An official website of the United States government
While integrated physical and control system co-design has been demonstrated successfully on several engineering system design applications, it has been primarily applied in a deterministic manner without considering uncertainties. An opportunity exists to study non-deterministic co-design strategies, taking into account various uncertainties in an integrated co-design framework. Reliability-based design optimization (RBDO) is one such method that can be used to ensure an optimized system design being obtained that satisfies all reliability constraints considering particular system uncertainties. While significant advancements have been made in co-design and RBDO separately, little is known about methods where reliability-based dynamic system design and control design optimization are considered jointly. In this article, a comparative study of the formulations and algorithms for reliability-based co-design is conducted, where the co-design problem is integrated with the RBDO framework to yield solutions consisting of an optimal system design and the corresponding control trajectory that satisfy all reliability constraints in the presence of parameter uncertainties. The presented study aims to lay the groundwork for the reliability-based co-design problem by providing a comparison of potential design formulations and problem–solving strategies. Specific problem formulations and probability analysis algorithms are compared using two numerical examples. In addition, the practical efficacy of the reliability-based co-design methodology is demonstrated via a horizontal-axis wind turbine structure and control design problem.
more »
« less
Machine learning enhanced control co-design optimization of an immersion cooled battery thermal management system
The development of lithium-ion battery technology has ensured that battery thermal management systems are an essential component of the battery pack for next-generation energy storage systems. Using dielectric immersion cooling, researchers have demonstrated the ability to attain high heat transfer rates due to the direct contact between cells and the coolant. However, feedback control has not been widely applied to immersion cooling schemes. Furthermore, current research has not considered battery pack plant design when optimizing feedback control. Uncertainties are inherent in the cooling equipment, resulting in temperature and flow rate fluctuations. Hence, it is crucial to systematically consider these uncertainties during cooling system design to improve the performance and reliability of the battery pack. To fill this gap, we established a reliability-based control co-design optimization framework using machine learning for immersion cooled battery packs. We first developed an experimental setup for 21700 battery immersion cooling, and the experiment data were used to build a high-fidelity multiphysics finite element model. The model can precisely represent the electrical and thermal profile of the battery. We then developed surrogate models based on the finite element simulations in order to reduce computational cost. The reliability-based control co-design optimization was employed to find the best plant and control design for the cooling system, in which an outer optimization loop minimized the cooling system cost while an inner loop ensured battery pack reliability. Finally, an optimal cooling system design was obtained and validated, which showed a 90% saving in cooling system energy consumption.
more »
« less
- Award ID(s):
- 2037898
- PAR ID:
- 10593803
- Publisher / Repository:
- American Institute of Physics
- Date Published:
- Journal Name:
- Journal of Applied Physics
- Volume:
- 136
- Issue:
- 2
- ISSN:
- 0021-8979
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Co-design, or integrated physical and control system design, has been demonstrated successfully for several engineering system design optimization applications, primarily in a deterministic manner. An opportunity exists to study non-deterministic co-design strategies, including incorporation of uncertainty-induced failures, into an integrated co-design framework. Reliability-based design optimization (RBDO) is one such method that can be used to increase the likelihood of having a feasible design that satisfies all reliability constraints. While significant recent advancements have been made in co-design and RBDO separately, limited work has been done where reliability-based dynamic system design and control design optimization are considered jointly. In this paper, the co-design problem is integrated with the RBDO framework to yield a system-optimal design and the corresponding control trajectory, which satisfy all reliability constraints in the presence of parameter variations. Different problem formulations and RBDO algorithms are compared through numerical examples. The design of a horizontal-axis wind turbine (HAWT) supported by a lattice tower (with parameter uncertainties) is presented to demonstrate the applicability of the proposed method.more » « less
-
Thermal comfort and energy efficiency are always the two most significant objectives in HVAC operations. However, for conventional HVAC systems, the pursuit of high energy efficiency may be at the expense of satisfactory thermal comfort. Therefore, even if centralized HVAC systems nowadays have higher energy efficiency than before in office buildings, most of them cannot adapt the dynamic occupant behaviors or individual thermal comfort. In order to realize high energy efficiency while still maintain satisfactory thermal environment for occupants indoors, the integrated hybrid HVAC system has been developed for years such as task-ambient conditioning system. Moreover, the occupant-based HVAC control system such as human- in-the-loop has also been investigated so that the system can be adaptive based on occupant behaviors. However, most of research related to personalized air-conditioning system only focuses on field-study with limited scale (i.e. only one office room), this paper has proposed a co- simulation model in energyplus to simulate the hybrid cooling system with synthetic thermal comfort distributions based on global comfort database I&II. An optimization framework on cooling set-point is proposed with the objective of energy performance and the constraints of thermal comfort distribution developed by unsupervised Gaussian mixture model (GMM) clustering and kernel density estimation (KDE). The co-simulation results have illustrated that with the proposed optimization algorithm and the hybrid cooling system, HVAC demand power has decreased 5.3% on average with at least 90% of occupants feeling satisfied.more » « less
-
Immersion cooling, where cooling fluid flows in direct contact with the Li-ion cell, provides superior temperature control compared to other battery thermal management systems (BTMSs). Although the temperature rise during charging/discharging is low for immersion cooling, the inherent complexity of the cooling approach makes it difficult to predict and control performance. In general, numerical approaches are required to design and analyze immersion cooled BTMS configurations. For accurate results, models must fully couple the electrochemical and thermal-fluid physics solvers. However, such a numerical approach is computationally expensive and may not be feasible, in particular, for large BTMS systems. In the present study, we develop a computationally-efficient approach with coupled electrochemical and thermo-fluid physics to study immersion cooling based BTMSs. The core strategy is to use either analytical expressions or combination of analytical and numerical solutions for all the governing physics. Depending on the discharge rate and on the final design objective, different levels of simplification are leveraged to analyze the thermal and electrochemical response of the system. For the present analysis, we consider discharging of a cylindrical nickel manganese cobalt oxide (NCM) 18650 cell that is immersed in a cooling fluid stream. Different combinations of mass flow rates and fluids (deionized water, mineral oil, and air) are considered to evaluate performance. For every configuration, we first analyze the system with a fully-coupled fully numerical model and this data serves as the reference to judge the accuracy of the newly developed models. Note that the parameters used in the electrochemical models (such as electrolyte and electrode properties, as well as the reaction rates) are the same for the fully-numerical and the quasi-analytical models allowing direct comparison of the results. To isolate the impact of using the simplified models for the electrochemical aspects, a second set of comparison data is generated using the analytical electrochemical model in conjunction with the full-scale numerical thermo-fluid model. The analytical models rely on calculating a heat transfer coefficient to include the impact of the fluid flow and the heat transfer coefficient can be estimated from correlations or from the fully-coupled fully-numerical models. In general, for air-cooled configuration, the thermal and electrochemical performance (i.e., trend and magnitude of temperature rise and cell potential) of the quasi-analytical models matches the fully-coupled full-scale numerical model. But for other fluids, the results deviate from the baseline fully-coupled fully-numerical models unless the numerical fluid models are used to estimate the evolution of heat transfer coefficient throughout the discharging process. Specifically, a small number of fully-coupled fully-numerical simulations are leveraged to train the quasi-analytical model (based on a particular geometry) for rapid analysis and optimization of the BTMS. In summary, the newly developed models including the numerical data-driven learning provide an efficient trade-off between computation cost and accuracy.more » « less
-
Abstract The data center’s server power density and heat generation have increased exponentially because of the recent, unparalleled rise in the processing and storing of massive amounts of data on a regular basis. One-third of the overall energy used in conventional air-cooled data centers is directed toward cooling information technology equipment (ITE). The traditional air-cooled data centers must have low air supply temperatures and high air flow rates to support high-performance servers, rendering air cooling inefficient and compelling data center operators to use alternative cooling technology. Due to the direct interaction of dielectric fluids with all the components in the server, single-phase liquid immersion cooling (Sp-LIC) addresses mentioned problems by offering a significantly greater thermal mass and a high percentage of heat dissipation. Sp-LIC is a viable option for hyper-scale, edge, and modular data center applications because, unlike direct-to-chip liquid cooling, it does not call for a complex liquid distribution system configuration and the dielectric liquid can make direct contact with all server components. Immersion cooling is superior to conventional air-cooling technology in terms of thermal energy management however, there have been very few studies on the reliability of such cooling technology. A detailed assessment of the material compatibility of different electronic packaging materials for immersion cooling was required to comprehend their failure modes and reliability. For the mechanical design of electronics, the modulus, and thermal expansion are essential material characteristics. The substrate is a crucial element of an electronic package that has a significant impact on the reliability and failure mechanisms of electronics at both the package and the board level. As per Open Compute Project (OCP) design guidelines for immersion-cooled IT equipment, the traditional material compatibility tests from standards like ASTM 3455 can be used with certain appropriate adjustments. The primary focus of this research is to address two challenges: The first part is to understand the impact of thermal aging on the thermo-mechanical properties of the halogen-free substrate core in the single-phase immersion cooling. Another goal of the study is to comprehend how thermal aging affects the thermo-mechanical characteristics of the substrate core in the air. In this research the substrate core is aged in synthetic hydrocarbon fluid (EC100), Polyalphaolefin 6 (PAO 6), and ambient air for 720 hours each at two different temperatures: 85°C and 125°C and the complex modulus before and after aging are calculated and compared.more » « less
