Frontloading hybrid vehicles controls development and calibration with multi-level simulation - 4 de junio de 2020 - TecnoWebinars.comWebinar • Siemens Industry Software: Digital Manufacturing • Industria y Fabricación
Frontloading hybrid vehicles controls development and calibration with multi-level simulationAgéndalo en tu calendario habitual ¡en tu horario!
Design the optimal control strategies to reach the expected performance levels balancing conflicting attributes
Jueves, 4 de junio de 2020, de 05.00 a 06.00 hs Horario de Ohio (US)
Webinar en inglés
Designing hybrid electric vehicles of tomorrow means predicting and balancing the performance of various attributes, such as fuel economy, power, comfort, and drivability. Getting insights early in the development cycle is valuable as multiple iterations of different hardware configurations and control strategies can be simulated and analyzed.
Developing the optimal supervisory controller overseeing the complete energy management strategy is complex, even more for hybrid architecture, and such a complexity increase can be tackled thanks to model-based optimization approaches.
In this webinar, experts will explain how to extend the system simulation-based methodology used in design phases to control development and calibration of hybrid powertrain systems. In addition, model-based development will allow to consider attributes balancing at earlier development sateg, which was not possible with test based calibration.
Dr. Jae Sung Bang from Hyundai Motor will precisely detail how they’re implementing model-based calibration for HEV control logic with high fidelity vehicle model, and how to deploy closed loop simulation model of transmission mounted electric device HEV which contains main controllers such as HCU, EMS, TCU, MCU, etc.
You will learn:
- How to use system simulation and multi-level models to design and validate complex control strategies for hybrid vehicles
- How to deploy the right models with the right level of fidelity to answer to hybrid controls requirements and optimal attributes balancing
- How to extend classical powertrain virtual control development at upper level to tackle hybrid vehicle increased complexity.
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