Energy Efficiency of Connected and Autonomous Electric Vehicles, by Sousso Kelouwani
Bio: Sousso Kelouwani received the B.S. and M.Sc.A. degrees in electrical engineering from the Université du Québec à Trois-Rivières (UQTR), Trois-Rivières, QC, Canada, in 2000 and 2002, respectively, and the Ph.D. degree in electrical engineering (automation and systems) from the École Polytechnique de Montréal, Montreal, QC, in 2010. He was a Software Engineer with Cylis 53 Inc. (Trois-Rivières, QC), from 2002 to 2005, and Openwave Inc. (Redwood City, CA, USA) from 2005 to 2006. He was a Scientist with the Hydrogen Research Institute, (UQTR, QC), from 2010 to 2012, where he is currently a Professor in the Department of Mechanical Engineering. His current research interests include fuel cell control and optimization, energy management for hybrid electric vehicle, mobile robotics and intelligent navigation system. He co-authored more than 45 peer-review journal and conference papers and holds three patents. He wins the best paper award at the IEEE International Conference on Industrial Technology 2017 (Toronto, Canada). Moreover, two of its intelligent range extenders based on low carbon footprint technologies won Quebec Association of Transportation Award of Excellence in Transportation Technology in 2017. Prof. Kelouwani was a recipient of the Governor General of Canada Gold Medal Award (2002) and is a Professional Engineer and a Member of the Ordre des Ingénieurs du Québec, Montreal since 2006.
Abstract: Powertrain electrification is one of the promising ways to reduce greenhouse emissions from fossil fuel. For a passenger car, the onboard energy storage for a purely electric drive is limited due to the capacity of batteries. 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). Furthermore, the overall trip duration is extended with the battery charging time and obviously, letting the battery to be depleted heavily before stopping for charging can help to reduce this trip duration. However, the battery lifespan is negatively affected by these high depth-of-discharges. On the other hand, 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. In this technical tutorial, a review of some of the well-known vehicle parameter identification methods will be presented prior to the formulation of the convex optimization problem that can produce a feasible charging schedule for an electric vehicle.
Energy Management for Hybrid Electric Vehicles and Plug-in Hybrid Electric Vehicles, by Zheng Chen
Bio: Zheng Chen, a senior member of IEEE, received the B.S. and M.S. in electrical engineering and the Ph.D. in control science engineering from Northwestern Polytechnical University, Xi’an, China, in 2004, 2007, and 2012, respectively. He is currently a Professor of Faculty of Transportation Engineering at Kunming University of Science and Technology, Kunming, Yunnan, China. He was a Postdoctoral Fellow and a Research Scholar with the University of Michigan, Dearborn, USA from 2008 to 2014. His research interests include battery management system, battery status estimation, and energy management of hybrid electric vehicles. He has conducted more than 20 projects, and has published more than 50 peer-reviewed journal papers and conference proceedings. He is the receiver of Yunnan Oversea High Talent Project, China and the second prize of IEEE VTS challenge 2017.
Abstract: Currently, hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs) with advantages of low emission and low fuel consumption, have attracted wide attention of government and corporation. The complex powertrain structure of HEVs/PHEVs exhibits more degrees to achieve the power split thereby improving fuel economy. It is imperative to conduct research into the energy management strategies with the target of optimizing the fuel economy and lowering the emission. The tutorial aims to provide the developed viewpoints of energy management in terms of HEVs/PHEVs, for the sake of introducing the current study progress and the future directions. The overall contexts mainly include: 1) an overview as well as the key difficulties for the energy management; 2) the state-of-the-art energy management strategies; and 3) the future exploratory directions.
Hardware-in-the-Loop (HIL) Simulation of EVs and HEVs, by Alain Bouscayrol
Bio: Alain BOUSCAYROL received Ph.D. degree in Electrical Engineering from Institut National Polytechnique de Toulouse, France, in 1995. From 1996 to 2005, he was Associate Professor at University Lille1, Sciences and Technologies, France, where he has been a Professor since 2005. From 1998 to 2004, he managed the Multi-machine Multi-converter Systems project of GdR-ME2MS, a national research program of CNRS (French National Centre of Scientific Research). Since 2004, he has managed the national network on Energy Management of Hybrid Electric Vehicles (MEGEVH). His research interests at the L2EP (Laboratory of Electrical Engineering) include graphical descriptions (Energetic Macroscopic Representation) for control of electric drives, wind energy conversion systems, railway traction systems, hybrid electric vehicles and hardware-in-the-loop simulation. His collaborative works with industry on energy management for vehicles include Siemens Mobility, PSA Peugeot Citroen, Nexter Systems and SNCF. He was General Chair of IEEE VPPC 2010 (Vehicle Power Propulsion Conference, Lille. 2010), and co-chair of EPE 2013 ECCE Europe (European Power Electronics and drives, Lille, 2013). In January 2014, he has been nominated Chair of the Vehicle Power Propulsion technical committee by IEEE Vehicular Technology Society (VTS). Since February 2014, he has been appointed Associate Editor of IEEE transactions on Vehicular Technology. Since 2016, has been elected Distinguished Lecturer by IEEE VTS.
Abstract: Electrical drives are increasingly used in automotive industry. Rigorous performance evaluation has to be made during equipment development and before implementation on actual systems. In particular, interactions of the drive with the motion part have to be studied thoroughly. Computer simulation of the entire system is an established means to investigate interactions between subsystems to set the technical requirements. Within the past decade, Hardware-In-the-Loop (HIL) simulations became an advanced means for investigative experimentation, model validation and testing before implementation of drives in actual processes. In addition to pure computer simulation, HIL simulation replaces some simulation models of a system by one or several actual components. The rest of the system and processes are simulated in real-time, which typically requires a parallel computing environment with adequate input-output capability for signals of adequate bandwidth. Most recently, incorporating power hardware (i.e. the drive) into an HIL simulation has been introduced by means of high power and high bandwidth power electronic amplification equipment. Due to the flexibility of HIL simulations to test a wide range of operating conditions and scenarios this method will contribute to improving the availability and reliability of drives (machines, power electronics, and/or control) and a better understanding of system interactions before their insertion on the system. HIL simulation has been intensively used for controller assessment for a long time. The aerospace industry has used this technique since flight control systems is a safety-critical aspect. This methodology yields exhaustive testing of a control system to prevent costly and damageable failures. Moreover, HIL simulations reduce development time and can enable more tests than on the actual system. From 90’s, many groups in automotive industry have employed HIL simulation for testing embedded Electronic Control Units (ECU). Indeed, this methodology avoids intense and complex integration tests on the actual vehicle. Thus, the time development can be reduced and a high quality assurance can be obtained. HIL simulation is becoming a standard for ECU development in the automotive industry. HIL simulation is nowadays more and more used to develop new components and actuators in many fields. Vehicle component evaluation, assessment of drive controls, railway traction systems for trains and subways, power propulsion systems for electric vehicles (EVs) and hybrid electric vehicle (HEVs).
How to model and manage advanced lithium-ion battery systems, by David A. Howey and Jorge V. Barreras
Bio (D. Howey): David A. Howey is an Associate Professor in Engineering Science at the University of Oxford, UK, with interests in model-based battery management, diagnostics and prognostics, system integration and thermal issues. He has over 55 peer-reviewed journal and conference papers and 3 patents filed, with more than 1220 citations and an h-index of 16 (Google Scholar). He is an IEEE Senior Member and an editor of the IEEE Transactions on Sustainable Energy, and was Guest Editor-in-Chief for the recently published (2016) Special Section on “Integration of Electrochemical Energy Storage in Sustainable Energy Systems”. In the past 5 years, he has grown a research group of 10 researchers in an area that previously did not exist at Oxford, and has been Principal Investigator and Co-Investigator on projects totalling >£3.4m direct to Oxford, from within a portfolio of more than £30m of collaborative projects. He has also given recent invited seminars at EPFL Lausanne (2016), the IMechE (2016), Culham Centre for Fusion Energy (2016), TU/Eindhoven (2015), University of Cambridge (2015), Politecnico di Milano (2015), the Open University (2015), the UK Energy Storage conference (2015), and the University of Warwick (2015). He was an Honorary Research Fellow at Imperial College London (2011-2014) and invited session chair at the 12th and 13th Symposia on Fuel Cell and Battery Modeling and Experimental Validation (ModVal) held respectively in Germany and Switzerland. He is an invited member of the Science Board of the EPSRC Energy Storage Supergen Hub (energysuperstore.org) and an invited member of the UK Energy Storage (UKES) conference 2016 Science Board. Website: http://epg.eng.ox.ac.uk/howey.
Bio (J. Barreras): Jorge V. Barreras is a Postdoc in Engineering Science at the University of Oxford, UK, with interests in novel electric vehicle concepts and li-ion battery modeling, simulation, emulation, diagnostics, prognostics and management. He pursued his PhD in Battery Management at Aalborg University, Denmark, where he also received the M. Sc. Degree in power electronics. Previously, he received the M. Sc. Degree in electrical engineering from University of Vigo, Spain, where he co-founded a photovoltaic consulting company. He is a founder member of the Danish Battery Society and representative on the Oxford Research Staff Society. He serves on the editorial board of Frontiers in Energy Research. He has been a guest lecturer at University Carlos III (2016), Aalborg University (2014-16), Faculty of Engineering of University of Porto (2015), University of Sfax (2016), Jaguar Land Rover Catapult Energy Storage Conference (2016) and the Danish Technological Institute (2016).
Abstract: Lithium-ion cells are the standard choice for e-mobility and consumer electronics, and costs continue to decrease rapidly. However, a reliable battery management system (BMS) is required to mitigate safety risks such as overheating or overcharging, as well as to track state of charge and other metrics. Battery models play an essential role in the design of battery packs and management systems, but a confusingly wide range of approaches is possible. This tutorial will equip attendees with a clear path through the possibilities. The first part (battery modelling) will cover how a lithium-ion cell works, how to model open circuit voltage, electrochemical models, equivalent circuit models, pack modelling, degradation and temperature effects. The second part of the tutorial (battery management) includes an overview of BMS functions, sensing requirements, diagnostics and prognostics approaches, balancing systems, and hardware in the loop simulators.
Guidelines for tutorials
VPPC2017 will include a number of tutorials on scientific and technological knowledge in the area of friendly transport systems (fuel cells, batteries, power electronics, electrical machines, drivetrains of road vehicles, embedded storage systems …). If you are interested in contributing to the conference through a tutorial, you are invited to propose within these topics, a half (1,5 hours) or a full (3 hours) tutorial to be presented during the conference.
Proposals should include:
- a title,
- the name of instructor(s),
- a 500 word (max) abstract,
- a detailed list of topics and instructor’s short CV.
Proposals should be sent to firstname.lastname@example.org before June 30, 2017.