In the automotive industry, digital twin technology serves as a bridge between the physical and virtual versions of vehicle prototypes and actual vehicles on the road. The digital twin in automotive industries has not only changed the dynamics of ordinary vehicles, but it has also provided a new perspective on electric vehicles. Digital twin solutions have allowed for the most methodical and cost-effective design and development of futuristic electric vehicles. Because of the long-term success of digital twin technology in the automotive industry, most of the world's leading Electric vehicle manufactures started adopting Artificial intelligence (AI) based digital twin. As a result, there is no doubt that the role of digital twin technology in the automotive industry has proven to be a game-changer. Stricter environmental regulations, as well as the rise of self-driving cars and shared mobility, are driving the demand for powertrain electrification. This has a significant impact on vehicle engineering processes and methods. The pressure to innovate and produce mass-market vehicles forces the entire transportation industry to adapt and deliver solutions that provide desired attributes - such as driving range, performance, life, and in-vehicle experience - at a low cost. Adopting a AI based real-time "digital twin" framework as a bridge between virtual and physical is critical to staying competitive and avoiding late technology defects or unexpected performance. Frontloading design and optimization with simulations from the early stages of prototype development until physical testing for advanced validation reduces the cost of costly design changes later in the product development process.

The aim of the book is to provide the digital engineering and IoT solutions, for developing high-potential digital twin solutions for electric vehicles. These solutions improve the productivity of the EV lifecycle by allowing for better analysis of difficult situations, scenario prediction, and cost reduction through system verification.
List of tentative topics
1 Introduction to digital twin for Electric Vehicles
2 Framework of digital twin technology
3 AI based digital twin for prognosis of Electric vehicle motor
4 Digital twin for automotive braking system
5 Digital twin driven prognostic and health management of Electric vehicles
6 Digital twin for drive train topologies for electric vehicles
7 Digital twin for vehicle power electronic converters
8 AI based Battery management system
9 Digital twin paradigm: vehicle to grid
10 Digital twin development and cloud deployment for electric vehicle
11 Digital twin for Internet of vehicles
12 Resilient future energy system: vehicle to grid
13 Digital twin for autonomous electric vehicle
14 Intelligent wireless charging and scheduling
15 Future for digital twin technology in smart electric vehicles

Submit your abstract in https://easychair.org/conferences/?conf=aidtev2022


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