Скачать или смотреть Optimising climate control for Electric Cars using Reinforcement Learning | Coventry Branch

The EU H2020 DOMUS project aimed to develop and demonstrate a revolutionary approach to the design of electric vehicles (EVs) from a user-centric perspective for optimal efficiency. The project's main objective was to reduce the energy consumption of future EVs in order to increase their range by 25%, without compromising passenger comfort and safety. In this talk, we will look at one aspect of the project, which was to virtualise the car cabin and then use Reinforcement Learning to develop an optimal controller. The saving from this method alone was 20%.
A key innovation in this work was the use of machine learning to develop fast simulations based on Computational Fluid Dynamics (CFD) models of the thermal environment within the cabin. While this technology is almost ready to be used in passenger vehicles, on-going studies will be looking at ensuring that the improved performance translates smoothly to real world vehicles and that the approach can be used to personalise comfort and optimise according to specific vehicles and climates.