Optimization of Control Variables of a Series-Parallel Hybrid Electric Power Train

A back propagation through time-like conjugate gradient-based algorithm is used for off-line optimization of a series-parallel hybrid power train control variables over standardized certification driving cycles. The aim is to minimize the fuel consumption subject to battery state-of-charge constraints. The optimization is carried out using a simplified power train model in order to find optimal engine speed and torque time responses. The optimization results are presented for three characteristic certification driving cycles.