£72.99
£72.99
This book covers core estimation methods, intelligent condition assessment, and management for energy storage systems. It provides a theoretical foundation and practical guide with rich examples for researchers and practitioners seeking to innovate in the field.
Closely aligned with market demand and facing technical challenges directly, while having significant academic value and practical significance, this book discusses in depth the estimation methods of core state parameters of energy storage systems, aiming to provide a solid theoretical foundation and practical operation guidelines for the research and practical application of energy storage technology.
The book not only comprehensively introduces the application areas of new power energy storage and identification modelling techniques of power systems, but also focuses on the key technical points of intelligent energy storage condition assessment and intelligent management and monitoring. With its distinctive features, systematic content structure and rich practical examples, the book provides readers with a comprehensive and in-depth technical perspective.
The authors believe that this book will make a positive contribution to the development of China’s power system technology application, and at the same time, it will provide a practical technical guide for researchers and practitioners in the related fields, and help them make innovations and breakthroughs in the field of battery energy storage technology.
This book describes human civilization from an energy perspective, showing how mastering energy catapulted our species to supremacy. It weaves a fascinating story from Stone Age tools to climate change, discussing the dark side and the future of renewables.
Heat transfer is vital for efficient power production. This book covers efficiently utilizing energy by integrating heat exchangers into power production units. It provides descriptions of heat transfer applications in everyday life and industry, supported by practical examples.
This book explores efficient energy utilization in industrial sites, offering a recipe to minimize Global Warming and Ozone Depletion. It presents insights into thermodynamics and energy management to help engineers deal with energy issues from a more global perspective.
This book presents a groundbreaking approach to estimating the state of charge (SOC) of lithium-ion batteries. This method combines neural networks and Kalman filtering to enhance accuracy and adapt to battery aging, paving the way for improved battery management systems.
This book focuses on the co-estimation strategies of State-of-Charge (SOC) and State-of-Health (SOH) for lithium-ion batteries. It proposes a collaborative optimization strategy based on neural networks, providing technical references for scholars and engineers.
This book explores how deep learning enhances the safety and efficiency of electric energy storage systems. It covers core principles, battery assessment, and real-world applications on the grid and user side. A practical guide for engineers, researchers, and students.
Real-time State of Energy (SOE) estimation is crucial for lithium-ion battery safety and predicting the driving range of electric vehicles. This book details an optimized algorithm combining a fuzzy controller and a Kalman filter for fast, accurate, and robust SOE estimation.
This book proposes a method for estimating lithium battery state of charge (SOC) by fusing deep learning and filtering algorithms. It uses BiLSTM neural networks to overcome the limitations of standard LSTM, resulting in improved feature extraction and greater accuracy.
This book focuses on the co-estimation strategies of State-of-Charge (SOC) and State-of-Health (SOH) for lithium-ion batteries. It proposes a collaborative optimization strategy based on neural networks, providing technical references for scholars and engineers.
This book explores how deep learning enhances the safety and efficiency of electric energy storage systems. It covers core principles, battery assessment, and real-world applications on the grid and user side. A practical guide for engineers, researchers, and students.
Real-time State of Energy (SOE) estimation is crucial for lithium-ion battery safety and predicting the driving range of electric vehicles. This book details an optimized algorithm combining a fuzzy controller and a Kalman filter for fast, accurate, and robust SOE estimation.
This book proposes a method for estimating lithium battery state of charge (SOC) by fusing deep learning and filtering algorithms. It uses BiLSTM neural networks to overcome the limitations of standard LSTM, resulting in improved feature extraction and greater accuracy.
This book focuses on the co-estimation strategies of State-of-Charge (SOC) and State-of-Health (SOH) for lithium-ion batteries. It proposes a collaborative optimization strategy based on neural networks, providing technical references for scholars and engineers.
This book explores how deep learning enhances the safety and efficiency of electric energy storage systems. It covers core principles, battery assessment, and real-world applications on the grid and user side. A practical guide for engineers, researchers, and students.
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