216,62 €
240,69 €
-10% with code: EXTRA
Modeling and State Estimation of Automotive Lithium-Ion Batteries
Modeling and State Estimation of Automotive Lithium-Ion Batteries
216,62
240,69 €
  • We will send in 10–14 business days.
This book aims to evaluate and improve the state of charge (SOC) and state of health (SOH) of automotive lithium-ion batteries.The authors first introduce the basic working principle and dynamic test characteristics of lithium-ion batteries. They present the dynamic transfer model, compare it with the traditional second-order reserve capacity (RC) model, and demonstrate the advantages of the proposed new model. In addition, they propose the chaotic firefly optimization algorithm and demonstrate…
  • Publisher:
  • ISBN-10: 1032777915
  • ISBN-13: 9781032777917
  • Format: 15.6 x 23.4 x 1 cm, hardcover
  • Language: English
  • SAVE -10% with code: EXTRA

Modeling and State Estimation of Automotive Lithium-Ion Batteries (e-book) (used book) | bookbook.eu

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This book aims to evaluate and improve the state of charge (SOC) and state of health (SOH) of automotive lithium-ion batteries.

The authors first introduce the basic working principle and dynamic test characteristics of lithium-ion batteries. They present the dynamic transfer model, compare it with the traditional second-order reserve capacity (RC) model, and demonstrate the advantages of the proposed new model. In addition, they propose the chaotic firefly optimization algorithm and demonstrate its effectiveness in improving the accuracy of SOC and SOH estimation through theoretical and experimental analysis.

The book will benefit researchers and engineers in the new energy industry, and provide students of science and engineering with some innovative aspects of battery modeling.

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  • Author: Shunli Wang
  • Publisher:
  • ISBN-10: 1032777915
  • ISBN-13: 9781032777917
  • Format: 15.6 x 23.4 x 1 cm, hardcover
  • Language: English English

This book aims to evaluate and improve the state of charge (SOC) and state of health (SOH) of automotive lithium-ion batteries.

The authors first introduce the basic working principle and dynamic test characteristics of lithium-ion batteries. They present the dynamic transfer model, compare it with the traditional second-order reserve capacity (RC) model, and demonstrate the advantages of the proposed new model. In addition, they propose the chaotic firefly optimization algorithm and demonstrate its effectiveness in improving the accuracy of SOC and SOH estimation through theoretical and experimental analysis.

The book will benefit researchers and engineers in the new energy industry, and provide students of science and engineering with some innovative aspects of battery modeling.

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