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Investigation of integrated uninterrupted dual input transmission and hybrid energy storage system for electric vehicles

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  • Yang, Weiwei
  • Ruan, Jiageng
  • Yang, Jue
  • Zhang, Nong

Abstract

Transportation sector is one of the major sources of pollutants as it contributes more than 80% of CO, while almost all HC and 90% of NOx and PM. Although battery electric vehicles are well-known for reducing environmental pollution, the driving range and battery lifespan put a significant barrier to its large-scale commercialization. In this study, an integrated system, which includes an uninterrupted dual input transmission and hybrid energy storage system, is proposed to improve energy efficiency and extend battery lifespan. Given the limitations of dynamic programming in practice, a real-time optimal control strategy is designed to evaluate the power loss and battery capacity degradation of the proposed integrated system based on detailed mathematical models of individual powertrain components. To achieve a desirable trade-off between battery degradation, energy consumption, and acquisition cost, a mixed-integer multi-objective genetic algorithm is implemented to optimize the parameters of the hybrid energy storage system, while Pareto principal is adopted to find the proper solution according to different purposes. The simulation results reveal that the proposed integrated system shows the potential of saving 15.85%–20.82% of the energy consumption in typical driving cycles and more than 22.61%–31.11% Life-cycle cost compared with the single-ratio transmission-based battery electric vehicles. The selected Pareto front can further enhance Life-cycle cost from 26.53% to 28.13% in the HWFET cycle. It can be concluded that the integrated uninterrupted dual input transmission and hybrid energy storage system not only can improve motor efficiency and reduce energy consumption, it also can extend the battery lifespan to decrease Life-cycle cost compared to conventional single-ratio battery-only EV.

Suggested Citation

  • Yang, Weiwei & Ruan, Jiageng & Yang, Jue & Zhang, Nong, 2020. "Investigation of integrated uninterrupted dual input transmission and hybrid energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:appene:v:262:y:2020:i:c:s0306261919321348
    DOI: 10.1016/j.apenergy.2019.114446
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    References listed on IDEAS

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    7. Ruan, Jiageng & Wu, Changcheng & Liang, Zhaowen & Liu, Kai & Li, Bin & Li, Weihan & Li, Tongyang, 2023. "The application of machine learning-based energy management strategy in a multi-mode plug-in hybrid electric vehicle, part II: Deep deterministic policy gradient algorithm design for electric mode," Energy, Elsevier, vol. 269(C).
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