Guangdong Key Laboratory of Automotive Engineering

Guangzhou, China

Guangdong Key Laboratory of Automotive Engineering

Guangzhou, China
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Qu J.,South China University of Technology | Qu J.,Guangdong Key Laboratory of Automotive Engineering | Xu B.,Tsinghua University | Jin Q.,China Academy of Machinery Science and Technology
Computers, Materials and Continua | Year: 2010

Large and complex macro-micro coupled constitutive models, which describe metal flow and microstructure evolution during metal forming, are sometimes overparameterized with respect to given sets of experimental datum. This results in poorly identifiable or non-identifiable model parameters. In this paper, a systemic parameter identification method for the large macro-micro coupled constitutive models is proposed. This method is based on the global and local identifiability analysis, in which two identifiability measures are adopted. The first measure accounts for the sensitivity of model results with respect to single parameters, and the second measure accounts for the degree of near-linear dependence of sensitivity functions of parameter subsets. The global identifiability analysis adopts a sampling strategy with only a limited number of model evaluations, and the strategy is a combination of Latin-hypercube sampling, one-factor-at-a-time sampling and elitism preservation strategy. The global identifiability index is the integration of the corresponding local index. A hybrid global optimization method is designed to identify the parameter. Firstly, the genetic algorithm is adopted to identify the model parameter rudely, and then the obtained parameter is further refined through the improved Levenberg-Marquardt algorithm. The niching method is used to maintain the population diversity and to choose the initial value for the Levenberg- Marquardt algorithm. A transition criterion between the genetic algorithm and the Levenberg-Marquardt algorithm is proposed, through the improvement on the average objective function value of the chromosomes and the objective function value of the best chromosome. During optimization by the Levenberg-Marquardt algorithm, the local identifiability analysis is taken at the beginning stage of each iteration, and then the variable with poor identifiability remains unchanged in this iteration; the problem of violation constraint for some solution is solved through adjusting the search step length. At last, taking Ti-6Al-4V as an example, a set of satisfactory material parameters is obtained. The calculated results agree with the experimental results well. The identified results show that some parameters involved in the model are poorly identifiable; at the same time, the identifiability analysis method can provide a guide to experiment design. Copyright © 2010 Tech Science Press.


Liu F.,South China University of Technology | Liu F.,Guangdong Key Laboratory of Automotive Engineering | Lan F.,South China University of Technology | Lan F.,Guangdong Key Laboratory of Automotive Engineering | And 2 more authors.
Journal of Power Sources | Year: 2016

Heat pipe cooling for battery thermal management systems (BTMSs) in electric vehicles (EVs) is growing due to its advantages of high cooling efficiency, compact structure and flexible geometry. Considering the transient conduction, phase change and uncertain thermal conditions in a heat pipe, it is challenging to obtain the dynamic thermal characteristics accurately in such complex heat and mass transfer process. In this paper, a "segmented" thermal resistance model of a heat pipe is proposed based on thermal circuit method. The equivalent conductivities of different segments, viz. the evaporator and condenser of pipe, are used to determine their own thermal parameters and conditions integrated into the thermal model of battery for a complete three-dimensional (3D) computational fluid dynamics (CFD) simulation. The proposed "segmented" model shows more precise than the "non-segmented" model by the comparison of simulated and experimental temperature distribution and variation of an ultra-thin micro heat pipe (UMHP) battery pack, and has less calculation error to obtain dynamic thermal behavior for exact thermal design, management and control of heat pipe BTMSs. Using the "segmented" model, the cooling effect of the UMHP pack with different natural/forced convection and arrangements is predicted, and the results correspond well to the tests. © 2016 Elsevier B.V. All rights reserved.


Ding K.,South China University of Technology | Ding K.,Guangdong Key Laboratory of Automotive Engineering | Zheng C.,South China University of Technology | Zheng C.,Guangdong Key Laboratory of Automotive Engineering | And 2 more authors.
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | Year: 2010

The influence of noise on frequency estimation accuracy of energy barycenter correction method for discrete spectrum is studied. The theoretical formula for frequency estimation error is deduced by applying energy barycenter correction method for discrete spectrum in the presence of Gaussian white noise, which is multiplied by a symmetrical window function. The theoretical error is analyzed for either right or wrong maximal spectrum line searched and the reasons for the frequency estimation error increasing under some conditions are presented. Measures are proposed that will be chose for the threshold phase difference between two spectrum lines is taken as the threshold to be the basis for selecting three or four spectrum lines to carry out the correction, so as to improve the accuracy of frequency estimation. Simulation analysis of discrete spectrum multiplied by Hanning window function is finally performed, which is consistent with theoretical derivation and verifies the correctness thereof, the results demonstrate that there is high frequency estimation accuracy even if the signal is badly influenced by strong noise, and show that the improved energy barycenter correction method for discrete spectrum has higher anti-noise performance, which expands the application scope of energy barycenter correction method. © 2010 Journal of Mechanical Engineering.


Ding K.,South China University of Technology | Ding K.,Guangdong Key Laboratory of Automotive Engineering | Zhu W.,South China University of Technology | Zhu W.,Guangdong Key Laboratory of Automotive Engineering | And 4 more authors.
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | Year: 2010

The parameter estimation error of continuous zoom analysis Fourier transform is studied by applying FFT and FT to spectrum correction. The relation between estimation error of frequency, phase and amplitude and zoom multiples is revealed in the presence of noise-free signal. Parameter estimation accuracy can be improved by increasing zoom multiples, and the maximum error of each parameter is very little when zoom multiple is greater than 40. To the signal with Gaussian white noise, the probability of finding the wrong maximum spectrum line increases with the rise of zoom multiple. Considering the influence of frequency resolution on frequency estimation accuracy and the probability mentioned above, two evaluation indicators, called normalized frequency estimation comprehensive error (NFE) and normalized frequency estimation maximum error (NFEM) are given to provide the best zoom multiple under different signal to noise ratio. The FFT and FT spectrum correction method is modified and improved, and the simulation results indicate that the improved method has higher correction accuracy and anti-noise ability. © 2010 Journal of Mechanical Engineering.

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