Design optimization of a hybrid electric vehicle powertrain
This paper presents an optimization work on hybrid electric vehicle (HEV) powertrain using Genetic Algorithm (GA) method. It focused on optimization of the parameters of powertrain components including supercapacitors to obtain maximum fuel economy. Vehicle modelling is based on Quasi-Static-Simula...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Institute of Physics Publishing
2017
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/56767/ http://irep.iium.edu.my/56767/ http://irep.iium.edu.my/56767/ http://irep.iium.edu.my/56767/1/56767_Design%20Optimization%20of%20a%20Hybrid_complete.pdf http://irep.iium.edu.my/56767/7/56767_Design%20Optimization%20of%20a%20Hybrid_SCOPUS.pdf |
| Summary: | This paper presents an optimization work on hybrid electric vehicle (HEV) powertrain using Genetic Algorithm (GA) method. It focused on optimization of the
parameters of powertrain components including supercapacitors to obtain maximum fuel economy. Vehicle modelling is based on Quasi-Static-Simulation (QSS) backward-facing approach. A combined city (FTP-75)-highway (HWFET) drive cycle is utilized for the design
process. Seeking global optimum solution, GA was executed with different initial settings to obtain sets of optimal parameters. Starting from a benchmark HEV, optimization results in a smaller engine (2 l instead of 3 l) and a larger battery (15.66 kWh instead of 2.01 kWh). This
leads to a reduction of 38.3% in fuel consumption and 30.5% in equivalent fuel consumption.
Optimized parameters are also compared with actual values for HEV in the market. |
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