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Energies 2018, 11(12), 3279; https://doi.org/10.3390/en11123279

Advanced Methodology for the Optimal Sizing of the Energy Storage System in a Hybrid Electric Refuse Collector Vehicle Using Real Routes

Department of Electronic Engineering MCIA UPC-BarcelonaTech, 08222 Terrassa, Spain
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Received: 20 September 2018 / Revised: 13 November 2018 / Accepted: 20 November 2018 / Published: 24 November 2018
(This article belongs to the Collection Electric and Hybrid Vehicles Collection)
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Abstract

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. View Full-Text
Keywords: energy storage; fuel economy; genetic algorithms; optimisation energy storage; fuel economy; genetic algorithms; optimisation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Cortez, E.; Moreno-Eguilaz, M.; Soriano, F. Advanced Methodology for the Optimal Sizing of the Energy Storage System in a Hybrid Electric Refuse Collector Vehicle Using Real Routes. Energies 2018, 11, 3279.

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