Electrified Powertrain Modeling with Powertrain Blockset and Simscape
To support the growing need for virtual vehicle simulation, MathWorks has released new products such as Powertrain Blockset, tailored to the needs of automotive engineers. This product provides a platform for automotive systems analyses throughout the engineering V-cycle – from system design through integration and HIL testing. Physical modeling tools like Simscape can complement these system level models by providing additional detail for the subsystem of interest.
In this session, we will provide an overview of Powertrain Blockset and demonstrate its use via an Electric Vehicle reference application that includes Simscape for the electrical and thermal subsystems. Additional examples will be shown to illustrate a variety of use cases, including:
- EV and HEV powertrain modeling
- Thermal circuit modeling
- Supervisory controls development
- Battery Management Systems (BMS)
- Electrified powertrain architecture selection
Date and Time
Location
Hosts
Registration
- Date: 10 Dec 2021
- Time: 03:00 PM to 04:00 PM
- All times are (GMT-05:00) America/Toronto
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- Starts 25 November 2021 09:00 AM
- Ends 10 December 2021 04:00 PM
- All times are (GMT-05:00) America/Toronto
- No Admission Charge
Speakers
Mike Sasena
Mike Sasena is a product manager, focusing on the automotive products developed at the MathWorks office in Novi, Michigan. Prior to joining MathWorks, Mike spent 14 years working on model-based system engineering projects for the automotive industry. His experience includes hybrid electric vehicle modeling for fuel economy analysis, Model Predictive Controls development and heterogeneous system simulation. Mike received his PhD in Mechanical Engineering from the University of Michigan in 2002.
Biography:
Mike Sasena is a product manager, focusing on the automotive products developed at the MathWorks office in Novi, Michigan. Prior to joining MathWorks, Mike spent 14 years working on model-based system engineering projects for the automotive industry. His experience includes hybrid electric vehicle modeling for fuel economy analysis, Model Predictive Controls development and heterogeneous system simulation. Mike received his PhD in Mechanical Engineering from the University of Michigan in 2002.