Special Session Ⅰ- Dynamics and Control of Distributed-drive Electric Vehicles

Session Chairs:  Shaohua Li (Professor, Shijiazhuang Tiedao University)

                             Lipeng Zhang (Professor, Yanshan University)

                             Jing Zhao (Professor, Northeastern University)

Special Session Information:

Dynamics and Control play important roles in the development of distributed-drive electric vehicles (DDEVs). With the advent of featured emerging technologies, such as big data, cloud computation and artificial intelligence, the distributed-drive electric vehicle dynamics control are faced with more opportunities and challenges. Therefore, this special session will focus on but not limited to dynamics analysis and motion control of distributed-drive electric vehicles, such as maneuverability control, energy efficiency control, driver assistance control, trajectory planning and tracking control, connected electrified vehicle dynamics control, so as to promote the development of the distributed-drive electric vehicles. 

Below is an incomplete list of potential topics to be covered in the Special Session:

• Maneuverability control of DDEVs

• Energy efficiency control of DDEVs

• Driver assistance control of DDEVs

• Fault diagnosis and fault tolerant control of DDEVs

• V2X communication and networked control of DDEVs

• Connected and autonomous DDEVs in smart cities

Special Session Keywords:

Distributed driven electric vehicle, Dynamics control, Maneuverability control, Energy efficiency control, Driver assistance control

Special Session Ⅱ - Intelligent Vehicle Chassis Design and Control

Session Chairs:  Yunfei Zha (Professor, Fujian University of Technology)

                             Zhiyong Zhang (Associate Professor, Changsha University of Science and Technology)

Special Session Information:

This session focuses on the latest developments in intelligent vehicle chassis design and control. It explores innovative chassis architectures and the integration of AI technologies with traditional vehicle dynamics to enhance automotive safety, efficiency, and performance. Experts in automotive engineering, robotics, and AI will discuss challenges, breakthroughs, and future directions in intelligent chassis systems. Attendees will learn about advanced methods and tools used in developing autonomous and semi-autonomous vehicles, emphasizing practical applications and theoretical foundations.

Below is an incomplete list of potential topics to be covered in the Special Session:

• Integration of AI with vehicle dynamics - Detailed exploration of how AI technologies are being used to augment traditional vehicle dynamics for improved performance and safety.

• Innovations in chassis architecture - Examination of cutting-edge chassis designs and how these innovations contribute to the efficiency and functionality of modern vehicles.

• Challenges in intelligent chassis systems - A discussion on the technical and logistical challenges faced in the development and implementation of intelligent chassis systems, including scalability, cost, and integration issues.

• Future directions in vehicle control systems - Insights into the future trends in vehicle control technology, focusing on anticipated advancements and the role of AI in shaping next-generation vehicle systems.

• Case studies on automotive engineering and robotics - Presentation of real-world applications and success stories that highlight the collaborative efforts of automotive engineering and robotics in enhancing chassis design and control.

Special Session Keywords:

Autonomous driving; Vehicle dynamics; Distributed driving; Cooperative control; Skateboard chassis

Special Session Ⅲ - Monitoring of Electric Vehicle Batteries and Motors

Session Chairs:  Xianbo Wang (Associate Research Fellow, Hainan Institute of Zhejiang University)

                             Fazhan Tao (Associate Professor, Henan University of Science and Technology)

Special Session Information:

The power battery and traction motor are the core systems of electric vehicles, and their health status directly affects the safety of both the vehicles and passengers. The vehicle health management system is capable of real-time monitoring of essential information data such as voltage, current, temperature, speed, and magnetic field of each component. In extreme scenarios, these data allow users to promptly identify potential hazards, avoiding catastrophic accidents such as battery thermal runaways and motor short circuits. In daily use, these data also provide insight into the performance status of various components, enabling users to schedule necessary maintenance work, such as battery capacity degradation, increased internal resistance, local demagnetization of motors, bearing wear, etc. At the same time, based on the accumulated data, manufacturers can actively formulate reasonable and personalized charging-discharging strategies to improve the endurance and driving performance of electric vehicles. Therefore, the full utilization of the status monitoring data of power batteries and traction motors is of great significance for the further advancement of electric vehicles.

Below is an incomplete list of potential topics to be covered in the Special Session:

• Model-driven/data-driven state monitoring and anomaly detection

• Intelligent power battery operation and maintenance in the Internet of things (IoTs) scenarios

• Design and development of vehicle health management systems considering the global vehicle information

• Fault simulation/emulation and data augmentation with few or no samples available

• Interpretability analysis of deep learning diagnostic models considering fault mechanisms

• Prognostic and Health Management (PHM)-oriented signal processing methods

• Fault mechanism studies of power batteries and traction motors

• Intelligent control and optimization of connected vehicles

• Energy management strategy of hybrid electric vehicles 

Special Session Keywords:

State Monitoring; Model Estimation; Fault Detection; Testing Methods; Fault Diagnosis

Special Session Ⅳ - Research and Development of Non-pneumatic Tire

Session Chairs:  Xu Ting (Associate Researcher, Jihua Laboratory)

                             Zhou Haichao (Professor, Jiangsu University)

Special Session Information:

Non-pneumatic tire (NPT) are leak free and tire burst free, thus eliminating the need for tire pressure monitoring and tire burst control, providing a "redundant" design for intelligent driving, especially unmanned driving.

NPT without tire pressure maintenance can greatly reduce the cost of tire pressure maintenance for shared cars and new energy vehicles without spare tires.

NPT have better grip and wear resistance than pneumatic tires of the same model, adapting to the characteristics of high torque and high curb weight of new energy vehicles.

Non pneumatic tires have an open structure without tire pressure, which is easier to intelligentize and can assist in the field of intelligent autonomous driving.

In summary, NPT can assist in the electrification, intelligence, networking, and sharing development of the automotive industry. It has become the mainstream development direction of the tire industry and is known as the "third revolution" of the tire industry.

At present, leading tire companies such as Michelin have mass-produced NPT for passenger cars. However, the limitations of structure, materials, and molding processes in China have greatly limited the development of NPT, resulting in its current application being limited to low-speed vehicles. High performance NPT for high-speed or heavy-duty vehicles such as passenger cars and military vehicles are still in the conceptual stage of research and development. 

This meeting will focus on introducing the latest progress of NPT, breaking through the technical bottleneck of  NPT development, and promoting the industrialization of NPT.

Below is an incomplete list of potential topics to be covered in the Special Session:

• Performance oriented NPT structure design mechanism;

• Forward design optimization of NPT structure;

• Research and preparation of NPT polymers and their composite materials, such as fiberglass composites, rubber materials, polyurethane materials, adhesives, etc;

• Mold design and molding process during NPT molding process;

• Key technologies for NPT and vehicle matching;

• Intelligent tire and intelligent NPT technology.

Special Session Keywords:

Vehicle and tire dynamics; Structure design and optimization; Fiberglass composite materials; High temperature and fatigue resistant adhesive; Pouring and injection molding; Intelligent tire

Special Session Ⅴ - Intelligent Management for Advanced Power Battery

Session Chairs:  Zeyu Chen (Professor, Northeastern University)

                             Xiaohua Wu (Professor, Xihua University)

                             Yanan Wang (Associate Professor, Shandong University)

Special Session Information:

Lithium-ion batteries and fuel cells are widely used as the onboard energy storage in electric vehicles. The continuous improvement of battery/fuel cell design and management technology is pushing the power, economy, and driving range of electric vehicles to new heights and also sparks many novel and critical research topics. This special session aims to provide recent researches related to the advanced design and management for lithium-ion battery, fuel cell, etc., applied in electric vehicles. 

Below is an incomplete list of potential topics to be covered in the Special Session:

• Battery material and design;

• Battery modeling and state estimation;

• Fault diagnosis and safety management;

• Thermal management of lithium-ion battery and fuel cell;

• Remaining life prediction;

• Fuel cell water management;

• Energy management strategy.

Special Session Keywords:

Lithium-ion Battery; Fuel Cell; Battery Management; Thermal Management; Electric Vehicles; Energy Management

Special Session Ⅵ - Advancements in Electronic Control Suspension Systems

Session Chairs:  Panshuo Li (Professor, Guangdong University of Technology)

                             Donghong Ning (Professor, Ocean University of China)

                             Shuaishuai Sun (Professor, University of Science and Technology of China)

Special Session Information:

With the rapid advancement of electric vehicles, the significance of electronic control suspension (ECS) has become increasingly apparent. ECS is a critical component within the vehicle chassis, enhancing ride quality, handling stability, and overall driving performance. The use of ECS enables precise and fast adjustment of suspension settings in real-time, optimizing vehicle dynamics and comfort based on varying road conditions and driving preferences. Moreover, the development of ECS introduces novel advantages while mitigating the limitations of traditional suspension systems. Typically, ECS can be classified into semi-active, active, and hybrid types, showcasing its versatility and adaptability.

Furthermore, significant advancements of ECS have been seen through integration with cutting-edge vehicular technologies, such as road information preview control, intelligent chassis integration design, and reinforcement learning algorithms. These innovations highlight the transformative potential of ECS in shaping the future of electric mobility.

It is with great pleasure that we extend an invitation to researchers, scholars, and engineers to participate in our conference session dedicated to advanced ECS technologies. This session aims to provide a collaborative platform for the exchange of research experiences and the sharing of new ideas to propel progress in this field. We welcome submissions of research papers covering all aspects of ECSs and relevant technologies to be presented at the 2nd International Conference on Electric Vehicle and Vehicle Engineering.

Below is an incomplete list of potential topics to be covered in the Special Session:

• Comfort improvement methodologies in autonomous vehicle systems;

• Semi-active suspension systems;

• Active suspension systems;

• Advanced control method of active suspension design;

• Suspensions for vehicles with in-wheel motor.

Special Session Keywords:

Vehicle Suspensions, Comfort Improvement, Vehicle Dynamics control, Vibration Control

Special Session VII - Intelligent Decision-Making, Resilient Control and Trustworthy Testing for CAVs

Session Chairs:  Haigen Min (Associate Professor, Chang'an University)

                             Rongjie Yu (Professor, Tongji University)

                             Hailong Huang (Assistant Professor, Hong Kong Polytechnic University)

Special Session Information:

Intelligent decision-making systems leverage machine learning and artificial intelligence technologies to analyze vast amounts of traffic data and environmental information in real-time, enabling optimal decisions in complex and dynamic traffic scenarios. Resilient control, through advanced control algorithms, ensures that vehicles maintain stable and safe driving behavior under various environmental conditions and unexpected situations. To validate the reliability of these systems, a series of advanced testing tools and theories are employed to simulate diverse real-world driving scenarios, enabling comprehensive fault detection and diagnosis, rigorous and reasonable testing, and evaluation to ensure the safety and stability of autonomous driving systems in practical applications.

Below is an incomplete list of potential topics to be covered in the Special Session:

• Cooperative Control for CAVs and Applications;

• Real-Time Decision Algorithms in Dynamic Traffic Environments;

• Resilient Control System Design;

• Longitudinal or(and) Lateral Dynamic Control;

• Control System Optimization for Various Weather Conditions;

• Real-Time Fault Detection Systems;

• Machine Learning-Based Fault Prediction Models;

• Trustworthy Testing and Validation;

• Combined Virtual Simulation and Real-World Testing Strategies;

• Human-Machine Interaction and User Experience;

• Human-Machine Interface Design for Autonomous Systems;

• Research on Driver Trust in Autonomous Systems;

• Autonomous Driving Simulation Platform and Methods.

Special Session Keywords:

Decision-Making, Vehicle Control, Testing Tools & Theory, Fault Detection & Diagnosis

Special Session VIII - Advanced Thermal Management of Electric Vehicles

Session Chairs:  Jun Xu (Professor, Xi'an Jiaotong University)

                             Zhechen Guo (Research Associate, Xi'an Jiaotong University)

Special Session Information:

Thermal management system (TMS) exerts a significant influence on the performance, driving range, safety, and user experience of electric vehicles (EVs). For the battery system, the TMS ensures that the batteries operate within the optimal temperature range, thereby safeguarding the operational safety, enhancing operational efficiency, and extending service life. In terms of the drive motors and power electronic control systems, the TMS maintains these components at appropriate temperatures that aims to minimize heat loss and improve energy conversion efficiency. In addition, the TMS adjusts the cabin temperature to provide a comfortable environment for passengers under extreme weather conditions. As EV technology continues to evolve, TMS are increasingly trending towards integration and intelligence. Leveraging advanced sensors, algorithms, and control technologies, these systems achieve efficient and precise thermal management. This session will focus on the latest research progress in TMSs for electric vehicles, including optimization design, system integration, fault analysis, intelligent control et al, with the aim of promoting the practical application and development of advanced thermal management technologies.

Special Session Keywords:

Thermal management system; System integration; Optimal design; Intelligent control; Thermal comfort

Special Session Ⅸ - Advanced Perception, Localization, and Control for Intelligent and Connected Vehicles

Session Chairs:  Guangwei Wang (Associate Professor, Guizhou University)

                             Jin Zhao (Professor, Guizhou University)

Special Session Information:

This session aims to explore the cutting-edge advancements in perception, localization, and control systems driving the future of Intelligent and Connected Vehicles (ICVs). We explore both the cooperative aspects of ICVs, such as cooperative perception, localization, and control, as well as challenges faced by autonomous vehicles in general, including decision-making, path planning, and the integration of Vehicle-Road-Cloud systems. The session welcomes contributions from researchers and practitioners showcasing novel solutions, algorithms, and methodologies that enhance the safety, efficiency, and intelligence of ICVs and autonomous driving.

Below is an incomplete list of potential topics to be covered in the Special Session:

• Cooperative Perception;

• Cooperative Localization;

• Cooperative Decision Making;

• Cooperative Control;

• Learning-based Decision, Planning and Control;

• Safety-Critical Control and Risk Assessment;

• Intelligent Planning and Adaptive Control;

• Environmental Perception and Mapping;

• Testing and Validation Methods;

• Autonomous Driving Simulation;

• Intelligent and Connected Vehicles;

• Intelligent Transportation Systems.

Special Session Keywords:

Intelligent Connected Vehicles, Safety-Critical Systems, Vehicle-Road-Cloud Collaboration, Cooperative Localization, Cooperative Control

Important Dates：

Submission Deadline: 31 October 2024