Quick Electrical Drive Selection Method for Bus Retrofitting
The article concerns the issue of retrofitting (i.e., the conversion of worn-out diesel buses into electric buses). As this solution is often cheaper than purchasing new electric buses, it can be attractive for low-population areas with a weaker economic infrastructure. The article aims to present a...
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Veröffentlicht in: | Sustainability 2023-07, Vol.15 (13), p.10484 |
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description | The article concerns the issue of retrofitting (i.e., the conversion of worn-out diesel buses into electric buses). As this solution is often cheaper than purchasing new electric buses, it can be attractive for low-population areas with a weaker economic infrastructure. The article aims to present an original method for rapidly selecting components for the electric traction system, such as the electric motor, inverter, and transmission systems, combined with a battery installed in a drawer. The battery swapping solution is dedicated to regions with underdeveloped power infrastructure that does not allow for fast charging of bus batteries using pantographs. A mathematical model in the form of a polynomial was developed to estimate the energy losses for a given route. This model consists of a bus physics model, an energy loss model in the propulsion system, and a battery model. The weight coefficients of the polynomials were determined based on an analytical analysis of the model dependencies. The obtained models were reduced using the Lasso regularization method in linear regression. The input data for the model includes route characteristics (or driving cycle) and technical characteristics of the traction system components. The model output provides a detailed profile of electric energy consumption and peak values of the drive system characteristics (e.g., maximum torque of the motor) which must not be exceeded. Implemented as computer software, the model—combined with a database of motors, inverters, drive transmission systems, and batteries—allows for a quick calculation of the possibilities of applying a selected configuration to cover a given route. The approach proposed in the article enables the rapid composition of electric traction devices based on required driving conditions during the initial vehicle prototyping stage. At the same time, it allows the state of the bus battery to be monitored and estimates the remaining range during the operation of upgraded buses. |
doi_str_mv | 10.3390/su151310484 |
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As this solution is often cheaper than purchasing new electric buses, it can be attractive for low-population areas with a weaker economic infrastructure. The article aims to present an original method for rapidly selecting components for the electric traction system, such as the electric motor, inverter, and transmission systems, combined with a battery installed in a drawer. The battery swapping solution is dedicated to regions with underdeveloped power infrastructure that does not allow for fast charging of bus batteries using pantographs. A mathematical model in the form of a polynomial was developed to estimate the energy losses for a given route. This model consists of a bus physics model, an energy loss model in the propulsion system, and a battery model. The weight coefficients of the polynomials were determined based on an analytical analysis of the model dependencies. The obtained models were reduced using the Lasso regularization method in linear regression. The input data for the model includes route characteristics (or driving cycle) and technical characteristics of the traction system components. The model output provides a detailed profile of electric energy consumption and peak values of the drive system characteristics (e.g., maximum torque of the motor) which must not be exceeded. Implemented as computer software, the model—combined with a database of motors, inverters, drive transmission systems, and batteries—allows for a quick calculation of the possibilities of applying a selected configuration to cover a given route. The approach proposed in the article enables the rapid composition of electric traction devices based on required driving conditions during the initial vehicle prototyping stage. At the same time, it allows the state of the bus battery to be monitored and estimates the remaining range during the operation of upgraded buses.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su151310484</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Buses ; Coal-fired power plants ; Costs ; Electric motors ; Electric vehicles ; Electricity ; Electricity distribution ; Energy consumption ; Energy loss ; Industrial plant emissions ; Infrastructure ; Inverters ; Local government ; Manufacturers ; Mathematical models ; Methods ; Payback periods ; Polynomials ; Propulsion systems ; Prototyping ; R&D ; Regularization ; Research & development ; Retrofitting ; Roads & highways ; Rural areas ; Sustainability</subject><ispartof>Sustainability, 2023-07, Vol.15 (13), p.10484</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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As this solution is often cheaper than purchasing new electric buses, it can be attractive for low-population areas with a weaker economic infrastructure. The article aims to present an original method for rapidly selecting components for the electric traction system, such as the electric motor, inverter, and transmission systems, combined with a battery installed in a drawer. The battery swapping solution is dedicated to regions with underdeveloped power infrastructure that does not allow for fast charging of bus batteries using pantographs. A mathematical model in the form of a polynomial was developed to estimate the energy losses for a given route. This model consists of a bus physics model, an energy loss model in the propulsion system, and a battery model. The weight coefficients of the polynomials were determined based on an analytical analysis of the model dependencies. The obtained models were reduced using the Lasso regularization method in linear regression. The input data for the model includes route characteristics (or driving cycle) and technical characteristics of the traction system components. The model output provides a detailed profile of electric energy consumption and peak values of the drive system characteristics (e.g., maximum torque of the motor) which must not be exceeded. Implemented as computer software, the model—combined with a database of motors, inverters, drive transmission systems, and batteries—allows for a quick calculation of the possibilities of applying a selected configuration to cover a given route. The approach proposed in the article enables the rapid composition of electric traction devices based on required driving conditions during the initial vehicle prototyping stage. At the same time, it allows the state of the bus battery to be monitored and estimates the remaining range during the operation of upgraded buses.</description><subject>Buses</subject><subject>Coal-fired power plants</subject><subject>Costs</subject><subject>Electric motors</subject><subject>Electric vehicles</subject><subject>Electricity</subject><subject>Electricity distribution</subject><subject>Energy consumption</subject><subject>Energy loss</subject><subject>Industrial plant emissions</subject><subject>Infrastructure</subject><subject>Inverters</subject><subject>Local government</subject><subject>Manufacturers</subject><subject>Mathematical models</subject><subject>Methods</subject><subject>Payback periods</subject><subject>Polynomials</subject><subject>Propulsion systems</subject><subject>Prototyping</subject><subject>R&D</subject><subject>Regularization</subject><subject>Research & development</subject><subject>Retrofitting</subject><subject>Roads & highways</subject><subject>Rural areas</subject><subject>Sustainability</subject><issn>2071-1050</issn><issn>2071-1050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpVkN9LAzEMxw9RcMw9-Q8c-CRys71efxz4MnXqYCJu-lxuvXR23q6z7Yn-93bMhy0hJITPNwlJknOMhoSU6Np3mGKCUSGKo6SXI44zjCg63qtPk4H3KxSNEFxi1ktuXjujPtNxAyo4o6omvXfmG9I5bDvGtukzhA9bp9q69Lbz6QyCs9qEYNrlWXKiq8bD4D_3k_eH8dvdUzZ9eZzcjaaZIhyHjHPGOMIcKaFEyeOBueBFoRheYK3zhaoVW5RMFzFKCgCI1jmuUQ0V04A56ScXu7kbZ7868EGubOfauFLmgrCiYDFFarijllUD0rTaBlep6DWsjbItaBP7I04FoZQKEQWXB4LIBPgJy6rzXk7ms0P2ascqZ713oOXGmXXlfiVGcvt-ufd-8gfW_HSR</recordid><startdate>20230701</startdate><enddate>20230701</enddate><creator>Kozłowski, Maciej</creator><creator>Czerepicki, Andrzej</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>4U-</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0002-1068-8991</orcidid><orcidid>https://orcid.org/0000-0002-8659-5695</orcidid></search><sort><creationdate>20230701</creationdate><title>Quick Electrical Drive Selection Method for Bus Retrofitting</title><author>Kozłowski, Maciej ; 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The input data for the model includes route characteristics (or driving cycle) and technical characteristics of the traction system components. The model output provides a detailed profile of electric energy consumption and peak values of the drive system characteristics (e.g., maximum torque of the motor) which must not be exceeded. Implemented as computer software, the model—combined with a database of motors, inverters, drive transmission systems, and batteries—allows for a quick calculation of the possibilities of applying a selected configuration to cover a given route. The approach proposed in the article enables the rapid composition of electric traction devices based on required driving conditions during the initial vehicle prototyping stage. 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subjects | Buses Coal-fired power plants Costs Electric motors Electric vehicles Electricity Electricity distribution Energy consumption Energy loss Industrial plant emissions Infrastructure Inverters Local government Manufacturers Mathematical models Methods Payback periods Polynomials Propulsion systems Prototyping R&D Regularization Research & development Retrofitting Roads & highways Rural areas Sustainability |
title | Quick Electrical Drive Selection Method for Bus Retrofitting |
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