High Level Synthesis for Optimising Hybrid Electric Vehicle Fuel Consumption Using FPGAs and Dynamic Programming

Abstract: The fuel usage of a hybrid electric vehicle can be reduced by strategically combining the usage of the combustion engine with the electric motor. One method to determine an optimal split between the two is to use dynamic programming. However, the amount of computations grows exponentially with the amount of states which makes its usage difficult on sequential hardware. This thesis project explores the usage of FPGAs for speeding up the required computations to possibly allow the optimisation to run in real time in the vehicle. A tool to convert a vehicle model to a hardware description language was developed and evaluated. The current version does not run fast enough to run in real time, but some optimisations which would allow that are proposed.