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