Advanced Control Strategies for Enhanced Performance and Efficiency in Electric Autonomous Vehicles
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 637
Special Issue Editor
Interests: path tracking of unmanned ground vehicles and mobile robots; model predictive control
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Enhancing the operating speed and control precision of autonomous vehicles is crucial for meeting the efficiency and safety demands of autonomous driving. Despite progress, existing autonomous driving strategies still face significant challenges in complex environments. Firstly, under high-speed conditions and urban settings, current control strategies suffer from inadequate real-time performance and a lack of effective high-speed vehicle stability management. Additionally, the accuracy of these strategies during actual operation requires further optimization. Secondly, in complex and constrained environments and during platoon driving conditions, the estimation of environmental and vehicle state parameters is also critical for the motion control of unmanned electric vehicles. On the other hand, as the application scenarios of electric vehicles expand, special configurations such as multi-axle electric vehicles and articulated electric vehicles are being introduced. Precisely and efficiently controlling these specially configured electric vehicles is equally of great practical significance. This Special Issue, titled "Advanced Control Strategies for Enhanced Performance and Efficiency in Electric Autonomous Vehicles", aims at exploring state-of-the-art control strategies for electric autonomous vehicles. It seeks to provide solutions that are not only highly precise and responsive but also efficient and safe, advancing the field of electric autonomous vehicle technology.
Therefore, topics of interest for this Special Issue include, but are not limited to, the following:
- Optimized control methods for electric vehicles considering real-time control performance.
- Vehicle stability control under extreme conditions.
- Enhancement methods for motion control considering uncertainties.
- Environmental and vehicle state parameter estimation for motion control.
- Data-Driven advanced vehicle motion control methods, such as reinforcement learning, deep learning, etc.
- Motion control methods for electric vehicles considering energy efficiency optimization.
- System integration and optimization of motion control for electric vehicles.
- Active fault-tolerant control to ensure vehicle safety.
- Motion planning and control of vehicles in spatially constrained environments.
- Optimized control methods for electric vehicles in complex and constrained environments.
- Modeling and motion control of electric vehicles with special configurations, such as multi-axle vehicles and articulated vehicles.
- Optimized motion control methods for electric vehicles considering actuator or communication delays.
- Cooperative control strategies for connected electric vehicles.
Generally, extreme conditions include, but are not limited to, high speeds, low adhesion coefficients, sharp curves, and emergency braking. Similarly, motion control encompasses, but is not limited to, path tracking control, trajectory tracking control, and handling stability control. Uncertainty includes uncertainties in vehicle dynamics states and environmental conditions.
Dr. Guoxing Bai
Guest Editor
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Keywords
- electric vehicles
- path tracking control
- vehicle dynamics
- real-time performance
- handling stability
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