Combine both a wider voltage range during driving operation, allowing a larger SoC range to be used, as well as higher charging powers during grid-charging.
Develop techniques to determine vehicle power requests (depending on vehicle state, road and weather conditions) such that battery state can be translated into accurate vehicle driving range estimation.
Develop vehicle energy management and driver coaching methodologies to extend driving range by more efficient energy usage.
RESULTS SO FAR
ALGOLiON has optimized their algorithm toolchain and added further methods for increasing the quality of the results
A physico-chemical-model-based approach for fast charging has been developed by A sensitivity analysis was performed, in order to reduce the complexity of physico-chemical-models for embedded systems
The evaluation of the physico-chemical-model for extending the energy and driving range is in preparation at the test benches of RWTH
Voltia has optimized and extended their prediction model of the energy consumption, considering GPS routs and characteristics of the driving environment
Optimizing the velocity profile and auxiliaries management was analysed by TU/e and can have a huge impact on the range.
The HVAC energy analysis was supported by SIEMENS PLM
VDL developed models and model based control strategies to optimize the driving range