The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Joachim Kurzke - One of the best experts on this subject based on the ideXlab platform.

  • Gas Turbine Cycle Design Methodology: A Comparison of Parameter Variation With Numerical Optimization
    Journal of Engineering for Gas Turbines and Power, 1999
    Co-Authors: Joachim Kurzke
    Abstract:

    In gas turbine performance simulations often the following question arises : what is the best thermodynamic cycle design point? This is an optimization task which can be attacked in two ways. One can do a series of Parameter Variations and pick from the resulting graphs the best solution or one can employ numerical optimization algorithms that produce a single cycle that fulfills all constraints. The conventional Parameter study builds strongly on the engineering judgement and gives useful information over a range of Parameter selections. However, when values for more than a few variables have to be determined while several constraints are existing, then numerical optimization routines can help to find the mathematical optimum faster and more accurately. Sometimes even an outstanding solution is found which was overlooked while doing a preliminary Parameter study. For any simulation task a sophisticated graphical user interface is of great benefit. This is especially true for automated numerical optimizations. It is quite helpful to see on the screen of a PC how the variables are changing and which constraints are limiting the design. A quick and clear graphical representation of trade studies is also of great advantage. The paper describes how numerical optimization and Parameter studies are implemented in a Windows-based PC program. As an example, the cycle selection of a derivative turbofan engine with a given core shows the merits of numerical optimization. The Parameter Variation is best suited for presenting the sensitivity of the result in the neighborhood of the optimum cycle design point.

  • Gas Turbine Cycle Design Methodology: A Comparison of Parameter Variation With Numerical Optimization
    Volume 2: Aircraft Engine; Marine; Microturbines and Small Turbomachinery, 1998
    Co-Authors: Joachim Kurzke
    Abstract:

    In gas turbine performance simulations often the question arises: What is the best thermodynamic cycle design point? This is an optimization task which can be attacked in two ways: One can do a series of Parameter Variations and pick from the resulting graphs the best solution or one can employ numerical optimization algorithms that produce a single cycle which fulfills all constraints.The conventional Parameter study builds strongly on the engineering judgement and gives useful information over a range of Parameter selections. However, when values for more than a few variables have to be determined while several constraints are existing, then numerical optimization routines can help to find the mathematical optimum faster and more accurately. Sometimes even an outstanding solution is found which was overlooked while doing a preliminary Parameter study.For any simulation task a sophisticated graphical user interface is of great benefit. This is especially true for automated numerical optimizations. It is quite helpful to see on the screen of a PC how the variables are changing and which constraints are limiting the design. A quick and clear graphical representation of trade studies is also of great advantage. The paper describes how numerical optimization and Parameter studies are implemented in a Windows-based PC program.As an example, the cycle selection of a derivative turbofan engine with a given core shows the merits of numerical optimization. The Parameter Variation is best suited for presenting the sensitivity of the result in the neighborhood of the optimum cycle design point.Copyright © 1998 by ASME

Yuejiu Zheng - One of the best experts on this subject based on the ideXlab platform.

  • a simulation study on Parameter Variation effects in battery packs for electric vehicles
    Energy Procedia, 2017
    Co-Authors: Long Zhou, Yuejiu Zheng, Minggao Ouyang
    Abstract:

    Abstract As one single cell cannot meet power and driving range requirement in an electric vehicle, This is needed to construct battery packs with hundreds of single cells connected in parallel and series. The most important difference between a single cell and a battery pack is cell Variation. Not only does cell Variation effects pack energy density and power density, but also it causes early fade of battery packs and even results in safety issues. This paper first introduces the characteristic and description of cell Variation in battery packs and establishes a pack model with 96 cells connected in series. Subsequently, the influence Parameters of cell Variation are studied. The results show that temperature and coulombic efficiency are the major Parameters which effect cell Variation and the results also imply that dissipative cell equalization is sufficient for battery equalization.

  • A study on Parameter Variation effects on battery packs for electric vehicles
    Journal of Power Sources, 2017
    Co-Authors: Long Zhou, Yuejiu Zheng, Languang Lu
    Abstract:

    As one single cell cannot meet power and driving range requirement in an electric vehicle, the battery packs with hundreds of single cells connected in parallel and series should be constructed. The most significant difference between a single cell and a battery pack is cell Variation. Not only does cell Variation affect pack energy density and power density, but also it causes early degradation of battery and potential safety issues. The cell Variation effects on battery packs are studied, which are of great significant to battery pack screening and management scheme. In this study, the description for the consistency characteristics of battery packs was first proposed and a pack model with 96 cells connected in series was established. A set of Parameters are introduced to study the cell Variation and their impacts on battery packs are analyzed through the battery pack capacity loss simulation and experiments. Meanwhile, the capacity loss composition of the battery pack is obtained and verified by the temperature Variation experiment. The results from this research can demonstrate that the temperature, self-discharge rate and coulombic efficiency are the major affecting Parameters of cell Variation and indicate the dissipative cell equalization is sufficient for the battery pack.

Long Zhou - One of the best experts on this subject based on the ideXlab platform.

  • a simulation study on Parameter Variation effects in battery packs for electric vehicles
    Energy Procedia, 2017
    Co-Authors: Long Zhou, Yuejiu Zheng, Minggao Ouyang
    Abstract:

    Abstract As one single cell cannot meet power and driving range requirement in an electric vehicle, This is needed to construct battery packs with hundreds of single cells connected in parallel and series. The most important difference between a single cell and a battery pack is cell Variation. Not only does cell Variation effects pack energy density and power density, but also it causes early fade of battery packs and even results in safety issues. This paper first introduces the characteristic and description of cell Variation in battery packs and establishes a pack model with 96 cells connected in series. Subsequently, the influence Parameters of cell Variation are studied. The results show that temperature and coulombic efficiency are the major Parameters which effect cell Variation and the results also imply that dissipative cell equalization is sufficient for battery equalization.

  • A study on Parameter Variation effects on battery packs for electric vehicles
    Journal of Power Sources, 2017
    Co-Authors: Long Zhou, Yuejiu Zheng, Languang Lu
    Abstract:

    As one single cell cannot meet power and driving range requirement in an electric vehicle, the battery packs with hundreds of single cells connected in parallel and series should be constructed. The most significant difference between a single cell and a battery pack is cell Variation. Not only does cell Variation affect pack energy density and power density, but also it causes early degradation of battery and potential safety issues. The cell Variation effects on battery packs are studied, which are of great significant to battery pack screening and management scheme. In this study, the description for the consistency characteristics of battery packs was first proposed and a pack model with 96 cells connected in series was established. A set of Parameters are introduced to study the cell Variation and their impacts on battery packs are analyzed through the battery pack capacity loss simulation and experiments. Meanwhile, the capacity loss composition of the battery pack is obtained and verified by the temperature Variation experiment. The results from this research can demonstrate that the temperature, self-discharge rate and coulombic efficiency are the major affecting Parameters of cell Variation and indicate the dissipative cell equalization is sufficient for the battery pack.

H Philip S Wong - One of the best experts on this subject based on the ideXlab platform.

  • on the switching Parameter Variation of metal oxide rram part ii model corroboration and device design strategy
    IEEE Transactions on Electron Devices, 2012
    Co-Authors: Ximeng Guan, H Philip S Wong
    Abstract:

    Using the model developed in Part I of this two-part paper, the simulated dc sweep and pulse transient characteristics of a metal oxide resistive random access memory cell are corroborated with the experimental data of HfOx memory. Key switching features such as the abrupt SET process, gradual RESET process, current fluctuation in the RESET process, and multilevel resistance state distributions are captured by the simulation. The current fluctuation in the RESET process is caused by the competition between the simultaneous oxygen vacancy recombination and generation processes. The origin of the high-resistance state Variation and the tail bit problem are attributed to the Variation of the tunneling gap distances and the stochastic nature of new Vo generation in the tunneling gap region, respectively. The use of the write-verify technique and a bilayer oxide structure are proposed to achieve a tighter resistance distribution.

  • on the switching Parameter Variation of metal oxide rram part i physical modeling and simulation methodology
    IEEE Transactions on Electron Devices, 2012
    Co-Authors: Ximeng Guan, Shimeng Yu, H Philip S Wong
    Abstract:

    The Variation of switching Parameters is one of the major challenges to both the scaling and volume production of metal-oxide-based resistive random-access memories (RRAMs). In this two-part paper, the source of such Parameter Variation is analyzed by a physics-based simulator, which is equipped with the capability to simulate a large number ( ~1000) of cyclic SET-RESET operations. By comparing the simulation results with experimental data, it is found that the random current fluctuation experimentally observed in the RESET processes is caused by the competition between trap generation and recombination, whereas the Variation of the high resistance states and the tail bits are directly correlated to the randomness of the trap dynamics. A combined strategy with a bilayer dielectric material and a write-verification technique is proposed to minimize the resistance Variation. We describe the simulation methodology and discuss the dc results in Part I. The corroboration of the model and the device optimization strategy will be discussed in Part II.

Languang Lu - One of the best experts on this subject based on the ideXlab platform.

  • A study on Parameter Variation effects on battery packs for electric vehicles
    Journal of Power Sources, 2017
    Co-Authors: Long Zhou, Yuejiu Zheng, Languang Lu
    Abstract:

    As one single cell cannot meet power and driving range requirement in an electric vehicle, the battery packs with hundreds of single cells connected in parallel and series should be constructed. The most significant difference between a single cell and a battery pack is cell Variation. Not only does cell Variation affect pack energy density and power density, but also it causes early degradation of battery and potential safety issues. The cell Variation effects on battery packs are studied, which are of great significant to battery pack screening and management scheme. In this study, the description for the consistency characteristics of battery packs was first proposed and a pack model with 96 cells connected in series was established. A set of Parameters are introduced to study the cell Variation and their impacts on battery packs are analyzed through the battery pack capacity loss simulation and experiments. Meanwhile, the capacity loss composition of the battery pack is obtained and verified by the temperature Variation experiment. The results from this research can demonstrate that the temperature, self-discharge rate and coulombic efficiency are the major affecting Parameters of cell Variation and indicate the dissipative cell equalization is sufficient for the battery pack.