Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars
The article presents a method for optimizing driving strategies aimed at minimizing energy consumption while driving. The method was developed for the needs of an electric powered racing vehicle built for the purposes of the Shell Eco-marathon (SEM), the most famous and largest race of energy effici...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/3614025 |
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| _version_ | 1832548778652991488 |
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| author | Mirosław Targosz Wojciech Skarka Piotr Przystałka |
| author_facet | Mirosław Targosz Wojciech Skarka Piotr Przystałka |
| author_sort | Mirosław Targosz |
| collection | DOAJ |
| description | The article presents a method for optimizing driving strategies aimed at minimizing energy consumption while driving. The method was developed for the needs of an electric powered racing vehicle built for the purposes of the Shell Eco-marathon (SEM), the most famous and largest race of energy efficient vehicles. Model-based optimization was used to determine the driving strategy. The numerical model was elaborated in Simulink environment, which includes both the electric vehicle model and the environment, i.e., the race track as well as the vehicle environment and the atmospheric conditions. The vehicle model itself includes vehicle dynamic model, numerical model describing issues concerning resistance of rolling tire, resistance of the propulsion system, aerodynamic phenomena, model of the electric motor, and control system. For the purpose of identifying design and functional features of individual subassemblies and components, numerical and stand tests were carried out. The model itself was tested on the research tracks to tune the model and determine the calculation parameters. The evolutionary algorithms, which are available in the MATLAB Global Optimization Toolbox, were used for optimization. In the race conditions, the model was verified during SEM races in Rotterdam where the race vehicle scored the result consistent with the results of simulation calculations. In the following years, the experience gathered by the team gave us the vice Championship in the SEM 2016 in London. |
| format | Article |
| id | doaj-art-ac408e8c04da45c89f6faadf2e8076dc |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-ac408e8c04da45c89f6faadf2e8076dc2025-02-03T06:13:10ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/36140253614025Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing CarsMirosław Targosz0Wojciech Skarka1Piotr Przystałka2Silesian University of Technology, Institute of Fundamentals of Machinery Design, 18A Konarskiego Street, 44-100 Gliwice, PolandSilesian University of Technology, Institute of Fundamentals of Machinery Design, 18A Konarskiego Street, 44-100 Gliwice, PolandSilesian University of Technology, Institute of Fundamentals of Machinery Design, 18A Konarskiego Street, 44-100 Gliwice, PolandThe article presents a method for optimizing driving strategies aimed at minimizing energy consumption while driving. The method was developed for the needs of an electric powered racing vehicle built for the purposes of the Shell Eco-marathon (SEM), the most famous and largest race of energy efficient vehicles. Model-based optimization was used to determine the driving strategy. The numerical model was elaborated in Simulink environment, which includes both the electric vehicle model and the environment, i.e., the race track as well as the vehicle environment and the atmospheric conditions. The vehicle model itself includes vehicle dynamic model, numerical model describing issues concerning resistance of rolling tire, resistance of the propulsion system, aerodynamic phenomena, model of the electric motor, and control system. For the purpose of identifying design and functional features of individual subassemblies and components, numerical and stand tests were carried out. The model itself was tested on the research tracks to tune the model and determine the calculation parameters. The evolutionary algorithms, which are available in the MATLAB Global Optimization Toolbox, were used for optimization. In the race conditions, the model was verified during SEM races in Rotterdam where the race vehicle scored the result consistent with the results of simulation calculations. In the following years, the experience gathered by the team gave us the vice Championship in the SEM 2016 in London.http://dx.doi.org/10.1155/2018/3614025 |
| spellingShingle | Mirosław Targosz Wojciech Skarka Piotr Przystałka Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars Journal of Advanced Transportation |
| title | Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars |
| title_full | Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars |
| title_fullStr | Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars |
| title_full_unstemmed | Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars |
| title_short | Model-Based Optimization of Velocity Strategy for Lightweight Electric Racing Cars |
| title_sort | model based optimization of velocity strategy for lightweight electric racing cars |
| url | http://dx.doi.org/10.1155/2018/3614025 |
| work_keys_str_mv | AT mirosławtargosz modelbasedoptimizationofvelocitystrategyforlightweightelectricracingcars AT wojciechskarka modelbasedoptimizationofvelocitystrategyforlightweightelectricracingcars AT piotrprzystałka modelbasedoptimizationofvelocitystrategyforlightweightelectricracingcars |