Electric vehicle powertrain design with battery swapping and vehicle to grid implementation.

Described in this work are methodologies for the design and development of electric vehicle (EV) powertrains through modeling, simulation and validation on a real-world systems, with detailed analysis of results. A system for swapping, storing and managing EV batteries, including a Deep Neural Network (DNN) based state of health estimation model is developed and analyzed. The system is designed to enable advanced interface with the electric grid and address challenges in the adoption of EVs which include : Cost, range anxiety, charging time and charging infrastructure, battery state of health, and impacts of vehicle to grid (V2G) operations. The EV battery swapping system (BSS) consists of the EV powertrain equipped with swapping capability, modular swappable battery packs, battery storage apparatus, bidirectional charging system, battery and charge management system, and battery swapping equipment. This system provides a cost-effective way of adopting electrification, reducing strain on the electricity grid during peak periods and extending the life of EV batteries.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Doctoral

Grantor

Baylor University.

Year dc:date.issued

2021

Author dc:creator

• Adegbohun, Feyijimi R., 1995-

Advisors dc:contributor.advisor

• von Jouanne, Annette.
• Lee, Kwang Y.

• Electric vehicle.
• Chassis dynamometer.
• Drive cycle.
• On-board diagnostics.
• Battery swapping.

Statement dc:rights

• Baylor University works are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact libraryquestions@baylor.edu for inquiries about permission.

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/2104/11416

OAI identifier oai:identifier

oai:baylor-ir.tdl.org:2104/11416