Improving BEV efficiency through online adaptative optimisation of thermal controls

The current BEV thermal strategy uses a distributed controls framework between HVAC, Powertrain thermal management and a vehicle level thermal management controller. To improve vehicle efficiency, we must move from a robust temperature-based controller to a robust energy-based controller. We define robustness as optimal performance in all environments including regardless of the noise affecting the system: Solar load, environmental temperature, drag (vehicle speed), and driver behaviour (drive & charging). Self-learning controls using data-driven methods presents an opportunity to improve system robustness.
Technical ambition: Self-learning distributed controller for optimal efficiency in all environments (cold & hot markets).