Energy Efficient Drive Management of Lightweight Urban Vehicle

In this paper, the energy saving effect of optimized driving strategy is presented and compared to human driving strategy. The driving strategy of a one-seated experimental electric vehicle is investigated and optimized in this study, where the objective function of optimization is the minimization...

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Main Authors: Zoltan Pusztai, Ferenc Szauter, Ferenc Friedler
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2023-10-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/13592
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author Zoltan Pusztai
Ferenc Szauter
Ferenc Friedler
author_facet Zoltan Pusztai
Ferenc Szauter
Ferenc Friedler
author_sort Zoltan Pusztai
collection DOAJ
description In this paper, the energy saving effect of optimized driving strategy is presented and compared to human driving strategy. The driving strategy of a one-seated experimental electric vehicle is investigated and optimized in this study, where the objective function of optimization is the minimization of the consumed energy. Measurement-based vehicle model is used during the optimization process. The initialization and constraints of optimization are set up by analyzing the acquired vehicle data of the driver. The analyzation is done using a transform algorithm, making the initialization of optimization automated. Genetic algorithm is used with mixed initial population acquired from measured driving data and from creation function. Using this hybrid initial population helped to decrease the time of optimization. The resulted velocity profile of the optimized driving strategy was used in field test measurements, where 4.28 % energy savings was achieved compared to the results prior to optimization.
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spelling doaj.art-ae2e323457a94639b79e6581185161d82023-10-14T22:44:57ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162023-10-01103Energy Efficient Drive Management of Lightweight Urban VehicleZoltan PusztaiFerenc SzauterFerenc FriedlerIn this paper, the energy saving effect of optimized driving strategy is presented and compared to human driving strategy. The driving strategy of a one-seated experimental electric vehicle is investigated and optimized in this study, where the objective function of optimization is the minimization of the consumed energy. Measurement-based vehicle model is used during the optimization process. The initialization and constraints of optimization are set up by analyzing the acquired vehicle data of the driver. The analyzation is done using a transform algorithm, making the initialization of optimization automated. Genetic algorithm is used with mixed initial population acquired from measured driving data and from creation function. Using this hybrid initial population helped to decrease the time of optimization. The resulted velocity profile of the optimized driving strategy was used in field test measurements, where 4.28 % energy savings was achieved compared to the results prior to optimization.https://www.cetjournal.it/index.php/cet/article/view/13592
spellingShingle Zoltan Pusztai
Ferenc Szauter
Ferenc Friedler
Energy Efficient Drive Management of Lightweight Urban Vehicle
Chemical Engineering Transactions
title Energy Efficient Drive Management of Lightweight Urban Vehicle
title_full Energy Efficient Drive Management of Lightweight Urban Vehicle
title_fullStr Energy Efficient Drive Management of Lightweight Urban Vehicle
title_full_unstemmed Energy Efficient Drive Management of Lightweight Urban Vehicle
title_short Energy Efficient Drive Management of Lightweight Urban Vehicle
title_sort energy efficient drive management of lightweight urban vehicle
url https://www.cetjournal.it/index.php/cet/article/view/13592
work_keys_str_mv AT zoltanpusztai energyefficientdrivemanagementoflightweighturbanvehicle
AT ferencszauter energyefficientdrivemanagementoflightweighturbanvehicle
AT ferencfriedler energyefficientdrivemanagementoflightweighturbanvehicle