Fengcheng, China
Fengcheng, China

Time filter

Source Type

Li S.G.,Shaanxi Automobile Group Co. | Sharkh S.M.,University of Southampton | Sharkh S.M.,HiT Systems Ltd. | Walsh F.C.,University of Southampton | Zhang C.N.,Beijing Institute of Technology
IEEE Transactions on Vehicular Technology | Year: 2011

Fuzzy logic is used to define a new quantity called the battery working state (BWS), which is based on both battery terminal voltage and state of charge (SOC), to overcome the problem of battery over-discharge and associated damage resulting from inaccurate estimates of the SOC. The BWS is used by a fuzzy logic energy-management system of a plug-in series hybrid electric vehicle (HEV) to make a decision on the power split between the battery and the engine, based on the BWS and vehicle power demand, while controlling the engine to work in its fuel economic region. The fuzzy logic management system was tested in real time using an HEV simulation test bench with a real battery in the loop. Simulation results are presented to demonstrate the performance of the proposed fuzzy logic energy-management system under different driving conditions and battery SOCs. The results indicate that the fuzzy logic energy-management system using the BWS was effective in ensuring that the engine operates in the vicinity of its maximum fuel efficiency region while preventing the battery from over-discharging. © 2011 IEEE.


Li S.-G.,Beijing Institute of Technology | Li S.-G.,Shaanxi Automobile Group Co. | Zhang C.-N.,Beijing Institute of Technology
Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology | Year: 2012

Evaluation of the state of charge (SOC) is a key technology for electric vehicle battery management. This work develops a method to establish the relationship among Coulomb efficiency, SOC and charge/discharge current (I). The curve of SOC to I (SOC-I) is provided that could supply a reasonable Coulomb efficiency during prediction. Moreover, the algorithm of adaptive unscented Kalman filtering (AUKF) is used for battery SOC evaluation. A new SOC-I-AUKF algorithm combined the AUKF algorithm with SOC-I curve is developed. During the process of SOC prediction, the new algorithm could adjust the Coulomb efficiency, process noise covariance and measurement noise covariance to reach the optimal evaluation. Experiment results indicate that the SOC-I-AUKF algorithm has better performance than UKF algorithm in prediction of absolute error, relative error and average error.


Song Y.-Q.,China University of Mining and Technology | Deng C.,Shaanxi Automobile Group Co.
Zhongguo Gonglu Xuebao/China Journal of Highway and Transport | Year: 2012

In order to study the safety of semi-rigid guard rail of transition section collided by vehicle at high speed on expressway and to enhance absorbing auto kinetic energy and rigid protection capability of guard rail of transition section, through a large number of investigations on the basis of collision accident, the flaw of current guard rail of transition section in China was analyzed. A new type of guard rail of transition section which had enough rigidity to resist the enormous energy produced by the collision between heavy vehicle and guard rail of transition section was designed. It played a better unloading result. Finite element software LS-DYNA was used to do numerical simulation about collision between vehicle and guard rail of transition section by high speed. Results show that the new type of guard rail of transition section can effectively increase safety factor of automobile and crew. Its design dimension is reasonable and realizes the effect of rigidity transition.


Chen T.,Chang'an University | Feng H.,Chang'an University | Zhang M.,Shaanxi Automobile Group Co.
ICIC Express Letters, Part B: Applications | Year: 2016

To study the tire’s friction characteristics of the LuGre model, an identification method of the tire’s parameters is put forward to obtain the static and dynamic parameters. According to the identified static parameters, a relationship curve between the adhesion coefficient and the slip ratio is plotted, which indicates that the simulation result agrees well with measured results of experiment. In addition, the sensitivity of static parameters μc, μs and σ2 to different experimental variables, including the normal force Fn, sideslip angle γ and slip ratio s is analyzed. Experimental results show that the static parameters are sensitive to different experimental conditions. © 2016 ICIC International.


Pang H.,Shaanxi Automobile Group Co. | Pang H.,Northwestern Polytechnical University | Li H.,Shaanxi Automobile Group Co. | Fang Z.,Northwestern Polytechnical University | Wang J.,Northwestern Polytechnical University
Applied Mechanics and Materials | Year: 2011

In order to reasonably match suspension stiffness and realize the optimization of vehicle ride comfort, a time-domain virtual prototyping model of the 8×4 heavy vehicle is established based on dynamic software ADAMS, and its vertical vibration responses are simulated and analyzed on road level B. After that, an optimal design method for heavy vehicle's suspension system is put forward. In this proposed method, the first, the second axle suspension stiffness and the balance suspension stiffness are taken as the optimal variables and the maximum values of Z-direction power spectral density (PSD) of the cab and cargo boxes mass center are chosen as the optimal target. By using SQP (Sequential Quadratic Programming) algorithms to conduct optimizing calculation, thus the optimal suspension stiffness parameters are obtained, which promotes and improves the heavy vehicle's ride comfort. © (2011) Trans Tech Publications.


Pang H.,Shaanxi Automobile Group Co. | Pang H.,Northwestern Polytechnical University | Fang Z.-D.,Northwestern Polytechnical University | Li H.-Y.,Shaanxi Automobile Group Co. | Wang J.-F.,Shaanxi Automobile Group Co.
Zhendong yu Chongji/Journal of Vibration and Shock | Year: 2012

In order to study matching and optimization between suspension stiffness and damping for a multi-axle heavy-duty truck, a new optimal design method based on ADAMS was developed. Firstly, the frequency-domain simulation model for a 8×4 heavy truck was built with ADAMS/View. Then, its acceleration response characteristics were gained when the full load truck with an excitation of B-level random road irregularities, and the optimal parameters for the suspension system were calculated with the proposed optimal method. Finally, a real vehicle road test was conducted to verify the correctness of the simulation model and the feasibility of the optimal method. The test results could be used as a reference to guide the integrated optimization and matching design of heavy truck chassis systems.


Song Q.,Shaanxi Automobile Group Co. | Song Q.,Chang'an University
Information Technology Journal | Year: 2012

Echo State Neural Network (ESN) has becoming much attractive in Artificial Neural Network (ANN) community since it can be easily constructed and adapted. Its superiority over traditional ANN has been demonstrated in many applications. The Wiener-Hopf solution is usually exploited to account for the adaptations. However, the solution can hardly ensure the Lyapunov stability of the trained Leaky-integrator ESNs (LiESNs), when they run in a closed-loop autonomously generative mode. LiESN is another type of ESN, which consists of leaky-integrator neurons. In this study, a sufficient condition of the Lyapunov stability for the autonomously running LiESNs is proposed and proved at first. And then, the output connection weight learning problem is translated into an optimization problem with a nonlinear restriction. Particle swarm optimization algorithm is explored to solve the optimization problem. The simulation experiment results show that the output weight adaptation algorithm, we proposed (we call it PSOESN) can effectively ensure the output precision as well as the Lyapunov stability of the trained LiESNs. It is concluded that the PSOESN is a more effective solution to the output connection weight adaptation problem of such autonomously running ESNs. © 2012 Asian Network for Scientific Information.


Pang H.,Shaanxi Automobile Group Co. | Pang H.,Northwestern Polytechnical University | Fang Z.-D.,Northwestern Polytechnical University | Li H.-Y.,Shaanxi Automobile Group Co. | Yang X.-H.,Northwestern Polytechnical University
Procedia Engineering | Year: 2011

In order to visualize time information of the complex workflow system, time parameter concept is firstly introduced to workflow model, and then a new modeling and time parameters calculating method for the practical business process system are proposed based on timing constraint Petri Nets(TCPN). Finally, an insurance claim process is modeled based on TCPN workflow model, which suggests that it is effective and consistent with the specification of the system requirement. © 2011 Published by Elsevier Ltd.


Song Q.,Shaanxi Automobile Group Co. | Song Q.,Chang'an University | Liu X.,Shaanxi Automobile Group Co. | Zhao X.,Chang'an University
International Journal of Advancements in Computing Technology | Year: 2012

In order to model time-varying dynamical systems with more accuracy, and to further exploit the potential capacities of recurrent neural networks, we propose a novel recursive least square (RLS) algorithm based on echo state network (ESN), and note it as RLSESN in this paper. ESN is a new paradigm for using recurrent neural networks (RNN) with a simpler training method. RLSESN consists of three main components: an ESN, a recursive least square (RLS) algorithm with adaptive forgetting factor and a change detection module. At first, the change detection module modifies the forgetting factor online according to ESN output errors. And then, the RLS algorithm regulates the ESN output connection weights. The simulation experiment results show that the proposed ESN-based filters can model nonlinear time-varying dynamical systems very well; the modeling performances are significantly better than those autoregressive moving average (ARMA) model based filters.


Song Q.,Shaanxi Automobile Group Co. | Song Q.,Chang'an University | Liu X.,Shaanxi Automobile Group Co. | Zhao X.,Chang'an University
International Journal of Digital Content Technology and its Applications | Year: 2012

An algorithm for short-term traffic flow and hourly electric load forecasting based on echo state neural networks (ESN) is proposed in this paper. ESN is a new paradigm for using recurrent neural networks (RNNs) with a simpler training method. While the prediction, traffic flows and load patterns are treated as time series signals; no further information is used than the past data records, such as weather, seasonal variations. The relation between key parameter of the ESN and the predicting performance is discussed; ESN and feedforward neural network (FNN) are compared with the same tasks also. Simulation experiment results demonstrate that the proposed ESN algorithm is valid and can obtain more accurate predicting results than the FNNs for these short-term traffic flow and hourly electric load prediction problems.

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