T1: Connected and Autonomous Electric Vehicle: From Modelling to Energy Efficiency Optimization
Co-organizer: Sousso Kelouwani, Université du Québec à Trois-Rivières (UQTR), Canada
Co-organizer: Marie Hébert, Université du Québec à Trois-Rivières (UQTR), Canada
Abstract: Powertrain electrification is one of the promising ways to reduce greenhouse emissions from fossil fuels. Also, the development of autonomous driving systems for vehicles is gaining a lot of interest in the scientific community. The convergence of electric powertrain and autonomous driving will open new opportunities to improve significantly the energy efficiency of the vehicle (battery vehicle) whilst decreasing road accidents. However, these two topics (powertrain electrification and autonomous driving) are still discussed separately. To accelerate their convergence, a unified modelling and system optimization need to be carried out.
Nowadays and without autonomous driving, some significant progress has been done in order to optimize the use of onboard electric energy for short trips (i.e. commuting trips). However, the global energy efficiency and the battery lifespan preservation need more investigations over a long trip (i.e. the trip length exceeds the available vehicle autonomy). Indeed, the overall trip duration is extended with the battery charging time, and obviously, letting the battery to be depleted heavily (high values of depth-of-discharge) before stopping for charging can help to reduce this trip duration. But the battery lifespan is negatively affected by these depth-of-discharges. Stopping often in order to charge the battery and prevent a high depth-of-discharge will potentially increase the overall trip duration. Therefore, a trade-off must be found between preserving the battery lifespan and keeping reasonable the trip duration whilst improving globally the efficiency.
This technical tutorial will start by introducing some well-known models for autonomous driving and an electric vehicle (battery vehicle). Then, using the convex optimization framework, we will discuss a method to use autonomous driving capability to increase energy efficiency, for urban and highway driving conditions (with and without traffic).
Holder of the Canada Research Chair in Energy Optimization of Intelligent Transport Systems and Holder of the Noovelia Research Chair in Intelligent Navigation of Autonomous Industrial Vehicles, Sousso Kelouwani received his Ph.D. in robotics systems from Ecole Polytechnique de Montreal in 2011 and completed a postdoctoral internship on fuel cell hybrid electric vehicles at the Université du Québec à Trois-Rivières (UQTR) in 2012. He developed expertise in the optimization and the intelligent control of vehicular applications. In 2019, his team received the 1st Innovation Prize in partnership with DIVEL, awarded by the Association des Manufacturiers de la Mauricie et Center-du-Québec for the development of an autonomous and natural navigation system. In 2017, he received the Environment Prize at the Gala des Grands Prix d’excellence en transport from the Association québécoise du Transport (AQTr) for the development of hydrogen range extenders for electric vehicles.
Full Professor of Mechatronics in the Department of Mechanical Engineering since 2017 and a member of the Hydrogen Research Institute, he holds 4 patents in the United States and Canada, in addition to having published more than 100 scientific articles. Prof. Kelouwani was co-president of the technical committees of the IEEE International Conferences on Vehicular Power and Propulsion in Chicago (USA, 2018) and in Hanoi (Vietnam, 2019). His research interests focus on optimizing energy systems for vehicle applications, advanced driver assistance techniques, and intelligent vehicle navigation taking into account winter climatic conditions. Winner of the Canada General Governor Gold Medal in 2003, he is a member of the Order of Engineers of Quebec.
Assistant professor at the Université du Québec at Trois-Rivières (UQTR) in the Department of mechanical engineering, Marie Hébert received her Ph.D. in Mechanical and Mechatronics engineering from the University of Waterloo in 2020. She developed her expertise in mechatronics and fluid dynamics. As a member of the Hydrogen Research Institute, she is actively involved in projects for the electrification of various vehicles with fuel cell systems. Her research interests include multiphysics systems, modelling, fuel cell systems, fluid dynamics, control, optimization of fluid supply, and microfluidics. She was awarded the Mechanical engineering medal in 2016 from Concordia University. She has also been the recipient of several scholarships such as the Nanofellowship from the Waterloo Institute for Nanotechnology, and the Canada Graduate Scholarships – Doctoral (CGS D) from the Natural Sciences and Engineering Research Council of Canada (NSERC).