http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Artificial intelligence applications in battery management systems and routing problems in electric vehicles
1 online resource ( xx, 342 pages) : illustrations {chiefly color).
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. Chapter 12. 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.
[edited by] S. Angalaeswari, T. Deepa, L. Ashok Kumar.
Includes bibliographical references and index.
Hershey, PA : Business Science Reference, [2023]
Advances in computer and electrical engineering (ACEE) book series