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関連する概念動画

Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

675
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
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Energy Stored in a Capacitor: Problem Solving01:26

Energy Stored in a Capacitor: Problem Solving

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In 1749, Benjamin Franklin coined the word battery for a series of capacitors connected to store energy. Capacitors store electric potential energy that can be released over a short time. This property means capacitors have a wide range of applications.
Capacitor-discharge ignition is a type of ignition system commonly found in small engines where the energy released from a capacitor ignites an induction coil that, in turn, fires the spark plug.
To calculate the energy stored in a capacitor of...
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Batteries and Fuel Cells03:12

Batteries and Fuel Cells

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A battery is a galvanic cell that is used as a source of electrical power for specific applications. Modern batteries exist in a multitude of forms to accommodate various applications, from tiny button batteries such as those that power wristwatches to the very large batteries used to supply backup energy to municipal power grids. Some batteries are designed for single-use applications and cannot be recharged (primary cells), while others are based on conveniently reversible cell reactions that...
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Charging Conductors By Induction01:15

Charging Conductors By Induction

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The Earth is a good conductor of electricity, and it is so big that it can be considered an infinite source or sink of charges. It can easily exchange charges with any matter.
Generally, conductors like metals do not allow any excess charge to be present on them. Any excess charge added to metals easily flows away, for example, when a metal is placed on the Earth. This process is called earthing.
However, conductors can be charged by a process called induction. For example, consider charging a...
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Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

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A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the...
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Continuous Charge Distributions01:17

Continuous Charge Distributions

7.8K
Imagine a bucket of water. It contains many molecules, of the order of 1026 molecules. Thus, although it contains discrete elements (molecules) at the microscopic level, macroscopically, it can be considered continuous. Small volume elements of water, infinitesimal compared to the bulk of the bucket's volume, still contain many molecules. Under this framework, quantized matter is approximated as continuous for practical purposes.
The electric charge can also be subjected to an analogical...
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関連する実験動画

Updated: Dec 28, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
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機械学習によるバッテリーの高速充電プロトコルのクローズドループ最適化

Peter M Attia1, Aditya Grover2, Norman Jin1

  • 1Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA.

Nature
|February 21, 2020
PubMed
まとめ

バッテリー充電プロトコルの最適化は遅い. この研究では 早期予測とベイジアン最適化による 機械学習を用いて リチウムイオン電池の寿命を最大限に延ばし 実験時間を大幅に短縮する方法を見つけました

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Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization
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Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

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Identification and Quantification of Decomposition Mechanisms in Lithium-Ion Batteries; Input to Heat Flow Simulation for Modeling Thermal Runaway
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Identification and Quantification of Decomposition Mechanisms in Lithium-Ion Batteries; Input to Heat Flow Simulation for Modeling Thermal Runaway

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関連する実験動画

Last Updated: Dec 28, 2025

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Identification and Quantification of Decomposition Mechanisms in Lithium-Ion Batteries; Input to Heat Flow Simulation for Modeling Thermal Runaway
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科学分野:

  • 材料科学
  • 電気化学
  • 機械学習アプリケーション

背景:

  • リチウムイオン電池などの時間のかかる実験で設計パラメータを最適化すると,科学研究と工学における瓶頸が生じます.
  • バッテリーの寿命を評価するには,数ヶ月から数年かかる広範な実験が必要で,大きなパラメータ空間と高い変動によってさらに複雑になります.
  • プロセスと制御の最適化に必要な実験の数と期間を減らすことが重要な課題です

研究 の 目的:

  • リチウムイオン電池のサイクル寿命を最大化するために,高速充電プロトコルを効率的に最適化するための機械学習 (ML) 方法論を開発し,実証する.
  • 早期予測モデルとベイジアン最適化アルゴリズムを組み合わせることで実験コストを削減する.
  • 優れた充電プロトコルを特定することで,電気自動車の利用者の距離不安を軽減します.

主な方法:

  • 6段階,10分間の高速充電プロトコルのための電流と電圧プロフィールを最適化するためのML方法論を開発しました.
  • 初期実験データから最終サイクルの寿命を予測するための早期予測モデルを統合し,個々の実験期間を短縮しました.
  • パラメータ空間を効率的に探求し,必要な実験の総数を最小限に抑えるために,ベイジアン最適化アルゴリズムを使用した.

主要な成果:

  • 16日間で224の候補者からの高速なサイクルライフチャージプロトコルが特定され,早期予測なしの徹底的な検索の500日以上と比較して大幅に減少しました.
  • ML主導の最適化アプローチの正確性と効率性を検証した.
  • 将来の最適化決定を導くために実験的なフィードバックを使用するクローズド・ループの方法論を示した.

結論:

  • MLの方法論は,リチウムイオン電池のサイクル寿命を最大限にするために,高速充電プロトコルの最適化を効果的に加速します.
  • 初期の予測とベイジアン最適化の組み合わせは,複雑な実験最適化に必要な時間とリソースを大幅に削減します.
  • この方法論は,時間のかかる実験と多次元パラメータ空間を持つ他のバッテリー設計アプリケーションと科学領域に一般化できます.