Disturbance Estimation Based Modeling Technique for Control and Prediction in Controllable Mechanical Turbo-Compounding System

Paper #:
  • 2016-01-0023

Published:
  • 2016-04-05
DOI:
  • 10.4271/2016-01-0023
Citation:
Lei, Z., Xie, H., and Shen, T., "Disturbance Estimation Based Modeling Technique for Control and Prediction in Controllable Mechanical Turbo-Compounding System," SAE Int. J. Passeng. Cars – Electron. Electr. Syst. 9(1):43-51, 2016, doi:10.4271/2016-01-0023.
Pages:
9
Abstract:
Modeling techniques matter a lot in many fields of engine engineering. Models are requested not only for control design but also for dynamic prediction. However, problems might be encountered during modeling process either because of the system complexity or the unaffordable modeling cost. As a result, a new modeling technique based on disturbance estimation is proposed in this paper. By employing the proposed modeling technique, models are set up in real time with the online information from input and output. The uncertainties of system dynamics are handled as internal disturbance of the system, while the perturbation from outside are taken as the external disturbance, and the combination of the two can be estimated online by a kind of active observer called extended state observer (ESO). Then a dummy variable which is equal to the sum of the known dynamics, estimated disturbance and control input can be used to establish a new simpler system, based on which control and prediction based management can be designed. Deductively, the real control variable can be solved out by the dummy variable equation. Simulation studies are conducted upon the tracking control and energy management of a controllable mechanical turbo-compounding system to verify the effectiveness of the proposed solution. This method is believed costs less than pure mechanism modeling method and is able to incorporate the total disturbance of the operating system into the system dynamics without sacrificing the computation speed, demonstrating satisfying accuracy, which is appealing for model based control and management in engine engineering.
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