Transmission power losses provide a major contribution to the overall energy loss in an electric vehicle. In relative terms, this contribution is much larger than in an equivalent IC-powered vehicle. Consequently, the ability to predict and minimise transmission losses provides an important avenue for improving the efficiency and thus extending the range of EVs. This project will develop a new model for prediction of EV gearbox efficiency including the influence of lubricant properties. The approach utilises a thermally-coupled gear lubrication model to accurately predict gear teeth friction as well as bearing and churning losses. Crucially, the model will use experimentally obtained lubricant rheology parameters as input which should allow it to differentiate between different lubricant formulations in terms of overall gearbox efficiency. The model is intended to be used as a tool for optimising the selection of transmission oils and gearbox architecture for improved efficiency and range of EVs. Results will assess the trends in transmission losses with a selection of existing and new oils and over a range of operating conditions typical of EV transmissions.