A new, electric vehicle (EV) transmission efficiency model is presented. The model accounts for gear friction, churning, bearing and seal losses, and can help to optimise gearbox design and lubricant properties to improve efficiency and hence range. Friction in gear teeth contacts is predicted using an iterative procedure to account for thermal coupling between the tooth temperature, oil properties, film thickness and friction during a mesh cycle. Crucially, the prediction of the evolution of the coefficient of friction (COF) along the path of contact incorporates measured lubricant rheological parameters and boundary friction, enabling lubricants of the same specification to be differentiated in terms of their impact on efficiency. Bearing losses are predicted using an existing empirical relationship and gear churning losses are predicted using a new empirical relationship developed with a custom test rig.
Heat transfers within the transmission and to the surroundings are accounted for using a thermal network approach, allowing component temperatures to be determined locally and oil properties to be more accurately determined. This improves loss predictions and allows gearbox temperature evolution over any given vehicle duty to be predicted. Temperature predictions compare well to measurements made on a current EV over a range of drive cycles.
Analyses at constant input power show that at low speeds/high torques, losses in the gear meshes and high-load bearings are most significant, whereas at high speeds/low torques, losses in high-speed input shaft bearings, and gear churning losses become more important. Gearbox losses can account for 15-25% of the overall power losses in an EV depending on road conditions, a significantly higher proportion than in an internal combustion engine (ICE) vehicle.
Finally, the influences of various lubricant and gearbox parameters on efficiency are explored through parameter studies, where the optimal lubricant viscosity is shown to be highly dependent on vehicle duty.