Optimal hybridization in two parallel hybrid electric vehicles using dynamic programming

Abstract

This study explores different hybridization ratios of two types of parallel hybrid electric vehicles, a torque assist parallel hybrid and a full parallel hybrid, with equal power-to-weight ratio. The powertrain consist of an internal combustion engine, an electric motor, and a NiMH battery. The different hybridization ratios are compared by their optimal fuel consumption for eight different drive cycles. The optimal fuel consumption is determined using dynamic programming for each of the different hybridization ratios. In the full parallel hybrid the engine and motor can be decoupled while in the torque assist hybrid the engine and motor are always mechanically connected. Results show that there are not only lower fuel consumption for the full hybrid but the need for hybridization is lower than in the torque assist hybrid for all eight cycles. The hybridization ratio where a full hybrid have the same fuel consumption as the optimal torque assist hybrid can differ as much as 51%.