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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Comparison of Optimal Energy Management Strategies Using Dynamic Programming, Model Predictive Control, and Constant Velocity Prediction

Due to the recent advancements in autonomous vehicle technology, future vehicle velocity predictions are becoming more robust which allows fuel economy (FE) improvements in hybrid electric vehicles through optimal energy management strategies (EMS). A realworld highway drive cycle (DC) and a controls-oriented 2017 Toyota Prius Prime model are used to study potential FE improvements. We proposed three important metrics for comparison: (1) perfect full drive cycle prediction using dynamic programming, (2) 10-second prediction horizon model predictive control (MPC), and (3) 10-second constant velocity prediction. These different velocity predictions are put into an optimal EMS derivation algorithm to derive optimal engine torque and engine speed. The results show that the constant velocity prediction algorithm outperformed the baseline control strategy but underperformed the MPC strategy with an average 1.58% and 2.45% of FE improvement with highway and city-highway DC. Also, using a 10-second prediction window MPC strategy provided FE improvement results close to the full drive cycle prediction case. MPC has the potential to achieve 60%-65% and 70% - 80% of global FE improvement over highway and city-highway DC respectively.

Patel, Amol Arvind↗
DOE OSTI2020

Comparison of Optimal Energy Management Strategies Using Dynamic Programming, Model Predictive Control, and Constant Velocity Prediction

Due to the recent advancements in autonomous vehicle technology, future vehicle velocity predictions are becoming more robust which allows fuel economy (FE) improvements in hybrid electric vehicles through optimal energy management strategies (EMS). A real- world highway drive cycle (DC) and a controls-oriented 2017 Toyota Prius Prime model are used to study potential FE improvements. We proposed three important metrics for comparison: (1) perfect full drive cycle prediction using dynamic programming, (2) 10-second prediction horizon model predictive control (MPC), and (3) 10-second constant velocity prediction. These different velocity predictions are put into an optimal EMS derivation algorithm to derive optimal engine torque and engine speed. The results show that the constant velocity prediction algorithm outperformed the baseline control strategy but underperformed the MPC strategy with an average 1.58% and 2.45% of FE improvement with highway and city-highway DC. Also, using a 10-second prediction window MPC strategy provided FE improvement results close to the full drive cycle prediction case. MPC has the potential to achieve 60%-65% and 70% - 80% of global FE improvement over highway and city-highway DC respectively.

Patel, Amol Arvind↗
DOE OSTI2024

MUPPET: An automated OpenMP mutation testing framework for performance optimization

MUPPET is a tool for OpenMP programs that identifies program modifications, called mutations, aimed at improving program performance. Existing performance optimization techniques, including profiling-based and auto-tuning techniques, fail to indicate program modifications at the source level thus preventing their portability across compilers. MUPPET aims to help HPC developers reason about performance defects and missed opportunities to improve performance at the source code level.

Parasyris, Konstantinos↗
DOE OSTI2018

Optimizing Distributed Photovoltaic System Set Points Under Uncertainty

We explore the potential for using dynamic programming (DP) and approximate dynamic programming (ADP) techniques to optimize the set points of distributed photovoltaic (DGPV) inverters under uncertainty about future DGPV deployment. We consider a case where a large (=1MW) system is installed first, and growth in deployment of small rooftop systems is anticipated, but uncertain. We find that for a real feeder (EPRI's J1 feeder), a significant reduction in the number and severity of voltage violations can be expected when DP or ADP is used compared to selecting set points based on the current conditions (the traditional myopic approach). Additionally, we find that using a simple ADP algorithm, sampled backward induction, is more than twice as fast as DP with similar outcomes.

14 SOLAR ENERGY↗
NASA NTRS1990

Geometric programming design of spacecraft protective structures to defeat earth-orbital space debris

A unique methodology providing global optimization of spacecraft protective structures is presented. The Geometric Programming optimization technique, which has a long history of application to structural design problems, is employed to minimize spacecraft weight of protective structural systems exposed to meteoroid and space debris hypervelocity impacts. The space debris and meteoroid environment are defined followed by the formulation of the general weight objective function. The Wilkinson, Burch, and Nysmith hypervelocity impact predictor models are then used in example cases to display Geometric Programming capabilities. Results show that global nonlinear design optimization can be performed for hypervelocity impact models that follow the Geometric Programming form.

Mog, Robert A.↗
NASA NTRS1975

The Use of General Purpose Computer Programs to Derive Equations of Motion for Optimal Isolation Studies

Techniques were developed that utilize general purpose structural analysis computer programs to generate the equations of motion necessary for limiting performance studies. The methodology necessary to couple available general purpose finite element structural programs to a limiting performance capability was developed. Primary emphasis was given to the use of the general purpose program to develop equations of motion in a form that can be used by the limiting performance program.

Pilkey, W. D.↗
NASA NTRS1971

Optimization techniques for FORTRAN 4 (G and H) programs written for the IBM 360 under OS

A fairly complete list is reported of programming techniques which are available to the programmer for optimizing the execution time of production programs written in FORTRAN IV (G and H) for the IBM 360 under OS. After the program has been complied under FORTRAN H, OPT=2, then the process of actually changing code begins. The bulk of execution time of FORTRAN programs can almost always be attributed to a few loops, and primary consideration is given to these.

Dean, J. L.↗
DOE OSTI2015

Security-Constrained Unit Commitment with Linearized AC Optimal Power Flow.

We propose a mathematical programming-based approach to optimize the security-constrained unit commitment problem with a full AC transmission network representation. Our approach is based on our previously introduced successive linear programming (SLP) approach to solving the non-linear, nonconvex AC optimal power flow (ACOPF) problem. By linearizing the ACOPF, we are able to leverage powerful commercial mixed-integer solvers to iteratively optimize the combined unit commitment plus ACOPF model. We demonstrate our approach on six-bus, IEEE RTS-96, and IEEE 118-bus test systems. We perform a comparative analysis of the relative impacts of singlebus, DC, and AC transmission network models on the unit commitment and dispatch solutions and their associated costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1990

Optimal input design for aircraft parameter estimation using dynamic programming principles

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

Klein, Vladislav↗
NASA NTRS1990

Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

Morelli, Eugene A.↗
NASA NTRS1986

Structural tailoring of SSME turbopump blades (SSME/STAEBL)

Computer structural optimization is applied to the design of Space Shuttle main engine turbopump blades. The optimization is implemented by the program SSME/STAEBL. A general description of this program is given. Design optimization studies for typical blade designs are presented.

Rubinstein, R.↗
NASA NTRS1989

Computational architecture for integrated controls and structures design

To facilitate the development of control structure interaction (CSI) design methodology, a computational architecture for interdisciplinary design of active structures is presented. The emphasis of the computational procedure is to exploit existing sparse matrix structural analysis techniques, in-core data transfer with control synthesis programs, and versatility in the optimization methodology to avoid unnecessary structural or control calculations. The architecture is designed such that all required structure, control and optimization analyses are performed within one program. Hence, the optimization strategy is not unduly constrained by cold starts of existing structural analysis and control synthesis packages.

Belvin, W. Keith↗
NASA NTRS1993

The use of CMAC neural architectures in obstacle avoidance

In this paper, CMAC neural architectures are used in conjunction with a hierarchical planning approach to find collision free paths over two dimensional analog valued obstacle fields. The method constructs a coarse resolution version of the original problem and then finds the corresponding coarse optimal path using multipass dynamic programming. CMAC artificial neural architectures are used to estimate the analog transition costs that dynamic programming requires. The coarse optimal path is then used as a baseline for the construction of a fine scale optimal path through the original obstacle array.

Peterson, James K.↗
DOE OSTI2021

A Novel Framework for Optimizing Ramping Capability of Hybrid Energy Storage Systems

Hybrid Energy Storage System has been widely applied in aerospace, electric vehicle, and microgrid applications. The advantages are that they include complimentary technologies with both high power and energy capabilities. HESS have the potential to be useful to the bulk power systems, for example to increase the value of energy produced by variable generation resource through enabling participation in ancillary service markets. Actualizing the benefits of HESSs requires optimizing the combined ramping capability of aggregated HESS resources. To provide quality ancillary service, source of HESSs locating at multiple sites of variable generation resource must be optimally sized and cohesively controlled. Optimizing aggregated resources can be formulated as an optimization problem. Successfully solving this problem not only requires using effective solution methods but also depends on accurately and rapidly setting the necessary parameters in the problem formula. This article proposes a novel framework with double-layer structure to solve the optimization problem of aggregating ramping capability. Program developed on the upper layer focuses on solving the optimization of aggregating ramping capability among multiple HESSs and is compatible with most existing optimization algorithms. Program on lower layer of the framework targets at optimizing the local control of a single HESS based on a thorough analytics of HESS operation strategy presented in this article. Result of local optimization is also provided to upper layer program for updating the parameters in formula of optimization problem. Real time hardware-in-the-loop test is conducted to verify the performance of the optimization framework developed. The work presented is expected to provide guidance for implementing this framework in practical operation.

Luo, Yushen↗
NASA NTRS1990

Robustness, generality and efficiency of optimization algorithms in practical applications

The theoretical foundations of two approaches, sequential quadratic programming (SQP) and optimality criteria (OC), are analyzed and compared, with emphasis on the critical importance of parameters such as accuracy, generality, robustness, efficiency, and ease of use in large scale structural optimization. A simplified fighter wing and active control of space structures are considered with other example problems. When applied to general system identification problems, the OC methods are shown to lose simplicity and demonstrate lack of generality, accuracy and robustness. It is concluded that the SQP method with a potential constraint strategy is a better choice as compared to the currently prevalent mathematical programming and OC approaches.

Thanedar, P. B.↗
NASA NTRS1988

A study of the use of linear programming techniques to improve the performance in design optimization problems

This project has two objectives. The first is to determine whether linear programming techniques can improve performance when handling design optimization problems with a large number of design variables and constraints relative to the feasible directions algorithm. The second purpose is to determine whether using the Kreisselmeier-Steinhauser (KS) function to replace the constraints with one constraint will reduce the cost of total optimization. Comparisons are made using solutions obtained with linear and non-linear methods. The results indicate that there is no cost saving using the linear method or in using the KS function to replace constraints.

Young, Katherine C.↗
DOE OSTI2022

Optimization of Integrated Energy Systems

Integrated energy systems that couple nuclear power plants with additional products including hydrogen, storage, or synthetic fuels provide a more flexible energy source that can be more economical than generating electricity alone. Determining the size and shape of these systems and optimizing their operation is challenging. INL, through the IES program, has developed optimization software to help solve these challenges. Holistic Energy Resource Optimization Network (HERON) is a software tool to optimize the size and capacity of integrated energy systems using stochastic optimization. Optimization of Real-time Capacity Allocation (ORCA) is a software tool under development to perform real-time economic optimization of these systems using economic model predictive control. An overview of these tools and a discussion of their optimization methods will be presented in this talk.

97 MATHEMATICS AND COMPUTING↗