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Route-based adaptive optimization for energy management of hybrid electric vehicles

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Abstract

Compared with real-time control, global optimization has a great advantage to improve the fuel economy due to considering the whole drive condition in advance. However, on-board controller doesn’t support the global optimization with a large amount of calculation. Remote data communicating technology provides a platform to make global optimization applied to on-board control at a pre-known driving cycle. In this paper, a route-based optimal control strategy for the real-time energy management of parallel hybrid electric vehicles is developed. The proposed control strategy employs computers to optimize the power-split and engine stop-start control based on the minimum principle at a predicted driving cycle. Guiding controller provides real-time control with CAN bus communication. The experiment results prove the proposed strategy has a 10% fuel economy improvement than rule-based control strategy.

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Authors and Affiliations

  1. School of Mechanical Engineering, Shanghai Jiao Tong University, Minhang District, Shanghai, 200240, China

    B. Yan, Y. Q. Hu, T. Yan, P. P. Ma & L. Yang

Authors
  1. B. Yan
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  2. Y. Q. Hu
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  3. T. Yan
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  4. P. P. Ma
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  5. L. Yang
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Correspondence to L. Yang.

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Yan, B., Hu, Y.Q., Yan, T. et al. Route-based adaptive optimization for energy management of hybrid electric vehicles. Int.J Automot. Technol. 15, 1175–1182 (2014). https://doi.org/10.1007/s12239-014-0122-7

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  • DOI: https://doi.org/10.1007/s12239-014-0122-7

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