Multilevel hierarchical estimation for thermal management systems of electrified vehicles with experimental validation

Pamela J. Tannous, Andrew G. Alleyne

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a multilevel model-based hierarchical estimation framework for complex thermal management systems of electrified vehicles. System dynamics are represented by physics-based lumped parameter models derived from a graph-based modeling approach. The complexity of the hierarchical models is reduced by applying an aggregation-based model-order reduction technique that preserves the physical correspondence between a reduced-order model and the physical system. This paper also presents a case study in which a hierarchical observer is designed to estimate the dynamics of a candidate system. The hierarchical observer is connected to a previously developed hierarchical controller for closed-loop control, and the closed-loop performance is demonstrated through simulation and real-time experimental results. A comparison between the proposed hierarchical observer and a centralized observer shows the tradeoff between the estimation accuracy and the computational complexity of the two approaches.

Original languageEnglish (US)
Article number111004
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Volume142
Issue number11
DOIs
StatePublished - Nov 2020

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications

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