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

Authors: Qiang Song; Pu Zeng

Addresses: Beijing Co-innovation Center for Electric Vehicles, National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, 100008, China ' Beijing Co-innovation Center for Electric Vehicles, National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, 100008, China

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.

Keywords: series hybrid electric bulldozers; dual-motor powertrain systems; engine-generator system; ultracapacitor; mathematical modelling; fuel consumption; control strategy; parameter optimisation; AGA; adaptive genetic algorithms; DOE; design of experiments; hybrid electric vehicles; HEVs; hybrid vehicles.

DOI: 10.1504/IJVD.2016.080018

International Journal of Vehicle Design, 2016 Vol.72 No.2, pp.132 - 142

Received: 11 Oct 2014
Accepted: 26 Oct 2015
Published online: 28 Oct 2016 *

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