Automated and Electric Vehicle: Design, Informatics and Sustainability

Yue Cao received his PhD degree from the Institute for Communication Systems (ICS) formerly known as Center for Communication Systems Research, at University of Surrey, Guildford, UK, in 2013. Further to his PhD study, he had conducted research fellow at University of Surrey, and academic faculty at Northumbria University, Lancaster University, UK, and Beihang University, China; and he is currently the Professor at School of Cyber-Science and Engineering, Wuhan University, China. He has participated in 2 UK EPSRC and 4 EU projects, been active in international engagement and leading several international exchange projects with New Zealand, Japan, Thailand, France, etc. Over the last few years, he has hopped from ICT into a multidisciplinary research field under the umbrella of intelligent transport systems, which includes “transport and energy,” “network communication and computation,” “Cyber-security and localization.” He has published over 20 IEEE journals as the first author through his research pathway, led several special issues on IEEE IoT Journal, IET ITS, etc., and been serving as Associate Editor of IEEE Access, Springer EURASIP Journal on Wireless Communications and Networking, KSII Transactions on Internet and Information Systems, etc. Dr Yuanjian Zhang is a Lecturer in the Department of Aeronautical and Automotive Engineering at Loughborough University.  He was awarded his PhD in Automotive Engineering from the Jilin University, China in 2018, and joined the research staff in the Centre for Automotive Engineering at University of Surrey in 2018. He moved to Sir William Wright Technology Centre at Queen’s University Belfast in early 2019. On December 2021, he started his work at Loughborough University as a Lecturer (Assistant Professor) in Intelligent Electric Vehicles. His research interests focus on new generation clean propulsion control and optimisation, digital modelling and simulation, intelligent transportation system and artificial intelligence (AI) in engineering practice. Chenghong Gu is Reader in smart energy systems with the University of Bath, where he was EPSRC Postdoctoral Fellow. His research designs novel models and tools for planning and operating smart energy systems, including electricity, natural gas, heating/cooling, and transportation toward net zero. Dr Gu attracted £1.3 million funding in total, out of which more than 615k as PI from EPSRC, British Council, National Grid, Northern Powergrid, and Shanghai Electric. He was a key researcher for two LCNF projects with WPD—LV Templates and Sola Bristol. Dr Gu has more than 90 peer-reviewed journal papers and won three paper prizes: CEPRI Prize, 2018; “Outstanding PhD Paper Prize” at the 7th EEM, 2010; and Outstanding CSEE Yearly Paper, Proceedings of the CSEE, 2009. He was a committee member of Ofgem’s Safety, Resilience, and Reliability working group and now serves as a member of IEEE Committee for power economics and market and IEEE Working Group on network charging. He co-chairs Supergen Energy Networks Hub—Markets and Regulation Working Group. Dr Gu is Subject Editor for IET Smart Grid. 

Chapter 1. Energy and Thermal Comfort Integrated Control of Vehicles.- Chapter 2. Battery Management System of Electric Vehicle.- Chapter 3. Vehicle speed prediction in multi-dimensional domain.- Chapter 4. Eco-driving Behavior of Automated Vehicle .- Chapter 5. Service Planning and Operation for Autonomous Valet Parking .- Chapter 6. Mining Passenger Regional Mobility in Ile-de-France using Multiple Data Sources.- Chapter 7. Grid Optimal Integration of Electric Vehicles: Vehicle-to-grid scheduling strategy.- Chapter 8. Artificial Intelligence for optimization  bi-directional V2G behaviors.- Chapter 9. Local energy trading with EV flexibility.- Chapter 10. Communication and Networking in Internet of Vehicles.- Chapter 11. The Overview of Non-orthogonal Multiple Access in Vehicle-to-Vehicle Communication.- Chapter 12. Trust Management for Internet of Vehicles.- Chapter 13. Instruction Detection of In-Vehicle Networks .- Chapter 14. Security and Privacy-Preserving for Automated Electric Vehicle.