scholarly journals Holistic vehicle simulation using Modelica - An application on thermal management and operation strategy for electrified vehicles

Author(s):  
Claude Bouvy ◽  
Sidney Baltzer ◽  
Peter Jeck ◽  
Jörg Gissing ◽  
Thomas Lichius ◽  
...  
Author(s):  
Pamela J. Tannous ◽  
Andrew G. Alleyne

Abstract This paper presents a multi-level 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 hierarchical models is reduced by applying an aggregation-based model order reduction technique that preserves the physical correspondence between a physical system and its reduced-order model. The paper 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 hierarchical controller for closed-loop control. A comparison between the proposed hierarchical observer and a centralized observer shows that a hierarchical observer enables a reduction in the required computational power.


2020 ◽  
Vol 142 (11) ◽  
Author(s):  
Pamela J. Tannous ◽  
Andrew G. Alleyne

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.


MTZ worldwide ◽  
2016 ◽  
Vol 77 (5) ◽  
pp. 38-43 ◽  
Author(s):  
Markus Wawzyniak ◽  
Achim Wiebelt

2021 ◽  
Vol 12 (2) ◽  
pp. 84
Author(s):  
Ehsan Sabri Islam ◽  
Ayman Moawad ◽  
Namdoo Kim ◽  
Aymeric Rousseau

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) supports research and development (R&D), as well as deployment of efficient and sustainable transportation technologies, that will improve energy efficiency and fuel economy and enable America to use less petroleum. To accelerate the creation and adoption of new technologies, DOE-VTO has developed specific targets for a wide range of powertrain technologies (e.g., engine, battery, electric machine, lightweighting, etc.). This paper quantifies the impact of VTO R&D on vehicle energy consumption and cost compared to expected historical improvements across vehicle classes, powertrains, component technologies and timeframes. We have implemented a large scale simulation process to develop and simulate tens of thousands of vehicles on U.S. standard driving cycles using Autonomie, a vehicle simulation tool developed by Argonne National Laboratory. Results demonstrate significant additional reductions in both cost and energy consumption due to the existence of VTO R&D targets compared to predicted historical trends. It is observed that, over time, the fuel consumption of different electrified vehicles is expected to decrease by 40–50% and a reduction of 45–55% for vehicle manufacturing costs owing to significant improvements through various VTO R&D targets.


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