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Techno-economic design of hybrid electric vehicles using multi objective optimization techniques

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  • Dimitrova, Zlatina
  • Maréchal, François

Abstract

The improvement of the efficiency of vehicle energy systems promotes an active search to find innovative solutions during the design process. Engineers can use computer-aided processes to find automatically the best design solutions. This kind of approach named “multi-objective optimization” is based on genetic algorithms.

Suggested Citation

  • Dimitrova, Zlatina & Maréchal, François, 2015. "Techno-economic design of hybrid electric vehicles using multi objective optimization techniques," Energy, Elsevier, vol. 91(C), pages 630-644.
    • Handle: RePEc:eee:energy:v:91:y:2015:i:c:p:630-644
    DOI: 10.1016/j.energy.2015.08.073
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    References listed on IDEAS

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    8. Finesso, Roberto & Spessa, Ezio & Venditti, Mattia, 2014. "Layout design and energetic analysis of a complex diesel parallel hybrid electric vehicle," Applied Energy, Elsevier, vol. 134(C), pages 573-588.
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    Cited by:

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    2. Pinto, Cláudio & Barreras, Jorge V. & de Castro, Ricardo & Araújo, Rui Esteves & Schaltz, Erik, 2017. "Study on the combined influence of battery models and sizing strategy for hybrid and battery-based electric vehicles," Energy, Elsevier, vol. 137(C), pages 272-284.
    3. Alipour, Manijeh & Mohammadi-Ivatloo, Behnam & Moradi-Dalvand, Mohammad & Zare, Kazem, 2017. "Stochastic scheduling of aggregators of plug-in electric vehicles for participation in energy and ancillary service markets," Energy, Elsevier, vol. 118(C), pages 1168-1179.
    4. Dimitrova, Zlatina & Nader, Wissam Bou, 2022. "PEM fuel cell as an auxiliary power unit for range extended hybrid electric vehicles," Energy, Elsevier, vol. 239(PA).
    5. Song, Ziyou & Zhang, Xiaobin & Li, Jianqiu & Hofmann, Heath & Ouyang, Minggao & Du, Jiuyu, 2018. "Component sizing optimization of plug-in hybrid electric vehicles with the hybrid energy storage system," Energy, Elsevier, vol. 144(C), pages 393-403.
    6. Hou, Daizheng & Sun, Qun & Bao, Chunjiang & Cheng, Xingqun & Guo, Hongqiang & Zhao, Ying, 2019. "An all-in-one design method for plug-in hybrid electric buses considering uncertain factor of driving cycles," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    7. Hu, Xiaosong & Zou, Yuan & Yang, Yalian, 2016. "Greener plug-in hybrid electric vehicles incorporating renewable energy and rapid system optimization," Energy, Elsevier, vol. 111(C), pages 971-980.
    8. Chen, Syuan-Yi & Wu, Chien-Hsun & Hung, Yi-Hsuan & Chung, Cheng-Ta, 2018. "Optimal strategies of energy management integrated with transmission control for a hybrid electric vehicle using dynamic particle swarm optimization," Energy, Elsevier, vol. 160(C), pages 154-170.
    9. Guo, Hongqiang & Sun, Qun & Wang, Chong & Wang, Qinpu & Lu, Silong, 2018. "A systematic design and optimization method of transmission system and power management for a plug-in hybrid electric vehicle," Energy, Elsevier, vol. 148(C), pages 1006-1017.
    10. Sun, Li & Walker, Paul & Feng, Kaiwu & Zhang, Nong, 2018. "Multi-objective component sizing for a battery-supercapacitor power supply considering the use of a power converter," Energy, Elsevier, vol. 142(C), pages 436-446.
    11. Roberto Finesso & Daniela Misul & Ezio Spessa & Mattia Venditti, 2018. "Optimal Design of Power-Split HEVs Based on Total Cost of Ownership and CO 2 Emission Minimization," Energies, MDPI, vol. 11(7), pages 1-28, July.
    12. Kavousi-Fard, Abdollah & Khodaei, Amin, 2016. "Efficient integration of plug-in electric vehicles via reconfigurable microgrids," Energy, Elsevier, vol. 111(C), pages 653-663.
    13. Mohammadnejad, Mehran & Abdollahi, Amir & Rashidinejad, Masoud, 2020. "Possibilistic-probabilistic self-scheduling of PEVAggregator for participation in spinning reserve market considering uncertain DRPs," Energy, Elsevier, vol. 196(C).
    14. Dimitrova, Zlatina & Maréchal, François, 2017. "Environomic design for electric vehicles with an integrated solid oxide fuel cell (SOFC) unit as a range extender," Renewable Energy, Elsevier, vol. 112(C), pages 124-142.
    15. Shen, Peihong & Zhao, Zhiguo & Zhan, Xiaowen & Li, Jingwei, 2017. "Particle swarm optimization of driving torque demand decision based on fuel economy for plug-in hybrid electric vehicle," Energy, Elsevier, vol. 123(C), pages 89-107.

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