Research on parameter optimisation of control strategy for powertrain system of series hybrid electric bulldozer

Qiang Song*, Pu Zeng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

To reduce the fuel consumption for a new type of series hybrid electric bulldozer, the parameters of control strategy for powertrain system should be optimised, especially for engine-generator system. In this paper, a new method based on multidisciplinary optimisation is proposed. The mathematical model of the series hybrid bulldozer system is established under MATLAB/Simulink software environment. On the basis of the idea of optimisation design, the parameters optimisation model for the control strategy is described. The optimised work flow is built by using the software of OPTIMUS, and adaptive genetic algorithm (AGA) is used to solve optimisation problem. The result shows that the bulldozer's fuel consumption after optimisation is reduced by about 6.74% compared with the former, and the method proposed in this paper can find the optimal solution in all global ranges, which greatly reduces the design and optimisation difficulties of the control strategy.

Original languageEnglish
Pages (from-to)132-142
Number of pages11
JournalInternational Journal of Vehicle Design
Volume72
Issue number2
DOIs
Publication statusPublished - 2016

Keywords

  • Adaptive genetic algorithm
  • Aga
  • Control strategy
  • Design on experiment
  • Doe
  • Dual-motor powertrain system
  • Engine-generator system
  • Fuel consumption
  • Mathematical model
  • Parameter optimisation
  • Series hybrid electric bulldozer
  • Ultracapacitor

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