Optimal Eco-Driving Cycles for Conventional Vehicles Using a Genetic Algorithm

The goal of this work is to compute the eco-driving cycles for vehicles equipped with internal combustion engines by using a genetic algorithm (GA) with a focus on reducing energy consumption. The proposed GA-based optimization method uses an optimal control problem (OCP), which is framed considerin...

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Main Authors: Subramaniam Saravana Sankar, Yiqun Xia, Julaluk Carmai, Saiprasit Koetniyom
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/13/17/4362
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spelling doaj-f56ec05d9396464b99d200975b54c0e32020-11-25T03:52:04ZengMDPI AGEnergies1996-10732020-08-01134362436210.3390/en13174362Optimal Eco-Driving Cycles for Conventional Vehicles Using a Genetic AlgorithmSubramaniam Saravana Sankar0Yiqun Xia1Julaluk Carmai2Saiprasit Koetniyom3Automotive Safety and Assessment Engineering Research Centre, The Sirindhorn International Thai–German Graduate School of Engineering (TGGS), King Mongkut’s University of Technology North Bangkok, Bangkok 10800, ThailandInstitut für Kraftfahrzeuge (ika), RWTH Aachen University, Aachen, 52074 North Rhine-Westphalia, GermanyAutomotive Safety and Assessment Engineering Research Centre, The Sirindhorn International Thai–German Graduate School of Engineering (TGGS), King Mongkut’s University of Technology North Bangkok, Bangkok 10800, ThailandAutomotive Safety and Assessment Engineering Research Centre, The Sirindhorn International Thai–German Graduate School of Engineering (TGGS), King Mongkut’s University of Technology North Bangkok, Bangkok 10800, ThailandThe goal of this work is to compute the eco-driving cycles for vehicles equipped with internal combustion engines by using a genetic algorithm (GA) with a focus on reducing energy consumption. The proposed GA-based optimization method uses an optimal control problem (OCP), which is framed considering both fuel consumption and driver comfort in the cost function formulation with the support of a tunable weight factor to enhance the overall performance of the algorithm. The results and functioning of the optimization algorithm are analyzed with several widely used standard driving cycles and a simulated real-world driving cycle. For the selected optimal weight factor, the simulation results show that an average reduction of eight percent in fuel consumption is achieved. The results of parallelization in computing the cost function indicates that the computational time required by the optimization algorithm is reduced based on the hardware used.https://www.mdpi.com/1996-1073/13/17/4362eco-driving cyclesgenetic algorithmoptimization problemenergy consumption reduction
collection DOAJ
language English
format Article
sources DOAJ
author Subramaniam Saravana Sankar
Yiqun Xia
Julaluk Carmai
Saiprasit Koetniyom
spellingShingle Subramaniam Saravana Sankar
Yiqun Xia
Julaluk Carmai
Saiprasit Koetniyom
Optimal Eco-Driving Cycles for Conventional Vehicles Using a Genetic Algorithm
Energies
eco-driving cycles
genetic algorithm
optimization problem
energy consumption reduction
author_facet Subramaniam Saravana Sankar
Yiqun Xia
Julaluk Carmai
Saiprasit Koetniyom
author_sort Subramaniam Saravana Sankar
title Optimal Eco-Driving Cycles for Conventional Vehicles Using a Genetic Algorithm
title_short Optimal Eco-Driving Cycles for Conventional Vehicles Using a Genetic Algorithm
title_full Optimal Eco-Driving Cycles for Conventional Vehicles Using a Genetic Algorithm
title_fullStr Optimal Eco-Driving Cycles for Conventional Vehicles Using a Genetic Algorithm
title_full_unstemmed Optimal Eco-Driving Cycles for Conventional Vehicles Using a Genetic Algorithm
title_sort optimal eco-driving cycles for conventional vehicles using a genetic algorithm
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2020-08-01
description The goal of this work is to compute the eco-driving cycles for vehicles equipped with internal combustion engines by using a genetic algorithm (GA) with a focus on reducing energy consumption. The proposed GA-based optimization method uses an optimal control problem (OCP), which is framed considering both fuel consumption and driver comfort in the cost function formulation with the support of a tunable weight factor to enhance the overall performance of the algorithm. The results and functioning of the optimization algorithm are analyzed with several widely used standard driving cycles and a simulated real-world driving cycle. For the selected optimal weight factor, the simulation results show that an average reduction of eight percent in fuel consumption is achieved. The results of parallelization in computing the cost function indicates that the computational time required by the optimization algorithm is reduced based on the hardware used.
topic eco-driving cycles
genetic algorithm
optimization problem
energy consumption reduction
url https://www.mdpi.com/1996-1073/13/17/4362
work_keys_str_mv AT subramaniamsaravanasankar optimalecodrivingcyclesforconventionalvehiclesusingageneticalgorithm
AT yiqunxia optimalecodrivingcyclesforconventionalvehiclesusingageneticalgorithm
AT julalukcarmai optimalecodrivingcyclesforconventionalvehiclesusingageneticalgorithm
AT saiprasitkoetniyom optimalecodrivingcyclesforconventionalvehiclesusingageneticalgorithm
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