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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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 |
work_keys_str_mv |
AT emanueleguerrazzi energyevaluationofdeeplaneautonomousvehiclestorageandretrievalsystem AT valeriamininno energyevaluationofdeeplaneautonomousvehiclestorageandretrievalsystem AT davidealoini energyevaluationofdeeplaneautonomousvehiclestorageandretrievalsystem AT riccardodulmin energyevaluationofdeeplaneautonomousvehiclestorageandretrievalsystem AT claudioscarpelli energyevaluationofdeeplaneautonomousvehiclestorageandretrievalsystem AT marcosabatini energyevaluationofdeeplaneautonomousvehiclestorageandretrievalsystem |
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