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Artificial intelligence applications in battery management systems and routing problems in electric vehicles

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial intelligence applications in battery management systems and routing problems in electric vehicles[edited by] S. Angalaeswari, T. Deepa, L. Ashok Kumar.
other author:	Angalaeswari, S.,
Published:	Hershey, Pennsylvania :IGI Global,2023.
Description:	1 online resource (342 p.) :ill. (chiefly col.)
Subject:	Electric vehiclesBatteries.
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-6631-5
ISBN:	9781668466339 (electronic bk.)

Artificial intelligence applications in battery management systems and routing problems in electric vehicles
Artificial intelligence applications in battery management systems and routing problems in electric vehicles[electronic resource] /[edited by] S. Angalaeswari, T. Deepa, L. Ashok Kumar. - Hershey, Pennsylvania :IGI Global,2023. - 1 online resource (342 p.) :ill. (chiefly col.)

Includes bibliographical references and index.

Section 1. Battery management systems. Chapter 1. Importance of battery pack design and battery management systems in electric vehicles ; Chapter 2. Battery monitoring system and SOC enhancement analysis using artificial intelligence techniques ; Chapter 3. Control of cell voltage difference balancing in battery management system charging circuits in electric vehicles ; Chapter 4. Design and evaluation of battery management systems for electric vehicle applications with Harris Hawk optimized algorithm (HHOA) based on fuzzy logic controller -- Section 2. Electric vehicles: modelling and control. Chapter 5. Electric vehicles and their types ; Chapter 6. Modelling and simulation of e-bikes driven by BLDC motors ; Chapter 7. Enhancement of suspension performance of the vehicle model using sliding mode controllers ; Chapter 8. Active suspension control of full car model using bat optimized PID controller -- Section 3. Analytics in electric vehicles. Chapter 9. Intelligent demand and supply of electrical vehicles ; Chapter 10. Data analytics in electric vehicles ; Chapter 11. Autonomous electric vehicles and edge computing -- Section 4. Latest trends in electric vehicles. Chapter12. Vehicle-to-grid and electric vehicle-integrated demand response management ; Chapter 13. Hybrid optimization based on genetic routing and scheduling scheme with secure transmission in wireless sensor networks ; Chapter 14. Thermal management system for batteries in electric vehicles.

"The Handbook of Research on Battery Management Systems and Routing Problems in Electric Vehicles focuses on the integration of renewable energy sources with the existing grid, introduces a power exchange scenario in the prevailing power market, considers the use of the electric vehicle market for creating cleaner and transformative energy, and optimizes the control variables with artificial intelligence techniques. Covering key topics such as artificial intelligence,smart grids, and sustainable development, this major reference work is ideal for government officials, industry professionals, policymakers, researchers, scholars, practitioners, academicians, instructors, and students"--

ISBN: 9781668466339 (electronic bk.)Subjects--Topical Terms:

712021
Electric vehicles
--Batteries.Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: TL220 / .A776 2023e

Dewey Class. No.: 629.22/93

Artificial intelligence applications in battery management systems and routing problems in electric vehicles
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300 $a 1 online resource (342 p.) : $b ill. (chiefly col.)
504 $a Includes bibliographical references and index.
505 0 $a Section 1. Battery management systems. Chapter 1. Importance of battery pack design and battery management systems in electric vehicles ; Chapter 2. Battery monitoring system and SOC enhancement analysis using artificial intelligence techniques ; Chapter 3. Control of cell voltage difference balancing in battery management system charging circuits in electric vehicles ; Chapter 4. Design and evaluation of battery management systems for electric vehicle applications with Harris Hawk optimized algorithm (HHOA) based on fuzzy logic controller -- Section 2. Electric vehicles: modelling and control. Chapter 5. Electric vehicles and their types ; Chapter 6. Modelling and simulation of e-bikes driven by BLDC motors ; Chapter 7. Enhancement of suspension performance of the vehicle model using sliding mode controllers ; Chapter 8. Active suspension control of full car model using bat optimized PID controller -- Section 3. Analytics in electric vehicles. Chapter 9. Intelligent demand and supply of electrical vehicles ; Chapter 10. Data analytics in electric vehicles ; Chapter 11. Autonomous electric vehicles and edge computing -- Section 4. Latest trends in electric vehicles. Chapter12. Vehicle-to-grid and electric vehicle-integrated demand response management ; Chapter 13. Hybrid optimization based on genetic routing and scheduling scheme with secure transmission in wireless sensor networks ; Chapter 14. Thermal management system for batteries in electric vehicles.
520 $a "The Handbook of Research on Battery Management Systems and Routing Problems in Electric Vehicles focuses on the integration of renewable energy sources with the existing grid, introduces a power exchange scenario in the prevailing power market, considers the use of the electric vehicle market for creating cleaner and transformative energy, and optimizes the control variables with artificial intelligence techniques. Covering key topics such as artificial intelligence,smart grids, and sustainable development, this major reference work is ideal for government officials, industry professionals, policymakers, researchers, scholars, practitioners, academicians, instructors, and students"-- $c Provided by publisher.
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650 0 $a Battery management systems. $3 866110
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700 1 $a Angalaeswari, S., $d 1981-. $3 952588
700 1 $a Deepa, T., $d 1978-. $3 952589
700 1 $a Kumar, L. Ashok. $3 859749
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