This paper presents a new methodology for optimal sizing of the energy storage system ( E S S ), with the aim of being used in the design process of a hybrid electric (HE) refuse collector vehicle ( R C V ). This methodology has, as the main element, to model a multi-objective optimisation problem that considers the specific energy of a basic cell of lithium polymer ( L i – P o ) battery and the cost of manufacture. Furthermore, optimal space solutions are determined from a multi-objective genetic algorithm that considers linear inequalities and limits in the decision variables. Subsequently, it is proposed to employ optimal space solutions for sizing the energy storage system, based on the energy required by the drive cycle of a conventional refuse collector vehicle. In addition, it is proposed to discard elements of optimal space solutions for sizing the energy storage system so as to achieve the highest fuel economy in the hybrid electric refuse collector vehicle design phase.

Abstract-This paper presents a new methodology to estimate the fuel economy in a hybrid electric refuse collector vehicle (RCV). This methodology is based on determinating the fuel consumption in a conventional RCV using real routes, through a quasi-static model that incorporates a mathematical modeling of each component of the powertrain, including the longitudinal dynamic of the conventional RCV. Moreover, a classification of different operational modes of a conventional RCV using real routes is proposed to determinate the required energy that must be provided by the hybrid electric counterpart. The optimal sizing of the energy storage system for the hybrid electric powertrain is presented in order to estimate the fuel consumption by using a real route. The error in the estimation of fuel consumption in a conventional RCV is less than 1.5% in the worst case scenario. The energy storage system sizing allows a 8.62% reduction in the hybrid electric refuse collector vehicle's fuel consumption, by considering 10% of hybridization.