Control Design for Electric Vehicles
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".
Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 15738
Special Issue Editor
Interests: linear and nonlinear systems; robust and optimal control; integrated control; sensor fusion; system identification and identification for control; machine learning; mechanical systems; vehicle dynamics and vehicle control
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
The recent research and development directions focus on exciting topics in the field of electrical and autonomous vehicles. This research enables to improve safety, energy efficiency, comfort and transport economy. The research tasks can be classified into several groups such as vehicle modeling, performance requirements, control of chassis elements and powertrain, and, moreover, route planning and trajectory design. The utilization of sensor fusion, actuator integration, V2X communication and cloud computing may also extend to both microscopic and macroscopic approaches in the field of traffic control.
The tools and methods for such developments range from classic and modern control theory, game-theoretical approaches, nonlinear programming, artificial intelligence, and machine learning. The new advantages of supervised and reinforcement learning also show high potential for individual and multi-agent control of electrical and autonomous vehicles.
In addition, road vehicles other components of transport systems are also included such as rail vehicles and ships, where simultaneous energy efficient and safe operation can be handled with similar tools and approaches.
As the machine learning based approaches of self-driving vehicles require high computational resources and a large amount of data for testing and validation, the development of different frameworks, such as hardware-in-the-loop, simulations, virtual- and augmented reality should also be encouraged.
Potential topics include, but are not limited to, the following:
- Self-driving vehicles, autonomous functions
- Automatic train operation
- V2X communications, sensor fusion
- Actuator and control integrations
- Energy-efficient control
- Machine learning, reinforcement learning
- Robust control, model predictive control
- Testing and validation
- Simulations, virtual- and augmented reality
- Development frameworks, prototype constructions
Prof. Dr. Peter Gaspar
Guest Editor
Manuscript Submission Information
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Keywords
- autonomous functions
- robust and predictive control
- machine learning
- reinforcement learning
- validation
- prototype systems
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