, Lso, CT, Cs, M, Rpi, RT, Rsi Rso) can be identified simultaneously input-output data. Simulations show that proposed robust measurements noise variation operation condition thus it suitable practical application.