EconPapers    
Economics at your fingertips  
 

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

Ernest Cortez, Manuel Moreno-Eguilaz and Francisco Soriano
Additional contact information
Ernest Cortez: Department of Electronic Engineering MCIA UPC-BarcelonaTech, 08222 Terrassa, Spain
Manuel Moreno-Eguilaz: Department of Electronic Engineering MCIA UPC-BarcelonaTech, 08222 Terrassa, Spain
Francisco Soriano: Department of Electronic Engineering MCIA UPC-BarcelonaTech, 08222 Terrassa, Spain

Energies, 2018, vol. 11, issue 12, 1-17

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.

Keywords: energy storage; fuel economy; genetic algorithms; optimisation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/12/3279/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/12/3279/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:12:p:3279-:d:185301

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3279-:d:185301