Chapter
Apr 26, 2012
Study on Multi-Energy Powertrain Control Strategy of Hybrid Electric Vehicle
Authors: Shifang Zhang [email protected], Shupeng Zhao [email protected], Jiuxi Li [email protected], and Jigang Li [email protected]Author Affiliations
Publication: International Conference on Transportation Engineering 2007
Abstract
Optimizing of Muti-Energy powertrain control strategy was the key technic of Hybrid Electric Vehicle. Three kind structure of HEV and their control strategy were investigated, Series Hybrid Electric Vehicle, Parallel Hybrid Electric Vehicle, and PSHEV. Considering about driving cycle of CYC_NEDC and CYC_HWFET, three control strategy such as Electric Assistant Control, Adaptive Control Strategy and Genetic Algorithms Control were simulated based on Advisor to analysis vehicle performance. The results of simulation indicated that the fuel consumption economics and exhaust character were improved by using Genetic Algorithms Control. In CYC_NEDC, compared with Electric Assistant Control, fuel consumption economics was improved 47.4%, HC decreased 6.2%, CO decreased 4.6%, and NOx decreased 7.7%. Compared with Adaptive Control Strategy, fuel consumption economics was improved 20.4%, HC decreased 0.6%, CO decreased 29.5%, and NOx decreased 13.5%. In CYC_HWFET, same results were achieved.
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Published In
International Conference on Transportation Engineering 2007
Pages: 2711 - 2716
Copyright
© 2007 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
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ASCE Technical Topics:
- Adaptive systems
- Algorithms
- Business management
- Economic factors
- Electric power
- Energy consumption
- Energy engineering
- Engineering fundamentals
- Highway transportation
- Hybrid methods
- Infrastructure
- Mathematics
- Methodology (by type)
- Practice and Profession
- Structural control
- Structural engineering
- Structural health monitoring
- Systems engineering
- Systems management
- Transportation engineering
- Vehicles
Authors
Affiliations
Artificial Intelligence Research Center, Agricultural University of He Bei Baoding, 071001, HeBei, China. E-mail: [email protected]
Artificial Intelligence Research Center, Agricultural University of He Bei Baoding, 071001, HeBei, China. E-mail: [email protected]
Artificial Intelligence Research Center, Agricultural University of He Bei Baoding, 071001, HeBei, China. E-mail: [email protected]
Artificial Intelligence Research Center, Agricultural University of He Bei Baoding, 071001, HeBei, China. E-mail: [email protected]
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