TOBEV: Thermally Optimised Battery Electric Vehicle

**TOBEV** or **T**hermally **O**ptimised **B**attery **E**lectric **V**ehicle is a project that brings a range of methodologies together to address the optimisation of the thermal system at several levels:

* Overall vehicle thermal and energy management using Optimal Control Theory
* Subsystem model predictive controls
* Architecture cost optimisation

The thermal management systems in battery electric vehicles are known to be significant energy consumers. For example, the cabin climate comfort is known to reduce the electric range of a vehicle by almost 1/3rd in cold and hot ambient conditions.

There have been many technologies proposed for reducing the thermal system energy consumption such as heat pumps, radiative heaters and other localised heating/cooling solutions however they often consider each technology in isolation without adapting the rest of the vehicle systems to take advantage of them.

This project will stand back from the individual technologies and consider the holistic vehicle thermal energy optimisation, by using models of the full vehicle combined with advanced optimisation approaches based on Optimal Control theory. This approach can automatically establish the best way of integrating new components and thermal system architectures into the overall vehicle operation, allowing robust comparisons of component choices -- since they are fully optimised in the target vehicle. The system level optimisation has the potential to increase the vehicle range significantly.

These results will be combined with an attribute optimisation to prioritise and deliver the best cost/benefit architectures, with significant reduction in overall cost.

Finally, the project will demonstrate the optimised solution in a demonstrator JLR I-PACE vehicle, a class leading electric vehicle. A model predictive controller will be integrated into the vehicle and used to deliver the increase in electric range whilst also reducing development times.