Energy management strategy of HEV based on simulated annealing
Nowadays, the developments of hybrid electric cars are not something new. There are a lot of research are being done on how to increase the effectiveness of hybrid electric cars. One of the main aspects that are being aim is to reduce the fuel consumption while increasing the HEV performance. Artifi...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
Penerbit UTHM
2020
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| Subjects: | |
| Online Access: | https://umpir.ump.edu.my/id/eprint/46166/1/Energy%20Management%20Strategy%20of%20HEV%20based%20on%20Simulated%20Annealing.pdf https://doi.org/10.30880/ijie.2020.12.02.004 https://umpir.ump.edu.my/id/eprint/46166/ |
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| Summary: | Nowadays, the developments of hybrid electric cars are not something new. There are a lot of research are being done on how to increase the effectiveness of hybrid electric cars. One of the main aspects that are being aim is to reduce the fuel consumption while increasing the HEV performance. Artificial Intelligence such as Simulated Annealing for example is widely used to solve many engineering problem. This work focuses on the optimization of fuel and electrical power consumption in the hybrid electric vehicle (HEV) by utilizing a Simulated Annealing (SA) algorithm. The aim is to find the optimal control parameters of HEV such that the power loss is minimized. In this study, a simplified model of HEV is considered. The performance of the SA based algorithm is analyzed in terms of the statistical analysis of the power loss. The results show that the SA based algorithm is able to minimize the power loss and increase the efficiency of the HEV. |
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