Intelligent Control and Smart Energy Management

Predictive Energy Management for Fuel Cell Hybrid Electric Vehicles (Zhou).- Plug-in Hybrid Electric Buses with Different Battery Chemistries Total Cost of Ownership Planning and Optimization at Fleet Level based on Battery Aging (López-Ibarra).- Stochastic Optimization Methods for the Stochastic Storage Processes Control (Knopov).- Challenges for a Massive Integration of Flexible Resources in LV Networks (Arboleya).- Electrical railway power supply systems for high-speed lines: from traditional grids to smart grids (Castano-Solisr).- Energy-efficient scheduling of intra-terminal container transport (Homayouni).- Learning-based Control for Hybrid Battery Management Systems (Castro).- Robust, Resilient, and Energy Efficient Satellite Formation Control (Phillips).- A Methodology for the Assessment of Efficiency in Systems under Transient Conditions: Case Study for Hybrid Storage Systems in Elevators (García).- A holistic approach to the energy-efficient smoothing of traffic via autonomous vehicles (Hayat).- Optimal energy management of electric vehicles supplied by battery and supercapacitors: A multi-objective approach (Nguyen).- Transient Stability and Protection Evaluation of Distribution Systems with Distributed Energy Resources (Morais).- Fuzzy Logic Control for Motor Drive Performance Improvement in EV Applications (C. Ta).

Maude Blondin is an assistant professor at the Université de Sherbrooke in Canada. She graduated with a Ph.D. in Electrical Engineering from the Université du Québec à Trois-Rivières,  where she obtained the prestigious Vanier Canada Graduate Scholarship. Her doctoral research was on computational intelligence methods and soft computing techniques applied to control engineering. After her Ph.D., Dr. Blondin did postdoctoral research in the mechanical and aerospace engineering department at the University of Florida. She expanded her research interests to multiobjective optimization applied to multiagent control strategies. Her current research is driven by developing distributed multiobjective optimization algorithms based on exploring the Pareto Front, soft computing methods, and swarm intelligence for multiagent systems. These algorithms apply to many applications ranging from energy management to military uses. Dr. Blondin is a Associate Editor of SN Operations ResearchForum, has co-edited two contributed books, and served as a reviewers for many recognized journals. She has published over 20 journal and conference articles on control and optimization for engineering applications and is the author of the Springer monograph, Controller tuning Optimization Methods for multi-constraints and non-linear systems. 
João Pedro F. Trovão (SM'17) received the M.Sc. degree and the Ph.D. degree in Electrical Engineering from the University of Coimbra, Coimbra, Portugal, in 2004 and 2013, respectively. From 2000 to 2014, he was a Teaching Assistant and an Assistant Professor with the Polytechnic Institute of Coimbra - Coimbra Institute of Engineering (IPC-ISEC), Portugal. Since 2014, he has been a Professor with the Department of Electrical Engineering and Computer Engineering, University of Sherbrooke, Sherbrooke, QC, Canada, where he holds the Canadian Research Chair position in Efficient Electric Vehicles with Hybridized Energy Storage Systems. He