Hybrid Electric Motors Optimization using modeFRONTIER
ENHANCE YOUR HEV ENGINE DESIGN, REDUCE YOUR FOOTPRINT
Top industry players have chosen ESTECO technology to effectively set up design tasks associated with EV/HEV systems and to quickly identify the right engineering strategies to cope with highly constrained design problems.
- Traction motors require recalibration for HEV/EV applications
- Designers lose time reviewing hundreds of designs
- Designs must consider structural and thermal limitations along with electromagnetic design constraints in motor magnetics
- Advanced designs require enormous computational resources
modeFRONTIER ALLOWS LEADING HEV/EV MANUFACTURERS TO:
- Identify optimal configuration and size of HEV / EV powertrains and components (motors, controllers, and energy management)
- Understand and enhance multi-disciplinary behavior at the system level – mechanical, electrical, thermal, and magnetics
- Develop optimal control strategies, power management, torque/speed coupling, and vehicle dynamics
- Enhance system safety and reliability owing to the Robust Design Optimization tool MORDO
The Series Hydraulic/Electric Synergy System (SHESS) has the potential to improve the overall energy efficiency of HEVs— a current limitation. In this paper, designers optimize energy performance and develop a method that simultaneously maintains reliability, contains maintenance costs, avoids energy loss, and maximizes regeneration and driving energy.
This paper builds on the previous published works in which the authors had employed nonlinear model predictive control for the (sub)optimal power management of a power-split hybrid electric vehicle (HEV). In addition to the battery’s state of charge, in this work we include the effect of inertial powertrain dynamics in the control-oriented model that are usually ignored because of their fast dynamics.
Lithium-ion batteries have proven higher energy density and longer life cycles than secondary batteries, yet HEV/EV manufacturers are held back due to thermal limitations. This paper presents a coupled experimental/computational method to simultaneously determine multiple thermal parameters of large laminated lithium-ion batteries.