A Polynomial Chaos-Based Method for Recursive Maximum Likelihood Parameter Estimation of Load Sensing Proportional Valve 2014-01-0721
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.
Citation: Ma, Z., Wu, J., Zhang, Y., and Jiang, M., "A Polynomial Chaos-Based Method for Recursive Maximum Likelihood Parameter Estimation of Load Sensing Proportional Valve," SAE Int. J. Commer. Veh. 7(1):124-131, 2014, https://doi.org/10.4271/2014-01-0721. Download Citation
Zeyu Ma, Jinglai Wu, Yunqing Zhang, Ming Jiang
Huazhong University of Science and Tech., Dongfeng Motor Co. Ltd.
SAE 2014 World Congress & Exhibition
SAE International Journal of Commercial Vehicles-V123-2EJ, SAE International Journal of Commercial Vehicles-V123-2