Modelling and heuristic control of a parallel hybrid electric vehicle

Wisdom Enang, Chris Bannister, Chris Brace, Chris Vagg

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Hybrid electric vehicles offer the potential for fuel consumption improvements when compared with conventional vehicle powertrains. The fuel consumption benefits which can be realised when utilising the hybrid electric vehicle architecture are dependent on how much braking energy is regenerated, and how well the regenerated energy is utilised. A number of power management strategies have been proposed in literature. Owing to the prospect of real-time implementation, many of these proposals have centred on the use of heuristics. Despite the research advances made, the key challenge with heuristic strategies remains achieving reasonable fuel savings without over-depleting the battery’s state of charge at the end of the trip. In view of this challenge, this paper offers two main contributions to existing energy management literature. The first is a novel, simple but effective heuristic control strategy which employs a tuneable parameter (the percentage of the maximum motor tractive power) to decide the control sequence, such that impressive fuel savings are achieved without over-depleting the final state of charge of the battery (the battery energy). The second is the quantitative exploration of braking patterns and its impact on kinetic energy regeneration. The potential of the proposed heuristic control strategy was explored over a range of driving cycles which reflect different driving scenarios. The results from this analysis show that fuel savings of as much as 19.07% can be achieved over the Japan 10–15 driving cycle. In comparison with a suboptimal controller whose control signals were derived from dynamic programming optimal control, our proposed strategy was found to be outperforming, in that it achieved impressive real-time fuel savings without much penalty to the final state of charge of the battery. Gentle braking patterns were also found to significantly improve brake energy regeneration by the electric motor.
Original languageEnglish
Pages (from-to)1494-1513
Number of pages20
JournalProceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Issue number11
Early online date19 Jan 2015
Publication statusPublished - 1 Sept 2015


  • hybrid electric vehicle (HEV)
  • Optimal control
  • Vehicle modelling
  • Dynamic programming
  • regenerative braking
  • heuristic control


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