In this paper, a new computational method is provided to identify the uncertain parameters of Load Sensing Proportional Valve (LSPV) in a heavy truck brake system by using the polynomial chaos theory. The simulation model of LSPV is built in the software AMESim depending on structure of the valve, and the estimation process is implemented relying on the experimental measurements by pneumatic bench test. With the polynomial chaos expansion carried out by collocation method, the output observation function of the nonlinear pneumatic model can be transformed into a linear and time-invariant form, and the general recursive functions based on Newton method can therefore be reformulated to fit for the computer programming and calculation. To improve the estimation accuracy, the Newton method is modified with reference to Simulated Annealing algorithm by introducing the Metropolis Principle to control the fluctuation during the estimation process and escape from the local minima. The comparison between the introduced computational method and other estimation method indicates that the proposed method can be performed with higher convergence speed and robustness.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Polynomial Chaos-Based Method for Recursive Maximum Likelihood Parameter Estimation of Load Sensing Proportional Valve


    Additional title:

    Sae Int. J. Commer. Veh


    Contributors:
    Wu, Jinglai (author) / Jiang, Ming (author) / Zhang, Yunqing (author) / Ma, Zeyu (author)

    Conference:

    SAE 2014 World Congress & Exhibition ; 2014



    Publication date :

    2014-04-01


    Size :

    8 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    A Polynomial Chaos-Based Method for Recursive Maximum Likelihood Parameter Estimation of Load Sensing Proportional Valve

    Ma, Z. / Wu, J. / Zhang, Y. et al. | British Library Conference Proceedings | 2014


    A Polynomial Chaos- Based Likelihood Approach for Parameter Estimation of Load Sensing Proportional Valve

    Ma, Z. / Wu, J. / Zhang, Y. et al. | British Library Conference Proceedings | 2013



    Load sensing proportional valve body and load sensing proportional valve

    CHEN JIE | European Patent Office | 2015

    Free access

    Maximum-Likelihood Parameter-Estimation Algorithm

    Eldred, D. B. / Hamidi, M. / Rodriguez, G. | NTRS | 1986