TY - JOUR
T1 - Design of the Online Optimal Control Strategy for a Hydraulic Hybrid Bus
TT - طراحی استراتژی کنترل بهینه آنلاین برای اتوبوس هیبرید هیدرولیک
JF - joc-isice
JO - joc-isice
VL - 8
IS - 1
UR - http://joc.kntu.ac.ir/article-1-179-en.html
Y1 - 2014
SP - 1
EP - 10
KW - Hydraulic Hybrid Bus
KW - Online Optimal Control Strategy
KW - Neural Network
KW - Dynamic Programming.
N2 - In this paper, design of an optimal control strategy for the powertrain of a parallel hydraulic hybrid bus is proposed. The powertrain includes an internal combustion engine as the first power generation source and a hydraulic pump/motor as the second one. Design procedure of a proper control strategy for the hybrid powertrains is extremely dependent on the speed trend of the driving cycle. This functionality is such that the control decision is affected by the future trend of the driving cycle speed, too. Here, a dynamic programming algorithm is used for generating the optimal control strategy in a special driving cycle. The disadvantage of the designed control strategy is that it is fully dependent to the future information of the driving cycle. This problem would be eliminated by using an intelligent control strategy. The control strategies including an identification unit for the driving cycle are named as the intelligent. An appropriate method to design the intelligent control strategy is using the online models of the optimal control strategies for some standard driving cycles in different time periods of a special driving cycle. In this paper, a set of models contains several neural networks is applied to generate the online models of the pre-developed optimal control strategies. The generated models are used as the online optimal control strategies on the hydraulic hybrid bus. Finally, the results of the bus simulation using the online optimal control strategy and a rule-based one are compared for assessment of the proposed design. It can be seen that the fuel consumption of the bus is reduced by using the online optimal control strategy.
M3
ER -