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Improving Nonlinear State Estimation Techniques by Hybrid Structures

Name: Improving Nonlinear State Estimation Techniques by Hybrid Structures
Brand: LAP Lambert Academic Publishing
SKU: 15870035
Price: 19.03 EUR
Availability: InStock
Author: Nicolae Tudoroiu
ISBN: 9783330044180

Nicolae Tudoroiu

Sorin Mihai Radu

Elena - Roxana Tudoroiu

Língua

Inglês

Livro Capa mole

Código Libristo: 15870035

Editoras LAP Lambert Academic Publishing, novembro 2016

This research investigates the way in which a nonlinear Gaussian Unscented Kalman Filter can be comb... Descrição completa

Código Libristo: 15870035

46 b

19.03 €

Armazenamento externo Envio em 5-8 dias

Política de devolução de 30 dias

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This research investigates the way in which a nonlinear Gaussian Unscented Kalman Filter can be combined with a nonlinear Bayesian Particles Filter in a hybrid structure capable to perform better in comparison to each one of these two estimators. Their state estimation performance is evaluated for the same case study, more precisely for a simplified model of a Ni-MH battery that is integrated in a Battery Management System in order to drive a Hybrid Electric Vehicle. A benchmark evaluates the performance of each estimator in terms of root mean square error, mean square error and mean absolute error statistics based on the battery state of charge residual. From this benchmark it is easy to get information about the battery state of charge estimation accuracy, the robustness and the modelling limitations of both estimators. The extensive simulations in real time are carried out in an attractive real-time MATLAB framework environment.