Zhu Y.,Zhejiang Institute of Quality Inspection Science |
Ma Y.,Jilin University |
Zhu J.,China North Vehicle Research Institute
Journal of Luminescence | Year: 2013
We present here the effect of counter anion size in tris(4,7-diphenyl-1,10- phenanthroline)ruthenium(II) complexes [Ru(dpp)3X2] (X=Cl-, BF4 -, ClO4 -, PF6 - and AsF6 -) on their doped electrophosphorescent device properties. The performance of organic light-emitting diodes (OLEDs) based on these complexes is influenced by the counter anions, that is the efficiency enhances by increasing the counter anion size from small Cl- to large AsF6 -. Among the five complexes, [Ru(dpp)3(AsF6)2] shows the best single layer diode performance with the luminous efficiency of 4.25 cd A-1. The possible reasons are carefully studied on the complex properties and their luminescence processes in light-emitting layers. It is found that the size of counter anion affects properties of complex in many aspects such as solubility and photophysical properties. The result shows that the differences in luminescence quantum yields of complexes, the energy-transfer abilities, as well as the charge injection, transfer and trapping abilities of devices related to the counter anions are the major factors in the different performance of doped OLEDs. © 2013 Elsevier B.V.
Xi J.,Beijing Institute of Technology |
Chen Y.,China North Vehicle Research Institute
Mathematical Problems in Engineering | Year: 2013
In order to satisfy the character of parallel hybrid electric vehicle (PHEV) in some special driving cycles, a collision decision problem between the shift decision and power split ratio is proposed. Based on a large amount of experimental data the optimal decisions are determined with evidential reasoning theory. The proposed decision strategy has been verified through real road test of Chongqing public transportation line 818 and the fuel economic improvement has also been achieved. © 2013 JunQiang Xi and Yongdan Chen.
HomChaudhuri B.,Clemson University |
Lin R.,China North Vehicle Research Institute |
Pisu P.,Clemson University
Transportation Research Part C: Emerging Technologies | Year: 2016
This paper presents a fuel efficient control strategy for a group of connected hybrid electric vehicles (HEVs) in urban road conditions. A hierarchical control architecture is proposed in this paper for every HEV, where the higher level and the lower level controller share information with each other and solve two different problems that aim at improving its fuel efficiency. The higher level controller of each HEV is considered to utilize traffic light information, through vehicle to infrastructure (V2I) communication, and state information of the vehicles in its near neighborhood, via vehicle to vehicle (V2V) communication. Apart from that, the higher level controller of each HEV uses the recuperation information from the lower level controller and provides it the optimal velocity profile by solving its problem in a model predictive control framework. Each lower level controller uses adaptive equivalent consumption minimization strategy (ECMS) for following their velocity profiles, obtained from the higher level controller, in a fuel efficient manner. In this paper, the vehicles are modeled in Autonomie software and the simulation results are provided in the paper that shows the effectiveness of the proposed control architecture. © 2015 Elsevier Ltd.
Xia Y.,Beijing Institute of Technology |
Dai L.,Beijing Institute of Technology |
Fu M.,Beijing Institute of Technology |
Li C.,China North Vehicle Research Institute |
Wang C.,Beijing Institute of Technology
Journal of the Franklin Institute | Year: 2014
The problem of position tracking for a tank gun control system with inertia uncertainty and external disturbance is investigated in this paper. The tank gun control system, demanding high tracking precision and stabilization precision, is a nonlinear system. Classical control methods are commonly used in the actual system, which is difficult to ensure high precision and high disturbance rejection capability. An active disturbance rejection control (ADRC) scheme is applied to guarantee the state variables of the closed loop system to converge to the reference state with the help of the extended state observer by estimating the inertia uncertainty and external disturbance. The basic theory of the ADRC is introduced here. According to the mathematical model, the parameters of ADRC are designed. Also, simulation results show that ADRC controller has advantages of high precision and high disturbance rejection ability. A comparison between ADRC and PID is also presented to show the effectiveness of the ADRC control strategy. © 2013 The Franklin Institute.
Shi Y.,Dalian University of Technology |
Li B.,China North Vehicle Research Institute |
Zhang Z.,Dalian University of Technology
Advanced Science Letters | Year: 2011
Layout design of a satellite module is the problem of arranging a set of components in satellite module such that a set of objectives and constraints are satisfied. This layout is a NP-hard engineering optimization problem. We propose a modified artificial bee colony algorithm (ABC-G for short) to tackle this problem. In the proposed ABC-G algorithm, the onlooker bees not only choose food sources depending on their experience, but also employed a gauss mutation from genetic algorithm to improve local solution, i.e., micro-adjust the placement of layout component. The comparative results with genetic algorithm (GA for short) showed that the ABC-G algorithm outperformed GA and the standard ABC algorithm. © 2011 American Scientific Publishers All rights reserved.
Teng H.-F.,Dalian University of Technology |
Chen Y.,Dalian University of Technology |
Zeng W.,China North Vehicle Research Institute |
Shi Y.-J.,Dalian University of Technology |
Hu Q.-H.,Dalian University of Technology
IEEE Transactions on Evolutionary Computation | Year: 2010
The layout design of complex engineering systems (such as satellite-module layout design) is very difficult to solve in polynomial time. This is not only a complex coupled system design problem but also a special combinatorial problem. The fitness function for this problem is characterized as multimodal because of interference constraints among layout components (objects), etc. This characteristic can easily result in premature convergence when solving this problem using evolutionary algorithms. To deal with the above two problems simultaneously, we propose a dual-system framework based on the cooperative coevolutionary algorithm (CCEA, e.g., cooperative coevolutionary genetic algorithm) like multidisciplinary design optimization. The proposed algorithm has the characteristic of solving the complex coupled system problem, increasing the diversity of population, and decreasing the premature convergence. The basis for the proposed algorithm is as follows. The original coupled system P is decomposed into several subsystems according to its physical structure. The system P is duplicated as systems A and B, respectively. The A system is solved on a global level (all-in-one), whereas the solving of B system is realized through the computation of its subsystems in parallel. The individual migration between A and B is implemented through the individual migration between their corresponding subsystems. To reduce the computational complexity produced additionally by the dual-systems A and B, we employ a variable-grain model of design variables. During the process of optimization, the two systems A and B gradually approximate to the original system P, respectively. The above-proposed algorithm is called the dual-system variable-grain cooperative coevolution algorithm (DVGCCEA) or Oboe-CCEA. The numerical experimental results of a simplified satellite-module layout design case show that the proposed algorithm can obtain better robustness and trade-off between computational precision and computational efficiency. © 2006 IEEE.
He Z.,China North Vehicle Research Institute |
Li X.,CAS Institute of Mechanics |
Liang X.,CAS Institute of Mechanics
Science China: Physics, Mechanics and Astronomy | Year: 2014
In spectral-like resolution-WENO hybrid schemes, if the switch function takes more grid points as discontinuity points, the WENO scheme is often turned on, and the numerical solutions may be too dissipative. Conversely, if the switch function takes less grid points as discontinuity points, the hybrid schemes usually are found to produce oscillatory solutions or just to be unstable. Even if the switch function takes less grid points as discontinuity points, the final hybrid scheme is inclined to be more stable, provided the spectral-like resolution scheme in the hybrid scheme has moderate shock-capturing capability. Following this idea, we propose nonlinear spectral-like schemes named weighted group velocity control (WGVC) schemes. These schemes show not only high-resolution for short waves but also moderate shock capturing capability. Then a new class of hybrid schemes is designed in which the WGVC scheme is used in smooth regions and the WENO scheme is used to capture discontinuities. These hybrid schemes show good resolution for small-scales structures and fine shock-capturing capabilities while the switch function takes less grid points as discontinuity points. The seven-order WGVC-WENO scheme has also been applied successfully to the direct numerical simulation of oblique shock wave-turbulent boundary layer interaction. © 2014 Science China Press and Springer-Verlag Berlin Heidelberg.
Cui Y.,China North Vehicle Research Institute |
Kurfess T.R.,Georgia Institute of Technology
Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME | Year: 2015
In this paper, a nonlinear full car model considering the nonlinear and hysteretic characteristics of the shock absorber is developed. An approach to integrate the hybrid shock absorber model into the vehicle model using system identification techniques is then presented. To validate the approach, parameter identification of the nominal linear full car model and parameter identification of the full car model with nonlinear/hysteresis shock absorber force input are compared. The target vehicle is tested on an MTS Systems Corporation tire-coupled 4-post road simulator and the experimental data validate the system identification methods proposed in this paper. Copyright © 2015 by ASME.
Chen W.,Dalian University of Technology |
Shi Y.-j.,Dalian University of Technology |
Teng H.-f.,Dalian University of Technology |
Lan X.-p.,China North Vehicle Research Institute |
Hu L.-c.,China North Vehicle Research Institute
Information Sciences | Year: 2010
We propose an efficient hybrid algorithm, known as ACOSS, for solving resource-constrained project scheduling problems (RCPSP) in real-time. The ACOSS algorithm combines a local search strategy, ant colony optimization (ACO), and a scatter search (SS) in an iterative process. In this process, ACO first searches the solution space and generates activity lists to provide the initial population for the SS algorithm. Then, the SS algorithm builds a reference set from the pheromone trails of the ACO, and improves these to obtain better solutions. Thereafter, the ACO uses the improved solutions to update the pheromone set. Finally in this iteration, the ACO searches the solution set using the new pheromone trails after the SS has terminated. In ACOSS, ACO and the SS share the solution space for efficient exchange of the solution set. The ACOSS algorithm is compared with state-of-the-art algorithms using a set of standard problems available in the literature. The experimental results validate the efficiency of the proposed algorithm. © 2009 Elsevier Inc. All rights reserved.
Bao P.F.,Dalian University of Technology |
Miao W.D.,China North Vehicle Research Institute |
Xie R.,Dalian University of Technology |
Shi Y.J.,Dalian University of Technology
Advanced Materials Research | Year: 2014
Engineering analysis and simulation are time-consuming, and often trapped to computational burden, such as analyzing forging press. We herein employ surrogate modeling to reduce such computation cost while keeping high precision. This paper use a BP neural networks to building the surrogate model (BPNN-SM for short), and predicting the analysis results of mechanical structures with this model. The predicting process include confining design variables, sampling, building finite element model with business software ANSYS, constructing surrogate model to replace the original model and finally predicting data with the new model. In such process, we build a back-propagation neural network, and train it with sampling data from ANSYS results. We tested our methods with a mechanical structure design of hydraulic forging press. The experimental results verified the surrogate modeling. © (2014) Trans Tech Publications, Switzerland.