Registration Link: https://in.mathworks.com/company/events/webinars/upcoming/electrical-system-design-exploration-for-electric-vehicles-3789626.html?s_tid=srchtitle
Overview
In this webinar, MathWorks will demonstrate a workflow that provides system-level electrical loading information to inform an electrical system design task. The electrical system in this case will be a parallel-connected fuel-cell stack and battery energy storage system. The aim of the electrical design is to develop the most efficient power supply to meet the needs of a given drive cycle. The electrical design is then evaluated in a full-system level model.
Highlights
Obtain motor loading information from a full vehicle simulation.
Expand model fidelity as appropriate in the electrical design task to support efficient design space exploration.
Incorporate optimization algorithms to provide efficient response between different generation units.
Evaluate the electrical system design in a full vehicle simulation.
Please allow approximately 45 minutes to attend the presentation and Q&A session. We will be recording this webinar, so if you can't make it for the live broadcast, register and we will send you a link to watch it on-demand.
About the Presenters
Graham Dudgeon, Principal Product Manager – Electrical Technology
Graham Dudgeon is principal product manager for electrical technology at MathWorks. Over the last two decades Graham has supported several industries in the electrical technology area, including aerospace, marine, automotive, industrial automation, medical devices, and power and utilities, with an emphasis on system modeling and simulation, control design, real-time simulation, machine learning, and data analytics. Prior to joining MathWorks, Graham was Senior Research Fellow at the Rolls-Royce University Technology Centre in Electrical Power Systems at the University of Strathclyde in Scotland, UK.
Jason Rodgers, Senior Application Engineer
Jason Rodgers is a senior application engineer at MathWorks. Prior to MathWorks, he spent five and a half years at Toyota R&D in the Model-Based Design group. He specialized in powertrain modeling and using model-based control, along with various optimization techniques to develop new powertrain systems. Jason earned a B.S.M.E. and an M.S.C. from the University of Michigan.