Building mathematical models of subsystems and components is one of the most important tasks in the analysis and design of hybrid vehicle systems. This chapter introduces basic theories and methodologies used to build a mathematical model and estimate the parameters of the model. There are many different methods that can be used to determine the parameters of a model, and there are also different criteria as to which method should be selected. The chapter also introduces the basic principle of the least squares estimation method, which is used widely in engineering. In order to solve the unstable issue of the recursive least squares estimation, it is necessary to have the covariance matrix strictly positive definite. The chapter further introduces a few common algorithms to achieve this goal. It describes two approaches for joint state and parameter estimation of a dynamic system, including extended Kalman filter, and singular pencil model.


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    Titel :

    Appendix A: System Identification, State and Parameter Estimation Techniques


    Beteiligte:
    Liu, Wei (Autor:in)


    Erscheinungsdatum :

    16.02.2017


    Format / Umfang :

    40 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch