Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval System

With the rise of a consciousness in warehousing sustainability, an increasing number of autonomous vehicle storage and retrieval systems (AVS/RS) is diffusing among automated warehouses. Moreover, manufacturers are offering the option of equipping machines with energy recovery systems. This study an...

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Main Authors: Emanuele Guerrazzi, Valeria Mininno, Davide Aloini, Riccardo Dulmin, Claudio Scarpelli, Marco Sabatini
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/11/14/3817
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spelling doaj-c696c0309f2a47b99c14c0a93b3b8f4c2020-11-24T21:46:36ZengMDPI AGSustainability2071-10502019-07-011114381710.3390/su11143817su11143817Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval SystemEmanuele Guerrazzi0Valeria Mininno1Davide Aloini2Riccardo Dulmin3Claudio Scarpelli4Marco Sabatini5Department of Information Engineering, University of Pisa, Via Girolamo Caruso 16, 56122 Pisa, ItalyDepartment of Energy, Systems, Territory, and Construction Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, ItalyDepartment of Energy, Systems, Territory, and Construction Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, ItalyDepartment of Energy, Systems, Territory, and Construction Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, ItalyDepartment of Energy, Systems, Territory, and Construction Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, ItalyCassioli Group srl, Località Guardavalle 63, 53049 Torrita di Siena, ItalyWith the rise of a consciousness in warehousing sustainability, an increasing number of autonomous vehicle storage and retrieval systems (AVS/RS) is diffusing among automated warehouses. Moreover, manufacturers are offering the option of equipping machines with energy recovery systems. This study analyzed a deep-lane AVS/RS provided with an energy recovery system in order to make an energy evaluation for such a system. A simulator able to emulate the operation of the warehouse has been developed, including a travel-time and an energy model to consider the real operating characteristics of lifts, shuttles and satellites. Referring to a single command cycle with a basic storing and picking algorithm for multiple-depth channels, energy balance and recovery measurements have been presented and compared to those of a traditional crane-based system. Results show significant savings in energy consumption with the use of a deep-lane AVS/RS.https://www.mdpi.com/2071-1050/11/14/3817sustainabilityenergy evaluationenergy recoveryautonomous vehicle storage and retrieval systemsimulation
collection DOAJ
language English
format Article
sources DOAJ
author Emanuele Guerrazzi
Valeria Mininno
Davide Aloini
Riccardo Dulmin
Claudio Scarpelli
Marco Sabatini
spellingShingle Emanuele Guerrazzi
Valeria Mininno
Davide Aloini
Riccardo Dulmin
Claudio Scarpelli
Marco Sabatini
Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval System
Sustainability
sustainability
energy evaluation
energy recovery
autonomous vehicle storage and retrieval system
simulation
author_facet Emanuele Guerrazzi
Valeria Mininno
Davide Aloini
Riccardo Dulmin
Claudio Scarpelli
Marco Sabatini
author_sort Emanuele Guerrazzi
title Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval System
title_short Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval System
title_full Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval System
title_fullStr Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval System
title_full_unstemmed Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval System
title_sort energy evaluation of deep-lane autonomous vehicle storage and retrieval system
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2019-07-01
description With the rise of a consciousness in warehousing sustainability, an increasing number of autonomous vehicle storage and retrieval systems (AVS/RS) is diffusing among automated warehouses. Moreover, manufacturers are offering the option of equipping machines with energy recovery systems. This study analyzed a deep-lane AVS/RS provided with an energy recovery system in order to make an energy evaluation for such a system. A simulator able to emulate the operation of the warehouse has been developed, including a travel-time and an energy model to consider the real operating characteristics of lifts, shuttles and satellites. Referring to a single command cycle with a basic storing and picking algorithm for multiple-depth channels, energy balance and recovery measurements have been presented and compared to those of a traditional crane-based system. Results show significant savings in energy consumption with the use of a deep-lane AVS/RS.
topic sustainability
energy evaluation
energy recovery
autonomous vehicle storage and retrieval system
simulation
url https://www.mdpi.com/2071-1050/11/14/3817
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