Hofer Powertrain: Hybrid electric vehicles architecture and energy management
“By providing a reliable, ready-to-use control strategy, Simcenter Amesim Hybrid Optimization Tool reduces the development timeline, enabling researchers to focus on design exploration and optimization.”
Hybrid powertrain performance is governed as much by control strategy as by hardware selection.
For modern dual-parallel and Dedicated Hybrid Transmission architectures, identifying the optimal energy management strategy across multiple operating scenarios presents a significant engineering and computational challenge. Traditional manual tuning approaches struggle to balance fuel efficiency, performance and battery state-of-charge robustness at system level.
This case demonstrates how HEEDS was used as the optimisation backbone for hybrid energy management development within a simulation-driven engineering workflow.
The Optimisation Solution
By embedding HEEDS at the centre of the workflow, the team established a scalable and repeatable optimisation framework capable of:
- Exploring competing objectives such as fuel efficiency, performance and battery behaviour
- Identifying non-intuitive design trade-offs that would be missed through manual tuning
- Supporting rapid iteration across architecture variants and operating scenarios
The approach moved energy management from a late-stage calibration task to a core design variable.
The Outcome
The HEEDS-led workflow enabled:
- Improvements in fuel efficiency – up to 6.3% fuel saving
- Improved acceleration and drivability metrics across tested cycles – 12.5% faster acceleration compared to baseline design
- A robust foundation for extending studies into thermal effects, real-world usage and life-cycle considerations
Read the Siemens Blog for more information
“By providing a reliable, ready-to-use control strategy, Simcenter Amesim Hybrid Optimization Tool reduces the development timeline, enabling researchers to focus on design exploration and optimization.”
