Multilevel Hierarchical Estimation for Thermal Management Systems of Electrified Vehicles With Experimental Validation

2020 ◽  
Vol 142 (11) ◽  
Author(s):  
Pamela J. Tannous ◽  
Andrew G. Alleyne
Keyword(s):  
Thermal Management ◽  
Closed Loop ◽  
Order Reduction ◽  
Management Systems ◽  
Estimation Accuracy ◽  
Loop Control ◽  
Hierarchical Estimation ◽  
Lumped Parameter ◽  
Lumped Parameter Models ◽  
Electrified Vehicles

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.

Multi-Level Hierarchical Estimation for Thermal Management Systems of Electrified Vehicles

2020 ◽  
Author(s):  
Pamela J. Tannous ◽  
Andrew G. Alleyne
Keyword(s):  
Thermal Management ◽  
Order Reduction ◽  
Management Systems ◽  
Loop Control ◽  
Hierarchical Estimation ◽  
Lumped Parameter ◽  
Lumped Parameter Models ◽  
Level Model ◽  
Multi Level ◽  
Electrified Vehicles

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.

The Galerkin Lumped Parameter Method for Thermal Problems

2012 ◽  
Author(s):  
Alfredo Bermúdez ◽  
Francisco Pena
Keyword(s):  
Reduction Method ◽  
Order Reduction ◽  
Parameter Method ◽  
The Finite Element Method ◽  
Reduced Basis ◽  
Model Order ◽  
Lumped Parameter ◽  
Lumped Parameter Models ◽  
Order Reduction Method ◽  
Lumped Parameter Method

In this contribution, we present a method called Galerkin lumped parameter (GLP) method, as a generalization of the lumped parameter models used in engineering. This method can also be seen as a model-order reduction method. Similarities and differences are discussed. In the GLP method, introduced in [1], domain is decomposed into several sub-domains and a time-independent adapted reduced basis is calculated solving elliptic problems in each sub-domain. The method seeks a global solution in the space spanned by this basis, by solving an ordinary differential system. This approach is useful for electric motors, since the decomposition into several pieces is natural. Numerical results concerning heat equation are presented. Firstly, the comparison with an analytic solution is shown to check the implementation of the numerical algorithm. Secondly, the thermal behavior of an electric motor is simulated, assuming that the electric losses are known. A comparison with the solution obtained by the finite element method is shown.

Closed-loop control of unsteadiness over a rounded backward-facing step

2012 ◽  
Vol 703 ◽  
pp. 326-362 ◽  
Author(s):  
Alexandre Barbagallo ◽  
Gregory Dergham ◽  
Denis Sipp ◽  
Peter J. Schmid ◽  
Jean-Christophe Robinet
Keyword(s):  
Closed Loop ◽  
Random Noise ◽  
Reduced Order Model ◽  
Estimation Accuracy ◽  
Closed Loop Control ◽  
Backward Facing Step ◽  
Order Model ◽  
Loop Control ◽  
Reduced Order ◽  
And Performance

AbstractThe two-dimensional, incompressible flow over a rounded backward-facing step at Reynolds number $\mathit{Re}= 600$ is characterized by a detachment of the flow close to the step followed by a recirculation zone. Even though the flow is globally stable, perturbations are amplified as they are convected along the shear layer, and the presence of upstream random noise renders the flow unsteady, leading to a broadband spectrum of excited frequencies. This paper is aimed at suppressing this unsteadiness using a controller that converts a shear-stress measurement taken from a wall-mounted sensor into a control law that is supplied to an actuator. A comprehensive study of various components of closed-loop control design – covering sensor placement, choice and influence of the cost functional, accuracy of the reduced-order model, compensator stability and performance – shows that successful control of this flow requires a judicious balance between estimation speed and estimation accuracy, and between stability limits and performance requirements. The inherent amplification behaviour of the flow can be reduced by an order of magnitude if the above-mentioned constraints are observed. In particular, to achieve superior controller performance, the estimation sensor should be placed upstream near the actuator to ensure sufficient estimation speed. Also, if high-performance compensators are sought, a very accurate reduced-order model is required, especially for the dynamics between the actuator and the estimation sensor; otherwise, very minute errors even at low energies and high frequencies may render the large-scale compensated linearized simulation unstable. Finally, coupling the linear compensator to nonlinear simulations shows a gradual deterioration in control performance as the amplitude of the noise increases.

Fault Detection and Isolation for Complex Thermal Management Systems

2019 ◽  
Vol 141 (6) ◽  
Author(s):  
Pamela J. Tannous ◽  
Andrew G. Alleyne
Keyword(s):  
Fault Detection ◽  
Thermal Management ◽  
Model Order Reduction ◽  
Order Reduction ◽  
Fault Detection And Isolation ◽  
Management Systems ◽  
False Alarms ◽  
Critical Systems ◽  
Model Order ◽  
Unknown Inputs

This paper presents a fault detection and isolation (FDI) approach for actuator faults of complex thermal management systems. In the case of safety critical systems, early fault diagnosis not only improves system reliability, but can also help prevent complete system failure (i.e., aircraft system). In this work, a robust unknown input observer (UIO)-based actuator FDI approach is applied on an example aircraft fluid thermal management system (FTMS). Robustness is achieved by decoupling the effect of unknown inputs modeled as additive disturbances (i.e., modeling errors, linearization errors, parameter variations, or model order reduction errors) from the residuals generated from a bank of UIOs. Robustness is central to avoid false alarms without reducing residual sensitivity to actual faults in the system. System dynamics are modeled using a graph-based approach. A structure preserving aggregation-based model-order reduction technique is used to reduce the complexity of the dynamic model. A reduced-order linearized state space model is then used in a bank of UIOs to generate a set of structured robust (in the sense of disturbance decoupling) residuals. Simulation and experimental results show successful (i.e., no false alarms) actuator FDI in the presence of unknown inputs.

The Impact of Visual Feedback Type on the Mastery of Visuo-Motor Transformations

2012 ◽  
Vol 220 (1) ◽  
pp. 3-9 ◽  
Author(s):  
Sandra Sülzenbrück
Keyword(s):  
Empirical Research ◽  
Visual Feedback ◽  
Closed Loop ◽  
Motor Planning ◽  
Visual Input ◽  
Closed Loop Control ◽  
Loop Control ◽  
Feedback Type ◽  
Effective Use ◽  
The Impact

For the effective use of modern tools, the inherent visuo-motor transformation needs to be mastered. The successful adjustment to and learning of these transformations crucially depends on practice conditions, particularly on the type of visual feedback during practice. Here, a review about empirical research exploring the influence of continuous and terminal visual feedback during practice on the mastery of visuo-motor transformations is provided. Two studies investigating the impact of the type of visual feedback on either direction-dependent visuo-motor gains or the complex visuo-motor transformation of a virtual two-sided lever are presented in more detail. The findings of these studies indicate that the continuous availability of visual feedback supports performance when closed-loop control is possible, but impairs performance when visual input is no longer available. Different approaches to explain these performance differences due to the type of visual feedback during practice are considered. For example, these differences could reflect a process of re-optimization of motor planning in a novel environment or represent effects of the specificity of practice. Furthermore, differences in the allocation of attention during movements with terminal and continuous visual feedback could account for the observed differences.

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