To diagnose faults in automotive suspension systems a particle filters based approach was evaluated. The look-ahead Rao-Blackwell Particle Filter was tested to online monitor different oil leaks in a magneto-rheological shock absorber. The non-linear semi-active suspension was modelled through the Jump Markov Linear Gaussian framework. The feasibility of this approach has been analyzed in a simulation environment using different road profiles. Early results with high precision and low variance are promised; however, the computing time is a hard constraint for an online application.
|Title of host publication||2016 European Control Conference, ECC 2016|
|Number of pages||1903|
|Publication status||Published - 2017|
Alcantara, D. H., Morales-Menendez, R., & Amezquita-Brooks, L. (2017). Fault diagnosis for an automotive suspension using particle filters. In 2016 European Control Conference, ECC 2016 (pp. 1898).  https://doi.org/10.1109/ECC.2016.7810568