Enhancing Vehicle Dynamics and Energy Efficiency in Electric Vehicles with Multiple Motors Via Torque Vectoring đŸ—“

— energy efficiency, stability control, torque allocation, net traction force, cornering response, experimental results …

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Webinar Date: Thursday, April 12, 2018
Time: 8:00 AM (PT)
Speaker: Basilio Lenzo, Sheffield Hallam University, UK
Sponsor: IEEE Transportation Electrification Community
Location: on the Web
Cost: none
RSVP: required
Event Details & Registration: tec.ieee.org/
Summary: Electric vehicles with multiple motors allow torque-vectoring (TV), i.e. the individual control of each drivetrain. TV has been largely studied in the literature since it can provide significant benefits in terms of vehicle safety and drivability. This webinar analyses recent experimental results of the EU FP7 Projects EVECTOORC and iCOMPOSE, in which torque vectoring is exploited for: i) enhancing vehicle dynamics; ii) maximising energy efficiency.
TV can enhance the handling qualities of a vehicle well beyond the capabilities achievable with conventional stability control systems, as it intervenes seamlessly and continuously without variation of the net traction force. A direct yaw moment can be generated through different torque allocation at the left and right sides of the vehicle, allowing the design of the cornering response of the vehicle. For instance, a “Sport” driving mode was designed to reduce the understeer gradient, extend the region of linear vehicle operation, and increase the maximum lateral acceleration compared to the passive vehicle.
As regards energy efficiency improvement, a simple and effective torque distribution strategy was developed. Basically, the torque demand on each vehicle side is compared to a “switching torque” value (function of the vehicle speed) which is defined based on the experimental measurements of the drivetrain power loss characteristic. The developed energy efficient torque distribution algorithm allows energy savings typically between 2% and 3% along common driving cycles, and up to ~4% during cornering conditions with respect to fixed torque distribution strategies.

Bio: Basilio Lenzo received the M.Sc. degree in mechanical engineering from the University of Pisa and Sant’Anna University in 2010. He received his Ph.D. degree in robotics from Sant’Anna University in 2013.
In 2010, he was an R&D Intern with Ferrari F1. In 2013, he was a Visiting Researcher at the University of Delaware and Columbia University. In 2013, he was appointed as a Research Fellow with Sant’Anna University, focusing on kinematics and dynamics of robotic mechanisms. He obtained the “Marzotto” grant providing 250,000 Euro for a robotics startup developed at PercRo (Perceptual Robotics Laboratory, Sant’Anna University). In 2014 he won the Bernardo Nobile award for the best PhD thesis resulting in a patent application.
In 2015-2016, he was a Research Fellow with the Centre for Automotive Engineering, University of Surrey, UK. His research was focused on vehicle dynamics and control (European Project iCOMPOSE), dealing with: development of vehicle simulation models and state-of-the-art controllers for vehicle dynamics and energy management; experimental assessments of the performance of such controllers on rolling road facilities and proving grounds. In 2015, he obtained the MIT Young Innovators Under 35 Italy award. He was also invited to give a TED talk at TEDxBergamo2015.
Since September 2016, he has been a Senior Lecturer in Automotive Engineering with Sheffield Hallam University, UK. His teaching/research interests include vehicle dynamics, control, and robotics.