Wang Shunli (170 results)

Condition: New.

Hardback or Cased Book. Condition: New. Application of Artificial Intelligence in Power System Monitoring and Fault Diagnosis. Book.

Condition: New.

Condition: As New. Unread book in perfect condition.

Hardback. Condition: New.

Condition: New. In English.

Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.

Condition: New. In English.

Paperback. Condition: New. Multidimensional Lithium-Ion Battery Status Monitoring focuses on equivalent circuit modeling, parameter identification, and state estimation in lithium-ion battery power applications. It explores the requirements of high-power lithium-ion batteries for new energy vehicles and systematically describes the key technologies in core state estimation based on battery equivalent modeling and parameter identification methods of lithium-ion batteries, providing a technical reference for the design and application of power lithium-ion battery management systems. Reviews Li-ion battery characteristics and applications. Covers battery equivalent modeling, including electrical circuit modeling and parameter identification theory Discusses battery state estimation methods, including state of charge estimation, state of energy prediction, state of power evaluation, state of health estimation, and cycle life estimation Introduces equivalent modeling and state estimation algorithms that can be applied to new energy measurement and control in large-scale energy storage Includes a large number of examples and case studies This book has been developed as a reference for researchers and advanced students in energy and electrical engineering.…

hardcover. Condition: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind.

Paperback. Condition: Brand New. 134 pages. 6.14x0.33x9.21 inches. In Stock.

Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Condition: New.

Hardback. Condition: New. Batteries are of vital importance for storing intermittent renewable energy for stationary and mobile applications. In order to charge the battery and maintain its capacity, the states of the battery - such as the current charge, safety and health, but also quantities that cannot be measured directly - need to be known to the battery management system. State estimation estimates the electrical state of a system by eliminating inaccuracies and errors from measurement data. Numerous methods and techniques are used for lithium-ion and other batteries. The various battery models seek to simplify the circuitry used in the battery management system. This concise work captures the methods and techniques for state estimation needed to keep batteries reliable. The book focuses particularly on mechanisms, parameters and influencing factors. Chapters convey equivalent modelling and several Kalman filtering techniques, including adaptive extended Kalman filtering for multiple battery state estimation, dual extended Kalman filtering prediction for complex working conditions, and particle filtering of safety estimation considering the capacity fading effect. This book is necessary reading for researchers in battery research and development, including battery management systems and related power electronics, for battery manufacturers, and for advanced students in power electronics.…

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New. Shunli Wang is Professor, Academic Dean, Academic Leader of the National Electrical Safety and Quality Testing Center, Academician of the Russian Academy of Natural Sciences, Senior Overseas Study Talent of Sichuan Province, and Academic and Techn.

Condition: As New. Unread book in perfect condition.

Condition: New.

Hardback. Condition: New. Batteries are a necessary part of a low-emission energy system, as they can store renewable electricity and assist the grid. Utility-scale batteries, with capacities of several to hundreds of MWh, are particularly important for condominiums, local grid nodes, and EV charging arrays. However, such batteries are expensive and need to be monitored and managed well to maintain capacity and reliability. Artificial intelligence offers a solution for effective monitoring and management of utility-scale batteries. This book systematically describes AI-based technologies for battery state estimation and modeling for utility-scale Li-ion batteries. Chapters cover utility-scale lithium-ion battery system characteristics, AI-based equivalent modeling, parameter identification, state of charge estimation, battery parameter estimation, offer samples and case studies for utility-scale battery operation, and conclude with a summary and prospect for AI-based battery status monitoring. The book provides practical references for the design and application of large-scale lithium-ion battery systems. AI for Status Monitoring of Utility-Scale Batteries is an invaluable resource for researchers in battery RandD, including battery management systems and related power electronics, battery manufacturers, and advanced students.…

Condition: New.

Condition: New.