Title: NLPQL of control rules for improving fuel economy of a parallel hydraulic hybrid bus

Authors: Yecui Yan, Guoqing Liu, Jie Chen, Tianming Na

Addresses: Institute of Automotive Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China. ' Institute of Automotive Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China. ' Institute of Automotive Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China. ' Institute of Automotive Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

Abstract: Hydraulic hybrid system can improve fuel economy significantly of conventional buses over an urban bus driving cycle. In this paper, a parallel hydraulic hybrid bus (PHHB) and the based traditional bus are modelled and simulated in AMESim, an advanced modelling environment. Over one simplified bus-driving cycle, fuel economy of PHHB is compared with the based conventional bus in simulation and in real road tests. On real road testing fuel economy of PHHB is tested improved by 28% compared to the traditional bus in SMVIC, the National Center of Supervision and Inspection on Motor Products Quality in Shanghai. The model is validated that the approximate improvement ratio of fuel economy is 30% by simulation results. The applied control rules, involving certain variables, are selected by engineering intuition not to fully explore the potential of improvement of fuel economy. Hence, for further improvement of fuel economy of buses, non-linear programming by quadratic Lagrangian (NLPQL) is applied to optimising control rules. Optimal results indicate that improvement can be obtained more than 40% of fuel economy of PHHB compared to the traditional bus over the typical urban bus cycle data in China, the represented driving cycle being more applicable.

Keywords: parallel hydraulic hybrid bus; PHHB; fuel economy; control rules; optimisation; nonlinear programming; quadratic Lagrangian; NLPQL; modelling; simulation; China; buses.

DOI: 10.1504/IJMIC.2009.027882

International Journal of Modelling, Identification and Control, 2009 Vol.7 No.4, pp.315 - 320

Published online: 14 Aug 2009 *

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