AI techniques for renewable source integration and battery charging methods in electric vehicle applications /
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| Other Authors: | , , |
| Format: | eBook |
| Language: | English |
| Published: |
Hershey, PA :
IGI Global, Engineering Science Reference,
[2023]
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| Series: | Advances in civil and industrial engineering (ACIE) book series.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Section 1. Electric vehicle batteries. Chapter 1. Peak load reduction via electric car batteries: V2G potential in winter conditions in Kirsehir City in 2030 ; Chapter 2. Swappable battery data management system ; Chapter 3. A deep learning approach for predicting the remaining useful lifetime of lithium-ion batteries using 1-D convolutional neural networks
- Section 2. Electric vehicle charging. Chapter 4. Wireless power transfer for high end and low end EV cars ; Chapter 5. RE-based multilevel inverter for EV charging ; Chapter 6. Autonomous vehicles using opencv and python with wireless charging ; Chapter 7. Software communication interface for OCPP-based DC fast charging stations
- Section 3. Renewable energy: monitoring and storage. Chapter 8. Renewable energy resources and their types ; Chapter 9. A deep learning-based solar photovoltaic emulator ; Chapter 10. IoT-based smart solar energy monitoring system ; Chapter 11. Hybrid energy storage systems for renewable energy integration and application
- Section 4. Recent advancements. Chapter 12. Artificial intelligence-based approaches in vehicular power energy application ; Chapter 13. Environmental economic load dispatch considering demand response using a new heuristic optimization algorithm ; Chapter 14. Implementation of AI techniques for tuning of controller parameters in a nonlinear system.