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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/17/4362 |
| _version_ | 1827707851209965568 |
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| author | Subramaniam Saravana Sankar Yiqun Xia Julaluk Carmai Saiprasit Koetniyom |
| author_facet | Subramaniam Saravana Sankar Yiqun Xia Julaluk Carmai Saiprasit Koetniyom |
| author_sort | Subramaniam Saravana Sankar |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T16:55:28Z |
| format | Article |
| id | doaj.art-f56ec05d9396464b99d200975b54c0e3 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T16:55:28Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-f56ec05d9396464b99d200975b54c0e32023-11-20T11:11:19ZengMDPI AGEnergies1996-10732020-08-011317436210.3390/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 |
| 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 |
| title | 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_short | Optimal Eco-Driving Cycles for Conventional Vehicles Using a Genetic Algorithm |
| title_sort | optimal eco driving cycles for conventional vehicles using a genetic algorithm |
| 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 |